From 32e2ed918b97a3b3599569a606465cd07d5102a0 Mon Sep 17 00:00:00 2001
From: GitHub Action <action@github.com>
Date: Fri, 4 Oct 2024 04:56:12 +0000
Subject: [PATCH] Updated datasets 2024-10-04 UTC

---
 datasets/ABLE_897_1.json                      |    4 +-
 .../ABoVE_Annual_Veg_Resilience_2374_1.json   |    4 +-
 .../ABoVE_CO2_CH4_Flux_Estimates_2121_1.json  |    4 +-
 .../ABoVE_Domain_Projected_LULC_2353_1.json   |    4 +-
 datasets/ABoVE_SAR_Surveys_2150_1.json        |    4 +-
 datasets/ABoVE_SnowModel_Data_2105_1.json     |    4 +-
 .../ABoVE_Soil_Respiration_Maps_1935_1.json   |    4 +-
 datasets/AERONET_aerosol_706_1.json           |    4 +-
 .../AGB_CanopyHt_Cover_NewEngland_1854_1.json |    4 +-
 .../AGB_Carbon_Sequestration_RGGI_1922_1.json |    4 +-
 ...AGB_NEP_Disturbance_US_Forests_1829_2.json |    4 +-
 datasets/AKFED_V1_1282_1.json                 |    4 +-
 datasets/AK_Regional_CO2_Flux_1389_1.json     |    4 +-
 datasets/ALT_GPR_Barrow_1355_1.json           |    4 +-
 datasets/ARME_898_1.json                      |    4 +-
 datasets/AVHRR_LST_826_1.json                 |    4 +-
 datasets/AVIRIS-NG_Data_Idaho_1533_1.json     |    4 +-
 .../African_Rainfall_Patterns_1263_1.json     |    4 +-
 ...Alaska_L4_WRF_STILT_Footprints_1544_1.json |    4 +-
 .../Alaska_L4_WRF_STILT_Particle_1571_1.json  |    4 +-
 datasets/Alaskan_CH4_CO2_Fluxes_1316_1.json   |    4 +-
 datasets/Alaskan_CO2_Flux_1325_1.1.json       |    4 +-
 ...ArcticTreeLine_Dendrometry_Env_2185_1.json |    4 +-
 .../ArcticTreeLine_Spruce_CO2_WV_1948_1.json  |    4 +-
 datasets/Arctic_Boreal_CO2_Flux_1934_1.json   |    4 +-
 datasets/Arctic_Soil_Properties_2149_1.json   |    4 +-
 datasets/Arctic_Vegetation_Maps_1323_1.json   |    4 +-
 ...Arctic_Wildlife_Refuge_Veg_Map_1384_1.json |    4 +-
 .../Atmospheric_CO2_California_1641_1.json    |    4 +-
 .../BC_Aerosol_Dynamics_Alaska_1340_1.json    |    4 +-
 datasets/BOREAS_CDS_1350_1.json               |    4 +-
 datasets/BOREAS_SLICER_508_2.json             |    4 +-
 .../Biogenic_CO2flux_SIF_SMUrF_1899_1.json    |    4 +-
 .../Boreal_Fire_Severity_Metrics_1520_1.json  |    4 +-
 datasets/CABARE_918_1.json                    |    4 +-
 datasets/CAMREX_904_1.json                    |    4 +-
 datasets/CARAFE_2016_2017_v2_2002_1.1.json    |    4 +-
 datasets/CARVE_Ecosystem_CH4_Flux_1558_1.json |    4 +-
 datasets/CARVE_L1_FTS_Spectra_1426_1.json     |    4 +-
 datasets/CARVE_L1_FlightPath_1425_1.json      |    4 +-
 .../CARVE_L1_FlightPath_Winds_1427_1.json     |    4 +-
 datasets/CARVE_L1_Ground_Flux_1424_1.json     |    4 +-
 datasets/CARVE_L1_Infrared_1428_1.json        |    4 +-
 datasets/CARVE_L2_AtmosGas_Ground_1419_1.json |    4 +-
 .../CARVE_L2_AtmosGas_Harvard_1403_1.json     |    4 +-
 datasets/CARVE_L2_AtmosGas_Merge_1402_1.json  |    4 +-
 datasets/CARVE_L2_AtmosGas_NOAA_1401_1.json   |    4 +-
 datasets/CARVE_L2_FTS_ColumnGas_1429_1.json   |    4 +-
 datasets/CARVE_L2_Flask_1404_1.json           |    4 +-
 datasets/CARVE_L2_Flask_Ground_1405_1.json    |    4 +-
 ...CARVE_L4_WRF-STILT_Footprint_1431_1.1.json |    4 +-
 .../CARVE_L4_WRF-STILT_Particle_1430_1.1.json |    4 +-
 datasets/CARVE_Land_Thaw_State_1383_1.1.json  |    4 +-
 datasets/CARVE_Photos_1435_1.json             |    4 +-
 datasets/CARVE_Reports_1434_1.json            |    4 +-
 datasets/CARVE_Videos_1433_1.json             |    4 +-
 datasets/CAR_BRDF_709_1.json                  |    4 +-
 datasets/CD01_BRAMS_907_1.json                |    4 +-
 .../CD01_CIRSAN_Meteorology_2001_1114_1.json  |    4 +-
 .../CD02_Atmosphere_CO2_Isotopes_1011_1.json  |    4 +-
 datasets/CD02_C_N_Isotopes_1097_1.json        |    4 +-
 datasets/CD02_C_N_O_Organic_983_1.json        |    4 +-
 .../CD02_Forest_Canopy_Structure_1009_1.json  |    4 +-
 .../CD02_Leaf_Level_Gas_Exchange_1010_1.json  |    4 +-
 .../CD02_Leaf_Water_Potential_1100_1.json     |    4 +-
 datasets/CD02_O_H_Isotopes_1008_1.json        |    4 +-
 datasets/CD03_Ceilometer_Km67_942_1.json      |    4 +-
 .../CD03_Mesoscale_Meteorology_944_1.json     |    4 +-
 datasets/CD03_Pasture_Flux_962_1.json         |    4 +-
 datasets/CD03_Tethered_Balloon_1108_1.json    |    4 +-
 datasets/CD04_Biomass_990_1.json              |    4 +-
 datasets/CD04_CO2_Profiles_947_1.json         |    4 +-
 datasets/CD04_Dendrometry_989_1.json          |    4 +-
 datasets/CD04_LAI_992_1.json                  |    4 +-
 datasets/CD04_LAI_Estimates_1103_1.json       |    4 +-
 .../CD04_Leaf_Level_Gas_Exchange_1060_1.json  |    4 +-
 datasets/CD04_Leaf_Litter_991_1.json          |    4 +-
 datasets/CD04_Logging_Damage_1038_1.json      |    4 +-
 datasets/CD04_Meteorology_Fluxes_946_1.json   |    4 +-
 datasets/CD04_Soil_Moisture_Km83_979_1.json   |    4 +-
 datasets/CD04_Soil_Respiration_1039_1.json    |    4 +-
 datasets/CD04_Tower_Flux_Gap_978_1.json       |    4 +-
 datasets/CD05_Fuel_Loads_1233_1.json          |    4 +-
 datasets/CD05_Micromet_1169_1.json            |    4 +-
 .../CD05_REE_Fuel_Sticks_Moisture_1232_1.json |    4 +-
 datasets/CD06_BGC_JiParana_1227_1.json        |    4 +-
 datasets/CD06_C02_Exchange_1136_1.json        |    4 +-
 datasets/CD06_C_Isotopes_1120_1.json          |    4 +-
 datasets/CD06_Camrex_1086_1.json              |    4 +-
 datasets/CD06_Carbon_respiration_1125_1.json  |    4 +-
 datasets/CD06_LULC_Map_JiParana_1087_1.json   |    4 +-
 ...D06_Landuse_Timeseries_JiParana_844_1.json |    4 +-
 datasets/CD06_Outgassing_1151_1.json          |    4 +-
 ...D06_Physical_Template_JiParana_1090_1.json |    4 +-
 datasets/CD06_Soils_JiParana_1088_1.json      |    4 +-
 .../CD06_Water_Balance_JiParana_1132_1.json   |    4 +-
 datasets/CD07_GOES_L3_Gridded_SRB_831_1.json  |    4 +-
 .../CD08_CWD_Res_and_Decomp_Manaus_911_1.json |    4 +-
 .../CD08_C_Isotopes_Belowground_1025_1.json   |    4 +-
 .../CD08_Ecosystem_Resp_Manaus_912_1.json     |    4 +-
 .../CD08_Leaf_Isotopes_Manaus_1245_1.json     |    4 +-
 datasets/CD08_Radiocarbon_Dates_997_1.json    |    4 +-
 .../CD08_Radiocarbon_Dates_Manaus_996_1.json  |    4 +-
 datasets/CD08_Tree_Growth_Manaus_1194_1.json  |    4 +-
 datasets/CD08_Tree_Inventory_Ducke_910_1.json |    4 +-
 datasets/CD09_Soils_Veg_Tapajos_1104_1.json   |    4 +-
 datasets/CD10_Biometry_Tapajos_854_1.json     |    4 +-
 datasets/CD10_CO2_Profiles_Tapajos_855_1.json |    4 +-
 datasets/CD10_CO_CO2_Maxaranguape_1012_1.json |    4 +-
 datasets/CD10_CO_Tapajos_856_1.json           |    4 +-
 datasets/CD10_CWD_Tapajos_858_1.json          |    4 +-
 datasets/CD10_DBH_Tapajos_859_1.json          |    4 +-
 datasets/CD10_EddyFlux_Tapajos_860_1.json     |    4 +-
 datasets/CD10_H2O_Profiles_Tapajos_861_1.json |    4 +-
 datasets/CD10_Litter_Tapajos_862_1.json       |    4 +-
 ...10_Temperature_Profiles_Tapajos_863_1.json |    4 +-
 datasets/CD11_Forest_Degradation_1118_1.json  |    4 +-
 datasets/CD15_Productivity_1167_1.json        |    4 +-
 datasets/CD17_Forest_Survey_1254_1.json       |    4 +-
 datasets/CD32_Fluxes_Brazil_1842_2.json       |    4 +-
 datasets/CD32_LBA_MIP_Drivers_1177_1.json     |    4 +-
 datasets/CD34_Amazon_Hyperion_1064_1.json     |    4 +-
 datasets/CD34_Amazon_Landsat_1176_1.json      |    4 +-
 datasets/CD36_SALDAS_1162_1.json              |    4 +-
 .../CD37_Biomass_Landsat_Glas_1145_1.json     |    4 +-
 datasets/CDIAC_NDP41_220_2.json               |    4 +-
 .../CH4_Aircraft_STILT_footprints_1300_1.json |    4 +-
 .../CH4_CO2_WaterBodies_YK_Delta_2178_1.json  |    4 +-
 ...CH4_Fluxes_ThermokarstLakes_AK_1870_1.json |    4 +-
 datasets/CH4_Plume_AVIRIS-NG_1727_1.json      |    4 +-
 datasets/CMAQ-N_Module_1661_1.json            |    4 +-
 datasets/CMS_CO2_Fluxes_TBMO_1315_1.json      |    4 +-
 datasets/CMS_CONUS_Biomass_1752_1.json        |    4 +-
 ...CMS_Coastal_Wetland_Resilience_1839_1.json |    4 +-
 datasets/CMS_DARTE_V2_1735_2.json             |    4 +-
 datasets/CMS_Daily_ET_MexFlux_1309_1.json     |    4 +-
 datasets/CMS_EFT_CONUS_1659_1.json            |    4 +-
 datasets/CMS_Fire_Weather_Data_AK_1509_1.json |    4 +-
 ...CMS_FluxEstimates_Aircraft_CO2_2336_1.json |    4 +-
 datasets/CMS_Forest_Carbon_Fluxes_1313_1.json |    4 +-
 .../CMS_Forest_Carbon_Maryland_1660_1.json    |    4 +-
 datasets/CMS_Forest_Productivity_1221_1.json  |    4 +-
 .../CMS_Global_Cropland_Carbon_1279_1.json    |    4 +-
 datasets/CMS_Global_Fire_Atlas_1642_1.json    |    4 +-
 datasets/CMS_Global_Forest_AGC_2180_1.json    |    4 +-
 datasets/CMS_Global_Forest_Age_2345_1.json    |    4 +-
 .../CMS_Global_Livestock_CH4_CO2_1329_2.json  |    4 +-
 .../CMS_Global_Mangrove_Forest_Ht_2251_1.json |    4 +-
 datasets/CMS_Global_Mangrove_Loss_1768_1.json |    4 +-
 ...S_Global_Map_Mangrove_Canopy_1665_1.3.json |    4 +-
 ...CMS_Global_Monthly_Wetland_CH4_1502_1.json |    4 +-
 .../CMS_Global_Soil_Respiration_1736_1.json   |    4 +-
 datasets/CMS_Great_Basin_Biomass_1755_1.json  |    4 +-
 datasets/CMS_Landcover_Indonesia_1838_1.json  |    4 +-
 .../CMS_Landscapes_Brazil_Forests_1301_1.json |    4 +-
 .../CMS_Landscapes_Brazil_LiDAR_1302_1.json   |    4 +-
 datasets/CMS_LiDAR_AGB_California_1537_1.json |    4 +-
 datasets/CMS_LiDAR_AGB_PEF_2012_1318_1.json   |    4 +-
 ...CMS_LiDAR_Biomass_CanHt_Sonoma_1523_1.json |    4 +-
 .../CMS_LiDAR_Biomass_MD_PA_DE_1538_2.json    |    4 +-
 datasets/CMS_LiDAR_Indonesia_1518_1.json      |    4 +-
 .../CMS_LiDAR_Point_Cloud_Zambezi_1521_1.json |    4 +-
 .../CMS_LiDAR_Products_Indonesia_1540_1.json  |    4 +-
 .../CMS_Mangrove_Biomass_Zambezi_1522_1.json  |    4 +-
 .../CMS_Mangrove_CanHt_Stand_Age_1377_1.json  |    4 +-
 .../CMS_Mangrove_Canopy_Height_1327_1.json    |    4 +-
 ...CMS_Mangrove_Canopy_Ht_Zambezi_1357_1.json |    4 +-
 datasets/CMS_Mangrove_Cover_1670_1.1.json     |    4 +-
 datasets/CMS_Maryland_AGB_Canopy_1320_1.json  |    4 +-
 .../CMS_Methane_Emissions_Boston_1291_1.json  |    4 +-
 ...CMS_Monthly_CO2_Gulf_of_Mexico_1668_1.json |    4 +-
 ...CMS_Pantropical_Forest_Biomass_1337_1.json |    4 +-
 .../CMS_Pennsylvania_Tree_Cover_1334_1.1.json |    4 +-
 datasets/CMS_Pilot_Biomass_1257_1.json        |    4 +-
 .../CMS_SABGOM_Model_Simulations_1510_1.json  |    4 +-
 datasets/CMS_SOC_Mexico_1754_1.json           |    4 +-
 datasets/CMS_SOC_Mexico_CONUS_1737_1.json     |    4 +-
 datasets/CMS_SST_GPP_Mexico_1310_1.json       |    4 +-
 .../CMS_Simulated_SIF_NiwotRidge_1720_1.json  |    4 +-
 datasets/CMS_Soil_CO2_Efflux_1298_1.json      |    4 +-
 ...CMS_WRF_Footprints_CO2_Signals_1381_1.json |    4 +-
 datasets/CMS_WRF_Model_Products_1338_1.json   |    4 +-
 datasets/COMEX_AJAX_CO2_CH4_2347_1.json       |    4 +-
 .../COMEX_AVIRIS_Classic_Flights_2343_1.json  |    4 +-
 datasets/COMEX_AVIRIS_NG_Flights_2342_1.json  |    4 +-
 ...COMEX_LongwaveInfrared_Imagery_2331_1.json |    4 +-
 ...CStocks_Greenness_Mangroves_MX_1853_1.json |    4 +-
 datasets/CV-580_710_1.json                    |    4 +-
 .../C_FluxStocks_CLM5_DART_WestUS_1856_1.json |    4 +-
 datasets/C_Pools_Fluxes_CONUS_1837_1.json     |    4 +-
 .../CircumArctic_Trends_Hotspots_2322_1.json  |    4 +-
 .../Climate_Normals_Modern_LGM_AK_1663_1.json |    4 +-
 .../Coastal_Carbon_Budget_NE_US_1594_1.json   |    4 +-
 .../Coastal_US_Elevation_Data_1844_1.json     |    4 +-
 ...Continuous_Lifeform_Maps_CONUS_1809_1.json |    4 +-
 .../Country_SOC_Latin_America_1615_1.json     |    4 +-
 datasets/CramerLeemans_416_1.json             |    4 +-
 datasets/Cropland_Carbon_Fluxes_2125_1.json   |    4 +-
 .../Crops_SIF_VegIndices_IL_NE_2136_1.json    |    4 +-
 ...CubeSat_Arctic_Boreal_LakeArea_1667_1.json |    4 +-
 datasets/DISCover_land_cover_679_1.json       |    4 +-
 datasets/DLEM_C_N_Export_1699_1.json          |    4 +-
 ...Daily_FineParticulateMatter_AK_2157_1.json |    4 +-
 datasets/Dairy_Methane_CA_V1-2_1902_1.2.json  |    4 +-
 datasets/Daymet_Annual_V4R1_2130_4.1.json     |    4 +-
 datasets/Daymet_Daily_V4R1_2129_4.1.json      |    4 +-
 datasets/Daymet_Monthly_V4R1_2131_4.1.json    |    4 +-
 .../Daymet_SubDaily_Puerto_Rico_1977_1.json   |    4 +-
 ...Daymet_V4_Daily_MonthlyLatency_1904_1.json |    4 +-
 datasets/Daymet_xval_V4R1_2132_4.1.json       |    4 +-
 datasets/Decadal_LULC_India_1336_1.json       |    4 +-
 ...DeciduousFractionl_CanopyCover_2296_1.json |    4 +-
 .../DeltaX_ADCP_Measurements_V2_2081_2.json   |    4 +-
 datasets/DeltaX_AGB_AGN_V2_2237_2.json        |    4 +-
 .../DeltaX_ANUGA_AtchafalayaBasin_2306_1.json |    4 +-
 ...DeltaX_ANUGA_Hydrodynamics_MRD_2310_1.json |    4 +-
 datasets/DeltaX_BGB_BGN_V2_2238_2.json        |    4 +-
 ...DeltaX_BG_Root_Stable_Isotopes_2193_1.json |    4 +-
 datasets/DeltaX_DEM_MRD_LA_2181_1.json        |    4 +-
 .../DeltaX_Delft3D_294_Terrebonne_2303_1.json |    4 +-
 .../DeltaX_Delft3D_322_Terrebonne_2312_1.json |    4 +-
 .../DeltaX_Delft3D_396_Terrebonne_2314_1.json |    4 +-
 .../DeltaX_Delft3D_399_Terrebonne_2313_1.json |    4 +-
 .../DeltaX_Delft3D_421_Terrebonne_2304_1.json |    4 +-
 ...DeltaX_Delft3D_Atchafalaya_MRD_2302_1.json |    4 +-
 .../DeltaX_Delft3D_Terrebonne_MRD_2301_1.json |    4 +-
 .../DeltaX_Ecogeomorphic_Products_2108_1.json |    4 +-
 .../DeltaX_Feldspar_Sediment_V3_2290_3.json   |    4 +-
 .../DeltaX_Foliar_Stable_Isotopes_2194_1.json |    4 +-
 .../DeltaX_H2O_Surface_Elevation_2086_1.json  |    4 +-
 .../DeltaX_Herb_WetlandSoil_V3_2239_3.json    |    4 +-
 datasets/DeltaX_Insitu_POC_2073_1.json        |    4 +-
 .../DeltaX_Insitu_Reflectance_V3_2153_3.json  |    4 +-
 ...DeltaX_Insitu_WQ_Indicators_V2_2080_2.json |    4 +-
 .../DeltaX_Island_Channel_Model_2106_1.json   |    4 +-
 ...eltaX_L1B_UAVSAR_WaterLevels_1979_1.1.json |    4 +-
 .../DeltaX_L1_AVIRIS_Radiance_1987_1.json     |    4 +-
 .../DeltaX_L1_UAVSAR_SLC_Stack_1984_1.1.json  |    4 +-
 datasets/DeltaX_L1b_AirSWOT_1996_1.1.json     |    4 +-
 .../DeltaX_L2A_AVIRIS-NG_BRDF_V2_2139_2.json  |    4 +-
 .../DeltaX_L2_AVIRIS_Reflectance_1988_1.json  |    4 +-
 ...DeltaX_L2_AirSWOT_WaterElev_V3_2350_3.json |    4 +-
 ...DeltaX_L2_UAVSAR_WaterLevels_2057_1.1.json |    4 +-
 .../DeltaX_L3_AVIRIS-NG_AGB_V2_2138_2.json    |    4 +-
 .../DeltaX_L3_AVIRIS-NG_Veg_Types_2352_1.json |    4 +-
 .../DeltaX_L3_AVIRIS-NG_Water_V3_2152_3.json  |    4 +-
 ...DeltaX_L3_AirSWOT_WaterElev_V2_2349_2.json |    4 +-
 ...DeltaX_L3_UAVSAR_WaterLevels_2058_1.1.json |    4 +-
 .../DeltaX_LandAccretionMap_WLD_2308_1.json   |    4 +-
 .../DeltaX_MarshAccretion_NUMAR_2354_1.json   |    4 +-
 .../DeltaX_Particle_Size_LISST_V2_2077_2.json |    4 +-
 datasets/DeltaX_RTK_Elevation_2071_1.json     |    4 +-
 .../DeltaX_Sediment_Grain_Size_V2_2135_2.json |    4 +-
 datasets/DeltaX_Sonar_Bathymetry_2085_1.json  |    4 +-
 .../DeltaX_TSS_Concentration_V2_2075_2.json   |    4 +-
 ...DeltaX_TotalSubsidenceRate_MRD_2307_1.json |    4 +-
 datasets/DeltaX_Turbidity_Data_V4_2241_4.json |    4 +-
 ...DeltaX_UAVSAR_L3_ChannelMap_V2_2344_2.json |    4 +-
 ...DeltaX_Vegetation_Structure_V2_2240_2.json |    4 +-
 .../Dendrophenology_Eastern_US_1369_1.json    |    4 +-
 datasets/Disturbance_Biomass_Maps_1679_1.json |    4 +-
 datasets/Dunne_545_1.json                     |    4 +-
 datasets/EDM_SA_Vegetation_1149_1.json        |    4 +-
 datasets/EDM_US_Carbon_1160_1.json            |    4 +-
 datasets/EF_Data_Mexico_1693_1.json           |    4 +-
 datasets/EM27_XCO2_XCH4_XCO_AK_1831_1.json    |    4 +-
 datasets/ENVISAT_SCIAMACHY_SIF_1871_1.json    |    4 +-
 datasets/ERS2_GOME_SIF_1758_1.json            |    4 +-
 datasets/EastAnglia10YearMean_549_1.json      |    4 +-
 datasets/EastAnglia30YearMean_550_1.json      |    4 +-
 datasets/EastAngliaClimate_542_1.json         |    4 +-
 datasets/EastAngliaPrecip_417_1.json          |    4 +-
 ...Estimated_Biomass_Stock_Amazon_1648_1.json |    4 +-
 datasets/Eurasia_Biomass_1278_1.json          |    4 +-
 datasets/FEWS_precip_711_1.json               |    4 +-
 .../FIA_Forest_Biomass_Estimates_1873_1.json  |    4 +-
 datasets/FIFE_CD_V3_130_1.json                |    4 +-
 .../FLEXPART_Influence_Functions_2018_1.json  |    4 +-
 datasets/FLOODAMA_903_1.json                  |    4 +-
 datasets/FLUAMAZON_896_1.json                 |    4 +-
 datasets/FLUXNET_Canada_1335_1.json           |    4 +-
 datasets/FieldData_Alaska_Tundra_2177_1.json  |    4 +-
 datasets/Fire_Emissions_Indonesia_2118_1.json |    4 +-
 datasets/FluxSat_GPP_FPAR_1835_2.json         |    4 +-
 datasets/Fluxnet_site_DB_1530_1.json          |    4 +-
 .../Fluxnet_website_archive_copy_1549_1.json  |    4 +-
 .../ForestHt_Biomass_GEDI_TDX_2298_1.json     |   16 +-
 datasets/Forest_AGB_NW_USA_1766_1.json        |    4 +-
 datasets/Forest_Carbon_Priority_1803_1.json   |    4 +-
 .../Forest_Disturbance_Intensity_2059_1.json  |    4 +-
 .../Forest_Inventory_Acre_Brazil_1654_1.json  |    4 +-
 datasets/Forest_Inventory_Brazil_2007_1.json  |    4 +-
 .../Forest_Inventory_Data_Brazil_1563_1.json  |    4 +-
 datasets/Forest_Inventory_Tapajos_1552_1.json |    4 +-
 ...Forested_Areas_Amazonas_Brazil_1515_1.json |    4 +-
 .../Forested_Areas_Para_Brazil_1514_1.json    |    4 +-
 ...Freeze_Thaw_NorthernHemisphere_2323_1.json |    4 +-
 .../GCAM_Land_Cover_2005-2095_1216_1.json     |    4 +-
 datasets/GCRW_DEM_2016_1793_1.json            |    4 +-
 datasets/GEDI_Fusion_Structure_2236_1.json    |   16 +-
 ...GEDI_HighQuality_Shots_Rasters_2339_1.json |    4 +-
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 datasets/tgb9nmhc_395_1.json                  |    4 +-
 datasets/tgbfenfx_378_1.json                  |    4 +-
 datasets/tgbfenne_379_1.json                  |    4 +-
 datasets/timber_125_1.json                    |    4 +-
 datasets/trajectory_images_792_1.json         |    4 +-
 datasets/tree_cover-1km_641_1.json            |    4 +-
 datasets/uk_met_c-130_720_1.json              |    4 +-
 datasets/umd_landcover_xdeg_969_1.json        |    4 +-
 .../veg_continuous_fields_xdeg_931_1.json     |    4 +-
 datasets/vegsoils_wilhend_642_1.json          |    4 +-
 datasets/vemap-1_VEMAP1_CDROM_566_1.json      |    4 +-
 datasets/vemap-1_VEMAP_Alaska_1344_1.json     |    4 +-
 datasets/vemap-1_climate_224_1.json           |    4 +-
 datasets/vemap-1_geog_222_1.json              |    4 +-
 datasets/vemap-1_results_731_1.json           |    4 +-
 datasets/vemap-1_scenario_223_1.json          |    4 +-
 datasets/vemap-1_siteFile_226_1.json          |    4 +-
 datasets/vemap-1_soil_227_1.json              |    4 +-
 datasets/vemap-1_veg_225_1.json               |    4 +-
 datasets/vemap-2_TCLIMATE_annual_571_1.json   |    4 +-
 datasets/vemap-2_TCLIMATE_daily_620_1.json    |    4 +-
 datasets/vemap-2_TCLIMATE_monthly_568_1.json  |    4 +-
 datasets/vemap-2_TSCENARIO_annual_570_1.json  |    4 +-
 datasets/vemap-2_TSCENARIO_daily_618_1.json   |    4 +-
 datasets/vemap-2_TSCENARIO_monthly_567_1.json |    4 +-
 datasets/vemap-2_results_annual_766_1.json    |    4 +-
 datasets/vemap-2_results_monthly_767_1.json   |    4 +-
 datasets/white_model_parameters_652_1.json    |    4 +-
 datasets/wilhend_687_1.json                   |    4 +-
 datasets/willmott_673_1.json                  |    4 +-
 datasets/woody_biomass_657_1.json             |    4 +-
 nasa_cmr_catalog.json                         | 5566 +++++++++--------
 nasa_cmr_catalog.tsv                          |   86 +-
 2399 files changed, 12179 insertions(+), 7425 deletions(-)
 create mode 100644 datasets/MASTER_GEMx_Spring_2024_2370_1.json
 create mode 100644 datasets/OCO2_L1B_Calibration_11.2r.json
 create mode 100644 datasets/OCO2_L1B_Science_11.2r.json
 create mode 100644 datasets/OCO2_L2_ABand_11.2r.json
 create mode 100644 datasets/OCO2_L2_CO2Prior_11.2r.json
 create mode 100644 datasets/OCO2_L2_Diagnostic_11.2r.json
 create mode 100644 datasets/OCO2_L2_IMAPDOAS_11.2r.json
 create mode 100644 datasets/OCO2_L2_Lite_FP_11.2r.json
 create mode 100644 datasets/OCO2_L2_Lite_SIF_11.2r.json
 create mode 100644 datasets/OCO2_L2_Met_11.2r.json
 create mode 100644 datasets/OCO2_L2_Standard_11.2r.json
 create mode 100644 datasets/OCO3_L1B_Calibration_11r.json
 create mode 100644 datasets/OCO3_L1B_Science_11r.json
 create mode 100644 datasets/OCO3_L2_ABand_11r.json
 create mode 100644 datasets/OCO3_L2_CO2Prior_11r.json
 create mode 100644 datasets/OCO3_L2_Diagnostic_11r.json
 create mode 100644 datasets/OCO3_L2_IMAPDOAS_11r.json
 create mode 100644 datasets/OCO3_L2_Lite_FP_11r.json
 create mode 100644 datasets/OCO3_L2_Met_11r.json
 create mode 100644 datasets/OCO3_L2_Standard_11r.json
 create mode 100644 datasets/OMPS_N21_LP_L1G_EV_1.0.json
 create mode 100644 datasets/OMPS_N21_LP_L2_O3_DAILY_1.0.json
 create mode 100644 datasets/PREFIRE_SAT2_0-BUS-TLM_R01.json
 create mode 100644 datasets/PREFIRE_SAT2_0-PAYLOAD-TLM_R01.json
 create mode 100644 datasets/PREFIRE_SAT2_0-PAYLOAD_R01.json
 create mode 100644 datasets/RSS18_AVIRIS_L1B_449_1.json
 create mode 100644 datasets/SNEX21_PS_DSM_1.json
 create mode 100644 datasets/SNEX21_PS_MET_1.json
 create mode 100644 datasets/TROPICS03PRPSL2B_1.0.json
 create mode 100644 datasets/TROPICS06PRPSL2B_1.0.json

diff --git a/datasets/ABLE_897_1.json b/datasets/ABLE_897_1.json
index 0a3f2d8fd..615004027 100644
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index 096c86a5a..d318b46af 100644
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index cb068c5eb..c1c4d3473 100644
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index 8507a2f74..aa89509f0 100644
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index 411b6be07..6f22ef412 100644
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index 2296213a7..2014d5d8e 100644
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diff --git a/datasets/ARME_898_1.json b/datasets/ARME_898_1.json
index 87210fc0d..99679e2b3 100644
--- a/datasets/ARME_898_1.json
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index 86a4a63b8..cdad6c530 100644
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diff --git a/datasets/Alaska_L4_WRF_STILT_Particle_1571_1.json b/datasets/Alaska_L4_WRF_STILT_Particle_1571_1.json
index adb34a354..0f6256857 100644
--- a/datasets/Alaska_L4_WRF_STILT_Particle_1571_1.json
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@@ -42,7 +42,7 @@
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index 9e4f1921e..8a862f68f 100644
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index 3374d30ba..b28872c4e 100644
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diff --git a/datasets/ArcticTreeLine_Dendrometry_Env_2185_1.json b/datasets/ArcticTreeLine_Dendrometry_Env_2185_1.json
index ff3d81a11..11fdbc074 100644
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index f450bd8bb..151475c37 100644
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diff --git a/datasets/Arctic_Boreal_CO2_Flux_1934_1.json b/datasets/Arctic_Boreal_CO2_Flux_1934_1.json
index 6dbf1a1b9..7ef53b445 100644
--- a/datasets/Arctic_Boreal_CO2_Flux_1934_1.json
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@@ -42,7 +42,7 @@
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--- a/datasets/Arctic_Soil_Properties_2149_1.json
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index 9f933eae1..f30079b69 100644
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index 9c2f7c86f..18b3d64d6 100644
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diff --git a/datasets/BC_Aerosol_Dynamics_Alaska_1340_1.json b/datasets/BC_Aerosol_Dynamics_Alaska_1340_1.json
index c877a1806..bd2a7fc35 100644
--- a/datasets/BC_Aerosol_Dynamics_Alaska_1340_1.json
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diff --git a/datasets/CABARE_918_1.json b/datasets/CABARE_918_1.json
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index 149349250..4d0bfe0cd 100644
--- a/datasets/CAMREX_904_1.json
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index 3279d1ec4..3c3444f3f 100644
--- a/datasets/CARAFE_2016_2017_v2_2002_1.1.json
+++ b/datasets/CARAFE_2016_2017_v2_2002_1.1.json
@@ -42,7 +42,7 @@
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index b62f3dc4e..50f76344a 100644
--- a/datasets/CARVE_Ecosystem_CH4_Flux_1558_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L1_FTS_Spectra_1426_1.json b/datasets/CARVE_L1_FTS_Spectra_1426_1.json
index ba1f9954c..9a6386c8d 100644
--- a/datasets/CARVE_L1_FTS_Spectra_1426_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L1_FlightPath_1425_1.json b/datasets/CARVE_L1_FlightPath_1425_1.json
index 61815e539..48eec2ab3 100644
--- a/datasets/CARVE_L1_FlightPath_1425_1.json
+++ b/datasets/CARVE_L1_FlightPath_1425_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L1_FlightPath_Winds_1427_1.json b/datasets/CARVE_L1_FlightPath_Winds_1427_1.json
index 10658ba4f..76a1d9296 100644
--- a/datasets/CARVE_L1_FlightPath_Winds_1427_1.json
+++ b/datasets/CARVE_L1_FlightPath_Winds_1427_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L1_Ground_Flux_1424_1.json b/datasets/CARVE_L1_Ground_Flux_1424_1.json
index c48c14db9..32270a761 100644
--- a/datasets/CARVE_L1_Ground_Flux_1424_1.json
+++ b/datasets/CARVE_L1_Ground_Flux_1424_1.json
@@ -42,7 +42,7 @@
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index 8e649acf5..ed9b398f4 100644
--- a/datasets/CARVE_L1_Infrared_1428_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L2_AtmosGas_Ground_1419_1.json b/datasets/CARVE_L2_AtmosGas_Ground_1419_1.json
index 415edd203..db8affaf8 100644
--- a/datasets/CARVE_L2_AtmosGas_Ground_1419_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L2_AtmosGas_Harvard_1403_1.json b/datasets/CARVE_L2_AtmosGas_Harvard_1403_1.json
index a58049d9e..e5a0a7c57 100644
--- a/datasets/CARVE_L2_AtmosGas_Harvard_1403_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L2_AtmosGas_Merge_1402_1.json b/datasets/CARVE_L2_AtmosGas_Merge_1402_1.json
index 268de45af..18c5b0967 100644
--- a/datasets/CARVE_L2_AtmosGas_Merge_1402_1.json
+++ b/datasets/CARVE_L2_AtmosGas_Merge_1402_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_L2_AtmosGas_NOAA_1401_1.json b/datasets/CARVE_L2_AtmosGas_NOAA_1401_1.json
index b0dd262a9..2b62146b0 100644
--- a/datasets/CARVE_L2_AtmosGas_NOAA_1401_1.json
+++ b/datasets/CARVE_L2_AtmosGas_NOAA_1401_1.json
@@ -42,7 +42,7 @@
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index 7669abcb8..7ade57212 100644
--- a/datasets/CARVE_L2_FTS_ColumnGas_1429_1.json
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diff --git a/datasets/CARVE_L2_Flask_1404_1.json b/datasets/CARVE_L2_Flask_1404_1.json
index b63099f8d..d3285f7f2 100644
--- a/datasets/CARVE_L2_Flask_1404_1.json
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@@ -42,7 +42,7 @@
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index 6cb6233d0..9cb706bd2 100644
--- a/datasets/CARVE_L2_Flask_Ground_1405_1.json
+++ b/datasets/CARVE_L2_Flask_Ground_1405_1.json
@@ -42,7 +42,7 @@
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index 51b6b51e3..baec04b05 100644
--- a/datasets/CARVE_L4_WRF-STILT_Footprint_1431_1.1.json
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index ff84e934c..dc061d85a 100644
--- a/datasets/CARVE_L4_WRF-STILT_Particle_1430_1.1.json
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diff --git a/datasets/CARVE_Land_Thaw_State_1383_1.1.json b/datasets/CARVE_Land_Thaw_State_1383_1.1.json
index d9c2011e0..82340ee8b 100644
--- a/datasets/CARVE_Land_Thaw_State_1383_1.1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_Photos_1435_1.json b/datasets/CARVE_Photos_1435_1.json
index 3d9ebcf48..340029e31 100644
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CARVE_Reports_1434_1.json b/datasets/CARVE_Reports_1434_1.json
index 8aa1be99b..5dee4f4f7 100644
--- a/datasets/CARVE_Reports_1434_1.json
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@@ -42,7 +42,7 @@
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index 75bfac883..f13691ca2 100644
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index 462f20218..b10d2153c 100644
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index 40be3bd26..f810da9f1 100644
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index b4b155c4c..70170568a 100644
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index 696d9d3b3..d943634fc 100644
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index 6eeedfcc8..dc0aaa2dc 100644
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diff --git a/datasets/CD02_O_H_Isotopes_1008_1.json b/datasets/CD02_O_H_Isotopes_1008_1.json
index 1137cf337..24bfe1a83 100644
--- a/datasets/CD02_O_H_Isotopes_1008_1.json
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index ebbad8147..14a0c303f 100644
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index d07bd5a70..33a51e489 100644
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index 5a1ba07c4..fdd2f0f65 100644
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index a209aed67..9dd47d422 100644
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index a051d560a..e592a05ad 100644
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index 98c6ae29f..0d890c818 100644
--- a/datasets/CD04_Leaf_Litter_991_1.json
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index 0104fba07..64e31a758 100644
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index 5fee3b12e..c68c72e4f 100644
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index 381d89a1d..567b03c6b 100644
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index 82185a8a3..e80ccc476 100644
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index 11e32d4cd..55ca75bd3 100644
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index dc0688408..34d50ff62 100644
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index 990936f69..428593976 100644
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index 6535a1116..b101018b3 100644
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index 1e24b92b8..f579f5d57 100644
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index 693f13af3..57fb9988a 100644
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index 1ab86d6db..65c27e241 100644
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index 4cc00d516..f3d3de5c0 100644
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index 78af1139a..5e53c1dc5 100644
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index 9eeb123ab..bcaf28066 100644
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index 46b411a21..65731f2c4 100644
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index a99bd830a..1f1acaae8 100644
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index c8f4ccc65..f18d04271 100644
--- a/datasets/CD17_Forest_Survey_1254_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CD32_Fluxes_Brazil_1842_2.json b/datasets/CD32_Fluxes_Brazil_1842_2.json
index 0ad750e45..551605e04 100644
--- a/datasets/CD32_Fluxes_Brazil_1842_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CD32_LBA_MIP_Drivers_1177_1.json b/datasets/CD32_LBA_MIP_Drivers_1177_1.json
index a4a7efa36..fbeee1228 100644
--- a/datasets/CD32_LBA_MIP_Drivers_1177_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CD34_Amazon_Hyperion_1064_1.json b/datasets/CD34_Amazon_Hyperion_1064_1.json
index 44a491385..a8516fbc4 100644
--- a/datasets/CD34_Amazon_Hyperion_1064_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CD34_Amazon_Landsat_1176_1.json b/datasets/CD34_Amazon_Landsat_1176_1.json
index 8e17808df..82e4e63aa 100644
--- a/datasets/CD34_Amazon_Landsat_1176_1.json
+++ b/datasets/CD34_Amazon_Landsat_1176_1.json
@@ -42,7 +42,7 @@
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index c55428067..489680236 100644
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index 3ba1b8320..81ab5fcfd 100644
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index e4311c574..0a6dcaadb 100644
--- a/datasets/CH4_Aircraft_STILT_footprints_1300_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CH4_CO2_WaterBodies_YK_Delta_2178_1.json b/datasets/CH4_CO2_WaterBodies_YK_Delta_2178_1.json
index b9ae19263..ffad8a811 100644
--- a/datasets/CH4_CO2_WaterBodies_YK_Delta_2178_1.json
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@@ -42,7 +42,7 @@
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index 47052de8b..a1f26ef88 100644
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index 9a1312338..6cc6f4b60 100644
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index c7230b1db..e79de0636 100644
--- a/datasets/CMS_CONUS_Biomass_1752_1.json
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index 21e7133ed..2d6237e0d 100644
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index dab482eef..6a659aa22 100644
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index a5f56d306..c3479d03b 100644
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index 405788b20..59a937d16 100644
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index 057fcbd48..d22e092ff 100644
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index 99ef00f42..0de2f5d2d 100644
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index f0d07fd4a..d32ac0480 100644
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index bf7b0ce31..04ee6d84f 100644
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diff --git a/datasets/CMS_Global_Forest_Age_2345_1.json b/datasets/CMS_Global_Forest_Age_2345_1.json
index 68a5b5e95..8631fabe2 100644
--- a/datasets/CMS_Global_Forest_Age_2345_1.json
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diff --git a/datasets/CMS_Global_Livestock_CH4_CO2_1329_2.json b/datasets/CMS_Global_Livestock_CH4_CO2_1329_2.json
index 95d001f4d..67aa11cbd 100644
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index 053ade1f8..0b159dc86 100644
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index 3370fdf3e..c5a728da7 100644
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index db95c00df..c3ddb10b3 100644
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index aed179b0c..93d253d7c 100644
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index e89f96f00..4b09c677e 100644
--- a/datasets/CMS_Global_Soil_Respiration_1736_1.json
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index 667ce2aac..8aa3a35f8 100644
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index d3aac9f6c..7c14422d3 100644
--- a/datasets/CMS_Landcover_Indonesia_1838_1.json
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index 4dc23be6f..ce601d64d 100644
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index bb8e2d074..31db4b66e 100644
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index f03ef1a08..877c15f34 100644
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index 7ed3934af..a816e48e4 100644
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index 2e6919433..c94475789 100644
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index 674f39c9c..9e2a81425 100644
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diff --git a/datasets/CMS_LiDAR_Indonesia_1518_1.json b/datasets/CMS_LiDAR_Indonesia_1518_1.json
index f49b0ad84..f18563896 100644
--- a/datasets/CMS_LiDAR_Indonesia_1518_1.json
+++ b/datasets/CMS_LiDAR_Indonesia_1518_1.json
@@ -42,7 +42,7 @@
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index 13b5a1e7f..543cbd856 100644
--- a/datasets/CMS_LiDAR_Point_Cloud_Zambezi_1521_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CMS_LiDAR_Products_Indonesia_1540_1.json b/datasets/CMS_LiDAR_Products_Indonesia_1540_1.json
index ec424db64..06fadc419 100644
--- a/datasets/CMS_LiDAR_Products_Indonesia_1540_1.json
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@@ -42,7 +42,7 @@
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index 89c90104f..35b2e0e6a 100644
--- a/datasets/CMS_Mangrove_Biomass_Zambezi_1522_1.json
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diff --git a/datasets/CMS_Mangrove_CanHt_Stand_Age_1377_1.json b/datasets/CMS_Mangrove_CanHt_Stand_Age_1377_1.json
index 038331158..0d8cb9780 100644
--- a/datasets/CMS_Mangrove_CanHt_Stand_Age_1377_1.json
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@@ -42,7 +42,7 @@
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index 3e7b2ddc4..78a27e99a 100644
--- a/datasets/CMS_Mangrove_Canopy_Height_1327_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CMS_Mangrove_Canopy_Ht_Zambezi_1357_1.json b/datasets/CMS_Mangrove_Canopy_Ht_Zambezi_1357_1.json
index 40005c5c6..216800255 100644
--- a/datasets/CMS_Mangrove_Canopy_Ht_Zambezi_1357_1.json
+++ b/datasets/CMS_Mangrove_Canopy_Ht_Zambezi_1357_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/CMS_Mangrove_Cover_1670_1.1.json b/datasets/CMS_Mangrove_Cover_1670_1.1.json
index 9486fb641..2d4d72765 100644
--- a/datasets/CMS_Mangrove_Cover_1670_1.1.json
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diff --git a/datasets/CMS_Maryland_AGB_Canopy_1320_1.json b/datasets/CMS_Maryland_AGB_Canopy_1320_1.json
index 690cfa88c..f3d8fcef3 100644
--- a/datasets/CMS_Maryland_AGB_Canopy_1320_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/CMS_Methane_Emissions_Boston_1291_1.json b/datasets/CMS_Methane_Emissions_Boston_1291_1.json
index 5ce2a6867..d7b0b2c65 100644
--- a/datasets/CMS_Methane_Emissions_Boston_1291_1.json
+++ b/datasets/CMS_Methane_Emissions_Boston_1291_1.json
@@ -42,7 +42,7 @@
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index 902d8781c..fb1edaedd 100644
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index 424b34ce4..5b4df8216 100644
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index ab56cb0c1..9f8a8f4b8 100644
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diff --git a/datasets/CMS_Pilot_Biomass_1257_1.json b/datasets/CMS_Pilot_Biomass_1257_1.json
index afcbf998a..15e067dd3 100644
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diff --git a/datasets/CMS_SABGOM_Model_Simulations_1510_1.json b/datasets/CMS_SABGOM_Model_Simulations_1510_1.json
index a91b699ac..d3a335c48 100644
--- a/datasets/CMS_SABGOM_Model_Simulations_1510_1.json
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index 278af093f..91a155bbe 100644
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index 56feaf249..6bc8a9d00 100644
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index b8980315a..efe68a1ac 100644
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diff --git a/datasets/CMS_Soil_CO2_Efflux_1298_1.json b/datasets/CMS_Soil_CO2_Efflux_1298_1.json
index 63091288f..1846a0985 100644
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index 1a655f103..bf2f4785d 100644
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index e85486e4e..e59bbc09d 100644
--- a/datasets/CMS_WRF_Model_Products_1338_1.json
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diff --git a/datasets/COMEX_AJAX_CO2_CH4_2347_1.json b/datasets/COMEX_AJAX_CO2_CH4_2347_1.json
index 249b9ed5f..5757a653e 100644
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diff --git a/datasets/COMEX_AVIRIS_Classic_Flights_2343_1.json b/datasets/COMEX_AVIRIS_Classic_Flights_2343_1.json
index ba29b7a48..5e7d10ba2 100644
--- a/datasets/COMEX_AVIRIS_Classic_Flights_2343_1.json
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@@ -42,7 +42,7 @@
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index 648a3bd38..18161ea13 100644
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index 9b50644b3..4053701b4 100644
--- a/datasets/COMEX_LongwaveInfrared_Imagery_2331_1.json
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index 23c08fccf..043bd79a4 100644
--- a/datasets/CStocks_Greenness_Mangroves_MX_1853_1.json
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index 61929883b..2d0df4dfa 100644
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index c7626949a..5bdba4e2b 100644
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index bb5421ddf..11c05280f 100644
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index 7e5d7ad88..399ec15dd 100644
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index 958687bbb..c1292cb64 100644
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index 59f74cef6..1c607e0b0 100644
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index e92f69b98..d6eb7834a 100644
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index e3d2afa11..f13585560 100644
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index 7946e8c18..c85601806 100644
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index 5d20b7507..17b7aff1d 100644
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index 0adf38327..069a6fac1 100644
--- a/datasets/Crops_SIF_VegIndices_IL_NE_2136_1.json
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index b58311df0..a701e5391 100644
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index f6256efe0..a6f699e3a 100644
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index aba6e611d..328d0a05f 100644
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index 65d0f97cd..c4888a387 100644
--- a/datasets/Daymet_SubDaily_Puerto_Rico_1977_1.json
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index 02a010fbf..ec7687fda 100644
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index 55e55f4c1..1c23dc5d4 100644
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index 63ab8e997..9bbb7bf63 100644
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index ec49deedd..5636c6230 100644
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index aafb72cfa..df3e1265b 100644
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index dc179d3ce..8bfa18616 100644
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index 431ef381e..2b2861733 100644
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index fbefa7755..abefec491 100644
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index 85362940d..523b41036 100644
--- a/datasets/DeltaX_BG_Root_Stable_Isotopes_2193_1.json
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index 8a38c0f98..07459541d 100644
--- a/datasets/DeltaX_DEM_MRD_LA_2181_1.json
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index 71693a40e..8b219bc33 100644
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@@ -42,7 +42,7 @@
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index d7e325a7e..a9f49bdbc 100644
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diff --git a/datasets/DeltaX_Delft3D_396_Terrebonne_2314_1.json b/datasets/DeltaX_Delft3D_396_Terrebonne_2314_1.json
index 7d736df77..44ffebb08 100644
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@@ -42,7 +42,7 @@
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index a3ec01480..095532b7c 100644
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index 1df308080..107340568 100644
--- a/datasets/DeltaX_Delft3D_421_Terrebonne_2304_1.json
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index 272ef9719..b655a09f0 100644
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index 112441058..0b177b395 100644
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diff --git a/datasets/DeltaX_Ecogeomorphic_Products_2108_1.json b/datasets/DeltaX_Ecogeomorphic_Products_2108_1.json
index ac68bb9fb..9a4d85408 100644
--- a/datasets/DeltaX_Ecogeomorphic_Products_2108_1.json
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@@ -42,7 +42,7 @@
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index 65c23d5c6..6107b5534 100644
--- a/datasets/DeltaX_Feldspar_Sediment_V3_2290_3.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/DeltaX_Foliar_Stable_Isotopes_2194_1.json b/datasets/DeltaX_Foliar_Stable_Isotopes_2194_1.json
index 4ff205392..e0d9c6b80 100644
--- a/datasets/DeltaX_Foliar_Stable_Isotopes_2194_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/DeltaX_H2O_Surface_Elevation_2086_1.json b/datasets/DeltaX_H2O_Surface_Elevation_2086_1.json
index 8dc714fba..13f7b7363 100644
--- a/datasets/DeltaX_H2O_Surface_Elevation_2086_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/DeltaX_Herb_WetlandSoil_V3_2239_3.json b/datasets/DeltaX_Herb_WetlandSoil_V3_2239_3.json
index c6a6cfeb1..233ba43c2 100644
--- a/datasets/DeltaX_Herb_WetlandSoil_V3_2239_3.json
+++ b/datasets/DeltaX_Herb_WetlandSoil_V3_2239_3.json
@@ -42,7 +42,7 @@
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index bb628552d..2e86ae034 100644
--- a/datasets/DeltaX_Insitu_POC_2073_1.json
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index 97604abe8..c8fa479b9 100644
--- a/datasets/DeltaX_Insitu_Reflectance_V3_2153_3.json
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index 33d3ffce8..ea1a5164e 100644
--- a/datasets/DeltaX_Insitu_WQ_Indicators_V2_2080_2.json
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diff --git a/datasets/DeltaX_Island_Channel_Model_2106_1.json b/datasets/DeltaX_Island_Channel_Model_2106_1.json
index fa623b55c..481369068 100644
--- a/datasets/DeltaX_Island_Channel_Model_2106_1.json
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@@ -42,7 +42,7 @@
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index 87b8f2829..2f01be2e2 100644
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index 640f2e0cc..449081230 100644
--- a/datasets/DeltaX_L1_AVIRIS_Radiance_1987_1.json
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index 811d5fc59..9bd646e0a 100644
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index f54f417d1..dd8ab7e52 100644
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index 1f004dc43..f8a9c52d8 100644
--- a/datasets/DeltaX_L2A_AVIRIS-NG_BRDF_V2_2139_2.json
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index 4bee32b2b..e5eda287c 100644
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index 606c7bdac..da21a86cd 100644
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index 46866712c..bc12d4e65 100644
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index 9aadfd395..46c8f8266 100644
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@@ -42,7 +42,7 @@
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index d2ad8d7a1..5d95eb414 100644
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index 9f3be6220..ccda94938 100644
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index 8afc96d2e..352a1d560 100644
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index 578b8380d..436206533 100644
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diff --git a/datasets/DeltaX_LandAccretionMap_WLD_2308_1.json b/datasets/DeltaX_LandAccretionMap_WLD_2308_1.json
index b03fa9222..950cf0a9e 100644
--- a/datasets/DeltaX_LandAccretionMap_WLD_2308_1.json
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index 462fae250..a195cd50c 100644
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index da7626cc1..65e9a7760 100644
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index 41e050fb0..22cb43e41 100644
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index 86fe64305..2702583e0 100644
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index e70a764e3..b06997926 100644
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index a9b2afdd0..dbe2c4a72 100644
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index d5a1534a5..c024c8c82 100644
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index c771ff39a..446ee0619 100644
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index 17107514c..58df78105 100644
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diff --git a/datasets/EDM_SA_Vegetation_1149_1.json b/datasets/EDM_SA_Vegetation_1149_1.json
index c6c5b7b2a..2455f747e 100644
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diff --git a/datasets/EDM_US_Carbon_1160_1.json b/datasets/EDM_US_Carbon_1160_1.json
index 4d07943d0..34452aad6 100644
--- a/datasets/EDM_US_Carbon_1160_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/EF_Data_Mexico_1693_1.json b/datasets/EF_Data_Mexico_1693_1.json
index aac80f6ce..92d424007 100644
--- a/datasets/EF_Data_Mexico_1693_1.json
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index f51d05fcf..9ca2c979d 100644
--- a/datasets/EM27_XCO2_XCH4_XCO_AK_1831_1.json
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@@ -42,7 +42,7 @@
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index c8fcb4fab..a9d58bcd0 100644
--- a/datasets/ENVISAT_SCIAMACHY_SIF_1871_1.json
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diff --git a/datasets/ERS2_GOME_SIF_1758_1.json b/datasets/ERS2_GOME_SIF_1758_1.json
index 0779d7572..6c7e1a71c 100644
--- a/datasets/ERS2_GOME_SIF_1758_1.json
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@@ -42,7 +42,7 @@
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index f61ba2276..dfd099832 100644
--- a/datasets/EastAnglia10YearMean_549_1.json
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index cfd6a2e16..1710f981d 100644
--- a/datasets/EastAnglia30YearMean_550_1.json
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index 5bfd9b760..1ab4ac13d 100644
--- a/datasets/EastAngliaClimate_542_1.json
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diff --git a/datasets/EastAngliaPrecip_417_1.json b/datasets/EastAngliaPrecip_417_1.json
index ec6a82c7e..e1d769383 100644
--- a/datasets/EastAngliaPrecip_417_1.json
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diff --git a/datasets/Estimated_Biomass_Stock_Amazon_1648_1.json b/datasets/Estimated_Biomass_Stock_Amazon_1648_1.json
index 4d5ff8364..9ec8ea771 100644
--- a/datasets/Estimated_Biomass_Stock_Amazon_1648_1.json
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index 664a437ec..8a89eaf91 100644
--- a/datasets/FLOODAMA_903_1.json
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index d0077d42d..b82fddef2 100644
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index 02276dd96..f4c8ba84d 100644
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index 34112c5ec..2c79244dd 100644
--- a/datasets/FieldData_Alaska_Tundra_2177_1.json
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diff --git a/datasets/Fire_Emissions_Indonesia_2118_1.json b/datasets/Fire_Emissions_Indonesia_2118_1.json
index 0a4249231..4b0215727 100644
--- a/datasets/Fire_Emissions_Indonesia_2118_1.json
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diff --git a/datasets/ForestHt_Biomass_GEDI_TDX_2298_1.json b/datasets/ForestHt_Biomass_GEDI_TDX_2298_1.json
index 2d43e6628..23d188f74 100644
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@@ -95,7 +95,7 @@
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     "assets": {
         "browse": {
-            "href": "https://daac.ornl.gov/GEDI/guides/ForestHt_Biomass_GEDI_TDX_Fig1.jpg",
+            "href": "https://daac.ornl.gov/VEGETATION/guides/ForestHt_Biomass_GEDI_TDX_Fig1.jpg",
             "type": "image/jpeg",
             "title": "Download ForestHt_Biomass_GEDI_TDX_Fig1.jpg",
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@@ -103,7 +103,7 @@
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         },
         "thumbnail": {
-            "href": "https://daac.ornl.gov/GEDI/guides/ForestHt_Biomass_GEDI_TDX_Fig1.jpg",
+            "href": "https://daac.ornl.gov/VEGETATION/guides/ForestHt_Biomass_GEDI_TDX_Fig1.jpg",
             "title": "Thumbnail",
             "description": "Forest canopy height from GEDI-TDX data fusion over Gabon, Mexico, French Guiana and the Amazon Basin. Source: height_mexico_25m.tif, height_gabon_25m.tif, height_frenchguiana_25m.tif, height_amazon_25m.tif",
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+            "href": "https://daac.ornl.gov/daacdata/global_vegetation/ForestHt_Biomass_GEDI_TDX/data/",
             "title": "Direct Download",
             "description": "This link allows direct data access via Earthdata login",
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@@ -126,9 +126,9 @@
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-            "title": "ornl_cumulus_prod_protected_gedi_ForestHt_Biomass_GEDI_TDX_",
+        "s3_ornl_cumulus_prod_protected_global_vegetation_ForestHt_Biomass_GEDI_TDX_": {
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+            "title": "ornl_cumulus_prod_protected_global_vegetation_ForestHt_Biomass_GEDI_TDX_",
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diff --git a/datasets/Forest_AGB_NW_USA_1766_1.json b/datasets/Forest_AGB_NW_USA_1766_1.json
index bddccfdf9..654318d50 100644
--- a/datasets/Forest_AGB_NW_USA_1766_1.json
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diff --git a/datasets/Forest_Carbon_Priority_1803_1.json b/datasets/Forest_Carbon_Priority_1803_1.json
index ae11f4a17..a012b40b3 100644
--- a/datasets/Forest_Carbon_Priority_1803_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/Forest_Disturbance_Intensity_2059_1.json b/datasets/Forest_Disturbance_Intensity_2059_1.json
index c2d1f762a..b70894e78 100644
--- a/datasets/Forest_Disturbance_Intensity_2059_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/Forest_Inventory_Acre_Brazil_1654_1.json b/datasets/Forest_Inventory_Acre_Brazil_1654_1.json
index 7ef3411a7..d807de5fc 100644
--- a/datasets/Forest_Inventory_Acre_Brazil_1654_1.json
+++ b/datasets/Forest_Inventory_Acre_Brazil_1654_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/Forest_Inventory_Brazil_2007_1.json b/datasets/Forest_Inventory_Brazil_2007_1.json
index 750bdd7cd..8f016805a 100644
--- a/datasets/Forest_Inventory_Brazil_2007_1.json
+++ b/datasets/Forest_Inventory_Brazil_2007_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/Forest_Inventory_Data_Brazil_1563_1.json b/datasets/Forest_Inventory_Data_Brazil_1563_1.json
index 20741f6d0..063d07051 100644
--- a/datasets/Forest_Inventory_Data_Brazil_1563_1.json
+++ b/datasets/Forest_Inventory_Data_Brazil_1563_1.json
@@ -42,7 +42,7 @@
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index 7aa14fce4..7d36cdaba 100644
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index bc99635e2..e550da407 100644
--- a/datasets/Forested_Areas_Amazonas_Brazil_1515_1.json
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index 7efd21c69..315cf0db0 100644
--- a/datasets/Forested_Areas_Para_Brazil_1514_1.json
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index 7cf6b1016..0376c360d 100644
--- a/datasets/Freeze_Thaw_NorthernHemisphere_2323_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/GCAM_Land_Cover_2005-2095_1216_1.json b/datasets/GCAM_Land_Cover_2005-2095_1216_1.json
index bd38c9b19..5ce33b4aa 100644
--- a/datasets/GCAM_Land_Cover_2005-2095_1216_1.json
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@@ -42,7 +42,7 @@
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index 40d025fc0..141ec8854 100644
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@@ -42,7 +42,7 @@
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diff --git a/datasets/GEDI_Fusion_Structure_2236_1.json b/datasets/GEDI_Fusion_Structure_2236_1.json
index 759162837..027cccba8 100644
--- a/datasets/GEDI_Fusion_Structure_2236_1.json
+++ b/datasets/GEDI_Fusion_Structure_2236_1.json
@@ -42,7 +42,7 @@
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@@ -103,7 +103,7 @@
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-            "href": "https://daac.ornl.gov/GEDI/guides/GEDI_Fusion_Structure_Fig1.png",
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@@ -111,7 +111,7 @@
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-            "href": "https://daac.ornl.gov/daacdata/gedi/GEDI_Fusion_Structure/",
+            "href": "https://daac.ornl.gov/daacdata/global_vegetation/GEDI_Fusion_Structure/data/",
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@@ -126,9 +126,9 @@
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diff --git a/datasets/GEDI_HighQuality_Shots_Rasters_2339_1.json b/datasets/GEDI_HighQuality_Shots_Rasters_2339_1.json
index 39c618c1b..4ea625fc2 100644
--- a/datasets/GEDI_HighQuality_Shots_Rasters_2339_1.json
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@@ -42,7 +42,7 @@
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index 65ac4bb41..359c4f8f5 100644
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@@ -103,7 +103,7 @@
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-            "href": "https://daac.ornl.gov/GEDI/guides/GEDI_ICESAT2_Global_Veg_Height_Fig1.jpg",
+            "href": "https://daac.ornl.gov/VEGETATION/guides/GEDI_ICESAT2_Global_Veg_Height_Fig1.jpg",
             "title": "Thumbnail",
             "description": "GEDI RH98 values (0-60 m) at 100-, 200-, 500-, and 1000-m resolutions around 8.9097 degrees N, -83.0326 degrees E.",
             "roles": [
@@ -111,7 +111,7 @@
             ]
         },
         "ornl": {
-            "href": "https://daac.ornl.gov/daacdata/gedi/GEDI_ICESAT2_Global_Veg_Height/",
+            "href": "https://daac.ornl.gov/daacdata/global_vegetation/GEDI_ICESAT2_Global_Veg_Height/data/",
             "title": "Direct Download",
             "description": "This link allows direct data access via Earthdata login",
             "roles": [
@@ -126,9 +126,9 @@
                 "metadata"
             ]
         },
-        "s3_ornl_cumulus_prod_protected_gedi_GEDI_ICESAT2_Global_Veg_Height_": {
-            "href": "s3://ornl-cumulus-prod-protected/gedi/GEDI_ICESAT2_Global_Veg_Height/",
-            "title": "ornl_cumulus_prod_protected_gedi_GEDI_ICESAT2_Global_Veg_Height_",
+        "s3_ornl_cumulus_prod_protected_global_vegetation_GEDI_ICESAT2_Global_Veg_Height_": {
+            "href": "s3://ornl-cumulus-prod-protected/global_vegetation/GEDI_ICESAT2_Global_Veg_Height/",
+            "title": "ornl_cumulus_prod_protected_global_vegetation_GEDI_ICESAT2_Global_Veg_Height_",
             "roles": [
                 "data"
             ]
diff --git a/datasets/GEDI_L3_LandSurface_Metrics_V2_1952_2.json b/datasets/GEDI_L3_LandSurface_Metrics_V2_1952_2.json
index 29f728485..c0bd326b1 100644
--- a/datasets/GEDI_L3_LandSurface_Metrics_V2_1952_2.json
+++ b/datasets/GEDI_L3_LandSurface_Metrics_V2_1952_2.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/GEDI_L4A_AGB_Density_GW_2028_1.1.json b/datasets/GEDI_L4A_AGB_Density_GW_2028_1.1.json
index 67d377f7e..fe8248f1b 100644
--- a/datasets/GEDI_L4A_AGB_Density_GW_2028_1.1.json
+++ b/datasets/GEDI_L4A_AGB_Density_GW_2028_1.1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/GEDI_L4A_AGB_Density_V2_1_2056_2.1.json b/datasets/GEDI_L4A_AGB_Density_V2_1_2056_2.1.json
index 20202daf3..8fabedebb 100644
--- a/datasets/GEDI_L4A_AGB_Density_V2_1_2056_2.1.json
+++ b/datasets/GEDI_L4A_AGB_Density_V2_1_2056_2.1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/GEDI_L4B_Country_Biomass_2321_1.json b/datasets/GEDI_L4B_Country_Biomass_2321_1.json
index 42f3dc379..4b55caae5 100644
--- a/datasets/GEDI_L4B_Country_Biomass_2321_1.json
+++ b/datasets/GEDI_L4B_Country_Biomass_2321_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/GEDI_L4B_Gridded_Biomass_V2_1_2299_2.1.json b/datasets/GEDI_L4B_Gridded_Biomass_V2_1_2299_2.1.json
index eff25dd6b..18f5d68d1 100644
--- a/datasets/GEDI_L4B_Gridded_Biomass_V2_1_2299_2.1.json
+++ b/datasets/GEDI_L4B_Gridded_Biomass_V2_1_2299_2.1.json
@@ -42,7 +42,7 @@
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index 80aaaef90..14a8e787d 100644
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index 00afd2008..a1ff76868 100644
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diff --git a/datasets/GPP_CONUS_TROPOMI_1875_1.json b/datasets/GPP_CONUS_TROPOMI_1875_1.json
index f28346e30..a3c2885cc 100644
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index 4fd6dc684..4f5864a38 100644
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index 6208051d0..f19ad2d3b 100644
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index c71849335..1d0e01ec5 100644
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index 25aeb6d09..fab5035ca 100644
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index f9195132d..fb9effdd1 100644
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index 3476015db..e78c6a761 100644
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index 5560de88a..4fd1aa858 100644
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index 90574909b..1aecfff60 100644
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index 978adc5f4..034fbf0e0 100644
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index 5d3106235..312925504 100644
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index 1f5d7f1e2..f8bfdfcac 100644
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index dccbb8ba4..c48de1e58 100644
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diff --git a/datasets/HWSD_1247_1.json b/datasets/HWSD_1247_1.json
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index 348466eb9..db7131e09 100644
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index 8dc253d71..764372dce 100644
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index ba727c353..1a1e867da 100644
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index e679263fe..b394b7b16 100644
--- a/datasets/Idaho_field_shrub_data_1503_1.json
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index e43b394a7..14e32904f 100644
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diff --git a/datasets/InSAR_Prudhoe_Bay_1267_1.json b/datasets/InSAR_Prudhoe_Bay_1267_1.json
index a5dd26ebd..9b0a84bff 100644
--- a/datasets/InSAR_Prudhoe_Bay_1267_1.json
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@@ -42,7 +42,7 @@
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index 22fa618ff..004119cf9 100644
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index ed7930529..a9c947fab 100644
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diff --git a/datasets/LAI_Africa_2325_1.json b/datasets/LAI_Africa_2325_1.json
index 39de678c6..20a3f6fc3 100644
--- a/datasets/LAI_Africa_2325_1.json
+++ b/datasets/LAI_Africa_2325_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/LAI_Canada_816_1.json b/datasets/LAI_Canada_816_1.json
index b429b90b2..b5e3deb65 100644
--- a/datasets/LAI_Canada_816_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/LAI_VALERI_Canada_829_1.json b/datasets/LAI_VALERI_Canada_829_1.json
index cd33bcca3..248885059 100644
--- a/datasets/LAI_VALERI_Canada_829_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/LC01_Boundaries_Ecuador_1057_1.json b/datasets/LC01_Boundaries_Ecuador_1057_1.json
index f7becd6ca..05c349bb5 100644
--- a/datasets/LC01_Boundaries_Ecuador_1057_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/LC01_Cities_Communities_Roads_1058_1.json b/datasets/LC01_Cities_Communities_Roads_1058_1.json
index 7fb206d61..b96c6a93c 100644
--- a/datasets/LC01_Cities_Communities_Roads_1058_1.json
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index 9926f99da..fd154b430 100644
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index 53cad72c5..d37c75ed1 100644
--- a/datasets/LC01_Hydrography_Edaphology_NEC_1059_1.json
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index eb4b2ce8d..3ae0107ac 100644
--- a/datasets/LC01_LULC_Classes_Ecuador_ISA_1084_1.json
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diff --git a/datasets/LC01_Landsat_1187_1.json b/datasets/LC01_Landsat_1187_1.json
index 85a7609b1..262230419 100644
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@@ -42,7 +42,7 @@
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index df7aeb181..ecd2d8f4a 100644
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index 2fdf8fe26..22c0b36fb 100644
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index 791e46725..579b9134b 100644
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diff --git a/datasets/LC02_GOES8_Hotpixel_Acre_1092_1.json b/datasets/LC02_GOES8_Hotpixel_Acre_1092_1.json
index b36792867..b3cf50e95 100644
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diff --git a/datasets/LC02_MAP_Fire_Indicators_1044_1.json b/datasets/LC02_MAP_Fire_Indicators_1044_1.json
index b0cc93f9a..8b17dd5c9 100644
--- a/datasets/LC02_MAP_Fire_Indicators_1044_1.json
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@@ -42,7 +42,7 @@
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index 74fa813be..27abc5c03 100644
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index c6a6f9eba..97cd56cd1 100644
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index 77b43bee9..ab8c92c7c 100644
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index 3ff13159d..f31615d23 100644
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index ac7d13d49..51836b42e 100644
--- a/datasets/LC07_Amazon_Wetlands_1284_2.json
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@@ -42,7 +42,7 @@
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index da8af80ea..42e268eaa 100644
--- a/datasets/LC07_Bathymetry_Curuai_999_1.json
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index 9d111f214..a9acdb3f9 100644
--- a/datasets/LC07_Biomass_LGrande_1127_1.json
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diff --git a/datasets/LC07_Curuai_chl_1134_1.json b/datasets/LC07_Curuai_chl_1134_1.json
index 49d5fce9f..5f07935a0 100644
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@@ -42,7 +42,7 @@
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diff --git a/datasets/LC07_Lake_Chlorophyll_MODIS_1000_1.json b/datasets/LC07_Lake_Chlorophyll_MODIS_1000_1.json
index 8418359a1..95fed1ff4 100644
--- a/datasets/LC07_Lake_Chlorophyll_MODIS_1000_1.json
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index 59d09236a..5e41ab94c 100644
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index 93c5d41b6..fc003623a 100644
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index 460588ee5..c9625dd03 100644
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index 08b788e2e..bba9fb12c 100644
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index bb1e7db60..52d71cb57 100644
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index 06412c600..0529ea84f 100644
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index f56ea0f53..5354b4835 100644
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index eda7281d4..e9f6db7e3 100644
--- a/datasets/LC09_Transition_Matricies_1098_1.json
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index 8a8c12a51..bb8119b9c 100644
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index ec0bf0e30..f0e93d25a 100644
--- a/datasets/LC10_Landsat_ETM_846_1.json
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diff --git a/datasets/LC13_GIS_Cauaxi_890_1.json b/datasets/LC13_GIS_Cauaxi_890_1.json
index ee9eb5bbd..f779e9230 100644
--- a/datasets/LC13_GIS_Cauaxi_890_1.json
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@@ -42,7 +42,7 @@
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index 8d3c89029..d7d8b78cc 100644
--- a/datasets/LC13_GIS_Juruena_888_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/LC13_GIS_Tapajos_893_1.json b/datasets/LC13_GIS_Tapajos_893_1.json
index bde64736d..f6bfc7d26 100644
--- a/datasets/LC13_GIS_Tapajos_893_1.json
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diff --git a/datasets/LC14_Aboveground_Prod_1196_1.json b/datasets/LC14_Aboveground_Prod_1196_1.json
index 1b7dcd29f..975f15971 100644
--- a/datasets/LC14_Aboveground_Prod_1196_1.json
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diff --git a/datasets/LC14_Amazon_Scenarios_1153_1.json b/datasets/LC14_Amazon_Scenarios_1153_1.json
index 514a9d3a2..24ce5ee74 100644
--- a/datasets/LC14_Amazon_Scenarios_1153_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/LC14_REE_SLA_1211_1.json b/datasets/LC14_REE_SLA_1211_1.json
index c28e49eff..338ef8de7 100644
--- a/datasets/LC14_REE_SLA_1211_1.json
+++ b/datasets/LC14_REE_SLA_1211_1.json
@@ -42,7 +42,7 @@
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index 9b6c50779..48b83dd68 100644
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index ea0782ef0..bb85bf628 100644
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diff --git a/datasets/LC15_AGLB_Distribution_Map_908_1.json b/datasets/LC15_AGLB_Distribution_Map_908_1.json
index 6ba38277c..34e691dd8 100644
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index f6bb12dab..da047b5f8 100644
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diff --git a/datasets/LC15_MODIS_TreeCover_1035_1.json b/datasets/LC15_MODIS_TreeCover_1035_1.json
index 5425acd4a..7a68bcc06 100644
--- a/datasets/LC15_MODIS_TreeCover_1035_1.json
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index a03d35e1d..74e50c54d 100644
--- a/datasets/LC15_Roughness_Map_1182_1.json
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diff --git a/datasets/LC15_SPOT_Metrics_1239_1.json b/datasets/LC15_SPOT_Metrics_1239_1.json
index a7922f86e..09b524094 100644
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index b6424e159..300ecc13a 100644
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diff --git a/datasets/LC18_Hyperion_889_1.json b/datasets/LC18_Hyperion_889_1.json
index c3fa2aef3..be07a4b1e 100644
--- a/datasets/LC18_Hyperion_889_1.json
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diff --git a/datasets/LC19_Field_2002_1261_1.json b/datasets/LC19_Field_2002_1261_1.json
index 8768f95ea..ef658f1c0 100644
--- a/datasets/LC19_Field_2002_1261_1.json
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@@ -42,7 +42,7 @@
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index 1d97ea031..d0318f806 100644
--- a/datasets/LC21_Foliar_Nutrients_1234_1.json
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index c08c8a119..0088dcae7 100644
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diff --git a/datasets/LC21_Selective_Logging_1172_1.json b/datasets/LC21_Selective_Logging_1172_1.json
index 5a27cc8f4..21b26a39e 100644
--- a/datasets/LC21_Selective_Logging_1172_1.json
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diff --git a/datasets/LC21_Soil_Characteristics_1236_1.json b/datasets/LC21_Soil_Characteristics_1236_1.json
index 975e4e9ba..6c84ebb20 100644
--- a/datasets/LC21_Soil_Characteristics_1236_1.json
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diff --git a/datasets/LC22_MODIS_Field_Val_2004_1262_1.json b/datasets/LC22_MODIS_Field_Val_2004_1262_1.json
index 09efb1e85..2575a69c3 100644
--- a/datasets/LC22_MODIS_Field_Val_2004_1262_1.json
+++ b/datasets/LC22_MODIS_Field_Val_2004_1262_1.json
@@ -42,7 +42,7 @@
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index ac23d4ed0..b24c7881e 100644
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index 65853e0bb..73d2b9e05 100644
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index 739626f64..676a4977e 100644
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index 0896cbe40..98856772d 100644
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index 30db67f10..0ff541831 100644
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index b10ddc776..67347ce3d 100644
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index 1216ae6c1..41234b29f 100644
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index 3eeb6418f..325c9bd89 100644
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index 492fe86ea..b72a9558d 100644
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index f6940a928..bea035df5 100644
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index ec14549b7..f1b5c4842 100644
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index 93edb4c36..e7a86d53a 100644
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index ccd09ff49..952c5b6fc 100644
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index 2330be55f..82086ee01 100644
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diff --git a/datasets/LC35_Landsat7_Fire_Masks_1071_1.json b/datasets/LC35_Landsat7_Fire_Masks_1071_1.json
index 2cb4dee6c..e49bb60e5 100644
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@@ -42,7 +42,7 @@
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index cd6384e65..1ea733d27 100644
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index 94e90c1cf..75b1e6d59 100644
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index d34867316..febf435e6 100644
--- a/datasets/LPRM_TMI_NT_SOILM3_001.json
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index 1076810d0..fbf014484 100644
--- a/datasets/LPRM_TMI_SOILM2_001.json
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index 5faef8fad..71905a64a 100644
--- a/datasets/LPRM_WINDSAT_DY_SOILM3_001.json
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diff --git a/datasets/LPRM_WINDSAT_NT_SOILM3_001.json b/datasets/LPRM_WINDSAT_NT_SOILM3_001.json
index 59709feee..d484e6c12 100644
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index 5e5147f8d..3b315dc19 100644
--- a/datasets/LPRM_WINDSAT_SOILM2_001.json
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diff --git a/datasets/LSM_807_1.json b/datasets/LSM_807_1.json
index 079ebc591..7f03dbbf0 100644
--- a/datasets/LSM_807_1.json
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index b1fec9d21..30c2d9ee7 100644
--- a/datasets/LUH2_GCB2019_1851_1.json
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index b36194326..d8e870030 100644
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diff --git a/datasets/LaSelva_Land_Use_1312_1.json b/datasets/LaSelva_Land_Use_1312_1.json
index 4450e4c4f..4a302053d 100644
--- a/datasets/LaSelva_Land_Use_1312_1.json
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index f97e3eeca..971c36a32 100644
--- a/datasets/LakeBathymetry_Model_NSlope_AK_2243_1.json
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index f24794a39..70a7d2805 100644
--- a/datasets/Land_Use_Harmonization_V1_1248_1.json
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index 100b3567d..6d18f4493 100644
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index 251710c51..e24dc4613 100644
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index ceb9b90c0..b8514e560 100644
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diff --git a/datasets/LiDAR_Forest_Inventory_Brazil_1644_1.json b/datasets/LiDAR_Forest_Inventory_Brazil_1644_1.json
index 371f8b10a..20b8edb1f 100644
--- a/datasets/LiDAR_Forest_Inventory_Brazil_1644_1.json
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@@ -42,7 +42,7 @@
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index 35982abe9..8f07a9dac 100644
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index 7d2421c71..ad034a30e 100644
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index 48bbea01e..b50bb0627 100644
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index ff74a73f3..85f66d59b 100644
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index ea1eb9ac2..330c0702a 100644
--- a/datasets/MASTER_DFRC_July-Aug_2001_V2_2144_2.json
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@@ -42,7 +42,7 @@
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index 90d25081d..a1b88d97d 100644
--- a/datasets/MASTER_DFRC_July_2004_2039_1.json
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@@ -42,7 +42,7 @@
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index 92580c0ee..dfd18681d 100644
--- a/datasets/MASTER_DFRC_June_1999_2100_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/MASTER_DFRC_June_2011_1976_1.json b/datasets/MASTER_DFRC_June_2011_1976_1.json
index 54f197491..3bdfc81bb 100644
--- a/datasets/MASTER_DFRC_June_2011_1976_1.json
+++ b/datasets/MASTER_DFRC_June_2011_1976_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/MASTER_DFRC_May-June_2008_2011_1.json b/datasets/MASTER_DFRC_May-June_2008_2011_1.json
index a710c9e12..9fc428aaf 100644
--- a/datasets/MASTER_DFRC_May-June_2008_2011_1.json
+++ b/datasets/MASTER_DFRC_May-June_2008_2011_1.json
@@ -42,7 +42,7 @@
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index 3208e927b..e9ed0a73f 100644
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index 9b325b650..7f7aba695 100644
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index 5116e7051..e13cee1ce 100644
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index b70b4ed86..e6fdb4e0d 100644
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diff --git a/datasets/MASTER_DFRC_September_2002_2064_1.json b/datasets/MASTER_DFRC_September_2002_2064_1.json
index b7f6a56c2..d23d8699c 100644
--- a/datasets/MASTER_DFRC_September_2002_2064_1.json
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@@ -42,7 +42,7 @@
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index 536ffc323..760c4034c 100644
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diff --git a/datasets/MASTER_GEMx_Spring_2024_2370_1.json b/datasets/MASTER_GEMx_Spring_2024_2370_1.json
new file mode 100644
index 000000000..67fa3a816
--- /dev/null
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@@ -0,0 +1,151 @@
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+            "type": "text/html",
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+        {
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+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3255928163-ORNL_CLOUD.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCB3ZXN0ZXJuIHVzLCBtYXksIDIwMDRcIixcIk9STkxfQ0xPVURcIixcIk1BU1RFUl9SU0xfTWF5XzIwMDRfMjA0MVwiLFwiMVwiLDI3MzE3NDg2MTYsMl0iLCJ1bW0iOiJbXCJtYXN0ZXI6IGFpcmJvcm5lIHNjaWVuY2UsIHdlc3Rlcm4gdXMsIG1heSwgMjAwNFwiLFwiT1JOTF9DTE9VRFwiLFwiTUFTVEVSX1JTTF9NYXlfMjAwNF8yMDQxXCIsXCIxXCIsMjczMTc0ODYxNiwyXSJ9/MASTER_GEMx_Spring_2024_2370_1",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD",
+            "type": "application/json",
+            "title": "ORNL_CLOUD STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCB3ZXN0ZXJuIHVzLCBtYXksIDIwMDRcIixcIk9STkxfQ0xPVURcIixcIk1BU1RFUl9SU0xfTWF5XzIwMDRfMjA0MVwiLFwiMVwiLDI3MzE3NDg2MTYsMl0iLCJ1bW0iOiJbXCJtYXN0ZXI6IGFpcmJvcm5lIHNjaWVuY2UsIHdlc3Rlcm4gdXMsIG1heSwgMjAwNFwiLFwiT1JOTF9DTE9VRFwiLFwiTUFTVEVSX1JTTF9NYXlfMjAwNF8yMDQxXCIsXCIxXCIsMjczMTc0ODYxNiwyXSJ9/MASTER_GEMx_Spring_2024_2370_1/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "ORNL_CLOUD",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "MASTER: Geological Earth Mapping Experiment (GEMx), Spring 2024",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -124.26,
+                    31.14,
+                    -108.08,
+                    43.2
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2024-04-02T00:00:01Z",
+                    "2024-06-28T23:23:59Z"
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://daac.ornl.gov/MASTER/guides/MASTER_GEMx_Spring_2024_Fig1.jpg",
+            "type": "image/jpeg",
+            "title": "Download MASTER_GEMx_Spring_2024_Fig1.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://daac.ornl.gov/MASTER/guides/MASTER_GEMx_Spring_2024_Fig1.jpg",
+            "title": "Thumbnail",
+            "description": "Single band images and an RGB composite image from flight track 1 acquired on 02 April 2024 over Primm, Nevada, US (approx. 35.60 lat, -115.40 lon). Source: MASTERL1B_2493400_01_20240402_1859_1902_V01.jpg",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "ornl": {
+            "href": "https://daac.ornl.gov/daacdata/master/MASTER_GEMx_Spring_2024/data/",
+            "title": "Direct Download",
+            "description": "This link allows direct data access via Earthdata login",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://doi.org/10.3334/ORNLDAAC/2370",
+            "title": "Provider Metadata",
+            "description": "Data set Landing Page DOI URL",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_ornl_cumulus_prod_protected_master_MASTER_GEMx_Spring_2024_": {
+            "href": "s3://ornl-cumulus-prod-protected/master/MASTER_GEMx_Spring_2024/",
+            "title": "ornl_cumulus_prod_protected_master_MASTER_GEMx_Spring_2024_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.ornldaac.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.ornldaac.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/MASTER_GEMx_Summer_2023_2319_1.json b/datasets/MASTER_GEMx_Summer_2023_2319_1.json
index 3b15b727b..a79aff105 100644
--- a/datasets/MASTER_GEMx_Summer_2023_2319_1.json
+++ b/datasets/MASTER_GEMx_Summer_2023_2319_1.json
@@ -42,7 +42,7 @@
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         {
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-            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCB3ZXN0ZXJuIHVzLCBvY3RvYmVyLCAyMDAzXCIsXCJPUk5MX0NMT1VEXCIsXCJNQVNURVJfREZSQ19PY3RvYmVyXzIwMDNfMjA0NFwiLFwiMVwiLDI3MzE3NTA5ODMsMl0iLCJ1bW0iOiJbXCJtYXN0ZXI6IGFpcmJvcm5lIHNjaWVuY2UsIHdlc3Rlcm4gdXMsIG9jdG9iZXIsIDIwMDNcIixcIk9STkxfQ0xPVURcIixcIk1BU1RFUl9ERlJDX09jdG9iZXJfMjAwM18yMDQ0XCIsXCIxXCIsMjczMTc1MDk4MywyXSJ9/MASTER_GEMx_Summer_2023_2319_1",
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         },
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@@ -53,7 +53,7 @@
         },
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diff --git a/datasets/MASTER_Hawaii_October_2001_V2_2142_2.json b/datasets/MASTER_Hawaii_October_2001_V2_2142_2.json
index cc5fb04e5..aeafb7294 100644
--- a/datasets/MASTER_Hawaii_October_2001_V2_2142_2.json
+++ b/datasets/MASTER_Hawaii_October_2001_V2_2142_2.json
@@ -42,7 +42,7 @@
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-            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCBjYWxpZm9ybmlhLW5ldmFkYS11dGFoLCBqdW5lLCAyMDAyXCIsXCJPUk5MX0NMT1VEXCIsXCJNQVNURVJfUlNMX0p1bmVfMjAwMl8yMDY3XCIsXCIxXCIsMjczMTc2MTgzOCwyXSIsInVtbSI6IltcIm1hc3RlcjogYWlyYm9ybmUgc2NpZW5jZSwgY2FsaWZvcm5pYS1uZXZhZGEtdXRhaCwganVuZSwgMjAwMlwiLFwiT1JOTF9DTE9VRFwiLFwiTUFTVEVSX1JTTF9KdW5lXzIwMDJfMjA2N1wiLFwiMVwiLDI3MzE3NjE4MzgsMl0ifQ%3D%3D/MASTER_Hawaii_October_2001_V2_2142_2",
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@@ -53,7 +53,7 @@
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-            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCBjYWxpZm9ybmlhLW5ldmFkYS11dGFoLCBqdW5lLCAyMDAyXCIsXCJPUk5MX0NMT1VEXCIsXCJNQVNURVJfUlNMX0p1bmVfMjAwMl8yMDY3XCIsXCIxXCIsMjczMTc2MTgzOCwyXSIsInVtbSI6IltcIm1hc3RlcjogYWlyYm9ybmUgc2NpZW5jZSwgY2FsaWZvcm5pYS1uZXZhZGEtdXRhaCwganVuZSwgMjAwMlwiLFwiT1JOTF9DTE9VRFwiLFwiTUFTVEVSX1JTTF9KdW5lXzIwMDJfMjA2N1wiLFwiMVwiLDI3MzE3NjE4MzgsMl0ifQ%3D%3D/MASTER_Hawaii_October_2001_V2_2142_2/items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCBjYWxpZm9ybmlhLW5ldmFkYS1uZXcgbWV4aWNvLCBtYXksIDIwMDIsIHYyXCIsXCJPUk5MX0NMT1VEXCIsXCJNQVNURVJfUlNMX01heV8yMDAyX1YyXzIxNDhcIixcIjJcIiwyNzMxNzk4MjAwLDJdIiwidW1tIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCBjYWxpZm9ybmlhLW5ldmFkYS1uZXcgbWV4aWNvLCBtYXksIDIwMDIsIHYyXCIsXCJPUk5MX0NMT1VEXCIsXCJNQVNURVJfUlNMX01heV8yMDAyX1YyXzIxNDhcIixcIjJcIiwyNzMxNzk4MjAwLDJdIn0%3D/MASTER_Hawaii_October_2001_V2_2142_2/items",
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diff --git a/datasets/MASTER_Houston_2010_2126_1.json b/datasets/MASTER_Houston_2010_2126_1.json
index 5a05effe3..976ea890c 100644
--- a/datasets/MASTER_Houston_2010_2126_1.json
+++ b/datasets/MASTER_Houston_2010_2126_1.json
@@ -42,7 +42,7 @@
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         {
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-            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibWFzdGVyOiBhaXJib3JuZSBzY2llbmNlLCB3ZXN0ZXJuIHVzLCBvY3RvYmVyLCAyMDAzXCIsXCJPUk5MX0NMT1VEXCIsXCJNQVNURVJfREZSQ19PY3RvYmVyXzIwMDNfMjA0NFwiLFwiMVwiLDI3MzE3NTA5ODMsMl0iLCJ1bW0iOiJbXCJtYXN0ZXI6IGFpcmJvcm5lIHNjaWVuY2UsIHdlc3Rlcm4gdXMsIG9jdG9iZXIsIDIwMDNcIixcIk9STkxfQ0xPVURcIixcIk1BU1RFUl9ERlJDX09jdG9iZXJfMjAwM18yMDQ0XCIsXCIxXCIsMjczMTc1MDk4MywyXSJ9/MASTER_Houston_2010_2126_1",
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diff --git a/datasets/MASTER_Houston_2011_1972_1.json b/datasets/MASTER_Houston_2011_1972_1.json
index 0102f03c9..ba5fe1489 100644
--- a/datasets/MASTER_Houston_2011_1972_1.json
+++ b/datasets/MASTER_Houston_2011_1972_1.json
@@ -42,7 +42,7 @@
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         {
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diff --git a/datasets/MASTER_HyspIRI_EarlyS2013_V2_2146_2.json b/datasets/MASTER_HyspIRI_EarlyS2013_V2_2146_2.json
index 5c3d6e9ab..5878ffdc8 100644
--- a/datasets/MASTER_HyspIRI_EarlyS2013_V2_2146_2.json
+++ b/datasets/MASTER_HyspIRI_EarlyS2013_V2_2146_2.json
@@ -42,7 +42,7 @@
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index 20fed189f..00ea1284f 100644
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index ed5ddfd06..1ba518add 100644
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index bf9a91e1d..5b45c7b4f 100644
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index fac1cb2fb..a51d2ae94 100644
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index 124a4b7fb..75d4754c9 100644
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index 92a3555d4..2dc25db89 100644
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index b813b524e..0b0e97d29 100644
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index 85d490b1a..45db848e4 100644
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index 6437eadf5..060689424 100644
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diff --git a/datasets/MASTER_RSL_April_2008_2016_1.json b/datasets/MASTER_RSL_April_2008_2016_1.json
index caa66dfac..374b08986 100644
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diff --git a/datasets/MASTER_RSL_August_2001_V2_2143_2.json b/datasets/MASTER_RSL_August_2001_V2_2143_2.json
index c609c14b7..73ec369ae 100644
--- a/datasets/MASTER_RSL_August_2001_V2_2143_2.json
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@@ -42,7 +42,7 @@
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index 1344a3e74..742c14e94 100644
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index 05b2a497b..c7e79162d 100644
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index 2afe204d1..ab0f10ac5 100644
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diff --git a/datasets/MASTER_RSL_December_1998_2104_1.json b/datasets/MASTER_RSL_December_1998_2104_1.json
index d90f25c84..16a53c5b8 100644
--- a/datasets/MASTER_RSL_December_1998_2104_1.json
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@@ -42,7 +42,7 @@
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index a10b31a48..28d3a8c05 100644
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index cefcd1cc4..988c9f766 100644
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index f23365282..b02d5da7d 100644
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index d5740a7ae..1c268af77 100644
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diff --git a/datasets/MASTER_RSL_June_2000_2096_1.1.json b/datasets/MASTER_RSL_June_2000_2096_1.1.json
index 29484e575..1d377ef82 100644
--- a/datasets/MASTER_RSL_June_2000_2096_1.1.json
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@@ -42,7 +42,7 @@
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index 071149791..886a86e06 100644
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diff --git a/datasets/MASTER_RSL_March_2002_2068_1.json b/datasets/MASTER_RSL_March_2002_2068_1.json
index 51b70411e..f93eb679e 100644
--- a/datasets/MASTER_RSL_March_2002_2068_1.json
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index ddf82c9fe..f7b63b885 100644
--- a/datasets/MASTER_RSL_May_1999_2101_1.json
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index 192f5abfe..4b1aa8053 100644
--- a/datasets/MASTER_RSL_May_2001_V2_2145_2.json
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index cc70c8af0..9b40ba16b 100644
--- a/datasets/MASTER_RSL_May_2002_V2_2148_2.json
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index a7498aaf4..2ebf2d661 100644
--- a/datasets/MASTER_RSL_May_2004_2041_1.json
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diff --git a/datasets/MASTER_RSL_May_2006_2029_1.json b/datasets/MASTER_RSL_May_2006_2029_1.json
index dcbe2b1f3..7109bb511 100644
--- a/datasets/MASTER_RSL_May_2006_2029_1.json
+++ b/datasets/MASTER_RSL_May_2006_2029_1.json
@@ -42,7 +42,7 @@
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index b4cf2cd68..62ce78c82 100644
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index 0646ed3fc..edc6266c1 100644
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diff --git a/datasets/MASTER_RSL_October_2007_2013_1.json b/datasets/MASTER_RSL_October_2007_2013_1.json
index 4b3fe8873..027a2e380 100644
--- a/datasets/MASTER_RSL_October_2007_2013_1.json
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index f851bc42c..d687a8c46 100644
--- a/datasets/MASTER_RSL_October_2010_2127_1.json
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index e6043373a..adb9e119b 100644
--- a/datasets/MASTER_RSL_September_2005_2037_1.json
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diff --git a/datasets/MASTER_SARP_2009_1990_1.json b/datasets/MASTER_SARP_2009_1990_1.json
index a950abc8d..cebd7f221 100644
--- a/datasets/MASTER_SARP_2009_1990_1.json
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diff --git a/datasets/MASTER_SARP_2010_1989_1.json b/datasets/MASTER_SARP_2010_1989_1.json
index 9622b6be6..db6c914b9 100644
--- a/datasets/MASTER_SARP_2010_1989_1.json
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diff --git a/datasets/MASTER_SARP_2011_1974_1.json b/datasets/MASTER_SARP_2011_1974_1.json
index 8201d2b20..17b0a2e17 100644
--- a/datasets/MASTER_SARP_2011_1974_1.json
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@@ -42,7 +42,7 @@
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index 3f7c9253e..49100354e 100644
--- a/datasets/MASTER_SARP_2012_1983_1.json
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@@ -42,7 +42,7 @@
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index 509800faf..739b4b658 100644
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diff --git a/datasets/MASTER_SARP_2014_1961_1.json b/datasets/MASTER_SARP_2014_1961_1.json
index 95ef0fbb3..f848e9524 100644
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diff --git a/datasets/MASTER_SARP_2015_1958_1.json b/datasets/MASTER_SARP_2015_1958_1.json
index 5cf7ce8cd..0687fd750 100644
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diff --git a/datasets/MASTER_SARP_2016_1912_1.2.json b/datasets/MASTER_SARP_2016_1912_1.2.json
index 28f52e56c..be8576ae5 100644
--- a/datasets/MASTER_SARP_2016_1912_1.2.json
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@@ -42,7 +42,7 @@
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index 0e3f17619..9e4f3e2ac 100644
--- a/datasets/MASTER_Sky_2003_2052_1.json
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index 950d6b6cb..4f14f0a41 100644
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index 9f5f70e7d..b3c8900bb 100644
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diff --git a/datasets/MASTER_SuomiNPP_2013_1969_1.json b/datasets/MASTER_SuomiNPP_2013_1969_1.json
index 1927494fd..720946d46 100644
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index e8d3081b1..d78a1e7f8 100644
--- a/datasets/MASTER_SuomiNPP_2015_1970_1.json
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index ccaf19017..94187ca56 100644
--- a/datasets/MASTER_TC4_2007_2021_1.1.json
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index d87f414b9..653b531ee 100644
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index 325b29210..4fa7a3543 100644
--- a/datasets/MASTER_WDTS_SeptOct_2020_1940_1.2.json
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index c812ad569..7a8b3953b 100644
--- a/datasets/MASTER_WDTS_Spring_2021_1953_1.1.json
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diff --git a/datasets/MASTER_WDTS_Spring_2023_2252_1.json b/datasets/MASTER_WDTS_Spring_2023_2252_1.json
index 8367f51bc..f391132d2 100644
--- a/datasets/MASTER_WDTS_Spring_2023_2252_1.json
+++ b/datasets/MASTER_WDTS_Spring_2023_2252_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/MAS_832_2.json b/datasets/MAS_832_2.json
index 562dc1652..e5d71cb46 100644
--- a/datasets/MAS_832_2.json
+++ b/datasets/MAS_832_2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/MCD19A3CMG_061.json b/datasets/MCD19A3CMG_061.json
index f30a43753..05b2e1113 100644
--- a/datasets/MCD19A3CMG_061.json
+++ b/datasets/MCD19A3CMG_061.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/MIL2ASAF_002.json b/datasets/MIL2ASAF_002.json
index fa6af016e..fa88740fb 100644
--- a/datasets/MIL2ASAF_002.json
+++ b/datasets/MIL2ASAF_002.json
@@ -86,11 +86,29 @@
         "temporal": {
             "interval": [
                 [
-                    "1999-12-18T00:00:00Z",
+                    "2017-11-01T00:00:00Z",
                     null
                 ]
             ]
         }
     },
-    "license": "proprietary"
+    "license": "proprietary",
+    "assets": {
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search/granules?p=C1542382556-LARC",
+            "title": "Direct Download [0]",
+            "description": "Data Access via Earthdata Search",
+            "roles": [
+                "data"
+            ]
+        },
+        "gov/data/MISR/MIL2ASAF": {
+            "href": "https://asdc.larc.nasa.gov/data/MISR/MIL2ASAF.002/",
+            "title": "Direct Download [1]",
+            "description": "Data Access via direct Download",
+            "roles": [
+                "data"
+            ]
+        }
+    }
 }
\ No newline at end of file
diff --git a/datasets/MIL2ASLF_002.json b/datasets/MIL2ASLF_002.json
index 128658ab5..ba2868234 100644
--- a/datasets/MIL2ASLF_002.json
+++ b/datasets/MIL2ASLF_002.json
@@ -2,7 +2,7 @@
     "type": "Collection",
     "id": "MIL2ASLF_002",
     "stac_version": "1.0.0",
-    "description": "This Level 2 FIRSTLOOK Land Surface product contains directional reflectance properties,albedo(spectral & PAR integrated),FPAR,radiation parameters & terrain-referenced geometric parameters, produced using ancillary input from the previous time period.",
+    "description": "This Level 2 FIRSTLOOK Land Surface product contains directional reflectance properties, albedo(spectral and PAR integrated), FPAR, radiation parameters, and terrain-referenced geometric parameters produced using ancillary input from the previous time period.\nMIL2ASLF_002 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 FIRSTLOOK Surface parameters version 2. It contains directional reflectance properties, albedo (spectral and photosynthetically active radiation (PAR) integrated), a fraction of photosynthetically active radiation absorbed by vegetation (FPAR), radiation parameters, and terrain-referenced geometric parameters produced using ancillary input from the previous time period. Data collection for this product is ongoing. This collection contains the Leaf Area Index (LAI).\\r\\n\\r\\nMulti-angle Imaging SpectroRadiometer (MISR) Level 2 Aerosol data products contain various information on the Earth's atmosphere. The aerosol data include tropospheric aerosol optical depth on 17. 6-km centers archived with a compositional model identifier and retrieval residuals, ancillary data including relative humidity, ozone optical depth, stratospheric aerosol optical depth, and retrieval flags. MISR multi-angle imagery will be used to monitor global and regional trends radiatively significant to optical properties (optical depth, single scattering albedo, and size distribution) and amounts (mass loading) of natural and anthropogenic aerosols, including those arising from industrial and volcanic emissions, slash-and-burn agriculture, and desertification. Coupled with MISR's determinations of top-of-atmosphere and surface albedos, these data will measure the global aerosol forcing of the shortwave planetary radiation budget. \\r\\n\\r\\nThe MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four forward, and four aftward. It takes seven minutes for all nine cameras to view the exact surface location. The view angles relative to the surface reference ellipsoid are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm.\nMISR is designed to view Earth with cameras in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successfully imaged by all nine cameras in 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the effects of sunlight on Earth and distinguish different types of clouds, particles, and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.",
     "links": [
         {
             "rel": "license",
@@ -86,11 +86,29 @@
         "temporal": {
             "interval": [
                 [
-                    "1999-12-18T00:00:00Z",
+                    "2017-11-01T00:00:00Z",
                     null
                 ]
             ]
         }
     },
-    "license": "proprietary"
+    "license": "proprietary",
+    "assets": {
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search/granules?p=C1542382559-LARC",
+            "title": "Direct Download [0]",
+            "description": "Data Access via Earthdata Search",
+            "roles": [
+                "data"
+            ]
+        },
+        "gov/data/MISR/MIL2ASLF": {
+            "href": "https://asdc.larc.nasa.gov/data/MISR/MIL2ASLF.002/",
+            "title": "Direct Download [1]",
+            "description": "Data Access via Direct Download",
+            "roles": [
+                "data"
+            ]
+        }
+    }
 }
\ No newline at end of file
diff --git a/datasets/MISR_885_1.json b/datasets/MISR_885_1.json
index 6efa0d4f8..2b8adb389 100644
--- a/datasets/MISR_885_1.json
+++ b/datasets/MISR_885_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/MISR_Forest_AGB_SW_US_1978_1.json b/datasets/MISR_Forest_AGB_SW_US_1978_1.json
index 412af478f..4c467c2ac 100644
--- a/datasets/MISR_Forest_AGB_SW_US_1978_1.json
+++ b/datasets/MISR_Forest_AGB_SW_US_1978_1.json
@@ -42,7 +42,7 @@
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index f33c17a8c..7f810a7d1 100644
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index dc63a21c8..f8c8acce3 100644
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index 7e380dab8..1fa41254a 100644
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diff --git a/datasets/Maryland_Temperature_Humidity_1319_1.json b/datasets/Maryland_Temperature_Humidity_1319_1.json
index cbdcabf4f..7be1d65fe 100644
--- a/datasets/Maryland_Temperature_Humidity_1319_1.json
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diff --git a/datasets/MatthewsVegetation_419_1.json b/datasets/MatthewsVegetation_419_1.json
index 13cc442cb..b908e6c76 100644
--- a/datasets/MatthewsVegetation_419_1.json
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index 6c5b9d7bc..4aad9aede 100644
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index 7a94ef732..3f76e205e 100644
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index f38468d4b..005e37c5f 100644
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index 3e6ac544f..31ca3827e 100644
--- a/datasets/Methane_Ethane_MA_NH_1982_1.json
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diff --git a/datasets/Methane_Flaring_Sites_VIIRS_1874_1.json b/datasets/Methane_Flaring_Sites_VIIRS_1874_1.json
index 7430732b3..d0b3b805f 100644
--- a/datasets/Methane_Flaring_Sites_VIIRS_1874_1.json
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index a102c0778..5befd82e6 100644
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index 22a83b791..b07589cca 100644
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index 969dc97da..0b725e8e1 100644
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index 458503c98..b6ab19e4f 100644
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diff --git a/datasets/NACP_Forest_Biophysical_1046_1.json b/datasets/NACP_Forest_Biophysical_1046_1.json
index 76660409f..93a80de4a 100644
--- a/datasets/NACP_Forest_Biophysical_1046_1.json
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index 120379e24..1e0c1e226 100644
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index fd2a11f58..9be63073c 100644
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index 50df93af3..e3df4fab2 100644
--- a/datasets/NACP_MCI_CO2_Inventory_1205_1.json
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index 3e7fd2b70..cce7cab79 100644
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index 80d093adf..466ca0416 100644
--- a/datasets/NACP_MCI_CO2_Measurements_1202_1.json
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index 447b3223e..00a0701ca 100644
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index e052ad94b..3cee99340 100644
--- a/datasets/NACP_MsTMIP_Model_Driver_1220_1.json
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index 3daaa81d6..66cd0f1b2 100644
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index 06fde6fd5..98a87b640 100644
--- a/datasets/NACP_MsTMIP_TBMO_1225_1.json
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index 9429e6199..d35c6501b 100644
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index cf4b36eef..6c27229ae 100644
--- a/datasets/NACP_NAM_HYSPLIT_Footprints_1586_1.json
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@@ -42,7 +42,7 @@
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index e902a4edc..005f0afbb 100644
--- a/datasets/NACP_PNW_Carbon_Balance_1317_1.json
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index 7dcf2b145..ed4795c74 100644
--- a/datasets/NACP_PalEON_MIP_1779_1.json
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diff --git a/datasets/NACP_Peatland_Burn-Severity_1283_1.json b/datasets/NACP_Peatland_Burn-Severity_1283_1.json
index d03508727..20a64db9b 100644
--- a/datasets/NACP_Peatland_Burn-Severity_1283_1.json
+++ b/datasets/NACP_Peatland_Burn-Severity_1283_1.json
@@ -42,7 +42,7 @@
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index 9826e9d3b..579f73cb7 100644
--- a/datasets/NACP_Regional_Obs_Model_Suppl_1158_1.json
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index 60512b778..557c93f88 100644
--- a/datasets/NACP_Site_Model_Data_Orig_Fmt_1192_1.json
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index 699ab91ae..024569723 100644
--- a/datasets/NACP_Site_Model_Flux_Std_Fmt_1183_1.json
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index 89bc05bfa..4108150a7 100644
--- a/datasets/NACP_Site_Tower_Met_and_Flux_1178_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/NACP_TERRA-PNW_1292_1.json b/datasets/NACP_TERRA-PNW_1292_1.json
index df40ae72e..41a6a9100 100644
--- a/datasets/NACP_TERRA-PNW_1292_1.json
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index 580d31452..105b18afd 100644
--- a/datasets/NACP_Vista_CA_CH4_Inventory_1726_1.json
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index f3b4577a8..87b4fea67 100644
--- a/datasets/NACP_Vista_LA_CH4_Inventory_1525_1.json
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index 8dfe18acc..d70273450 100644
--- a/datasets/NACP_Wild_Cropland_Fuel_Map_1163_1.json
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index 0d6f1da88..3a8b02f10 100644
--- a/datasets/NACP_Woody_Veg_N_Slope_AK_V2_1365_2.json
+++ b/datasets/NACP_Woody_Veg_N_Slope_AK_V2_1365_2.json
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diff --git a/datasets/NAFD-NEX_Attribution_1799_1.json b/datasets/NAFD-NEX_Attribution_1799_1.json
index ebd23bad1..370cc0a22 100644
--- a/datasets/NAFD-NEX_Attribution_1799_1.json
+++ b/datasets/NAFD-NEX_Attribution_1799_1.json
@@ -42,7 +42,7 @@
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index 586414d16..339077706 100644
--- a/datasets/NASADEM_SC_001.json
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diff --git a/datasets/NASADEM_SHHP_001.json b/datasets/NASADEM_SHHP_001.json
index c39eb4976..370e21df0 100644
--- a/datasets/NASADEM_SHHP_001.json
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diff --git a/datasets/NASADEM_SIM_001.json b/datasets/NASADEM_SIM_001.json
index 860184547..be676e421 100644
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index 50fd2dddc..1d24694fb 100644
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index c9ffd9e22..59c1ad334 100644
--- a/datasets/NASASatellite_Dev_Applications_2293_1.json
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index b953c29ef..ea1598267 100644
--- a/datasets/NASMo_TiAM_250m_2326_1.json
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index 85fd7135b..3d1998a35 100644
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index 1e247d43f..1cfdf479a 100644
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index 069a49892..3b283950e 100644
--- a/datasets/ND01_Georectified_Products_1165_1.json
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index 9816b600a..197465244 100644
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index 88bddcc10..d18253e5b 100644
--- a/datasets/ND01_Pasture_Nutrients_1135_1.json
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index 44534fa97..0936d262e 100644
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index 80228e774..dfb0a7a9c 100644
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index ba8352d33..3fdca124f 100644
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index 4c9398361..3fc0dce56 100644
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index b92c7a9fc..089910de9 100644
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index 371072de2..fb761defd 100644
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diff --git a/datasets/ND04_Soil_H2O_Manaus_1246_1.json b/datasets/ND04_Soil_H2O_Manaus_1246_1.json
index 9de06257a..fb5771696 100644
--- a/datasets/ND04_Soil_H2O_Manaus_1246_1.json
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diff --git a/datasets/ND04_Termite_Mounds_1072_1.json b/datasets/ND04_Termite_Mounds_1072_1.json
index dd233a6b7..4d91af2bf 100644
--- a/datasets/ND04_Termite_Mounds_1072_1.json
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diff --git a/datasets/ND06_LandUse_Studies_1130_1.json b/datasets/ND06_LandUse_Studies_1130_1.json
index bbb3a0fbd..66e2cc15c 100644
--- a/datasets/ND06_LandUse_Studies_1130_1.json
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index 854bc4ad1..4899ec914 100644
--- a/datasets/ND07_15N_Leaves_Soils_1121_1.json
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index 760f5134e..d38d63dbe 100644
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index 48d269cf1..378a985cb 100644
--- a/datasets/ND08_Soil_Respiration_1250_1.json
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diff --git a/datasets/ND10_Soil_Chemistry_1171_1.json b/datasets/ND10_Soil_Chemistry_1171_1.json
index 991579643..5ee2179c2 100644
--- a/datasets/ND10_Soil_Chemistry_1171_1.json
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index 4ae31e8e7..a22aea83e 100644
--- a/datasets/ND11_Carbon_Export_CPOM_913_1.json
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diff --git a/datasets/ND11_Logging_Damage_MT_977_1.json b/datasets/ND11_Logging_Damage_MT_977_1.json
index f0e163106..1b82c32b6 100644
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diff --git a/datasets/ND11_Nitrogen_Transfer_Leaf_Litter_915_1.json b/datasets/ND11_Nitrogen_Transfer_Leaf_Litter_915_1.json
index 92933152c..8db06ab23 100644
--- a/datasets/ND11_Nitrogen_Transfer_Leaf_Litter_915_1.json
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index 544acd618..c465fad8e 100644
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index 35e5ac825..4574703ba 100644
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index 8d8c4428f..071d296a0 100644
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index f14e246f6..52aaac074 100644
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index 009b4220f..9ad4d4e79 100644
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index a954dddb0..b9b9135ad 100644
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index dda8a1a4e..2c780b1b4 100644
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index d900543a1..b023698d6 100644
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index 5885a2018..9d4e8a57d 100644
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diff --git a/datasets/NPP_BDK_203_2.json b/datasets/NPP_BDK_203_2.json
index d4b9cf261..bcb525248 100644
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index e0ee75ee8..9b02c21cf 100644
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index 52925b741..9c8a1516e 100644
--- a/datasets/NPP_BRD_205_2.json
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index c5063a7d1..b32f7ed78 100644
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index 703bf207f..98e72d770 100644
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diff --git a/datasets/NPP_CBAY_473_2.json b/datasets/NPP_CBAY_473_2.json
index 5f5f4ebdb..a426f7621 100644
--- a/datasets/NPP_CBAY_473_2.json
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index bf7fe3a0f..594c6cc16 100644
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index 2ef2c74bb..8dbbf1ff2 100644
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index 0d05ad614..eeeac3534 100644
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index 7e7db6244..aaf3e199e 100644
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diff --git a/datasets/NPP_CNS_191_2.json b/datasets/NPP_CNS_191_2.json
index b61c86ff9..c53167686 100644
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index 6db59a0be..4abb83221 100644
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index 232aac652..44b467728 100644
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diff --git a/datasets/NPP_DRN_215_2.json b/datasets/NPP_DRN_215_2.json
index 493c26e3d..e5860db69 100644
--- a/datasets/NPP_DRN_215_2.json
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diff --git a/datasets/NPP_DZH_192_2.json b/datasets/NPP_DZH_192_2.json
index 7b315e1fd..8b565b610 100644
--- a/datasets/NPP_DZH_192_2.json
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diff --git a/datasets/NPP_EMDI_615_3.json b/datasets/NPP_EMDI_615_3.json
index cc3797a0d..c3c7e0eda 100644
--- a/datasets/NPP_EMDI_615_3.json
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diff --git a/datasets/NPP_FLK_201_2.json b/datasets/NPP_FLK_201_2.json
index 2f68a7de5..012a513e2 100644
--- a/datasets/NPP_FLK_201_2.json
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index afc9fa50a..e3f264376 100644
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index 6c79a781d..d9b2944ff 100644
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index 5df572c30..ebd2c11ac 100644
--- a/datasets/NPP_GRIDDED_GPPDI_614_4.json
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index 79acc0414..0a16e4cf4 100644
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index ae37aa481..be37ee9fd 100644
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index 87d484299..32ded322a 100644
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index 91cbea476..0cd8e0346 100644
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diff --git a/datasets/NPP_IBP_198_2.json b/datasets/NPP_IBP_198_2.json
index 7393fb376..9f6909322 100644
--- a/datasets/NPP_IBP_198_2.json
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diff --git a/datasets/NPP_JDR_202_2.json b/datasets/NPP_JDR_202_2.json
index 127c850b6..a61dd7cc0 100644
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diff --git a/datasets/NPP_JHN_475_2.json b/datasets/NPP_JHN_475_2.json
index 5aa39db64..ba8c93b50 100644
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diff --git a/datasets/NPP_JRN_209_2.json b/datasets/NPP_JRN_209_2.json
index 076cc7004..0a20e0be6 100644
--- a/datasets/NPP_JRN_209_2.json
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index f003caba8..9cf65cf81 100644
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index 114a502dc..9592d74ab 100644
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index 0688c90de..02b78c985 100644
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index 9bd884734..df49347bf 100644
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index 34da15700..19d1d3098 100644
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index c67e76515..56baf3f4f 100644
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index 2ae7273aa..0736aca10 100644
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index d4d0dc33c..6715136e1 100644
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index adf39fdf5..137cdc8ee 100644
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index b6d56affb..7f19c0893 100644
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index 0480cd417..0a35fa7f7 100644
--- a/datasets/NPP_MTD_469_2.json
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index ee8312ae1..1a49ceba6 100644
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index ad1a74c8c..55a496045 100644
--- a/datasets/NPP_Multi-Biome_125_Sites_1352_1.json
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index eab869cb1..5659b9267 100644
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index 18c7d4d91..1f42c30aa 100644
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diff --git a/datasets/NPP_ODS_214_2.json b/datasets/NPP_ODS_214_2.json
index 64a7e731a..0106c5108 100644
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diff --git a/datasets/NPP_OLK_195_2.json b/datasets/NPP_OLK_195_2.json
index f40be9256..7a12a3af5 100644
--- a/datasets/NPP_OLK_195_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/NPP_OSG_211_2.json b/datasets/NPP_OSG_211_2.json
index 31e43a604..1f2b10850 100644
--- a/datasets/NPP_OSG_211_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/NPP_OTR_152_2.json b/datasets/NPP_OTR_152_2.json
index 0d95bcd8d..79c2ba7fa 100644
--- a/datasets/NPP_OTR_152_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/NPP_OTTER_472_2.json b/datasets/NPP_OTTER_472_2.json
index d3c2a197d..050383d69 100644
--- a/datasets/NPP_OTTER_472_2.json
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diff --git a/datasets/NPP_PIK_575_2.json b/datasets/NPP_PIK_575_2.json
index 854dde6e0..7cd52254e 100644
--- a/datasets/NPP_PIK_575_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/NPP_PMP_212_2.json b/datasets/NPP_PMP_212_2.json
index f82dc2d9f..3ceead25e 100644
--- a/datasets/NPP_PMP_212_2.json
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@@ -42,7 +42,7 @@
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index 105cfc3ae..c66b02973 100644
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index ef42a2faa..cd114a3d9 100644
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index 4be96a95a..9e610a937 100644
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index d56a1aa92..1b7304581 100644
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index c75c972bc..ff8364835 100644
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diff --git a/datasets/NPP_SES_480_2.json b/datasets/NPP_SES_480_2.json
index 53e760109..9d8fcc531 100644
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index db284919a..a941db59a 100644
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index c77c0c466..3cc9d0514 100644
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index 3b34f0625..07772bf85 100644
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index ab6eb774c..8df4665c4 100644
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index 58c2a5e0e..a445a09e9 100644
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index c10925ead..be469835d 100644
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index b9fc0ec5a..df33397f5 100644
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diff --git a/datasets/NPP_TVA_155_2.json b/datasets/NPP_TVA_155_2.json
index c487da7fc..8c00a0a28 100644
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index 9c904fecc..d9f5a18c6 100644
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index dcea345d9..173b867ca 100644
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index b6946ccdb..a215d8fce 100644
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diff --git a/datasets/NPP_WBW_819_2.json b/datasets/NPP_WBW_819_2.json
index 8787b3b09..f884756d7 100644
--- a/datasets/NPP_WBW_819_2.json
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index 277bc6dbb..816d2d94f 100644
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diff --git a/datasets/NPP_XLN_156_2.json b/datasets/NPP_XLN_156_2.json
index 2db134142..0250c1cc8 100644
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diff --git a/datasets/North_Slope_Transect_Veg_Maps_1386_1.json b/datasets/North_Slope_Transect_Veg_Maps_1386_1.json
index 25d977208..5c600fd3b 100644
--- a/datasets/North_Slope_Transect_Veg_Maps_1386_1.json
+++ b/datasets/North_Slope_Transect_Veg_Maps_1386_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/Northern_Alaska_Veg_Maps_1359_1.json b/datasets/Northern_Alaska_Veg_Maps_1359_1.json
index 3407561dc..14e3f19b8 100644
--- a/datasets/Northern_Alaska_Veg_Maps_1359_1.json
+++ b/datasets/Northern_Alaska_Veg_Maps_1359_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L1B_Calibration_11.2r.json b/datasets/OCO2_L1B_Calibration_11.2r.json
new file mode 100644
index 000000000..4fec7c53a
--- /dev/null
+++ b/datasets/OCO2_L1B_Calibration_11.2r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L1B_Calibration_11.2r",
+    "stac_version": "1.0.0",
+    "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.\n\nThe Orbiting Carbon Observatory is the first NASA missiondesigned to collect space-based measurements of atmospheric carbon dioxidewith the precision, resolution, and coverage needed to characterize theprocesses controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and inmolecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time tothe Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO2_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
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+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
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+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 1B calibrated, geolocated calibration spectra Retrospective Processing V11.2r (OCO2_L1B_Calibration) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-11-30T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L1B_Calibration.11.2r/",
+            "title": "Direct Download [1]",
+            "description": "Access the data via HTTP.",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO2_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L1B_Calibration",
+            "title": "Direct Download [0]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L1B_Calibration_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L1B_Science_11.2r.json b/datasets/OCO2_L1B_Science_11.2r.json
new file mode 100644
index 000000000..8b05d9e02
--- /dev/null
+++ b/datasets/OCO2_L1B_Science_11.2r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L1B_Science_11.2r",
+    "stac_version": "1.0.0",
+    "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the output from the Level 1B process. It converts the raw instrument data numbers into calibrated radiances. This conversion is based upon files of instrument characteristics and algorithm parameters that may vary over time. In addition to calibrated radiances, the Level 1B output products have geolocation information recorded for each measurement for use in higher-level processes.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMWEgY29sbGF0ZWQsIHBhcnNlZCwgY2FsaWJyYXRpb24gZGF0YSB2MTAgKG9jbzJfbDFhaW5fcGl4ZWwpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT0NPMl9MMWFJbl9QaXhlbFwiLFwiMTBcIiwxNjg1NzgzOTc0LDIzXSIsInVtbSI6IltcIm9jby0yIGxldmVsIDFhIGNvbGxhdGVkLCBwYXJzZWQsIGNhbGlicmF0aW9uIGRhdGEgdjEwIChvY28yX2wxYWluX3BpeGVsKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDFhSW5fUGl4ZWxcIixcIjEwXCIsMTY4NTc4Mzk3NCwyM10ifQ%3D%3D/OCO2_L1B_Science_11.2r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMWEgY29sbGF0ZWQsIHBhcnNlZCwgY2FsaWJyYXRpb24gZGF0YSB2MTAgKG9jbzJfbDFhaW5fcGl4ZWwpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT0NPMl9MMWFJbl9QaXhlbFwiLFwiMTBcIiwxNjg1NzgzOTc0LDIzXSIsInVtbSI6IltcIm9jby0yIGxldmVsIDFhIGNvbGxhdGVkLCBwYXJzZWQsIGNhbGlicmF0aW9uIGRhdGEgdjEwIChvY28yX2wxYWluX3BpeGVsKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDFhSW5fUGl4ZWxcIixcIjEwXCIsMTY4NTc4Mzk3NCwyM10ifQ%3D%3D/OCO2_L1B_Science_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 1B calibrated, geolocated science spectra Retrospective Processing V11.2r (OCO2_L1B_Science) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-11-30T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L1B_Science.11.2r/",
+            "title": "Direct Download [1]",
+            "description": "Access the data via HTTP.",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO2_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L1B_Science",
+            "title": "Direct Download [0]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L1B_Science_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_ABand_10r.json b/datasets/OCO2_L2_ABand_10r.json
index accf49f40..4b750783c 100644
--- a/datasets/OCO2_L2_ABand_10r.json
+++ b/datasets/OCO2_L2_ABand_10r.json
@@ -42,7 +42,7 @@
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         {
             "rel": "self",
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_ABand_10r",
             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
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         {
             "rel": "items",
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_ABand_10r/items",
             "type": "application/json"
         }
     ],
diff --git a/datasets/OCO2_L2_ABand_11.2.json b/datasets/OCO2_L2_ABand_11.2.json
index f7c0e34b8..2bdf252d2 100644
--- a/datasets/OCO2_L2_ABand_11.2.json
+++ b/datasets/OCO2_L2_ABand_11.2.json
@@ -42,7 +42,7 @@
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         {
             "rel": "self",
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO2_L2_ABand_11.2r.json b/datasets/OCO2_L2_ABand_11.2r.json
new file mode 100644
index 000000000..10ce2379e
--- /dev/null
+++ b/datasets/OCO2_L2_ABand_11.2r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L2_ABand_11.2r",
+    "stac_version": "1.0.0",
+    "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3133987494-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3133987494-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3133987494-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3133987494-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3133987494-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_ABand_11.2r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMiBtZXRlb3JvbG9naWNhbCBwYXJhbWV0ZXJzIGludGVycG9sYXRlZCBmcm9tIGdsb2JhbCBhc3NpbWlsYXRpb24gbW9kZWwgZm9yIGVhY2ggc291bmRpbmcsIHJldHJvc3BlY3RpdmUgcHJvY2Vzc2luZyB2OXIgKG9jbzJfbDJfbWV0KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDJfTWV0XCIsXCI5clwiLDE1Mzc0NjY3MzUsMjhdIiwidW1tIjoiW1wib2NvLTIgbGV2ZWwgMiBtZXRlb3JvbG9naWNhbCBwYXJhbWV0ZXJzIGludGVycG9sYXRlZCBmcm9tIGdsb2JhbCBhc3NpbWlsYXRpb24gbW9kZWwgZm9yIGVhY2ggc291bmRpbmcsIHJldHJvc3BlY3RpdmUgcHJvY2Vzc2luZyB2OXIgKG9jbzJfbDJfbWV0KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDJfTWV0XCIsXCI5clwiLDE1Mzc0NjY3MzUsMjhdIn0%3D/OCO2_L2_ABand_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor Retrospective Processing V11.2r (OCO2_L2_ABand) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-11-30T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_ABand.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO2_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_ABand",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_ABand_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_ABand_11r.json b/datasets/OCO2_L2_ABand_11r.json
index 550734075..ec025eb8c 100644
--- a/datasets/OCO2_L2_ABand_11r.json
+++ b/datasets/OCO2_L2_ABand_11r.json
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diff --git a/datasets/OCO2_L2_CO2Prior_10r.json b/datasets/OCO2_L2_CO2Prior_10r.json
index ffea7300d..73e2cd4a6 100644
--- a/datasets/OCO2_L2_CO2Prior_10r.json
+++ b/datasets/OCO2_L2_CO2Prior_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L2_CO2Prior_11.2.json b/datasets/OCO2_L2_CO2Prior_11.2.json
index abf4dc5f9..ee93ffaab 100644
--- a/datasets/OCO2_L2_CO2Prior_11.2.json
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new file mode 100644
index 000000000..69f784b5c
--- /dev/null
+++ b/datasets/OCO2_L2_CO2Prior_11.2r.json
@@ -0,0 +1,137 @@
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+        {
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_CO2Prior_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air Retrospective Processing V11.2r (OCO2_L2_CO2Prior) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-11-30T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_CO2Prior.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO2_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_CO2Prior",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_CO2Prior_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_CO2Prior_11r.json b/datasets/OCO2_L2_CO2Prior_11r.json
index 40a6c901d..7624e592a 100644
--- a/datasets/OCO2_L2_CO2Prior_11r.json
+++ b/datasets/OCO2_L2_CO2Prior_11r.json
@@ -42,7 +42,7 @@
         },
         {
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         },
         {
@@ -53,7 +53,7 @@
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_CO2Prior_11r/items",
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diff --git a/datasets/OCO2_L2_Diagnostic_10r.json b/datasets/OCO2_L2_Diagnostic_10r.json
index 370d4d089..29d7a9c91 100644
--- a/datasets/OCO2_L2_Diagnostic_10r.json
+++ b/datasets/OCO2_L2_Diagnostic_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L2_Diagnostic_11.2.json b/datasets/OCO2_L2_Diagnostic_11.2.json
index 1c4060d9d..1e1cc5aa4 100644
--- a/datasets/OCO2_L2_Diagnostic_11.2.json
+++ b/datasets/OCO2_L2_Diagnostic_11.2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L2_Diagnostic_11.2r.json b/datasets/OCO2_L2_Diagnostic_11.2r.json
new file mode 100644
index 000000000..0b2474705
--- /dev/null
+++ b/datasets/OCO2_L2_Diagnostic_11.2r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L2_Diagnostic_11.2r",
+    "stac_version": "1.0.0",
+    "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass various data fields used for diagnostic and pre-processing, including aerosol optical depth, albedo, absorption coefficients, fluorescence, XCO2 uncertainties, averaging kernel, surface type, etc.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090472506-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090472506-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090472506-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090472506-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090472506-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Diagnostic_11.2r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Diagnostic_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information Retrospective Processing V11.2r (OCO2_L2_Diagnostic) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-11-30T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_Diagnostic.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_Dia_10__10132021.png",
+            "type": "image/jpeg",
+            "title": "Download OCO2_L2_Dia_10__10132021.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_Dia_10__10132021.png",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_Diagnostic",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_Diagnostic_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_Diagnostic_11r.json b/datasets/OCO2_L2_Diagnostic_11r.json
index f977faf65..fa2e7f33f 100644
--- a/datasets/OCO2_L2_Diagnostic_11r.json
+++ b/datasets/OCO2_L2_Diagnostic_11r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L2_IMAPDOAS_10r.json b/datasets/OCO2_L2_IMAPDOAS_10r.json
index c8040e6d1..bedc8fabf 100644
--- a/datasets/OCO2_L2_IMAPDOAS_10r.json
+++ b/datasets/OCO2_L2_IMAPDOAS_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L2_IMAPDOAS_11.2.json b/datasets/OCO2_L2_IMAPDOAS_11.2.json
index 7ea219668..0f5db7801 100644
--- a/datasets/OCO2_L2_IMAPDOAS_11.2.json
+++ b/datasets/OCO2_L2_IMAPDOAS_11.2.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO2_L2_IMAPDOAS_11.2r.json b/datasets/OCO2_L2_IMAPDOAS_11.2r.json
new file mode 100644
index 000000000..320ce6980
--- /dev/null
+++ b/datasets/OCO2_L2_IMAPDOAS_11.2r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L2_IMAPDOAS_11.2r",
+    "stac_version": "1.0.0",
+    "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090466573-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090466573-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090466573-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090466573-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090466573-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_IMAPDOAS_11.2r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_IMAPDOAS_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP) Retrospective Processing V11.2r (OCO2_L2_IMAPDOAS) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-11-30T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_IMAPDOAS.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO2_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_IMAPDOAS",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_IMAPDOAS_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_IMAPDOAS_11r.json b/datasets/OCO2_L2_IMAPDOAS_11r.json
index 6989d69ae..518de24ad 100644
--- a/datasets/OCO2_L2_IMAPDOAS_11r.json
+++ b/datasets/OCO2_L2_IMAPDOAS_11r.json
@@ -42,7 +42,7 @@
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             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_IMAPDOAS_11r/items",
             "type": "application/json"
         }
     ],
diff --git a/datasets/OCO2_L2_Lite_FP_10r.json b/datasets/OCO2_L2_Lite_FP_10r.json
index 6f5b372a9..146e23957 100644
--- a/datasets/OCO2_L2_Lite_FP_10r.json
+++ b/datasets/OCO2_L2_Lite_FP_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L2_Lite_FP_11.1r.json b/datasets/OCO2_L2_Lite_FP_11.1r.json
index ab6875730..169b8d98b 100644
--- a/datasets/OCO2_L2_Lite_FP_11.1r.json
+++ b/datasets/OCO2_L2_Lite_FP_11.1r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO2_L2_Lite_FP_11.2r.json b/datasets/OCO2_L2_Lite_FP_11.2r.json
new file mode 100644
index 000000000..190dcc8ab
--- /dev/null
+++ b/datasets/OCO2_L2_Lite_FP_11.2r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L2_Lite_FP_11.2r",
+    "stac_version": "1.0.0",
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+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
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+        },
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+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912085112-GES_DISC.html",
+            "type": "text/html",
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+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912085112-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912085112-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912085112-GES_DISC.json",
+            "type": "application/json",
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+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912085112-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
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+        },
+        {
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+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
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+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2014-06-01T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_Lite_FP.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO_L2_Lite_FP_v11r_220331_final.png",
+            "type": "image/jpeg",
+            "title": "Download OCO_L2_Lite_FP_v11r_220331_final.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO_L2_Lite_FP_v11r_220331_final.png",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_Lite_FP",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_Lite_FP_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO2_DATA_OCO2_L2_Lite_FP_11_2r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO2_DATA/OCO2_L2_Lite_FP.11.2r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO2_DATA_OCO2_L2_Lite_FP_11_2r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_Lite_SIF_11.2r.json b/datasets/OCO2_L2_Lite_SIF_11.2r.json
new file mode 100644
index 000000000..6090e1e37
--- /dev/null
+++ b/datasets/OCO2_L2_Lite_SIF_11.2r.json
@@ -0,0 +1,159 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L2_Lite_SIF_11.2r",
+    "stac_version": "1.0.0",
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+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912084771-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912084771-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912084771-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912084771-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2912084771-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMWEgY29sbGF0ZWQsIHBhcnNlZCwgY2FsaWJyYXRpb24gZGF0YSB2MTAgKG9jbzJfbDFhaW5fcGl4ZWwpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT0NPMl9MMWFJbl9QaXhlbFwiLFwiMTBcIiwxNjg1NzgzOTc0LDIzXSIsInVtbSI6IltcIm9jby0yIGxldmVsIDFhIGNvbGxhdGVkLCBwYXJzZWQsIGNhbGlicmF0aW9uIGRhdGEgdjEwIChvY28yX2wxYWluX3BpeGVsKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDFhSW5fUGl4ZWxcIixcIjEwXCIsMTY4NTc4Mzk3NCwyM10ifQ%3D%3D/OCO2_L2_Lite_SIF_11.2r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMWEgY29sbGF0ZWQsIHBhcnNlZCwgY2FsaWJyYXRpb24gZGF0YSB2MTAgKG9jbzJfbDFhaW5fcGl4ZWwpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT0NPMl9MMWFJbl9QaXhlbFwiLFwiMTBcIiwxNjg1NzgzOTc0LDIzXSIsInVtbSI6IltcIm9jby0yIGxldmVsIDFhIGNvbGxhdGVkLCBwYXJzZWQsIGNhbGlicmF0aW9uIGRhdGEgdjEwIChvY28yX2wxYWluX3BpeGVsKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDFhSW5fUGl4ZWxcIixcIjEwXCIsMTY4NTc4Mzk3NCwyM10ifQ%3D%3D/OCO2_L2_Lite_SIF_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 2 bias-corrected solar-induced fluorescence and other select fields from the IMAP-DOAS algorithm aggregated as daily files, Retrospective processing V11.2r (OCO2_L2_Lite_SIF) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2014-09-01T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_Lite_SIF.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_Lite_SIF_v11r__20220331.png",
+            "type": "image/jpeg",
+            "title": "Download OCO2_L2_Lite_SIF_v11r__20220331.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_Lite_SIF_v11r__20220331.png",
+            "title": "Thumbnail",
+            "description": "OCO-2 L2 Lite Product , Solar-Induced Chlorophyll Fluorescence, (SIF) at 757nm, one day (3/31/2022), variable \"Daily_SIF_757nm\", in W/m^2/sr/micron units. Note that, although the data range is truncated at 0, small negatives values are retained in the data to avoid positive biases in SIF distributions.",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_Lite_SIF",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_Lite_SIF_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO2_DATA_OCO2_L2_Lite_SIF_11_2r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO2_DATA/OCO2_L2_Lite_SIF.11.2r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO2_DATA_OCO2_L2_Lite_SIF_11_2r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_Met_10r.json b/datasets/OCO2_L2_Met_10r.json
index ce314b239..8b07c1954 100644
--- a/datasets/OCO2_L2_Met_10r.json
+++ b/datasets/OCO2_L2_Met_10r.json
@@ -42,7 +42,7 @@
         },
         {
             "rel": "self",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_10r",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_10r",
             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
         },
         {
             "rel": "items",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_10r/items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_10r/items",
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     ],
diff --git a/datasets/OCO2_L2_Met_11.2.json b/datasets/OCO2_L2_Met_11.2.json
index 35638df20..9d001da07 100644
--- a/datasets/OCO2_L2_Met_11.2.json
+++ b/datasets/OCO2_L2_Met_11.2.json
@@ -42,7 +42,7 @@
         },
         {
             "rel": "self",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_11.2",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMiBiaWFzLWNvcnJlY3RlZCBzb2xhci1pbmR1Y2VkIGZsdW9yZXNjZW5jZSBhbmQgb3RoZXIgc2VsZWN0IGZpZWxkcyBmcm9tIHRoZSBpbWFwLWRvYXMgYWxnb3JpdGhtIGFnZ3JlZ2F0ZWQgYXMgZGFpbHkgZmlsZXMsIHJldHJvc3BlY3RpdmUgcHJvY2Vzc2luZyB2MTFyIChvY28yX2wyX2xpdGVfc2lmKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDJfTGl0ZV9TSUZcIixcIjExclwiLDIyNDg2NTI2NDksMTBdIiwidW1tIjoiW1wib2NvLTIgbGV2ZWwgMiBiaWFzLWNvcnJlY3RlZCBzb2xhci1pbmR1Y2VkIGZsdW9yZXNjZW5jZSBhbmQgb3RoZXIgc2VsZWN0IGZpZWxkcyBmcm9tIHRoZSBpbWFwLWRvYXMgYWxnb3JpdGhtIGFnZ3JlZ2F0ZWQgYXMgZGFpbHkgZmlsZXMsIHJldHJvc3BlY3RpdmUgcHJvY2Vzc2luZyB2MTFyIChvY28yX2wyX2xpdGVfc2lmKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDJfTGl0ZV9TSUZcIixcIjExclwiLDIyNDg2NTI2NDksMTBdIn0%3D/OCO2_L2_Met_11.2",
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         },
         {
@@ -53,7 +53,7 @@
         },
         {
             "rel": "items",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_11.2/items",
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diff --git a/datasets/OCO2_L2_Met_11.2r.json b/datasets/OCO2_L2_Met_11.2r.json
new file mode 100644
index 000000000..33abf5a2c
--- /dev/null
+++ b/datasets/OCO2_L2_Met_11.2r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L2_Met_11.2r",
+    "stac_version": "1.0.0",
+    "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. \n\nThis collection encompass meteorological parameters interpolated from global assimilation model for each sounding.\n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090460016-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090460016-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090460016-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090460016-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090460016-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_11.2r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Met_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding Retrospective Processing V11.2r (OCO2_L2_Met) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2014-06-01T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_Met.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO2_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_Met",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_Met_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_Met_11r.json b/datasets/OCO2_L2_Met_11r.json
index eca1e607b..59b0ed633 100644
--- a/datasets/OCO2_L2_Met_11r.json
+++ b/datasets/OCO2_L2_Met_11r.json
@@ -42,7 +42,7 @@
         },
         {
             "rel": "self",
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO2_L2_Met_9r.json b/datasets/OCO2_L2_Met_9r.json
index 0d27803ac..ed3f48541 100644
--- a/datasets/OCO2_L2_Met_9r.json
+++ b/datasets/OCO2_L2_Met_9r.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO2_L2_Standard_10r.json b/datasets/OCO2_L2_Standard_10r.json
index ce70e1753..a1828b44b 100644
--- a/datasets/OCO2_L2_Standard_10r.json
+++ b/datasets/OCO2_L2_Standard_10r.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO2_L2_Standard_11.2.json b/datasets/OCO2_L2_Standard_11.2.json
index cbe1a1b56..92f194733 100644
--- a/datasets/OCO2_L2_Standard_11.2.json
+++ b/datasets/OCO2_L2_Standard_11.2.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO2_L2_Standard_11.2r.json b/datasets/OCO2_L2_Standard_11.2r.json
new file mode 100644
index 000000000..c3ec00242
--- /dev/null
+++ b/datasets/OCO2_L2_Standard_11.2r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO2_L2_Standard_11.2r",
+    "stac_version": "1.0.0",
+    "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090432546-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090432546-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090432546-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090432546-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3090432546-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Standard_11.2r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Standard_11.2r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-2 Level 2 geolocated XCO2 retrievals results, physical model Retrospective Processing V11.2r (OCO2_L2_Standard) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-11-30T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "11": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO2_DATA/OCO2_L2_Standard.11.2r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_Std_10__10132021.png",
+            "type": "image/jpeg",
+            "title": "Download OCO2_L2_Std_10__10132021.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO2_L2_Std_10__10132021.png",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO2_L2_Standard",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO2_L2_Standard_11.2r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO2_L2_Standard_11r.json b/datasets/OCO2_L2_Standard_11r.json
index 27c87a759..0958c2fb9 100644
--- a/datasets/OCO2_L2_Standard_11r.json
+++ b/datasets/OCO2_L2_Standard_11r.json
@@ -42,7 +42,7 @@
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO2_L2_Standard_11r",
             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
         },
         {
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diff --git a/datasets/OCO3_L1B_Calibration_10.json b/datasets/OCO3_L1B_Calibration_10.json
index c3b6d149f..2414ef177 100644
--- a/datasets/OCO3_L1B_Calibration_10.json
+++ b/datasets/OCO3_L1B_Calibration_10.json
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index 12ebc3ff2..7b20a96dd 100644
--- a/datasets/OCO3_L1B_Calibration_10r.json
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diff --git a/datasets/OCO3_L1B_Calibration_11r.json b/datasets/OCO3_L1B_Calibration_11r.json
new file mode 100644
index 000000000..f218a166c
--- /dev/null
+++ b/datasets/OCO3_L1B_Calibration_11r.json
@@ -0,0 +1,158 @@
+{
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+    "id": "OCO3_L1B_Calibration_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. \n\nThe OCO-3 incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.\n\nThis L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO3_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.\n\nThis is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.\n",
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+            "name": "NASA EOSDIS",
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+            "roles": [
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+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L1B_Calibration_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L1B_Calibration_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L1B_Calibration.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L1B_Calibration_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L1B_Science_10.json b/datasets/OCO3_L1B_Science_10.json
index 9e1c1d176..f544f2fdf 100644
--- a/datasets/OCO3_L1B_Science_10.json
+++ b/datasets/OCO3_L1B_Science_10.json
@@ -42,7 +42,7 @@
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L1B_Science_10",
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@@ -53,7 +53,7 @@
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L1B_Science_10/items",
             "type": "application/json"
         }
     ],
diff --git a/datasets/OCO3_L1B_Science_10r.json b/datasets/OCO3_L1B_Science_10r.json
index 0fc7dd94b..8ff3ee5ec 100644
--- a/datasets/OCO3_L1B_Science_10r.json
+++ b/datasets/OCO3_L1B_Science_10r.json
@@ -42,7 +42,7 @@
         },
         {
             "rel": "self",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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_L1B_Science_10r",
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@@ -53,7 +53,7 @@
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         {
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             "type": "application/json"
         }
     ],
diff --git a/datasets/OCO3_L1B_Science_11r.json b/datasets/OCO3_L1B_Science_11r.json
new file mode 100644
index 000000000..9de5c11b0
--- /dev/null
+++ b/datasets/OCO3_L1B_Science_11r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L1B_Science_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091100-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091100-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091100-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091100-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091100-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L1B_Science_11r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L1B_Science_11r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 1B calibrated, geolocated science spectra, Retrospective Processing V11r (OCO3_L1B_Science) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO3_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L1B_Science",
+            "title": "Direct Download [0]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L1B_Science": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L1B_Science.11r/",
+            "title": "Direct Download [1]",
+            "description": "Access the data via HTTP.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L1B_Science_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L1B_Science_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L1B_Science.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L1B_Science_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L2_ABand_10.json b/datasets/OCO3_L2_ABand_10.json
index 8cbf02b49..bdde1e3cf 100644
--- a/datasets/OCO3_L2_ABand_10.json
+++ b/datasets/OCO3_L2_ABand_10.json
@@ -42,7 +42,7 @@
         },
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diff --git a/datasets/OCO3_L2_ABand_10r.json b/datasets/OCO3_L2_ABand_10r.json
index 3bad97514..18a63d29b 100644
--- a/datasets/OCO3_L2_ABand_10r.json
+++ b/datasets/OCO3_L2_ABand_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_ABand_11r.json b/datasets/OCO3_L2_ABand_11r.json
new file mode 100644
index 000000000..74f8ba696
--- /dev/null
+++ b/datasets/OCO3_L2_ABand_11r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L2_ABand_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090703-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090703-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090703-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090703-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
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+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090703-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
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+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
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+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Retrospective Processing V11r (OCO3_L2_ABand) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO3_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L2_ABand": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L2_ABand.11r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L2_ABand",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L2_ABand_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_ABand_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L2_ABand.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_ABand_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L2_CO2Prior_10.json b/datasets/OCO3_L2_CO2Prior_10.json
index c90731d4b..9876de4a7 100644
--- a/datasets/OCO3_L2_CO2Prior_10.json
+++ b/datasets/OCO3_L2_CO2Prior_10.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_CO2Prior_10r.json b/datasets/OCO3_L2_CO2Prior_10r.json
index 46573fb5a..6c82a7036 100644
--- a/datasets/OCO3_L2_CO2Prior_10r.json
+++ b/datasets/OCO3_L2_CO2Prior_10r.json
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diff --git a/datasets/OCO3_L2_CO2Prior_11r.json b/datasets/OCO3_L2_CO2Prior_11r.json
new file mode 100644
index 000000000..29dc2abcb
--- /dev/null
+++ b/datasets/OCO3_L2_CO2Prior_11r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L2_CO2Prior_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091433-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091433-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091433-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091433-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
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+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910091433-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
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+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_CO2Prior_11r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air, Retrospective Processing V11r (OCO3_L2_CO2Prior) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO3_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L2_CO2Prior": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L2_CO2Prior.11r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L2_CO2Prior",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L2_CO2Prior_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_CO2Prior_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L2_CO2Prior.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_CO2Prior_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L2_Diagnostic_10.json b/datasets/OCO3_L2_Diagnostic_10.json
index 4c5b0453e..3a35eeb05 100644
--- a/datasets/OCO3_L2_Diagnostic_10.json
+++ b/datasets/OCO3_L2_Diagnostic_10.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_Diagnostic_10r.json b/datasets/OCO3_L2_Diagnostic_10r.json
index d944c13de..183d7d67f 100644
--- a/datasets/OCO3_L2_Diagnostic_10r.json
+++ b/datasets/OCO3_L2_Diagnostic_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_Diagnostic_11r.json b/datasets/OCO3_L2_Diagnostic_11r.json
new file mode 100644
index 000000000..baceceba9
--- /dev/null
+++ b/datasets/OCO3_L2_Diagnostic_11r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L2_Diagnostic_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090458-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090458-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090458-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090458-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
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+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910090458-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
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+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_Diagnostic_11r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information, Retrospective Processing V11r (OCO3_L2_Diagnostic) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO3_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L2_Diagnostic": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L2_Diagnostic.11r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L2_Diagnostic",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L2_Diagnostic_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_Diagnostic_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L2_Diagnostic.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_Diagnostic_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L2_IMAPDOAS_10.json b/datasets/OCO3_L2_IMAPDOAS_10.json
index 4d0533d67..e0b532cea 100644
--- a/datasets/OCO3_L2_IMAPDOAS_10.json
+++ b/datasets/OCO3_L2_IMAPDOAS_10.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_IMAPDOAS_10r.json b/datasets/OCO3_L2_IMAPDOAS_10r.json
index 435a2ca8b..9bdee8225 100644
--- a/datasets/OCO3_L2_IMAPDOAS_10r.json
+++ b/datasets/OCO3_L2_IMAPDOAS_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_IMAPDOAS_11r.json b/datasets/OCO3_L2_IMAPDOAS_11r.json
new file mode 100644
index 000000000..70490a2eb
--- /dev/null
+++ b/datasets/OCO3_L2_IMAPDOAS_11r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L2_IMAPDOAS_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089793-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089793-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089793-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089793-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089793-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_IMAPDOAS_11r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_IMAPDOAS_11r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V11r (OCO3_L2_IMAPDOAS) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO3_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L2_IMAPDOAS": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L2_IMAPDOAS.11r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L2_IMAPDOAS",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L2_IMAPDOAS_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_IMAPDOAS_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L2_IMAPDOAS.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_IMAPDOAS_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L2_Lite_FP_10.4r.json b/datasets/OCO3_L2_Lite_FP_10.4r.json
index f83b0f34c..de81b8a9e 100644
--- a/datasets/OCO3_L2_Lite_FP_10.4r.json
+++ b/datasets/OCO3_L2_Lite_FP_10.4r.json
@@ -42,7 +42,7 @@
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         {
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO3_L2_Lite_FP_11r.json b/datasets/OCO3_L2_Lite_FP_11r.json
new file mode 100644
index 000000000..ea50228c7
--- /dev/null
+++ b/datasets/OCO3_L2_Lite_FP_11r.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L2_Lite_FP_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086168-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086168-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086168-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086168-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086168-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_Lite_FP_11r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
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+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V11r (OCO3_L2_Lite_FP) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_L2_Lite_FP_10r.png",
+            "type": "image/jpeg",
+            "title": "Download OCO3_L2_Lite_FP_10r.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_L2_Lite_FP_10r.png",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L2_Lite_FP": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L2_Lite_FP.11r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L2_Lite_FP",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L2_Lite_FP_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L2_Lite_SIF_10r.json b/datasets/OCO3_L2_Lite_SIF_10r.json
index b90efe9d6..466143294 100644
--- a/datasets/OCO3_L2_Lite_SIF_10r.json
+++ b/datasets/OCO3_L2_Lite_SIF_10r.json
@@ -42,7 +42,7 @@
         },
         {
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             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
         },
         {
             "rel": "items",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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_L2_Lite_SIF_10r/items",
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diff --git a/datasets/OCO3_L2_Met_10.json b/datasets/OCO3_L2_Met_10.json
index 071dc579c..0eef222b3 100644
--- a/datasets/OCO3_L2_Met_10.json
+++ b/datasets/OCO3_L2_Met_10.json
@@ -42,7 +42,7 @@
         },
         {
             "rel": "self",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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_L2_Met_10",
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO3_L2_Met_10r.json b/datasets/OCO3_L2_Met_10r.json
index f8cd07583..4d8b779ad 100644
--- a/datasets/OCO3_L2_Met_10r.json
+++ b/datasets/OCO3_L2_Met_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_Met_11r.json b/datasets/OCO3_L2_Met_11r.json
new file mode 100644
index 000000000..6faff3c18
--- /dev/null
+++ b/datasets/OCO3_L2_Met_11r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L2_Met_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089375-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089375-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089375-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089375-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910089375-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_Met_11r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
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+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO3_L2_Met) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO3_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L2_Met": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L2_Met.11r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L2_Met",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L2_Met_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_Met_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L2_Met.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_Met_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OCO3_L2_Standard_10.json b/datasets/OCO3_L2_Standard_10.json
index d04334b09..033cf0567 100644
--- a/datasets/OCO3_L2_Standard_10.json
+++ b/datasets/OCO3_L2_Standard_10.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/OCO3_L2_Standard_10r.json b/datasets/OCO3_L2_Standard_10r.json
index 85f88eec6..da681ec9b 100644
--- a/datasets/OCO3_L2_Standard_10r.json
+++ b/datasets/OCO3_L2_Standard_10r.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OCO3_L2_Standard_11r.json b/datasets/OCO3_L2_Standard_11r.json
new file mode 100644
index 000000000..085188fd2
--- /dev/null
+++ b/datasets/OCO3_L2_Standard_11r.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OCO3_L2_Standard_11r",
+    "stac_version": "1.0.0",
+    "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.\n\nThe Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.\n\nThe Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.\n\nOCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. \n\nOxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.\n\nThe OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol. \n\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_Standard_11r",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=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%3D/OCO3_L2_Standard_11r/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V11r (OCO3_L2_Standard) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2019-08-06T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "type": "image/jpeg",
+            "title": "Download OCO3_logo.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/OCO/OCO3_logo.jpg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/OCO3_DATA/OCO3_L2_Standard": {
+            "href": "https://oco2.gesdisc.eosdis.nasa.gov/data/OCO3_DATA/OCO3_L2_Standard.11r/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTP",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OCO3_L2_Standard",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OCO3_L2_Standard_11r.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_Standard_11r_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/OCO3_DATA/OCO3_L2_Standard.11r/",
+            "title": "gesdisc_cumulus_prod_protected_OCO3_DATA_OCO3_L2_Standard_11r_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OMAEROG_003.json b/datasets/OMAEROG_003.json
index bb902c468..e59535861 100644
--- a/datasets/OMAEROG_003.json
+++ b/datasets/OMAEROG_003.json
@@ -42,7 +42,7 @@
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             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
         },
         {
             "rel": "items",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbGV2ZWwgMWIgdXYgZ2xvYmFsIGdlb2xvY2F0ZWQgZWFydGhzaGluZSByYWRpYW5jZXMgdjAwNCAob21sMWJydWcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01MMUJSVUdcIixcIjRcIiwyMDQ1Nzk0Nzg0LDhdIiwidW1tIjoiW1wib21pL2F1cmEgbGV2ZWwgMWIgdXYgZ2xvYmFsIGdlb2xvY2F0ZWQgZWFydGhzaGluZSByYWRpYW5jZXMgdjAwNCAob21sMWJydWcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01MMUJSVUdcIixcIjRcIiwyMDQ1Nzk0Nzg0LDhdIn0%3D/OMAEROG_003/items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbGV2ZWwgMWIgdXYgem9vbS1pbiBnZW9sb2NhdGVkIGVhcnRoc2hpbmUgcmFkaWFuY2VzIDEtb3JiaXQgbDIgc3dhdGggMTN4MTIga20gdjAwMyAob21sMWJydXopIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01MMUJSVVpcIixcIjNcIiwxMjM5OTY2NzgwLDM4XSIsInVtbSI6IltcIm9taS9hdXJhIGxldmVsIDFiIHV2IHpvb20taW4gZ2VvbG9jYXRlZCBlYXJ0aHNoaW5lIHJhZGlhbmNlcyAxLW9yYml0IGwyIHN3YXRoIDEzeDEyIGttIHYwMDMgKG9tbDFicnV6KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9NTDFCUlVaXCIsXCIzXCIsMTIzOTk2Njc4MCwzOF0ifQ%3D%3D/OMAEROG_003/items",
             "type": "application/json"
         }
     ],
diff --git a/datasets/OMAEROZ_003.json b/datasets/OMAEROZ_003.json
index 395c75339..1aed3a05d 100644
--- a/datasets/OMAEROZ_003.json
+++ b/datasets/OMAEROZ_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMAERO_003.json b/datasets/OMAERO_003.json
index d3fb238e7..f0a2d088a 100644
--- a/datasets/OMAERO_003.json
+++ b/datasets/OMAERO_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMAEROe_003.json b/datasets/OMAEROe_003.json
index 391cdd2f9..837656537 100644
--- a/datasets/OMAEROe_003.json
+++ b/datasets/OMAEROe_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMAERUVG_003.json b/datasets/OMAERUVG_003.json
index 7adbc49fb..91a1c3e42 100644
--- a/datasets/OMAERUVG_003.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OMAERUV_003.json b/datasets/OMAERUV_003.json
index 77a9a1b1d..d67c46c2f 100644
--- a/datasets/OMAERUV_003.json
+++ b/datasets/OMAERUV_003.json
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diff --git a/datasets/OMAERUV_004.json b/datasets/OMAERUV_004.json
index 956124cc0..643ddf9c4 100644
--- a/datasets/OMAERUV_004.json
+++ b/datasets/OMAERUV_004.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMAERUV_CPR_003.json b/datasets/OMAERUV_CPR_003.json
index be5ac85d0..651732097 100644
--- a/datasets/OMAERUV_CPR_003.json
+++ b/datasets/OMAERUV_CPR_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMAERUVd_003.json b/datasets/OMAERUVd_003.json
index bc846e111..542b02f0d 100644
--- a/datasets/OMAERUVd_003.json
+++ b/datasets/OMAERUVd_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMBRO_003.json b/datasets/OMBRO_003.json
index 0ae46fd7e..a8de46218 100644
--- a/datasets/OMBRO_003.json
+++ b/datasets/OMBRO_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDO2G_003.json b/datasets/OMCLDO2G_003.json
index 118f408fd..66fb3c85b 100644
--- a/datasets/OMCLDO2G_003.json
+++ b/datasets/OMCLDO2G_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDO2Z_003.json b/datasets/OMCLDO2Z_003.json
index 23cc17fde..e68751c48 100644
--- a/datasets/OMCLDO2Z_003.json
+++ b/datasets/OMCLDO2Z_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDO2_003.json b/datasets/OMCLDO2_003.json
index 4d10dea3b..d61bcc51d 100644
--- a/datasets/OMCLDO2_003.json
+++ b/datasets/OMCLDO2_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDO2_CPR_003.json b/datasets/OMCLDO2_CPR_003.json
index 6f5206498..67a1ac287 100644
--- a/datasets/OMCLDO2_CPR_003.json
+++ b/datasets/OMCLDO2_CPR_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDRRG_003.json b/datasets/OMCLDRRG_003.json
index 872003349..2e8169802 100644
--- a/datasets/OMCLDRRG_003.json
+++ b/datasets/OMCLDRRG_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDRR_003.json b/datasets/OMCLDRR_003.json
index 2a7dac028..5714d8c61 100644
--- a/datasets/OMCLDRR_003.json
+++ b/datasets/OMCLDRR_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDRR_004.json b/datasets/OMCLDRR_004.json
index cb1658194..0a4b5ed97 100644
--- a/datasets/OMCLDRR_004.json
+++ b/datasets/OMCLDRR_004.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMCLDRR_CPR_003.json b/datasets/OMCLDRR_CPR_003.json
index 5088b2b6b..f25af76f7 100644
--- a/datasets/OMCLDRR_CPR_003.json
+++ b/datasets/OMCLDRR_CPR_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMDOAO3G_003.json b/datasets/OMDOAO3G_003.json
index e45f2a689..3e153f9f2 100644
--- a/datasets/OMDOAO3G_003.json
+++ b/datasets/OMDOAO3G_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMDOAO3Z_003.json b/datasets/OMDOAO3Z_003.json
index 5b3cff21e..1d9b4bf6b 100644
--- a/datasets/OMDOAO3Z_003.json
+++ b/datasets/OMDOAO3Z_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMDOAO3_003.json b/datasets/OMDOAO3_003.json
index 22d9f8513..6b1a1c189 100644
--- a/datasets/OMDOAO3_003.json
+++ b/datasets/OMDOAO3_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMDOAO3e_003.json b/datasets/OMDOAO3e_003.json
index 57262ac13..e9098e6c9 100644
--- a/datasets/OMDOAO3e_003.json
+++ b/datasets/OMDOAO3e_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMGLER_003.json b/datasets/OMGLER_003.json
index 1c624b2a3..9f5e3572d 100644
--- a/datasets/OMGLER_003.json
+++ b/datasets/OMGLER_003.json
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diff --git a/datasets/OMHCHOG_003.json b/datasets/OMHCHOG_003.json
index 054606428..359cacc07 100644
--- a/datasets/OMHCHOG_003.json
+++ b/datasets/OMHCHOG_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMHCHO_003.json b/datasets/OMHCHO_003.json
index 48dfbe366..76c407c59 100644
--- a/datasets/OMHCHO_003.json
+++ b/datasets/OMHCHO_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMHCHOd_003.json b/datasets/OMHCHOd_003.json
index 4cc1e4b2a..0ca11a595 100644
--- a/datasets/OMHCHOd_003.json
+++ b/datasets/OMHCHOd_003.json
@@ -42,7 +42,7 @@
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index b6be973d4..ffa5598a3 100644
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diff --git a/datasets/OMI_MINDS_NO2G_1.1.json b/datasets/OMI_MINDS_NO2G_1.1.json
index e94e32279..36819c98c 100644
--- a/datasets/OMI_MINDS_NO2G_1.1.json
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index 5d387f1e8..72060b73b 100644
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index bb2d64ae9..9f71a9205 100644
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diff --git a/datasets/OML1BIRR_003.json b/datasets/OML1BIRR_003.json
index 9acd0beb8..f90f9c872 100644
--- a/datasets/OML1BIRR_003.json
+++ b/datasets/OML1BIRR_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OML1BIRR_004.json b/datasets/OML1BIRR_004.json
index 836c0b091..562ebf399 100644
--- a/datasets/OML1BIRR_004.json
+++ b/datasets/OML1BIRR_004.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OML1BRUG_003.json b/datasets/OML1BRUG_003.json
index d22268963..dc85407c4 100644
--- a/datasets/OML1BRUG_003.json
+++ b/datasets/OML1BRUG_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OML1BRUG_004.json b/datasets/OML1BRUG_004.json
index fd898c18f..150c9fdf3 100644
--- a/datasets/OML1BRUG_004.json
+++ b/datasets/OML1BRUG_004.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OML1BRUZ_003.json b/datasets/OML1BRUZ_003.json
index 42cee10c5..5284dc948 100644
--- a/datasets/OML1BRUZ_003.json
+++ b/datasets/OML1BRUZ_003.json
@@ -42,7 +42,7 @@
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index 5fd21cef2..52ef3f26a 100644
--- a/datasets/OML1BRUZ_004.json
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@@ -42,7 +42,7 @@
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index 7e0e62702..810f5d18b 100644
--- a/datasets/OML1BRVG_003.json
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diff --git a/datasets/OML1BRVG_004.json b/datasets/OML1BRVG_004.json
index 1d68d5be9..24b558dfa 100644
--- a/datasets/OML1BRVG_004.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OML1BRVZ_003.json b/datasets/OML1BRVZ_003.json
index f4636ad03..b5f646f76 100644
--- a/datasets/OML1BRVZ_003.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OML1BRVZ_004.json b/datasets/OML1BRVZ_004.json
index 123b38364..7e0067bf6 100644
--- a/datasets/OML1BRVZ_004.json
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@@ -42,7 +42,7 @@
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index 759192375..9180e33bd 100644
--- a/datasets/OMLER_003.json
+++ b/datasets/OMLER_003.json
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diff --git a/datasets/OMMYDAGEO_003.json b/datasets/OMMYDAGEO_003.json
index 27550ebe1..8354093e6 100644
--- a/datasets/OMMYDAGEO_003.json
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diff --git a/datasets/OMMYDCLD_003.json b/datasets/OMMYDCLD_003.json
index 722b7df5a..6b61d7b82 100644
--- a/datasets/OMMYDCLD_003.json
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diff --git a/datasets/OMNO2G_003.json b/datasets/OMNO2G_003.json
index e97a62156..5e5c1275f 100644
--- a/datasets/OMNO2G_003.json
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diff --git a/datasets/OMNO2_003.json b/datasets/OMNO2_003.json
index e4b0d87a9..915a8f285 100644
--- a/datasets/OMNO2_003.json
+++ b/datasets/OMNO2_003.json
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diff --git a/datasets/OMNO2_CPR_003.json b/datasets/OMNO2_CPR_003.json
index a2bb3aedd..94de9fe7f 100644
--- a/datasets/OMNO2_CPR_003.json
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diff --git a/datasets/OMNO2d_003.json b/datasets/OMNO2d_003.json
index 6c889fc0b..7832c1f8c 100644
--- a/datasets/OMNO2d_003.json
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diff --git a/datasets/OMO3PR_003.json b/datasets/OMO3PR_003.json
index ef9157d89..b57c73a49 100644
--- a/datasets/OMO3PR_003.json
+++ b/datasets/OMO3PR_003.json
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diff --git a/datasets/OMOCLO_003.json b/datasets/OMOCLO_003.json
index 6f207d19b..37e31c33e 100644
--- a/datasets/OMOCLO_003.json
+++ b/datasets/OMOCLO_003.json
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index 7c55b5717..e3fa68296 100644
--- a/datasets/OMPIXCORZ_003.json
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index 59d53d27b..d3a6e6ce5 100644
--- a/datasets/OMPIXCOR_003.json
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diff --git a/datasets/OMPS_N20_NMHCHO_L2_1.json b/datasets/OMPS_N20_NMHCHO_L2_1.json
index 8599d3b2b..2dc3ed9d2 100644
--- a/datasets/OMPS_N20_NMHCHO_L2_1.json
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index 2fe338356..21bc7904a 100644
--- a/datasets/OMPS_N20_NMSO2_PCA_L2_Step1_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OMPS_N21_LP_L1G_EV_1.0.json b/datasets/OMPS_N21_LP_L1G_EV_1.0.json
new file mode 100644
index 000000000..230564101
--- /dev/null
+++ b/datasets/OMPS_N21_LP_L1G_EV_1.0.json
@@ -0,0 +1,138 @@
+{
+    "type": "Collection",
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+    "stac_version": "1.0.0",
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+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
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+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_N21_LP_L1G_EV_1.0",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_N21_LP_L1G_EV_1.0/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V1.0 (OMPS_N21_LP_L1G_EV) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -84,
+                    180,
+                    84
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2022-11-10T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "1": {
+            "href": "https://snpp-omps.gesdisc.eosdis.nasa.gov/data/NOAA21_OMPS_Level1B/OMPS_N21_LP_L1G_EV.1.0/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTPS.",
+            "roles": [
+                "data"
+            ]
+        },
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/OMPS_NPP_LP_L1G_EV_2.6.jpeg",
+            "type": "image/jpeg",
+            "title": "Download OMPS_NPP_LP_L1G_EV_2.6.jpeg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/OMPS_NPP_LP_L1G_EV_2.6.jpeg",
+            "title": "Thumbnail",
+            "description": "OMPS Logo",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/search?q=OMPS_N21_LP_L1G_EV_1": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OMPS_N21_LP_L1G_EV_1.0",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OMPS_N21_LP_L1G_EV_1.0.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OMPS_N21_LP_L2_O3_DAILY_1.0.json b/datasets/OMPS_N21_LP_L2_O3_DAILY_1.0.json
new file mode 100644
index 000000000..c15618a89
--- /dev/null
+++ b/datasets/OMPS_N21_LP_L2_O3_DAILY_1.0.json
@@ -0,0 +1,158 @@
+{
+    "type": "Collection",
+    "id": "OMPS_N21_LP_L2_O3_DAILY_1.0",
+    "stac_version": "1.0.0",
+    "description": "The OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit collection contains ozone measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA-21 satellite. The LP ozone product measures the vertical distribution of ozone in the stratosphere and lower mesosphere. The algorithm derives ozone profile values along with errors in the UV from 29.5 km and 52.5 km, and in the visible from cloud top to 37.5 km (when there are no clouds the lower limit is 12.5 km). \n\nEach granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, the data from the center of the LP three slits are used to make a vertical profile. The profile is measured from the ground up to about 60 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.\n\nThe data are written using the Hierarchical Data Format Version 5 or HDF5.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_N21_LP_L2_O3_DAILY_1.0",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_N21_LP_L2_O3_DAILY_1.0/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit V1.0 (OMPS_N21_LP_L2_O3_DAILY) at GES DISC",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2022-11-10T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/OMPS_N21_LP_L2_O3_DAILY_1.0.jpeg",
+            "type": "image/jpeg",
+            "title": "Download OMPS_N21_LP_L2_O3_DAILY_1.0.jpeg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/OMPS_N21_LP_L2_O3_DAILY_1.0.jpeg",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/NOAA21_OMPS_Level2/OMPS_N21_LP_L2_O3_DAILY": {
+            "href": "https://snpp-omps.gesdisc.eosdis.nasa.gov/data/NOAA21_OMPS_Level2/OMPS_N21_LP_L2_O3_DAILY.2/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTPS.",
+            "roles": [
+                "data"
+            ]
+        },
+        "gov/search?q=OMPS_N21_LP_L2_O3_DAILY_1": {
+            "href": "https://search.earthdata.nasa.gov/search?q=OMPS_N21_LP_L2_O3_DAILY_1.0",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search Client to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/OMPS_N21_LP_L2_O3_DAILY_1.0.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_gesdisc_cumulus_prod_protected_NOAA21_OMPS_Level2_OMPS_N21_LP_L2_O3_DAILY_2_": {
+            "href": "s3://gesdisc-cumulus-prod-protected/NOAA21_OMPS_Level2/OMPS_N21_LP_L2_O3_DAILY.2/",
+            "title": "gesdisc_cumulus_prod_protected_NOAA21_OMPS_Level2_OMPS_N21_LP_L2_O3_DAILY_2_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.gesdisc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/OMPS_NPP_LP_L1G_EV_2.6.json b/datasets/OMPS_NPP_LP_L1G_EV_2.6.json
index f33cb81b3..2bff3be62 100644
--- a/datasets/OMPS_NPP_LP_L1G_EV_2.6.json
+++ b/datasets/OMPS_NPP_LP_L1G_EV_2.6.json
@@ -42,7 +42,7 @@
         },
         {
             "rel": "self",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbDIgbm0gZm9ybWFsZGVoeWRlIChoY2hvKSB0b3RhbCBjb2x1bW4gc3dhdGggb3JiaXRhbFwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NSENIT19MMlwiLFwiMVwiLDI0Nzc3NTE1MzYsN10iLCJ1bW0iOiJbXCJvbXBzLW4yMCBsMiBubSBmb3JtYWxkZWh5ZGUgKGhjaG8pIHRvdGFsIGNvbHVtbiBzd2F0aCBvcmJpdGFsXCIsXCJHRVNfRElTQ1wiLFwiT01QU19OMjBfTk1IQ0hPX0wyXCIsXCIxXCIsMjQ3Nzc1MTUzNiw3XSJ9/OMPS_NPP_LP_L1G_EV_2.6",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L1G_EV_2.6",
             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
         },
         {
             "rel": "items",
-            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbDIgbm0gZm9ybWFsZGVoeWRlIChoY2hvKSB0b3RhbCBjb2x1bW4gc3dhdGggb3JiaXRhbFwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NSENIT19MMlwiLFwiMVwiLDI0Nzc3NTE1MzYsN10iLCJ1bW0iOiJbXCJvbXBzLW4yMCBsMiBubSBmb3JtYWxkZWh5ZGUgKGhjaG8pIHRvdGFsIGNvbHVtbiBzd2F0aCBvcmJpdGFsXCIsXCJHRVNfRElTQ1wiLFwiT01QU19OMjBfTk1IQ0hPX0wyXCIsXCIxXCIsMjQ3Nzc1MTUzNiw3XSJ9/OMPS_NPP_LP_L1G_EV_2.6/items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L1G_EV_2.6/items",
             "type": "application/json"
         }
     ],
diff --git a/datasets/OMPS_NPP_LP_L1G_EV_2.json b/datasets/OMPS_NPP_LP_L1G_EV_2.json
index 2cf2193c0..85400efc9 100644
--- a/datasets/OMPS_NPP_LP_L1G_EV_2.json
+++ b/datasets/OMPS_NPP_LP_L1G_EV_2.json
@@ -42,7 +42,7 @@
         },
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index 7dd1733e6..c30b02abe 100644
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index 59e6c1156..fb0908ace 100644
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index bad783c89..12959089a 100644
--- a/datasets/OMPS_NPP_LP_L2_O3_DAILY_2.json
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diff --git a/datasets/OMPS_NPP_LP_L2_Temp_DAILY_1.0.json b/datasets/OMPS_NPP_LP_L2_Temp_DAILY_1.0.json
index a0bcfa0b3..e6590262f 100644
--- a/datasets/OMPS_NPP_LP_L2_Temp_DAILY_1.0.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OMPS_NPP_LP_L3_AER_MONTHLY_1.json b/datasets/OMPS_NPP_LP_L3_AER_MONTHLY_1.json
index b7a4e2d97..380e66dab 100644
--- a/datasets/OMPS_NPP_LP_L3_AER_MONTHLY_1.json
+++ b/datasets/OMPS_NPP_LP_L3_AER_MONTHLY_1.json
@@ -42,7 +42,7 @@
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index 181dba763..16f7d8ca8 100644
--- a/datasets/OMPS_NPP_NMCLDRR_L2_2.json
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index 6b0875f20..0a2fe0bef 100644
--- a/datasets/OMPS_NPP_NMEV_L1B_2.json
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diff --git a/datasets/OMPS_NPP_NMHCHO_L2_1.json b/datasets/OMPS_NPP_NMHCHO_L2_1.json
index 68312af10..baee0234e 100644
--- a/datasets/OMPS_NPP_NMHCHO_L2_1.json
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index 42ba0ef48..67e0d37c0 100644
--- a/datasets/OMPS_NPP_NMMIEAI_L2_2.json
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diff --git a/datasets/OMPS_NPP_NMNO2_L2_2.json b/datasets/OMPS_NPP_NMNO2_L2_2.json
index 7b9d75965..ba453c911 100644
--- a/datasets/OMPS_NPP_NMNO2_L2_2.json
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index 608e39242..0e99e0a15 100644
--- a/datasets/OMPS_NPP_NMSO2_L2_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OMPS_NPP_NMSO2_PCA_L2_2.json b/datasets/OMPS_NPP_NMSO2_PCA_L2_2.json
index 7de9bd0f8..d47c9f47f 100644
--- a/datasets/OMPS_NPP_NMSO2_PCA_L2_2.json
+++ b/datasets/OMPS_NPP_NMSO2_PCA_L2_2.json
@@ -42,7 +42,7 @@
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index 76c2aa139..5080f2cef 100644
--- a/datasets/OMPS_NPP_NMSO2_PCA_L3_DAILY_1.json
+++ b/datasets/OMPS_NPP_NMSO2_PCA_L3_DAILY_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMPS_NPP_NMTO3_L2_2.json b/datasets/OMPS_NPP_NMTO3_L2_2.json
index 95acba641..dcf104064 100644
--- a/datasets/OMPS_NPP_NMTO3_L2_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OMPS_NPP_NMTO3_L3_DAILY_2.json b/datasets/OMPS_NPP_NMTO3_L3_DAILY_2.json
index 4f33d1fca..a246d077a 100644
--- a/datasets/OMPS_NPP_NMTO3_L3_DAILY_2.json
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@@ -42,7 +42,7 @@
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index 3262d7d1e..159c17467 100644
--- a/datasets/OMPS_NPP_NPBUVO3_L2_2.9.json
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@@ -42,7 +42,7 @@
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index 3a288aa67..62ae07e5e 100644
--- a/datasets/OMPS_NPP_NPBUVO3_L2_2.json
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index f800f1d06..5c4affca2 100644
--- a/datasets/OMPS_NPP_NPEV_L1B_2.json
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diff --git a/datasets/OMSO2G_003.json b/datasets/OMSO2G_003.json
index fc49dd4c7..334b25d11 100644
--- a/datasets/OMSO2G_003.json
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diff --git a/datasets/OMSO2_003.json b/datasets/OMSO2_003.json
index c3dacc7dc..f19e38e5e 100644
--- a/datasets/OMSO2_003.json
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index 8c7a3a615..d8f6d94f3 100644
--- a/datasets/OMSO2_CPR_003.json
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index 5fa69d8f3..0103223be 100644
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diff --git a/datasets/OMTO3G_003.json b/datasets/OMTO3G_003.json
index f03fccf3e..081e2b070 100644
--- a/datasets/OMTO3G_003.json
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diff --git a/datasets/OMTO3_003.json b/datasets/OMTO3_003.json
index d6afe3d65..7588bab75 100644
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diff --git a/datasets/OMTO3_CPR_003.json b/datasets/OMTO3_CPR_003.json
index ff4079fd3..c0df4720d 100644
--- a/datasets/OMTO3_CPR_003.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/OMTO3d_003.json b/datasets/OMTO3d_003.json
index 0291d0966..ac6472228 100644
--- a/datasets/OMTO3d_003.json
+++ b/datasets/OMTO3d_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMTO3e_003.json b/datasets/OMTO3e_003.json
index c6a1046c6..19172f7ff 100644
--- a/datasets/OMTO3e_003.json
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diff --git a/datasets/OMUANC_004.json b/datasets/OMUANC_004.json
index 2030db3ea..a99be652f 100644
--- a/datasets/OMUANC_004.json
+++ b/datasets/OMUANC_004.json
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diff --git a/datasets/OMUVBG_003.json b/datasets/OMUVBG_003.json
index 1b73a0253..b7f3bbcbe 100644
--- a/datasets/OMUVBG_003.json
+++ b/datasets/OMUVBG_003.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OMUVB_003.json b/datasets/OMUVB_003.json
index 67d9d567e..3fa59b7bc 100644
--- a/datasets/OMUVB_003.json
+++ b/datasets/OMUVB_003.json
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diff --git a/datasets/OMUVBd_003.json b/datasets/OMUVBd_003.json
index 1ade82c7d..920fb815e 100644
--- a/datasets/OMUVBd_003.json
+++ b/datasets/OMUVBd_003.json
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diff --git a/datasets/OMVANC_004.json b/datasets/OMVANC_004.json
index d22778297..a226d2bef 100644
--- a/datasets/OMVANC_004.json
+++ b/datasets/OMVANC_004.json
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diff --git a/datasets/OPERA_L3_DIST-ALERT-HLS_V1_1.json b/datasets/OPERA_L3_DIST-ALERT-HLS_V1_1.json
index 2c411bde8..113f97f56 100644
--- a/datasets/OPERA_L3_DIST-ALERT-HLS_V1_1.json
+++ b/datasets/OPERA_L3_DIST-ALERT-HLS_V1_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/OPERA_L3_DIST-ANN-HLS_V1_1.json b/datasets/OPERA_L3_DIST-ANN-HLS_V1_1.json
index 1f967777c..85be80ee5 100644
--- a/datasets/OPERA_L3_DIST-ANN-HLS_V1_1.json
+++ b/datasets/OPERA_L3_DIST-ANN-HLS_V1_1.json
@@ -42,7 +42,7 @@
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index ba4c51b73..cbd5d1653 100644
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diff --git a/datasets/PET_PU_3H025_001.json b/datasets/PET_PU_3H025_001.json
index ba9957e76..ea4c6f583 100644
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diff --git a/datasets/PET_PU_3H025_002.json b/datasets/PET_PU_3H025_002.json
index 7df813204..4b0af7464 100644
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diff --git a/datasets/PMRN6L1RAD_CDROM_001.json b/datasets/PMRN6L1RAD_CDROM_001.json
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diff --git a/datasets/PREFIRE_SAT2_0-BUS-TLM_R01.json b/datasets/PREFIRE_SAT2_0-BUS-TLM_R01.json
new file mode 100644
index 000000000..5c4c63907
--- /dev/null
+++ b/datasets/PREFIRE_SAT2_0-BUS-TLM_R01.json
@@ -0,0 +1,152 @@
+{
+    "type": "Collection",
+    "id": "PREFIRE_SAT2_0-BUS-TLM_R01",
+    "stac_version": "1.0.0",
+    "description": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Telemetry (PREFIRE_SAT2_0-BUS-TLM) contains positioning and pointing information for one of two PREFIRE polar orbiting CubeSats. Both CubeSats carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 \u00b5m. Most polar emissions are in the FIR but have not been measured on a large scale.  PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions.  This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.\r\n\r\nThis collection contains the time, beta angle, orbit position and velocity, and the quaternion of PREFIRE Satellite 2 (PREFIRE-SAT2).  Combined with a Digital Elevation Map, these telemeters geolocate PREFIRE data on the Earth\u2019s surface.  \r\n\r\nData retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions.  This data is retrieved at a frequency of 1Hz and is available in CSV format.\r\n\r\nPositioning and pointing information for the sister satellite, PREFIRE-SAT1, can be found in the PREFIRE_SAT1_0-BUS-TLM collection.\r\n\r\n",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/PREFIRE_SAT2_0-BUS-TLM_R01",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD",
+            "type": "application/json",
+            "title": "LARC_CLOUD STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/PREFIRE_SAT2_0-BUS-TLM_R01/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "LARC_CLOUD",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 telemetry R01",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -84,
+                    180,
+                    84
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2024-05-01T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://asdc.larc.nasa.gov/static/images/project_logos/prefire.png",
+            "type": "image/jpeg",
+            "title": "Download prefire.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://asdc.larc.nasa.gov/static/images/project_logos/prefire.png",
+            "title": "Thumbnail",
+            "description": "Mission Logo",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search/granules?p=C3246712895-LARC_CLOUD",
+            "title": "Direct Download",
+            "description": "Earthdata Search for PREFIRE_SAT2_0-BUS-TLM_R01\n (NASA Application to search, discover, visualize, refine, and access NASA Earth Observation data)",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata_0": {
+            "href": "https://asdc.larc.nasa.gov/project/PREFIRE",
+            "title": "Provider Metadata [0]",
+            "description": "PREFIRE Data Set Landing Page ASDC",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "provider_metadata_1": {
+            "href": "https://doi.org/10.5067/PREFIRE-SAT2/PREFIRE/BUS-TLM_L0.R01",
+            "title": "Provider Metadata [1]",
+            "description": "DOI data set landing page for PREFIRE_SAT2_0-BUS-TLM_V01",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.asdc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.asdc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/PREFIRE_SAT2_0-PAYLOAD-TLM_R01.json b/datasets/PREFIRE_SAT2_0-PAYLOAD-TLM_R01.json
new file mode 100644
index 000000000..036fe2986
--- /dev/null
+++ b/datasets/PREFIRE_SAT2_0-PAYLOAD-TLM_R01.json
@@ -0,0 +1,152 @@
+{
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+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
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+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712936-LARC_CLOUD.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712936-LARC_CLOUD.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
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+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712936-LARC_CLOUD.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
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+            "title": "CMR UMM_JSON metadata for collection"
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+        {
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+            "roles": [
+                "host"
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+            ]
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+    },
+    "license": "proprietary",
+    "assets": {
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+            "type": "image/jpeg",
+            "title": "Download prefire.png",
+            "roles": [
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+        },
+        "thumbnail": {
+            "href": "https://asdc.larc.nasa.gov/static/images/project_logos/prefire.png",
+            "title": "Thumbnail",
+            "description": "Mission Logo",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search/granules?p=C3246712936-LARC_CLOUD",
+            "title": "Direct Download",
+            "description": "Earthdata Search for PREFIRE_SAT2_0-PAYLOAD-TLM_R01 (NASA Application to search, discover, visualize, refine, and access NASA Earth Observation data)",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata_0": {
+            "href": "https://asdc.larc.nasa.gov/project/PREFIRE",
+            "title": "Provider Metadata [0]",
+            "description": "PREFIRE Data Set Landing Page ASDC",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "provider_metadata_1": {
+            "href": "https://doi.org/10.5067/PREFIRE-SAT2/PREFIRE/PAYLOAD-TLM_L0.R01",
+            "title": "Provider Metadata [1]",
+            "description": "DOI data set landing page for PREFIRE_SAT2_0-PAYLOAD-TLM_R01",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.asdc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.asdc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/PREFIRE_SAT2_0-PAYLOAD_R01.json b/datasets/PREFIRE_SAT2_0-PAYLOAD_R01.json
new file mode 100644
index 000000000..13367da2b
--- /dev/null
+++ b/datasets/PREFIRE_SAT2_0-PAYLOAD_R01.json
@@ -0,0 +1,152 @@
+{
+    "type": "Collection",
+    "id": "PREFIRE_SAT2_0-PAYLOAD_R01",
+    "stac_version": "1.0.0",
+    "description": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Payload (PREFIRE_SAT2_0-PAYLOAD) contains the uncurated raw measurements from one of two PREFIRE Thermal Infrared Spectrometers (TIRS-PREFIRE), which is a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 \u00b5m. Most polar emissions are in the FIR but have not been measured on a large scale.  PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions.  This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.\r\n\r\nThis collection contains the raw and uncurated digital number counts for TIRS-PREFIRE aboard PREFIRE Satellite 2 (PREFIRE-SAT2).  Data retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions.  This data has a temporal resolution of 0.707 seconds and is available in binary format.\r\n\r\nRaw, uncurated digital number counts for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_0-PAYLOAD collection.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/PREFIRE_SAT2_0-PAYLOAD_R01",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD",
+            "type": "application/json",
+            "title": "LARC_CLOUD STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/PREFIRE_SAT2_0-PAYLOAD_R01/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "LARC_CLOUD",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Payload R01",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -84,
+                    180,
+                    84
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2024-05-01T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://asdc.larc.nasa.gov/static/images/project_logos/prefire.png",
+            "type": "image/jpeg",
+            "title": "Download prefire.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://asdc.larc.nasa.gov/static/images/project_logos/prefire.png",
+            "title": "Thumbnail",
+            "description": "Mission Logo",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search/granules?p=C3246712916-LARC_CLOUD",
+            "title": "Direct Download",
+            "description": "Earthdata Search for PREFIRE_SAT2_0-PAYLOAD_R01 (NASA Application to search, discover, visualize, refine, and access NASA Earth Observation data)",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata_0": {
+            "href": "https://asdc.larc.nasa.gov/project/PREFIRE",
+            "title": "Provider Metadata [0]",
+            "description": "PREFIRE Data Set Landing Page ASDC",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "provider_metadata_1": {
+            "href": "https://doi.org/10.5067/PREFIRE-SAT2/PREFIRE/PAYLOAD_L0.R01",
+            "title": "Provider Metadata [1]",
+            "description": "DOI data set landing page for PREFIRE_SAT2_0-PAYLOAD_R01",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.asdc.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.asdc.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/Peatland_carbon_balance_1382_1.json b/datasets/Peatland_carbon_balance_1382_1.json
index 04379c7f5..56000a833 100644
--- a/datasets/Peatland_carbon_balance_1382_1.json
+++ b/datasets/Peatland_carbon_balance_1382_1.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/PermafrostThaw_CarbonEmissions_1872_1.json b/datasets/PermafrostThaw_CarbonEmissions_1872_1.json
index 6078e6b3e..ab0138869 100644
--- a/datasets/PermafrostThaw_CarbonEmissions_1872_1.json
+++ b/datasets/PermafrostThaw_CarbonEmissions_1872_1.json
@@ -42,7 +42,7 @@
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+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wicHJlLWxiYSBmbHVhbWF6b24gZXhwZXJpbWVudCBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJGTFVBTUFaT05fODk2XCIsXCIxXCIsMjgwNDgyMDgwNiwyXSIsInVtbSI6IltcInByZS1sYmEgZmx1YW1hem9uIGV4cGVyaW1lbnQgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwiRkxVQU1BWk9OXzg5NlwiLFwiMVwiLDI4MDQ4MjA4MDYsMl0ifQ%3D%3D/PermafrostThaw_CarbonEmissions_1872_1/items",
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diff --git a/datasets/PhenoCam_V2_1674_2.json b/datasets/PhenoCam_V2_1674_2.json
index 15df6abc4..cb911eb30 100644
--- a/datasets/PhenoCam_V2_1674_2.json
+++ b/datasets/PhenoCam_V2_1674_2.json
@@ -42,7 +42,7 @@
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index 66602cac6..0c82cc270 100644
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index 4350c6c59..9c1b02203 100644
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index 9dad66aa3..eb7935197 100644
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index 9c605733f..1ed9171e8 100644
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index f742012b1..44cbd0683 100644
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+++ b/datasets/Polar-VPRM_Alaskan-NEE_1314_1.json
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index 34457d019..aaefa3933 100644
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index 503972df7..8b56625e5 100644
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index bed185f10..6d0fc8bbd 100644
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diff --git a/datasets/PreDeltaX_Insitu_Reflectance_1804_1.json b/datasets/PreDeltaX_Insitu_Reflectance_1804_1.json
index 065312da6..9af3fe37a 100644
--- a/datasets/PreDeltaX_Insitu_Reflectance_1804_1.json
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@@ -42,7 +42,7 @@
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index d446a3c0f..cc1cb7c64 100644
--- a/datasets/PreDeltaX_L2_AVIRIS_SR_1826_1.json
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index ae87df0db..aa3b8e165 100644
--- a/datasets/PreDeltaX_L2_AirSWOT_1818_1.json
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diff --git a/datasets/PreDeltaX_L3_AVIRIS_Biomass_1821_1.json b/datasets/PreDeltaX_L3_AVIRIS_Biomass_1821_1.json
index 758371ed9..ad44fdfa7 100644
--- a/datasets/PreDeltaX_L3_AVIRIS_Biomass_1821_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/PreDeltaX_L3_AVIRIS_Sediment_1822_1.json b/datasets/PreDeltaX_L3_AVIRIS_Sediment_1822_1.json
index ad5dc3f94..cbc801e12 100644
--- a/datasets/PreDeltaX_L3_AVIRIS_Sediment_1822_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/PreDeltaX_L3_AirSWOT_WL_1819_1.json b/datasets/PreDeltaX_L3_AirSWOT_WL_1819_1.json
index 1fced6cbb..3994bd0ac 100644
--- a/datasets/PreDeltaX_L3_AirSWOT_WL_1819_1.json
+++ b/datasets/PreDeltaX_L3_AirSWOT_WL_1819_1.json
@@ -42,7 +42,7 @@
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index fe4ed45bd..1dcc3117e 100644
--- a/datasets/PreDeltaX_Sonar_Bathymetry_1807_1.json
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@@ -42,7 +42,7 @@
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index c08cb3f5c..74acbd04e 100644
--- a/datasets/PreDeltaX_TSS_Concentration_1802_1.json
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index b1db62bc5..aa6c60157 100644
--- a/datasets/PreDeltaX_UAVSAR_Channel_Maps_1954_1.json
+++ b/datasets/PreDeltaX_UAVSAR_Channel_Maps_1954_1.json
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diff --git a/datasets/PreDeltaX_UAVSAR_SLC_1816_1.json b/datasets/PreDeltaX_UAVSAR_SLC_1816_1.json
index 155d2c57d..ea0921812 100644
--- a/datasets/PreDeltaX_UAVSAR_SLC_1816_1.json
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index 40a7b51d0..2af7f3eb6 100644
--- a/datasets/PreDeltaX_UAVSAR_WaterLevel_1823_1.json
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index 7ccea4a0f..a9776cc10 100644
--- a/datasets/PreDeltaX_Vegetation_Structure_1805_1.json
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index f7dea153a..29422cca2 100644
--- a/datasets/PreDeltaX_Water_Level_Data_1801_1.json
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index d2ae50ff8..5e76539d5 100644
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index e7105b9a2..f8eeb68a2 100644
--- a/datasets/Prudhoe_Bay_Veg_Maps_1387_1.json
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diff --git a/datasets/RADAMBrasil_941_1.json b/datasets/RADAMBrasil_941_1.json
index f8f151133..c607998cf 100644
--- a/datasets/RADAMBrasil_941_1.json
+++ b/datasets/RADAMBrasil_941_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/RBLE_917_1.json b/datasets/RBLE_917_1.json
index 7de5e414a..1458b8a99 100644
--- a/datasets/RBLE_917_1.json
+++ b/datasets/RBLE_917_1.json
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diff --git a/datasets/RSS18_AVIRIS_L1B_449_1.json b/datasets/RSS18_AVIRIS_L1B_449_1.json
new file mode 100644
index 000000000..56d501c9e
--- /dev/null
+++ b/datasets/RSS18_AVIRIS_L1B_449_1.json
@@ -0,0 +1,159 @@
+{
+    "type": "Collection",
+    "id": "RSS18_AVIRIS_L1B_449_1",
+    "stac_version": "1.0.0",
+    "description": "This dataset holds Level 1B (L1B) radiance data collected by the AVIRIS-Classic instrument near Prince Albert, Saskatchewan, Canada, on August 14, 1996.  This imagery was acquired for the Boreal Ecosystem-Atmosphere Study (BOREAS) project in the boreal forests of central Canada. BOREAS focused on improving the understanding of exchanges of radiative energy, sensible heat, water, CO2 and trace gases between the boreal forest and the lower atmosphere. NASA's AVIRIS-Classic is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-Classic measures reflected radiance in 224 contiguous bands at approximately 10-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 400-2500 nm. The AVIRIS-Classic sensor has a 1 milliradian instantaneous field of view, providing altitude dependent ground sampling distances from 20 m to sub meter range. For these data, AVIRIS-Classic was deployed on NASA's ER-2 high altitude aircraft.  These spectra are acquired as images with 20-meter spatial resolution, 11 km swath width, and flight lines up to 800 km in length. The measurements are spectrally, radiometrically, and geometrically calibrated. There are seven flight lines subdivided into 66 scenes. The dataset includes the radiance imagery cube for each scene along with calibration and navigation information. The radiance data are in instrument coordinates, georeferenced by center of each scan line, and provided in a binary file. Metadata are included in a mixture of binary and text file formats.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHJzcy0xNCBnb2VzLTcgbGV2ZWwtMiBzaG9ydHdhdmUgYW5kIGxvbmd3YXZlIHJhZGlhdGlvbiBpbWFnZXNcIixcIk9STkxfQ0xPVURcIixcImdvZXM3Ml81NTRcIixcIjFcIiwyOTI5MTYzODk2LDJdIiwidW1tIjoiW1wiYm9yZWFzIHJzcy0xNCBnb2VzLTcgbGV2ZWwtMiBzaG9ydHdhdmUgYW5kIGxvbmd3YXZlIHJhZGlhdGlvbiBpbWFnZXNcIixcIk9STkxfQ0xPVURcIixcImdvZXM3Ml81NTRcIixcIjFcIiwyOTI5MTYzODk2LDJdIn0%3D/RSS18_AVIRIS_L1B_449_1",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD",
+            "type": "application/json",
+            "title": "ORNL_CLOUD STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHJzcy0xNCBnb2VzLTcgbGV2ZWwtMiBzaG9ydHdhdmUgYW5kIGxvbmd3YXZlIHJhZGlhdGlvbiBpbWFnZXNcIixcIk9STkxfQ0xPVURcIixcImdvZXM3Ml81NTRcIixcIjFcIiwyOTI5MTYzODk2LDJdIiwidW1tIjoiW1wiYm9yZWFzIHJzcy0xNCBnb2VzLTcgbGV2ZWwtMiBzaG9ydHdhdmUgYW5kIGxvbmd3YXZlIHJhZGlhdGlvbiBpbWFnZXNcIixcIk9STkxfQ0xPVURcIixcImdvZXM3Ml81NTRcIixcIjFcIiwyOTI5MTYzODk2LDJdIn0%3D/RSS18_AVIRIS_L1B_449_1/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "ORNL_CLOUD",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "BOREAS RSS-18 Level 1B AVIRIS At-Sensor Radiance Imagery",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -106.49,
+                    53.45,
+                    -105.03,
+                    54.32
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "1996-08-14T16:24:39Z",
+                    "1996-08-14T17:48:33Z"
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://daac.ornl.gov/BOREAS/guides/RSS18_AVIRIS_L1B_Fig1.jpg",
+            "type": "image/jpeg",
+            "title": "Download RSS18_AVIRIS_L1B_Fig1.jpg",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://daac.ornl.gov/BOREAS/guides/RSS18_AVIRIS_L1B_Fig1.jpg",
+            "title": "Thumbnail",
+            "description": "False color image of AVIRIS-Classic scene acquired over Waskesiu Lake, north of Prince Albert, Saskatchewan, Canada, on 1996-08-14.Flight: f960814t01, run 01, scene 07; latitude 53.9709, longitude -106.3295. Image shows channels 128 (1563 nm), 33 (666 nm), and 10 (458 nm) as red, green, and blue, respectively.",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "ornl": {
+            "href": "https://daac.ornl.gov/daacdata/boreas/RSS/RSS18_AVIRIS_L1B/data/",
+            "title": "Direct Download [0]",
+            "description": "This link allows direct data access via Earthdata login",
+            "roles": [
+                "data"
+            ]
+        },
+        "gov/protected/bundle/RSS18_AVIRIS_L1B_449": {
+            "href": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/RSS18_AVIRIS_L1B_449.zip",
+            "title": "Direct Download [1]",
+            "description": "Collection bundle",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://doi.org/10.3334/ORNLDAAC/449",
+            "title": "Provider Metadata",
+            "description": "Data set Landing Page DOI URL",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_ornl_cumulus_prod_protected_boreas_RSS_RSS18_AVIRIS_L1B_": {
+            "href": "s3://ornl-cumulus-prod-protected/boreas/RSS/RSS18_AVIRIS_L1B/",
+            "title": "ornl_cumulus_prod_protected_boreas_RSS_RSS18_AVIRIS_L1B_",
+            "roles": [
+                "data"
+            ]
+        },
+        "s3_credentials": {
+            "href": "https://data.ornldaac.earthdata.nasa.gov/s3credentials",
+            "title": "S3 credentials API endpoint",
+            "roles": [
+                "metadata"
+            ]
+        },
+        "s3_credentials_documentation": {
+            "href": "https://data.ornldaac.earthdata.nasa.gov/s3credentialsREADME",
+            "title": "S3 credentials API endpoint documentation",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/ReSALT_ALT_GPR_1265_1.json b/datasets/ReSALT_ALT_GPR_1265_1.json
index fed82dd1f..fa9b0bf2e 100644
--- a/datasets/ReSALT_ALT_GPR_1265_1.json
+++ b/datasets/ReSALT_ALT_GPR_1265_1.json
@@ -42,7 +42,7 @@
         },
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-            "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wicGFudHJvcGljYWwgZm9yZXN0IGhlaWdodCBhbmQgYmlvbWFzcyBmcm9tIGdlZGkgYW5kIHRhbmRlbS14IGRhdGEgZnVzaW9uXCIsXCJPUk5MX0NMT1VEXCIsXCJGb3Jlc3RIdF9CaW9tYXNzX0dFRElfVERYXzIyOThcIixcIjFcIiwyODgzNjIzMTc0LDJdIiwidW1tIjoiW1wicGFudHJvcGljYWwgZm9yZXN0IGhlaWdodCBhbmQgYmlvbWFzcyBmcm9tIGdlZGkgYW5kIHRhbmRlbS14IGRhdGEgZnVzaW9uXCIsXCJPUk5MX0NMT1VEXCIsXCJGb3Jlc3RIdF9CaW9tYXNzX0dFRElfVERYXzIyOThcIixcIjFcIiwyODgzNjIzMTc0LDJdIn0%3D/ReSALT_ALT_GPR_1265_1",
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             "type": "application/json"
         },
         {
@@ -53,7 +53,7 @@
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index 319822d5c..95ee36d60 100644
--- a/datasets/ReSALT_InSAR_Barrow_1266_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/Respiration_622_1.json b/datasets/Respiration_622_1.json
index daefc5fdc..3e5b3009e 100644
--- a/datasets/Respiration_622_1.json
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diff --git a/datasets/Russian_Forest_Disturbance_1294_1.json b/datasets/Russian_Forest_Disturbance_1294_1.json
index 5543a43bf..6db0bec3e 100644
--- a/datasets/Russian_Forest_Disturbance_1294_1.json
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@@ -42,7 +42,7 @@
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index 6e9fb5de0..714c958bd 100644
--- a/datasets/S2K_EACM_Subset_623_1.json
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diff --git a/datasets/S5P_L1B_IR_SIR_1.json b/datasets/S5P_L1B_IR_SIR_1.json
index 28dd8636a..849eb4a46 100644
--- a/datasets/S5P_L1B_IR_SIR_1.json
+++ b/datasets/S5P_L1B_IR_SIR_1.json
@@ -42,7 +42,7 @@
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index 4e0ca4108..3b32a9074 100644
--- a/datasets/S5P_L1B_IR_SIR_2.json
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index 6fbe4b16b..4397a1dcc 100644
--- a/datasets/S5P_L1B_IR_UVN_1.json
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index 5b6615b13..66700f54d 100644
--- a/datasets/S5P_L1B_IR_UVN_2.json
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index 093668897..da9e97d16 100644
--- a/datasets/S5P_L1B_RA_BD1_1.json
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index 090d39acd..3e6e2da40 100644
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index a4c17efd8..cfb861f2c 100644
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index 1be1918dc..9762b835a 100644
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index 1b9f59346..cf54fff79 100644
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index 31bac131a..55d665779 100644
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index 722ff9a50..7e2d11253 100644
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index 50be2bbc0..4c64e2b4d 100644
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index cf66df48f..505742ce4 100644
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index 7135225c8..28914f275 100644
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index 82235cc47..b2c63204d 100644
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index 75e53d6d7..768554e33 100644
--- a/datasets/S5P_L1B_RA_BD5_1.json
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index f1eceaee7..cee8e878b 100644
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index 106a52a07..8d6828e72 100644
--- a/datasets/S5P_L1B_RA_BD6_1.json
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diff --git a/datasets/S5P_L1B_RA_BD6_HiR_1.json b/datasets/S5P_L1B_RA_BD6_HiR_1.json
index 41e0e4e62..3287074c8 100644
--- a/datasets/S5P_L1B_RA_BD6_HiR_1.json
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@@ -42,7 +42,7 @@
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index 068c99088..e4a3cde2a 100644
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index 0303d98ee..dfebb5b4c 100644
--- a/datasets/S5P_L1B_RA_BD7_1.json
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index 6bc15af06..00975427c 100644
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index e994b7b08..29977a21d 100644
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index 1e20a098c..a34226401 100644
--- a/datasets/S5P_L1B_RA_BD8_1.json
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index 44e3a6d1e..4303c3f16 100644
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index 054c5668a..c8437dd9a 100644
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index a862d4cc4..2e32ba4f5 100644
--- a/datasets/S5P_L2__AER_AI_1.json
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index 140e24bf1..1d06cc72f 100644
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index 5646bcc8c..494881460 100644
--- a/datasets/S5P_L2__AER_AI_HiR_2.json
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index f65d02e45..579203232 100644
--- a/datasets/S5P_L2__AER_LH_1.json
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index 8da9f0dd2..831eab81d 100644
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index f5027a870..c22fb32bc 100644
--- a/datasets/S5P_L2__AER_LH_HiR_2.json
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diff --git a/datasets/S5P_L2__CH4____1.json b/datasets/S5P_L2__CH4____1.json
index 2ff27bdcb..0de0edfa3 100644
--- a/datasets/S5P_L2__CH4____1.json
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index 8a3417e09..3318a34af 100644
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index 80eb9e025..9ee5b6d2a 100644
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index c84269237..76fd4ee03 100644
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index ce40a5708..137190016 100644
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diff --git a/datasets/S5P_L2__NP_BD3_1.json b/datasets/S5P_L2__NP_BD3_1.json
index df020f773..f6c496b24 100644
--- a/datasets/S5P_L2__NP_BD3_1.json
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index 3f0dea4fa..c37c6e942 100644
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index 91e8b2d7e..a2c1de179 100644
--- a/datasets/S5P_L2__NP_BD3_HiR_2.json
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diff --git a/datasets/S5P_L2__NP_BD6_1.json b/datasets/S5P_L2__NP_BD6_1.json
index 3bd1f1756..b54b38f03 100644
--- a/datasets/S5P_L2__NP_BD6_1.json
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index 74a72752d..e5455d421 100644
--- a/datasets/S5P_L2__NP_BD6_HiR_1.json
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index 00267d42f..c73c14a9b 100644
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index 0f1098e52..912f9a3c0 100644
--- a/datasets/S5P_L2__NP_BD7_1.json
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index 61ab73ea8..42b28f15e 100644
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diff --git a/datasets/S5P_L2__NP_BD7_HiR_2.json b/datasets/S5P_L2__NP_BD7_HiR_2.json
index 10e675f71..13e0d3b48 100644
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@@ -42,7 +42,7 @@
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index 88dd7df16..9ac3cdc5e 100644
--- a/datasets/S5P_L2__O3_TCL_1.json
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diff --git a/datasets/S5P_L2__O3_TCL_2.json b/datasets/S5P_L2__O3_TCL_2.json
index dc4ee76ec..384300a78 100644
--- a/datasets/S5P_L2__O3_TCL_2.json
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diff --git a/datasets/S5P_L2__O3_TOT_1.json b/datasets/S5P_L2__O3_TOT_1.json
index 19989f081..7e34742b8 100644
--- a/datasets/S5P_L2__O3_TOT_1.json
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index f7be1432f..6b493b9a8 100644
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index cf3182c90..856b9114e 100644
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index 65f96a3a6..2b9cac4c6 100644
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index 20bb1e20d..f976a21ae 100644
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diff --git a/datasets/SAMSN7L1RAD_CDROM_001.json b/datasets/SAMSN7L1RAD_CDROM_001.json
index f091f7b33..693f7e446 100644
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diff --git a/datasets/SAMSN7L1RAT_001.json b/datasets/SAMSN7L1RAT_001.json
index c3691a2cd..98d485fae 100644
--- a/datasets/SAMSN7L1RAT_001.json
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diff --git a/datasets/SAMSN7L3GRIDT_001.json b/datasets/SAMSN7L3GRIDT_001.json
index 8595e8cc3..89f377e62 100644
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@@ -42,7 +42,7 @@
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index 3d8319720..6e0aff1a6 100644
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index 38605d700..84ecee765 100644
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index f84b620f3..af6c35390 100644
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index 2a01d7120..cdafc9e2a 100644
--- a/datasets/SBUV2N09L3zm_1.json
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index debed3b56..5aa11b727 100644
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diff --git a/datasets/SBUV2N11L2_1.json b/datasets/SBUV2N11L2_1.json
index ed5487985..ae5511d5b 100644
--- a/datasets/SBUV2N11L2_1.json
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index 32492c84e..f3ce3e486 100644
--- a/datasets/SBUV2N11O3_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SBUV2N14L2_1.json b/datasets/SBUV2N14L2_1.json
index d860e4997..5c03196d5 100644
--- a/datasets/SBUV2N14L2_1.json
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@@ -42,7 +42,7 @@
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index ed6d34bc3..a44f164f1 100644
--- a/datasets/SBUV2N14L3zm_1.json
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@@ -42,7 +42,7 @@
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index 7b9f66441..ae55f7fd3 100644
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@@ -42,7 +42,7 @@
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index 2da9aae44..a66c0c019 100644
--- a/datasets/SBUV2N16L3zm_1.json
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@@ -42,7 +42,7 @@
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index 7df35b400..72ac7567f 100644
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index 7c79976b8..5dcf72a7a 100644
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index c2cb02a88..076217a5b 100644
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diff --git a/datasets/SBUV2N18L2_1.json b/datasets/SBUV2N18L2_1.json
index aa72280d2..3e4ef41e3 100644
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@@ -42,7 +42,7 @@
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index 9c985ef2b..c4423bade 100644
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index 01f8a86cb..ecab6923c 100644
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index 6ecad464a..a4ae8c4f6 100644
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diff --git a/datasets/SBUVN07L2_1.json b/datasets/SBUVN07L2_1.json
index 387bd479e..e34a7f234 100644
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SBUVN07L3zm_1.json b/datasets/SBUVN07L3zm_1.json
index 45111cef0..459e04b84 100644
--- a/datasets/SBUVN07L3zm_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SBUVN7O3_008.json b/datasets/SBUVN7O3_008.json
index 12a6e2171..af514e969 100644
--- a/datasets/SBUVN7O3_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SCAMSN6IM_001.json b/datasets/SCAMSN6IM_001.json
index d43cd630a..ccc157d8f 100644
--- a/datasets/SCAMSN6IM_001.json
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index fdcc6a5e8..429b196b1 100644
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index 262f26ed4..ff3c32239 100644
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index 0a5a7e78c..eb78928e8 100644
--- a/datasets/SCMRN5L1RAD_001.json
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index a200052d1..6432935fb 100644
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index ee0a47cd3..c55f8fcaa 100644
--- a/datasets/SCRN4L1RAD_CDROM_001.json
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diff --git a/datasets/SCRN5L1RAD_001.json b/datasets/SCRN5L1RAD_001.json
index 6f3fd2179..253f2317f 100644
--- a/datasets/SCRN5L1RAD_001.json
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index f51883f5d..881cd2ab3 100644
--- a/datasets/SENTINEL-1A_DP_GRD_FULL_1.json
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index e0dbaf03a..cfbb7d6e8 100644
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index 1ce1c687e..da3c95755 100644
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index ac6032e48..678aa5bdd 100644
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index f7ba2cc4f..cebac01e2 100644
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index ad1fe06c9..525fda900 100644
--- a/datasets/SENTINEL-1A_META_RAW_1.json
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index 94e92048b..4881b0222 100644
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index 4e09e7994..fc41cfa49 100644
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index 5d5ce5663..1946cdfbb 100644
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index bae40b032..b2d3589e6 100644
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index dbefb68cd..979d709cf 100644
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index 6f3ae5651..174671d8f 100644
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index 219bebd27..35f36fb05 100644
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index 5ad0af0fb..e2edb7212 100644
--- a/datasets/SHIFT_AVNG_Canopy_WaterContent_2242_1.json
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index 44c908460..4bee38f28 100644
--- a/datasets/SHIFT_AVNG_FullRes_QkLook_2189_1.json
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index 02230b8c5..066195506 100644
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index 5dee30368..aa14d1a17 100644
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diff --git a/datasets/SHIFT_Field_Survey_Metadata_2295_1.json b/datasets/SHIFT_Field_Survey_Metadata_2295_1.json
index 0f6e70b2d..254416141 100644
--- a/datasets/SHIFT_Field_Survey_Metadata_2295_1.json
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index 291ae325b..a4b5ebf59 100644
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index 72c1aeb54..7cca764cf 100644
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index fc0e89266..11a918786 100644
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index 042785f90..d4d431edc 100644
--- a/datasets/SISTER_Workflow_V004_2335_4.json
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index 425cc9263..dba646571 100644
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index 4f79c9ccd..59f4fad05 100644
--- a/datasets/SMAP_L1_L3_ANC_GEOS_1.json
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index 160f47ef5..29f1fcbe3 100644
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diff --git a/datasets/SMAP_L1_L3_ANC_SATELLITE_1.json b/datasets/SMAP_L1_L3_ANC_SATELLITE_1.json
index aea79f83e..691ad5820 100644
--- a/datasets/SMAP_L1_L3_ANC_SATELLITE_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SMAP_L1_L3_ANC_STATIC_1.json b/datasets/SMAP_L1_L3_ANC_STATIC_1.json
index ac8485012..777c3cc1e 100644
--- a/datasets/SMAP_L1_L3_ANC_STATIC_1.json
+++ b/datasets/SMAP_L1_L3_ANC_STATIC_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SMAP_L4_C_ANC_BPLUT_1.json b/datasets/SMAP_L4_C_ANC_BPLUT_1.json
index 384407f8f..94cc49d6f 100644
--- a/datasets/SMAP_L4_C_ANC_BPLUT_1.json
+++ b/datasets/SMAP_L4_C_ANC_BPLUT_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SMAP_L4_C_ANC_FPAR_CLIM_1.json b/datasets/SMAP_L4_C_ANC_FPAR_CLIM_1.json
index 48ffa4986..0418e708a 100644
--- a/datasets/SMAP_L4_C_ANC_FPAR_CLIM_1.json
+++ b/datasets/SMAP_L4_C_ANC_FPAR_CLIM_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SMAP_L4_C_ANC_MDL_LOG_1.json b/datasets/SMAP_L4_C_ANC_MDL_LOG_1.json
index 9882d54e4..ccdf5a643 100644
--- a/datasets/SMAP_L4_C_ANC_MDL_LOG_1.json
+++ b/datasets/SMAP_L4_C_ANC_MDL_LOG_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SMAP_L4_C_ANC_MDL_RIP_1.json b/datasets/SMAP_L4_C_ANC_MDL_RIP_1.json
index cacb484cb..a534f82fc 100644
--- a/datasets/SMAP_L4_C_ANC_MDL_RIP_1.json
+++ b/datasets/SMAP_L4_C_ANC_MDL_RIP_1.json
@@ -42,7 +42,7 @@
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index 24b3fb8ed..39a84bcbf 100644
--- a/datasets/SMAP_L4_C_ANC_MET_1.json
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@@ -42,7 +42,7 @@
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index 625d21214..5e3198f04 100644
--- a/datasets/SMAP_L4_C_ANC_MET_LOG_1.json
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index 66d098045..0b78f81a0 100644
--- a/datasets/SMAP_L4_C_ANC_MET_RIP_1.json
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index 2b53d0686..4d91965c2 100644
--- a/datasets/SMAP_L4_C_ANC_MOD_LOG_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SMAP_L4_C_ANC_MOD_RIP_1.json b/datasets/SMAP_L4_C_ANC_MOD_RIP_1.json
index 5a6820f5d..b51367c65 100644
--- a/datasets/SMAP_L4_C_ANC_MOD_RIP_1.json
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index 530031c5c..74973461c 100644
--- a/datasets/SMAP_L4_C_ANC_PARAM_1.json
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index 6773452be..66445b1ad 100644
--- a/datasets/SMAP_L4_C_ANC_SOC_RST_1.json
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index 8f2620e0d..f933d577a 100644
--- a/datasets/SMAP_L4_SM_ANC_CAT_TILE_1.json
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index 5667b089a..5cc61bfa7 100644
--- a/datasets/SMAP_L4_SM_ANC_CLIM_1.json
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diff --git a/datasets/SMAP_L4_SM_ANC_LOG_1.json b/datasets/SMAP_L4_SM_ANC_LOG_1.json
index ea1cdd6be..e8a363101 100644
--- a/datasets/SMAP_L4_SM_ANC_LOG_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SMAP_L4_SM_ANC_PARAM_1.json b/datasets/SMAP_L4_SM_ANC_PARAM_1.json
index 721cb0bc2..548943228 100644
--- a/datasets/SMAP_L4_SM_ANC_PARAM_1.json
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index 19d0e2ea0..24221b4d9 100644
--- a/datasets/SMAP_L4_SM_ANC_RIP_1.json
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index a50b8faea..4d175331b 100644
--- a/datasets/SMAP_L4_SM_ANC_RST_1.json
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diff --git a/datasets/SMERGE_RZSM0_40CM_2.0.json b/datasets/SMERGE_RZSM0_40CM_2.0.json
index f3d527ec8..1dcdd555c 100644
--- a/datasets/SMERGE_RZSM0_40CM_2.0.json
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index f8f889ed4..b943c1e10 100644
--- a/datasets/SMMRN7IM_001.json
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index 90341e130..9032b9e07 100644
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index 7ff0536eb..fe3781303 100644
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diff --git a/datasets/SNDR13CHRP1_2.json b/datasets/SNDR13CHRP1_2.json
index b164486bd..17652e992 100644
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@@ -42,7 +42,7 @@
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index fa3a1cfb9..acfa25dad 100644
--- a/datasets/SNDR13IML3SSDFCNSAT_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDR13IML3SSDFCVPD_2.json b/datasets/SNDR13IML3SSDFCVPD_2.json
index 731331e16..55f189017 100644
--- a/datasets/SNDR13IML3SSDFCVPD_2.json
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diff --git a/datasets/SNDRAQIL2CCPCCR_2.json b/datasets/SNDRAQIL2CCPCCR_2.json
index c9152ddc4..4367863e0 100644
--- a/datasets/SNDRAQIL2CCPCCR_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRAQIL2CCPRET_2.json b/datasets/SNDRAQIL2CCPRET_2.json
index a46b26c46..025bdb8e5 100644
--- a/datasets/SNDRAQIL2CCPRET_2.json
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@@ -42,7 +42,7 @@
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index d7417f07a..003f52bba 100644
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index d110e442b..ead83df13 100644
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index a4e464679..14dda05d6 100644
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index 37268b5b5..20c56bb97 100644
--- a/datasets/SNDRAQIL3SSDFCNSAT_2.json
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index 047e4170e..47356db17 100644
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index 157f589f0..07a373ed4 100644
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index 22c3ae519..1f894d9cb 100644
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diff --git a/datasets/SNDRAQIML2CCPCCR_2.json b/datasets/SNDRAQIML2CCPCCR_2.json
index 6604d29b9..914696e81 100644
--- a/datasets/SNDRAQIML2CCPCCR_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRAQIML2CCPRET_2.json b/datasets/SNDRAQIML2CCPRET_2.json
index b4b21d51e..6139587c8 100644
--- a/datasets/SNDRAQIML2CCPRET_2.json
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diff --git a/datasets/SNDRAQIML2CPS_2.1.json b/datasets/SNDRAQIML2CPS_2.1.json
index 2f6c59f6d..b16392011 100644
--- a/datasets/SNDRAQIML2CPS_2.1.json
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diff --git a/datasets/SNDRAQIML3CDCCP_2.json b/datasets/SNDRAQIML3CDCCP_2.json
index 297f7bc0c..2915dbe06 100644
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@@ -42,7 +42,7 @@
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index 4cff9e2d1..8ea9c8a3a 100644
--- a/datasets/SNDRAQIML3CMCCP_2.json
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index 45c4654cf..f47c01992 100644
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index 9cabe843b..5092d64d7 100644
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index 684a82ce5..344e70b88 100644
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index 32712bf4d..459677fd6 100644
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diff --git a/datasets/SNDRJ1IML2CCPRET_2.json b/datasets/SNDRJ1IML2CCPRET_2.json
index 9267364cc..0595adc8e 100644
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index b819ab3a6..5da8ecbc3 100644
--- a/datasets/SNDRJ1IML2CPS_2.1.json
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index 9d2e3140c..4f3ff4b01 100644
--- a/datasets/SNDRJ1IML3CDCCP_2.json
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index 6c027c425..54395514f 100644
--- a/datasets/SNDRJ1IML3CMCCP_2.json
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index 74fc17fb9..f28c68eee 100644
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index d77d50f82..7c3bdbaa2 100644
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index 0e03aaba2..d3f7d60c2 100644
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index 035d34146..f7d72cf56 100644
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index e0c295001..019d78b68 100644
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index 153ad29c8..859584153 100644
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index 672da0920..a3fad32ba 100644
--- a/datasets/SNDRSNATMSMAP_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNCrISL1BIMGC_2.json b/datasets/SNDRSNCrISL1BIMGC_2.json
index f85075616..6d8d84ac1 100644
--- a/datasets/SNDRSNCrISL1BIMGC_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNCrISL1BIMG_2.json b/datasets/SNDRSNCrISL1BIMG_2.json
index 841ba5709..fff8c15dc 100644
--- a/datasets/SNDRSNCrISL1BIMG_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIL1BCALSUBRNDN_2.json b/datasets/SNDRSNIL1BCALSUBRNDN_2.json
index 2427b3b89..85b3c5368 100644
--- a/datasets/SNDRSNIL1BCALSUBRNDN_2.json
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index 60b850584..0c0e498d4 100644
--- a/datasets/SNDRSNIL1BCALSUBSUMN_2.json
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diff --git a/datasets/SNDRSNIML2CCPCCRN_2.json b/datasets/SNDRSNIML2CCPCCRN_2.json
index b5cd14a78..6c8ab044c 100644
--- a/datasets/SNDRSNIML2CCPCCRN_2.json
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@@ -42,7 +42,7 @@
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index a0f72aa94..7efab0879 100644
--- a/datasets/SNDRSNIML2CCPCCR_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML2CCPRETN_2.json b/datasets/SNDRSNIML2CCPRETN_2.json
index cffebb848..c219ce270 100644
--- a/datasets/SNDRSNIML2CCPRETN_2.json
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@@ -42,7 +42,7 @@
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index 02a808ec6..5e0b9afdb 100644
--- a/datasets/SNDRSNIML2CCPRET_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML2CHTCCRN_1.json b/datasets/SNDRSNIML2CHTCCRN_1.json
index 61d508266..89fd3be48 100644
--- a/datasets/SNDRSNIML2CHTCCRN_1.json
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index e35b4e454..74498f522 100644
--- a/datasets/SNDRSNIML2CHTRETN_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML2CPSN_2.1.json b/datasets/SNDRSNIML2CPSN_2.1.json
index 88a3262ed..d64ac1cef 100644
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diff --git a/datasets/SNDRSNIML2CPS_2.1.json b/datasets/SNDRSNIML2CPS_2.1.json
index 4732b4843..f5772c646 100644
--- a/datasets/SNDRSNIML2CPS_2.1.json
+++ b/datasets/SNDRSNIML2CPS_2.1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML2SFSPRET_2.json b/datasets/SNDRSNIML2SFSPRET_2.json
index 06d60f025..4a778c581 100644
--- a/datasets/SNDRSNIML2SFSPRET_2.json
+++ b/datasets/SNDRSNIML2SFSPRET_2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML2SFSPSUP_2.json b/datasets/SNDRSNIML2SFSPSUP_2.json
index 8d1ec4b4c..959c3a568 100644
--- a/datasets/SNDRSNIML2SFSPSUP_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3CDCCPN_2.json b/datasets/SNDRSNIML3CDCCPN_2.json
index f6972fc62..b6eb2f387 100644
--- a/datasets/SNDRSNIML3CDCCPN_2.json
+++ b/datasets/SNDRSNIML3CDCCPN_2.json
@@ -42,7 +42,7 @@
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index 1b1531e9e..a0c4a15fa 100644
--- a/datasets/SNDRSNIML3CDCCP_2.json
+++ b/datasets/SNDRSNIML3CDCCP_2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3CDCHTN_1.json b/datasets/SNDRSNIML3CDCHTN_1.json
index cba43ed89..79ef374d8 100644
--- a/datasets/SNDRSNIML3CDCHTN_1.json
+++ b/datasets/SNDRSNIML3CDCHTN_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3CMCCPN_2.json b/datasets/SNDRSNIML3CMCCPN_2.json
index e75aa2c7d..afb3d25de 100644
--- a/datasets/SNDRSNIML3CMCCPN_2.json
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@@ -42,7 +42,7 @@
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index d50c5c2e1..6d22ddabc 100644
--- a/datasets/SNDRSNIML3CMCCP_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3CMCHTN_1.json b/datasets/SNDRSNIML3CMCHTN_1.json
index 96abee2c4..5867740b3 100644
--- a/datasets/SNDRSNIML3CMCHTN_1.json
+++ b/datasets/SNDRSNIML3CMCHTN_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3SDCCPN_2.json b/datasets/SNDRSNIML3SDCCPN_2.json
index fa870f7c6..5b6840833 100644
--- a/datasets/SNDRSNIML3SDCCPN_2.json
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@@ -42,7 +42,7 @@
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index 746abe11f..6fe6a2aa5 100644
--- a/datasets/SNDRSNIML3SDCCP_2.json
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@@ -42,7 +42,7 @@
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index 0a5e2f4d0..c0ec87fb2 100644
--- a/datasets/SNDRSNIML3SDCHTN_1.json
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@@ -42,7 +42,7 @@
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index 0d6a7a4d4..91bcaf2e8 100644
--- a/datasets/SNDRSNIML3SDSFSP_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3SMCCPN_2.json b/datasets/SNDRSNIML3SMCCPN_2.json
index c55f551ea..359bb8389 100644
--- a/datasets/SNDRSNIML3SMCCPN_2.json
+++ b/datasets/SNDRSNIML3SMCCPN_2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3SMCCP_2.json b/datasets/SNDRSNIML3SMCCP_2.json
index b97118ad0..65a4dc61f 100644
--- a/datasets/SNDRSNIML3SMCCP_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3SMCHTN_1.json b/datasets/SNDRSNIML3SMCHTN_1.json
index a75241e54..b9e5a53cd 100644
--- a/datasets/SNDRSNIML3SMCHTN_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNIML3SMSFSP_2.json b/datasets/SNDRSNIML3SMSFSP_2.json
index c2b3f83d2..40da3bfc0 100644
--- a/datasets/SNDRSNIML3SMSFSP_2.json
+++ b/datasets/SNDRSNIML3SMSFSP_2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNML2RMSSUP_3.json b/datasets/SNDRSNML2RMSSUP_3.json
index f95304b55..4766cf4de 100644
--- a/datasets/SNDRSNML2RMSSUP_3.json
+++ b/datasets/SNDRSNML2RMSSUP_3.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNML2RMS_1.json b/datasets/SNDRSNML2RMS_1.json
index 2fe98735a..993e7965f 100644
--- a/datasets/SNDRSNML2RMS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNDRSNML2RMS_3.json b/datasets/SNDRSNML2RMS_3.json
index ae3b6e38b..2a4b1a905 100644
--- a/datasets/SNDRSNML2RMS_3.json
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@@ -42,7 +42,7 @@
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index ff8e8e748..ab6798ab6 100644
--- a/datasets/SNDRSNML3DRMS_3.json
+++ b/datasets/SNDRSNML3DRMS_3.json
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index 531800f44..2210235de 100644
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new file mode 100644
index 000000000..19f36fbc8
--- /dev/null
+++ b/datasets/SNEX21_PS_DSM_1.json
@@ -0,0 +1,130 @@
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+    "links": [
+        {
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+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3241729770-NSIDC_ECS.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
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+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3241729770-NSIDC_ECS.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
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+            "roles": [
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+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
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+    "license": "proprietary",
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+                "data"
+            ]
+        },
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+            "description": "NASA's newest search and order tool for subsetting, reprojecting, and reformatting data.",
+            "roles": [
+                "data"
+            ]
+        },
+        "https://nsidc": {
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+            "description": "Search and filter data files using a map-based interface",
+            "roles": [
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+            ]
+        },
+        "provider_metadata": {
+            "href": "https://doi.org/10.5067/2JA2F0NF99TF",
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+            "description": "Provides access to data, documentation, tools, citation information, support, and other resources.",
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+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/SNEX21_PS_MET_1.json b/datasets/SNEX21_PS_MET_1.json
new file mode 100644
index 000000000..4b92b0703
--- /dev/null
+++ b/datasets/SNEX21_PS_MET_1.json
@@ -0,0 +1,130 @@
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+    "links": [
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+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
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+        },
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+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3241728800-NSIDC_ECS.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3241728800-NSIDC_ECS.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
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+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
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+            "title": "CMR UMM_JSON metadata for collection"
+        },
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+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS",
+            "type": "application/json",
+            "title": "NSIDC_ECS STAC Catalog"
+        },
+        {
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+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "NSIDC_ECS",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "SnowEx21 Prairie Station Hourly Meteorological Data V001",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -109.956783,
+                    47.060545,
+                    -109.956783,
+                    47.060545
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2020-11-12T00:00:00Z",
+                    "2021-04-02T23:59:59.999000Z"
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "org/SNOWEX/SNEX21_PS_MET": {
+            "href": "https://n5eil01u.ecs.nsidc.org/SNOWEX/SNEX21_PS_MET.001/",
+            "title": "Direct Download [0]",
+            "description": "Direct download via HTTPS protocol.",
+            "roles": [
+                "data"
+            ]
+        },
+        "nasa": {
+            "href": "https://search.earthdata.nasa.gov/search?q=SNEX21_PS_MET+V001",
+            "title": "Direct Download [1]",
+            "description": "NASA's newest search and order tool for subsetting, reprojecting, and reformatting data.",
+            "roles": [
+                "data"
+            ]
+        },
+        "https://nsidc": {
+            "href": "https://nsidc.org/data/data-access-tool/SNEX21_PS_MET/versions/1",
+            "title": "Direct Download [2]",
+            "description": "Search and filter data files using a map-based interface",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://doi.org/10.5067/PVE8RWNUZTKS",
+            "title": "Provider Metadata",
+            "description": "Provides access to data, documentation, tools, citation information, support, and other resources.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/SNEX23_BCEF_TLS_1.json b/datasets/SNEX23_BCEF_TLS_1.json
index fa8c9170a..902554fef 100644
--- a/datasets/SNEX23_BCEF_TLS_1.json
+++ b/datasets/SNEX23_BCEF_TLS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_BCEF_TLS_Raw_1.json b/datasets/SNEX23_BCEF_TLS_Raw_1.json
index 5b0a9c0a1..caab7849c 100644
--- a/datasets/SNEX23_BCEF_TLS_Raw_1.json
+++ b/datasets/SNEX23_BCEF_TLS_Raw_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_CRREL_GPR_1.json b/datasets/SNEX23_CRREL_GPR_1.json
index cfe54c5ed..c24547f4c 100644
--- a/datasets/SNEX23_CRREL_GPR_1.json
+++ b/datasets/SNEX23_CRREL_GPR_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_CRREL_GPR_Raw_1.json b/datasets/SNEX23_CRREL_GPR_Raw_1.json
index e5ca660ba..b7f1eeba0 100644
--- a/datasets/SNEX23_CRREL_GPR_Raw_1.json
+++ b/datasets/SNEX23_CRREL_GPR_Raw_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_CSU_GPR_Raw_1.json b/datasets/SNEX23_CSU_GPR_Raw_1.json
index c0f09446c..6b5ce95b6 100644
--- a/datasets/SNEX23_CSU_GPR_Raw_1.json
+++ b/datasets/SNEX23_CSU_GPR_Raw_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_Lidar_1.json b/datasets/SNEX23_Lidar_1.json
index fe2dea546..91079d379 100644
--- a/datasets/SNEX23_Lidar_1.json
+++ b/datasets/SNEX23_Lidar_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_MAR22_SD_1.json b/datasets/SNEX23_MAR22_SD_1.json
index dcb2c6ecc..e06bb1e8c 100644
--- a/datasets/SNEX23_MAR22_SD_1.json
+++ b/datasets/SNEX23_MAR22_SD_1.json
@@ -42,7 +42,7 @@
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index fd354b0ff..384be1f5f 100644
--- a/datasets/SNEX23_MAR23_SD_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_SSA_1.json b/datasets/SNEX23_SSA_1.json
index 313744567..7145c5bff 100644
--- a/datasets/SNEX23_SSA_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_SSA_SO_1.json b/datasets/SNEX23_SSA_SO_1.json
index 06f95bd18..84212489b 100644
--- a/datasets/SNEX23_SSA_SO_1.json
+++ b/datasets/SNEX23_SSA_SO_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_SWE_1.json b/datasets/SNEX23_SWE_1.json
index 17966ef79..90a49db36 100644
--- a/datasets/SNEX23_SWE_1.json
+++ b/datasets/SNEX23_SWE_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNEX23_UW_GPR_1.json b/datasets/SNEX23_UW_GPR_1.json
index de514a9b7..1b5aef341 100644
--- a/datasets/SNEX23_UW_GPR_1.json
+++ b/datasets/SNEX23_UW_GPR_1.json
@@ -42,7 +42,7 @@
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index dda8302e7..c3608a71d 100644
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index e44ff4f5a..656417cbf 100644
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index 0fad7bc22..a2cbdc03f 100644
--- a/datasets/SNF_CJ_SITES_187_1.json
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index 408506a41..ea49c1670 100644
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index 4af98e728..6bbf266f9 100644
--- a/datasets/SNF_LEAFCARY_183_1.json
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index 1beebe650..a1f79abfa 100644
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index 1b1497a8f..f3ff01cb7 100644
--- a/datasets/SNF_LEAF_TMS_184_1.json
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diff --git a/datasets/SNF_MET_1972_158_1.json b/datasets/SNF_MET_1972_158_1.json
index daf562425..a0267612d 100644
--- a/datasets/SNF_MET_1972_158_1.json
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index ec68234c3..845cb62f2 100644
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diff --git a/datasets/SNF_MET_1973_160_1.json b/datasets/SNF_MET_1973_160_1.json
index 7c5000fad..b728d1e7e 100644
--- a/datasets/SNF_MET_1973_160_1.json
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index 360264930..769f969dc 100644
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index 90db110c3..a2e9eadb0 100644
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index 41fa1aa65..23206f11c 100644
--- a/datasets/SNF_MET_1986_173_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNF_MET_1987_174_1.json b/datasets/SNF_MET_1987_174_1.json
index 5af39e77b..671604fa2 100644
--- a/datasets/SNF_MET_1987_174_1.json
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@@ -42,7 +42,7 @@
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index 08b4c95d3..c9647b075 100644
--- a/datasets/SNF_MET_1988_175_1.json
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@@ -42,7 +42,7 @@
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index 402658067..b8f487d6f 100644
--- a/datasets/SNF_MET_1989_176_1.json
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@@ -42,7 +42,7 @@
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index 4cb991c14..1cd0e1f7c 100644
--- a/datasets/SNF_MET_1990_177_1.json
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@@ -42,7 +42,7 @@
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index 0207dbe5a..7b71afeb7 100644
--- a/datasets/SNF_MET_SUMM_178_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNF_NS001_185_1.json b/datasets/SNF_NS001_185_1.json
index 030f6fb67..124deba28 100644
--- a/datasets/SNF_NS001_185_1.json
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@@ -42,7 +42,7 @@
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index 62c5c2779..f882e65f9 100644
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index 296603bfe..4c3ccde7c 100644
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index 537cb7561..573c60d8b 100644
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index 344f8ec24..73d883000 100644
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diff --git a/datasets/SNPPATMSL1B_2.json b/datasets/SNPPATMSL1B_2.json
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diff --git a/datasets/SNPPATMSL1B_3.json b/datasets/SNPPATMSL1B_3.json
index 11ef939f1..6f1ddcc66 100644
--- a/datasets/SNPPATMSL1B_3.json
+++ b/datasets/SNPPATMSL1B_3.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SNPPCrISL1BNSR_2.json b/datasets/SNPPCrISL1BNSR_2.json
index 003aacca9..f58a13068 100644
--- a/datasets/SNPPCrISL1BNSR_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNPPCrISL1BNSR_3.json b/datasets/SNPPCrISL1BNSR_3.json
index 1a40af07a..85c2cfc19 100644
--- a/datasets/SNPPCrISL1BNSR_3.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SNPPCrISL1B_2.json b/datasets/SNPPCrISL1B_2.json
index ea4a444cf..f930e2890 100644
--- a/datasets/SNPPCrISL1B_2.json
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@@ -42,7 +42,7 @@
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index a9e29b0c7..c49cc49e7 100644
--- a/datasets/SNPPCrISL1B_3.json
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@@ -42,7 +42,7 @@
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index 5fac2a3b3..c4e5528b2 100644
--- a/datasets/SNPP_CrIS_VIIRS750m_IND_1.json
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index 18593c4a7..fff743bb9 100644
--- a/datasets/SOC_3M_Maps_NE_TidalWetlands_1905_1.json
+++ b/datasets/SOC_3M_Maps_NE_TidalWetlands_1905_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SOC_Stocks_Great_Plains_1603_1.json b/datasets/SOC_Stocks_Great_Plains_1603_1.json
index 133a255ee..1aa8d0753 100644
--- a/datasets/SOC_Stocks_Great_Plains_1603_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SOIL_CO2_Flux_Costa_Rica_1373_1.json b/datasets/SOIL_CO2_Flux_Costa_Rica_1373_1.json
index 7138df734..22d3d2642 100644
--- a/datasets/SOIL_CO2_Flux_Costa_Rica_1373_1.json
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@@ -42,7 +42,7 @@
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index 9135ab627..bddcdd0fb 100644
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index 84571bc19..232faee9c 100644
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diff --git a/datasets/SOR3SIMD_TAV_002.json b/datasets/SOR3SIMD_TAV_002.json
index 37d109117..4206b89a3 100644
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diff --git a/datasets/SOR3SOLD_HIGH_018.json b/datasets/SOR3SOLD_HIGH_018.json
index 94eeff47d..32dab57b5 100644
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diff --git a/datasets/SOR3SOLD_MGII_018.json b/datasets/SOR3SOLD_MGII_018.json
index ceedb2ad3..6ae416f60 100644
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index d0982a125..da0591a9d 100644
--- a/datasets/SOR3SOLFUVD_018.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SOR3SOLMUVD_018.json b/datasets/SOR3SOLMUVD_018.json
index 90248065c..a7b2fe37e 100644
--- a/datasets/SOR3SOLMUVD_018.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SOR3SOLS_LA_018.json b/datasets/SOR3SOLS_LA_018.json
index f06922226..3939d635d 100644
--- a/datasets/SOR3SOLS_LA_018.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SOR3SOLS_MGII_018.json b/datasets/SOR3SOLS_MGII_018.json
index c4a169b04..3d946d30f 100644
--- a/datasets/SOR3SOLS_MGII_018.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SOR3TSI6_019.json b/datasets/SOR3TSI6_019.json
index e88fc3756..3f3f0a9f8 100644
--- a/datasets/SOR3TSI6_019.json
+++ b/datasets/SOR3TSI6_019.json
@@ -42,7 +42,7 @@
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index a1d6992b5..9d054e140 100644
--- a/datasets/SOR3TSID_019.json
+++ b/datasets/SOR3TSID_019.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SOR3XPS6_012.json b/datasets/SOR3XPS6_012.json
index 10af76f3a..18f73a0e0 100644
--- a/datasets/SOR3XPS6_012.json
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diff --git a/datasets/SOR3XPSD_012.json b/datasets/SOR3XPSD_012.json
index 86325d547..428027139 100644
--- a/datasets/SOR3XPSD_012.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/SOR4XPS5_012.json b/datasets/SOR4XPS5_012.json
index f348ed80f..9ce060a4e 100644
--- a/datasets/SOR4XPS5_012.json
+++ b/datasets/SOR4XPS5_012.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/SOR4XPSD_HIGH_012.json b/datasets/SOR4XPSD_HIGH_012.json
index 97ac4d09d..5e12161c6 100644
--- a/datasets/SOR4XPSD_HIGH_012.json
+++ b/datasets/SOR4XPSD_HIGH_012.json
@@ -42,7 +42,7 @@
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index 0fd77b3ae..13995f623 100644
--- a/datasets/SRTMGL3N_003.json
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@@ -42,7 +42,7 @@
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index 6cd6b9629..a6921d326 100644
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index 06da031e3..4a3b9ab1e 100644
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index e7f6476e8..0fb1df293 100644
--- a/datasets/SRTMGL3_NC_003.json
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index ef0a0dc75..100faee00 100644
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index efa696526..a9b4eadf9 100644
--- a/datasets/SRTMIMGM_003.json
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index 99443dfe7..b995147cd 100644
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index db250731a..bacd88059 100644
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index fc17b2cb0..c3a3e1bf7 100644
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index a21f8227f..32775f7a8 100644
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diff --git a/datasets/SSFR_irradiance_841_1.json b/datasets/SSFR_irradiance_841_1.json
index 914c8b87a..c5392a0d0 100644
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@@ -42,7 +42,7 @@
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index e02eaca1c..8568dfdf4 100644
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diff --git a/datasets/SWDB_L3MC05_004.json b/datasets/SWDB_L3MC05_004.json
index 8402e07f2..e6af84b39 100644
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index 4ead27bd5..834e8dc0b 100644
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index 6a766a05f..ebab0a676 100644
--- a/datasets/Sahel_Water_Bodies_1269_1.json
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index 488d8e15c..5b87f387c 100644
--- a/datasets/SatelliteDerived_Forest_Mexico_2320_1.json
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index f22b9fafa..48284a690 100644
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@@ -42,7 +42,7 @@
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index 6f920820c..1b028ab64 100644
--- a/datasets/Seward_Peninsula_Veg_Maps_1363_1.json
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index 5d971d4e4..300010511 100644
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index 25590c94b..9562002fd 100644
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index 0e17e2a4a..21a1e4655 100644
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index 2c7d896ae..52fab3269 100644
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index 855415d8e..1446c4998 100644
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index 8542f7f13..452ce80e3 100644
--- a/datasets/SoilSCAPE_1339_1.json
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@@ -42,7 +42,7 @@
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index a89d8c9bc..a69ac561e 100644
--- a/datasets/SoilSCAPE_V2_2049_2.json
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@@ -42,7 +42,7 @@
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index b2a0b86bf..cb1969d84 100644
--- a/datasets/Soil_Carbon_Flux_Maps_1683_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/Soil_Moisture_Alaska_Alberta_2123_1.json b/datasets/Soil_Moisture_Alaska_Alberta_2123_1.json
index 3568c036b..4faa96525 100644
--- a/datasets/Soil_Moisture_Alaska_Alberta_2123_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/Sonoma_County_Forest_AGB_1764_1.json b/datasets/Sonoma_County_Forest_AGB_1764_1.json
index 472f2cb47..5f0d776aa 100644
--- a/datasets/Sonoma_County_Forest_AGB_1764_1.json
+++ b/datasets/Sonoma_County_Forest_AGB_1764_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TEMPO_CLDO4_L3_V03.json b/datasets/TEMPO_CLDO4_L3_V03.json
index 2737052ed..89b3adf59 100644
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index 251f662bc..e029dd07c 100644
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index 8ac5f7398..9206f0d96 100644
--- a/datasets/TEMPO_IRRR_L1_V03.json
+++ b/datasets/TEMPO_IRRR_L1_V03.json
@@ -42,7 +42,7 @@
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index 8433520cd..52af4d535 100644
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index bfae36199..a342fae76 100644
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index dc1eda3a9..e94b63602 100644
--- a/datasets/TEMPO_NO2_L2_V03.json
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index 7cfcdad28..caec87a9c 100644
--- a/datasets/TEMPO_O3TOT_L2_V03.json
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index 434d1936d..e0baf527d 100644
--- a/datasets/TEMPO_O3TOT_L3_V03.json
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index 805767256..5fc3cdac7 100644
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index defb75fbf..b8e0015e3 100644
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index 2665dfb67..a619813fc 100644
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index cf53688aa..515c70e48 100644
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index ca67b785d..68a57120a 100644
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index 1c1b1f4f1..579cefb6c 100644
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index 3b60f1fec..7f73a9f38 100644
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index 371298da0..294b385d1 100644
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index a91694a33..794b4fe50 100644
--- a/datasets/TG07_Litter_Decomposition_925_1.json
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index 45717a5f5..8b02af17d 100644
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index 7f9966eb8..b94f10b9e 100644
--- a/datasets/TG07_Root_Mortality_Experiment_924_1.json
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index 208d2f9bc..f3eee83b2 100644
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index ed24725ea..def9a2505 100644
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index 9c6bbb03b..a36ae231c 100644
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index 5d075d550..1dd4aaf75 100644
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--- a/datasets/TG08_Soil_Gas_Wetting_1101_1.json
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--- a/datasets/TG09_N2O_Soils_1013_1.json
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index 62bd02d07..1487b2aca 100644
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diff --git a/datasets/THIRN4L1CH67_001.json b/datasets/THIRN4L1CH67_001.json
index 5fd3146c8..8063b1888 100644
--- a/datasets/THIRN4L1CH67_001.json
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diff --git a/datasets/THIRN5L1CH115_001.json b/datasets/THIRN5L1CH115_001.json
index 01399fb50..03b8dc2a4 100644
--- a/datasets/THIRN5L1CH115_001.json
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diff --git a/datasets/THIRN5L1CH67_001.json b/datasets/THIRN5L1CH67_001.json
index 8b0d4b510..2774a9c24 100644
--- a/datasets/THIRN5L1CH67_001.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/THIRN6IM_001.json b/datasets/THIRN6IM_001.json
index 22f199565..b2f7fbcab 100644
--- a/datasets/THIRN6IM_001.json
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@@ -42,7 +42,7 @@
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index 28c907dfb..f76cc06c7 100644
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index 6ba451c55..575b638a8 100644
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index 1a977d842..8dc795d21 100644
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index 420a2925f..ef257609d 100644
--- a/datasets/THIRN7L1BCLT_001.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/THIRN7L1CLDT_001.json b/datasets/THIRN7L1CLDT_001.json
index 71a2715eb..205a0e200 100644
--- a/datasets/THIRN7L1CLDT_001.json
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diff --git a/datasets/TIROS2L1FMRT_001.json b/datasets/TIROS2L1FMRT_001.json
index c7ea6c36f..a27089ef3 100644
--- a/datasets/TIROS2L1FMRT_001.json
+++ b/datasets/TIROS2L1FMRT_001.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TIROS3L1FMRT_001.json b/datasets/TIROS3L1FMRT_001.json
index 7055f7cec..b9d78aa02 100644
--- a/datasets/TIROS3L1FMRT_001.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TIROS3L1ORT_001.json b/datasets/TIROS3L1ORT_001.json
index 1d8504104..8276f07aa 100644
--- a/datasets/TIROS3L1ORT_001.json
+++ b/datasets/TIROS3L1ORT_001.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TIROS4L1FMRT_001.json b/datasets/TIROS4L1FMRT_001.json
index d8f4e38e8..4d17d6365 100644
--- a/datasets/TIROS4L1FMRT_001.json
+++ b/datasets/TIROS4L1FMRT_001.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TIROS4L1ORR_001.json b/datasets/TIROS4L1ORR_001.json
index 4e5438953..f93c2efb6 100644
--- a/datasets/TIROS4L1ORR_001.json
+++ b/datasets/TIROS4L1ORR_001.json
@@ -42,7 +42,7 @@
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index 9ac8e3610..ce192473b 100644
--- a/datasets/TIROS4L1ORT_001.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TIROS7L1FMRT_001.json b/datasets/TIROS7L1FMRT_001.json
index 27696d48d..64daa8dca 100644
--- a/datasets/TIROS7L1FMRT_001.json
+++ b/datasets/TIROS7L1FMRT_001.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSEPAER_2.json b/datasets/TOMSEPAER_2.json
index 1f23aba79..265301cb0 100644
--- a/datasets/TOMSEPAER_2.json
+++ b/datasets/TOMSEPAER_2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSEPL2_008.json b/datasets/TOMSEPL2_008.json
index 8f5314d1c..946015943 100644
--- a/datasets/TOMSEPL2_008.json
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index a01baf867..e74d52626 100644
--- a/datasets/TOMSEPL3_008.json
+++ b/datasets/TOMSEPL3_008.json
@@ -42,7 +42,7 @@
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index f3eb865eb..eeb5b2417 100644
--- a/datasets/TOMSEPL3daer_008.json
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diff --git a/datasets/TOMSEPL3dery_008.json b/datasets/TOMSEPL3dery_008.json
index 513225461..8be4d938b 100644
--- a/datasets/TOMSEPL3dery_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSEPL3dref_008.json b/datasets/TOMSEPL3dref_008.json
index aef026ee6..b21fdaacd 100644
--- a/datasets/TOMSEPL3dref_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSEPL3dtoz_008.json b/datasets/TOMSEPL3dtoz_008.json
index c02503194..597212fa7 100644
--- a/datasets/TOMSEPL3dtoz_008.json
+++ b/datasets/TOMSEPL3dtoz_008.json
@@ -42,7 +42,7 @@
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index 2ee960145..021f66c15 100644
--- a/datasets/TOMSEPL3maer_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSEPL3mery_008.json b/datasets/TOMSEPL3mery_008.json
index 17e0c1582..1e4b7dcf4 100644
--- a/datasets/TOMSEPL3mery_008.json
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diff --git a/datasets/TOMSEPL3mref_008.json b/datasets/TOMSEPL3mref_008.json
index d0883b1b2..1cd608323 100644
--- a/datasets/TOMSEPL3mref_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSEPL3mtoz_008.json b/datasets/TOMSEPL3mtoz_008.json
index c9fbc21c8..fed2427df 100644
--- a/datasets/TOMSEPL3mtoz_008.json
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@@ -42,7 +42,7 @@
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index 33157432b..0f22c1352 100644
--- a/datasets/TOMSEPL3zaer_008.json
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index bbdedc618..a9002ba2d 100644
--- a/datasets/TOMSEPL3zref_008.json
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index 78057d786..2e2502539 100644
--- a/datasets/TOMSEPL3ztoz_008.json
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index dbbf49d0f..c30d6c4a0 100644
--- a/datasets/TOMSEPOVP_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSM3L3_008.json b/datasets/TOMSM3L3_008.json
index dc492300d..68cbb2389 100644
--- a/datasets/TOMSM3L3_008.json
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index 9d374ab38..c156ceef5 100644
--- a/datasets/TOMSM3L3dref_008.json
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index 0b17308bc..614ef0434 100644
--- a/datasets/TOMSM3L3dtoz_008.json
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diff --git a/datasets/TOMSM3OVP_008.json b/datasets/TOMSM3OVP_008.json
index e26917016..69bb26dd6 100644
--- a/datasets/TOMSM3OVP_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSN7AER_2.json b/datasets/TOMSN7AER_2.json
index 879d7e62f..c235768c5 100644
--- a/datasets/TOMSN7AER_2.json
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index 1db6784c2..1202a5704 100644
--- a/datasets/TOMSN7L2_008.json
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@@ -42,7 +42,7 @@
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index 113e8bfc5..4208745a0 100644
--- a/datasets/TOMSN7L3_008.json
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diff --git a/datasets/TOMSN7L3daer_008.json b/datasets/TOMSN7L3daer_008.json
index 046996da8..1d3543444 100644
--- a/datasets/TOMSN7L3daer_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSN7L3dery_008.json b/datasets/TOMSN7L3dery_008.json
index b5bba3ec5..71a1a0b5c 100644
--- a/datasets/TOMSN7L3dery_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSN7L3dref_008.json b/datasets/TOMSN7L3dref_008.json
index eb06d715c..926d00f37 100644
--- a/datasets/TOMSN7L3dref_008.json
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@@ -42,7 +42,7 @@
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index 3ff49866b..3929637cb 100644
--- a/datasets/TOMSN7L3dtoz_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSN7L3maer_008.json b/datasets/TOMSN7L3maer_008.json
index 05ab3d903..97715fa47 100644
--- a/datasets/TOMSN7L3maer_008.json
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diff --git a/datasets/TOMSN7L3mery_008.json b/datasets/TOMSN7L3mery_008.json
index 96fddd755..0424d101f 100644
--- a/datasets/TOMSN7L3mery_008.json
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diff --git a/datasets/TOMSN7L3mref_008.json b/datasets/TOMSN7L3mref_008.json
index 2ab0e240b..bc7562b96 100644
--- a/datasets/TOMSN7L3mref_008.json
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@@ -42,7 +42,7 @@
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index b90d571b8..72bd2dbee 100644
--- a/datasets/TOMSN7L3mtoz_008.json
+++ b/datasets/TOMSN7L3mtoz_008.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSN7L3zaer_008.json b/datasets/TOMSN7L3zaer_008.json
index 1957f2110..d12b0aa72 100644
--- a/datasets/TOMSN7L3zaer_008.json
+++ b/datasets/TOMSN7L3zaer_008.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSN7L3zref_008.json b/datasets/TOMSN7L3zref_008.json
index accf2fa74..6287795e6 100644
--- a/datasets/TOMSN7L3zref_008.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMSN7L3ztoz_008.json b/datasets/TOMSN7L3ztoz_008.json
index 6c809430a..5d97d6c50 100644
--- a/datasets/TOMSN7L3ztoz_008.json
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diff --git a/datasets/TOMSN7OVP_008.json b/datasets/TOMSN7OVP_008.json
index 65fe99679..61752ceaa 100644
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diff --git a/datasets/TOMSN7SO2_3.json b/datasets/TOMSN7SO2_3.json
index 827d54202..6fd86d105 100644
--- a/datasets/TOMSN7SO2_3.json
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diff --git a/datasets/TOMS_aerosol_823_1.json b/datasets/TOMS_aerosol_823_1.json
index 5574a128e..676f6f9bc 100644
--- a/datasets/TOMS_aerosol_823_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOMS_ozone_824_1.json b/datasets/TOMS_ozone_824_1.json
index 5f56c3806..3f47841c2 100644
--- a/datasets/TOMS_ozone_824_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOVSA5ND_01.json b/datasets/TOVSA5ND_01.json
index 975e69646..f1e51a272 100644
--- a/datasets/TOVSA5ND_01.json
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diff --git a/datasets/TOVSA5NF_01.json b/datasets/TOVSA5NF_01.json
index 68b32c0d9..59a0d8ec4 100644
--- a/datasets/TOVSA5NF_01.json
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diff --git a/datasets/TOVSA5NG_01.json b/datasets/TOVSA5NG_01.json
index a9490558a..a1e734f7a 100644
--- a/datasets/TOVSA5NG_01.json
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@@ -42,7 +42,7 @@
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index 4995cc3b9..bc96357f6 100644
--- a/datasets/TOVSA5NH_01.json
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diff --git a/datasets/TOVSA5TN_01.json b/datasets/TOVSA5TN_01.json
index c12c81bbe..c4dcca3b7 100644
--- a/datasets/TOVSA5TN_01.json
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diff --git a/datasets/TOVSADND_01.json b/datasets/TOVSADND_01.json
index 30a10c628..365eda669 100644
--- a/datasets/TOVSADND_01.json
+++ b/datasets/TOVSADND_01.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOVSADNF_01.json b/datasets/TOVSADNF_01.json
index a3d263ac6..dc2994e77 100644
--- a/datasets/TOVSADNF_01.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TOVSADNG_01.json b/datasets/TOVSADNG_01.json
index be0458765..7b789619c 100644
--- a/datasets/TOVSADNG_01.json
+++ b/datasets/TOVSADNG_01.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOVSADNH_01.json b/datasets/TOVSADNH_01.json
index bfd6d30c2..279dda4f7 100644
--- a/datasets/TOVSADNH_01.json
+++ b/datasets/TOVSADNH_01.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOVSADTN_01.json b/datasets/TOVSADTN_01.json
index c0e3cbe8c..395bf9743 100644
--- a/datasets/TOVSADTN_01.json
+++ b/datasets/TOVSADTN_01.json
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index adb952875..a61909da0 100644
--- a/datasets/TOVSAMNA_02.json
+++ b/datasets/TOVSAMNA_02.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TOVSAMNC_02.json b/datasets/TOVSAMNC_02.json
index 2e20129ff..5bfcaca8b 100644
--- a/datasets/TOVSAMNC_02.json
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diff --git a/datasets/TOVSAMND_01.json b/datasets/TOVSAMND_01.json
index c9d2c85bd..a88ecc3e8 100644
--- a/datasets/TOVSAMND_01.json
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diff --git a/datasets/TOVSAMND_02.json b/datasets/TOVSAMND_02.json
index 3b64a356f..182b8c1ff 100644
--- a/datasets/TOVSAMND_02.json
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diff --git a/datasets/TOVSAMNE_02.json b/datasets/TOVSAMNE_02.json
index 0585e6ec3..1d5337ad8 100644
--- a/datasets/TOVSAMNE_02.json
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diff --git a/datasets/TOVSAMNF_01.json b/datasets/TOVSAMNF_01.json
index 34980fd63..c7e698981 100644
--- a/datasets/TOVSAMNF_01.json
+++ b/datasets/TOVSAMNF_01.json
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index 5d46195d5..4d1589970 100644
--- a/datasets/TOVSAMNF_02.json
+++ b/datasets/TOVSAMNF_02.json
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index 1b90b4df3..e2357cd2d 100644
--- a/datasets/TOVSAMNG_01.json
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diff --git a/datasets/TOVSAMNG_02.json b/datasets/TOVSAMNG_02.json
index 99069a2eb..e6fd23d58 100644
--- a/datasets/TOVSAMNG_02.json
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diff --git a/datasets/TOVSAMNH_01.json b/datasets/TOVSAMNH_01.json
index 0bba47e9c..dbc7a52df 100644
--- a/datasets/TOVSAMNH_01.json
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diff --git a/datasets/TOVSAMNH_02.json b/datasets/TOVSAMNH_02.json
index 59cb3dca9..59a05e30c 100644
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index 8549be21b..8a8255926 100644
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index 946853fac..67aacbc90 100644
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+++ b/datasets/TOVSAMTN_01.json
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index 2cc26c2be..af8ae253f 100644
--- a/datasets/TOVSAMTN_02.json
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diff --git a/datasets/TOVSB5ND_01.json b/datasets/TOVSB5ND_01.json
index fb9cefbdd..b4fdec696 100644
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index a5d81c91f..d0dd55ead 100644
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index 732bc17ac..c102d9ea6 100644
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index cc5b6b718..e7d15ddc0 100644
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index 09d2a639b..4188916dc 100644
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index 6aad285a7..962e1437f 100644
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index 2599d6508..4cf260b07 100644
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index 98173c404..9ac802b8a 100644
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index 00c197eb2..e2196813e 100644
--- a/datasets/TRACE-A_AircraftRemoteSensing_DC8_DIAL_Data_1.json
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index 2b50a490a..1598a7cb7 100644
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index 590eeec80..bb4870299 100644
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index 3058e8636..213874412 100644
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index 5d3242499..aea7b5424 100644
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index cfb4d05be..69098a6b8 100644
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index cb16d4d35..cea2c0479 100644
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index 0395252f3..6ce085aa7 100644
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index 589f5d680..8c55835c6 100644
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index 51f3a2246..1735d0efc 100644
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index 68cb579bc..daeb81531 100644
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index 8c0882086..266649885 100644
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index 82b426c1f..631d3a380 100644
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index 14659928d..afde94152 100644
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index 39e47a639..4990e6aba 100644
--- a/datasets/TRMM_2A21_7.json
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@@ -42,7 +42,7 @@
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index 7c191096c..c0f88973f 100644
--- a/datasets/TRMM_2A23_7.json
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diff --git a/datasets/TRMM_2A25_7.json b/datasets/TRMM_2A25_7.json
index 6f8aabd2d..6fa019a3a 100644
--- a/datasets/TRMM_2A25_7.json
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diff --git a/datasets/TRMM_2A52_7.json b/datasets/TRMM_2A52_7.json
index 5c19d0e5e..643b52e8c 100644
--- a/datasets/TRMM_2A52_7.json
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diff --git a/datasets/TRMM_2A53UW_7.json b/datasets/TRMM_2A53UW_7.json
index 93a3c935f..c33483722 100644
--- a/datasets/TRMM_2A53UW_7.json
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index 5736a8ffc..9bd5229e7 100644
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index 8e296c15f..afaabab6c 100644
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index 1b34fa91f..5e1379dec 100644
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diff --git a/datasets/TRMM_3A12_7.json b/datasets/TRMM_3A12_7.json
index 39ba38dee..ad888fb21 100644
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diff --git a/datasets/TRMM_3A25_7.json b/datasets/TRMM_3A25_7.json
index 3f01f5feb..b79497c38 100644
--- a/datasets/TRMM_3A25_7.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRMM_3A26_7.json b/datasets/TRMM_3A26_7.json
index 3e61c65a7..4b784b6a0 100644
--- a/datasets/TRMM_3A26_7.json
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index 1e30c0ee8..e9172b500 100644
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index 11be906c5..94d7479af 100644
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index 95b40e208..0bb6ac8a2 100644
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diff --git a/datasets/TRMM_3B31_7.json b/datasets/TRMM_3B31_7.json
index 2ddf4d7a0..16e77570f 100644
--- a/datasets/TRMM_3B31_7.json
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index 5007abfb3..b8660d893 100644
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index 51da274d2..fbf6f06ea 100644
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index ca005c79b..552666cb3 100644
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index 4019040a4..89b1b15b2 100644
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index e965f4d1f..1641ff18d 100644
--- a/datasets/TRMM_3B42_Daily_7.json
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index 1e2575a42..ffdc4c76e 100644
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index 509a2ed8c..dfcd2de61 100644
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index 0e1171ca3..0e0f8bf1e 100644
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diff --git a/datasets/TRMM_3H31_7.json b/datasets/TRMM_3H31_7.json
index 36c7dc688..8e09ae9c7 100644
--- a/datasets/TRMM_3H31_7.json
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@@ -42,7 +42,7 @@
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index 726f60606..562d36399 100644
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index d5fe0b59b..f0ffbfedb 100644
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diff --git a/datasets/TROPICS01ANTTL1A_1.0.json b/datasets/TROPICS01ANTTL1A_1.0.json
index fb487a6c9..e7393c60c 100644
--- a/datasets/TROPICS01ANTTL1A_1.0.json
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index b40365d9f..fe29499e5 100644
--- a/datasets/TROPICS01BRTTL1B_1.0.json
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index 79a235e5c..80a15c243 100644
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index 7cfad800c..afeb887d3 100644
--- a/datasets/TROPICS01PRPSL2B_1.0.json
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index 42ffda2de..70162d634 100644
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diff --git a/datasets/TROPICS03ANTTL1A_1.0.json b/datasets/TROPICS03ANTTL1A_1.0.json
index a9af3bf37..f2889b631 100644
--- a/datasets/TROPICS03ANTTL1A_1.0.json
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diff --git a/datasets/TROPICS03BRTTL1B_1.0.json b/datasets/TROPICS03BRTTL1B_1.0.json
index 09cb95632..51a17c2b0 100644
--- a/datasets/TROPICS03BRTTL1B_1.0.json
+++ b/datasets/TROPICS03BRTTL1B_1.0.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TROPICS03MIRSL2B_0.2.json b/datasets/TROPICS03MIRSL2B_0.2.json
index 02feb4eaa..a2f841fda 100644
--- a/datasets/TROPICS03MIRSL2B_0.2.json
+++ b/datasets/TROPICS03MIRSL2B_0.2.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TROPICS03PRPSL2B_1.0.json b/datasets/TROPICS03PRPSL2B_1.0.json
new file mode 100644
index 000000000..0e2b4d792
--- /dev/null
+++ b/datasets/TROPICS03PRPSL2B_1.0.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "TROPICS03PRPSL2B_1.0",
+    "stac_version": "1.0.0",
+    "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. \n\nEach SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.\n\nThis dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. \n\nThis provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles.\u00a0See README for this and other calibration observations and the Data Product Users Guide for orbit details.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGVzcyBjcmlzLXNucHAgbDIgd2F0ZXIgZm9yIGZvcndhcmQgc3RyZWFtLCBzdGFuZGFyZCBwcm9kdWN0IHYxICh0cnBzZGwyaDJvY3JzZnMpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJQU0RMMkgyT0NSU0ZTXCIsXCIxXCIsMjA0MTk2NDk1MiwxNV0iLCJ1bW0iOiJbXCJ0cm9wZXNzIGNyaXMtc25wcCBsMiB3YXRlciBmb3IgZm9yd2FyZCBzdHJlYW0sIHN0YW5kYXJkIHByb2R1Y3QgdjEgKHRycHNkbDJoMm9jcnNmcykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUlBTREwySDJPQ1JTRlNcIixcIjFcIiwyMDQxOTY0OTUyLDE1XSJ9/TROPICS03PRPSL2B_1.0",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
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+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "TROPICS03\u00a0Pathfinder\u00a0L2B Instantaneous Surface Rain Rate (ISRR) V1.0",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2021-07-19T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/TROPICS01PRPSL2B_v1.0.png",
+            "type": "image/jpeg",
+            "title": "Download TROPICS01PRPSL2B_v1.0.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/TROPICS01PRPSL2B_v1.0.png",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/TROPICS_L2B/TROPICS03PRPSL2B_1": {
+            "href": "https://disc2.gesdisc.eosdis.nasa.gov/data/TROPICS_L2B/TROPICS03PRPSL2B_1.0/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTPS",
+            "roles": [
+                "data"
+            ]
+        },
+        "gov/search?q=TROPICS03PRPSL2B_1": {
+            "href": "https://search.earthdata.nasa.gov/search?q=TROPICS03PRPSL2B_1.0",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/TROPICS03PRPSL2B_1.0.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/TROPICS03URADL2A_1.0.json b/datasets/TROPICS03URADL2A_1.0.json
index a690a56de..0c61e3cd3 100644
--- a/datasets/TROPICS03URADL2A_1.0.json
+++ b/datasets/TROPICS03URADL2A_1.0.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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index 6b1ea4ec2..f79d13e33 100644
--- a/datasets/TROPICS05ANTTL1A_0.2.json
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diff --git a/datasets/TROPICS05BRTTL1B_0.2.json b/datasets/TROPICS05BRTTL1B_0.2.json
index 04836e52b..900bece38 100644
--- a/datasets/TROPICS05BRTTL1B_0.2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TROPICS05URADL2A_0.2.json b/datasets/TROPICS05URADL2A_0.2.json
index 6e6cd2f88..48db84607 100644
--- a/datasets/TROPICS05URADL2A_0.2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TROPICS06ANTTL1A_1.0.json b/datasets/TROPICS06ANTTL1A_1.0.json
index 53968584b..94da583c4 100644
--- a/datasets/TROPICS06ANTTL1A_1.0.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TROPICS06BRTTL1B_1.0.json b/datasets/TROPICS06BRTTL1B_1.0.json
index db7491f4f..3ab3b57e2 100644
--- a/datasets/TROPICS06BRTTL1B_1.0.json
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diff --git a/datasets/TROPICS06MIRSL2B_0.2.json b/datasets/TROPICS06MIRSL2B_0.2.json
index 404611d58..dcc7f0b01 100644
--- a/datasets/TROPICS06MIRSL2B_0.2.json
+++ b/datasets/TROPICS06MIRSL2B_0.2.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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diff --git a/datasets/TROPICS06PRPSL2B_1.0.json b/datasets/TROPICS06PRPSL2B_1.0.json
new file mode 100644
index 000000000..568485413
--- /dev/null
+++ b/datasets/TROPICS06PRPSL2B_1.0.json
@@ -0,0 +1,137 @@
+{
+    "type": "Collection",
+    "id": "TROPICS06PRPSL2B_1.0",
+    "stac_version": "1.0.0",
+    "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload. \n\nEach SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.\n\nThis dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. \n\nThis provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles.\u00a0See README for this and other calibration observations and the Data Product Users Guide for orbit details.",
+    "links": [
+        {
+            "rel": "license",
+            "href": "https://science.nasa.gov/earth-science/earth-science-data/data-information-policy",
+            "type": "text/html",
+            "title": "EOSDIS Data Use Policy"
+        },
+        {
+            "rel": "about",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.html",
+            "type": "text/html",
+            "title": "HTML metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.native",
+            "type": "application/xml",
+            "title": "Native metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.echo10",
+            "type": "application/echo10+xml",
+            "title": "ECHO10 metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.json",
+            "type": "application/json",
+            "title": "CMR JSON metadata for collection"
+        },
+        {
+            "rel": "via",
+            "href": "https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.umm_json",
+            "type": "application/vnd.nasa.cmr.umm+json",
+            "title": "CMR UMM_JSON metadata for collection"
+        },
+        {
+            "rel": "self",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGVzcyBjcmlzLXNucHAgbDIgd2F0ZXIgZm9yIGZvcndhcmQgc3RyZWFtLCBzdGFuZGFyZCBwcm9kdWN0IHYxICh0cnBzZGwyaDJvY3JzZnMpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJQU0RMMkgyT0NSU0ZTXCIsXCIxXCIsMjA0MTk2NDk1MiwxNV0iLCJ1bW0iOiJbXCJ0cm9wZXNzIGNyaXMtc25wcCBsMiB3YXRlciBmb3IgZm9yd2FyZCBzdHJlYW0sIHN0YW5kYXJkIHByb2R1Y3QgdjEgKHRycHNkbDJoMm9jcnNmcykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUlBTREwySDJPQ1JTRlNcIixcIjFcIiwyMDQxOTY0OTUyLDE1XSJ9/TROPICS06PRPSL2B_1.0",
+            "type": "application/json"
+        },
+        {
+            "rel": "root",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC",
+            "type": "application/json",
+            "title": "GES_DISC STAC Catalog"
+        },
+        {
+            "rel": "items",
+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGVzcyBjcmlzLXNucHAgbDIgd2F0ZXIgZm9yIGZvcndhcmQgc3RyZWFtLCBzdGFuZGFyZCBwcm9kdWN0IHYxICh0cnBzZGwyaDJvY3JzZnMpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJQU0RMMkgyT0NSU0ZTXCIsXCIxXCIsMjA0MTk2NDk1MiwxNV0iLCJ1bW0iOiJbXCJ0cm9wZXNzIGNyaXMtc25wcCBsMiB3YXRlciBmb3IgZm9yd2FyZCBzdHJlYW0sIHN0YW5kYXJkIHByb2R1Y3QgdjEgKHRycHNkbDJoMm9jcnNmcykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUlBTREwySDJPQ1JTRlNcIixcIjFcIiwyMDQxOTY0OTUyLDE1XSJ9/TROPICS06PRPSL2B_1.0/items",
+            "type": "application/json"
+        }
+    ],
+    "provider": [
+        {
+            "name": "GES_DISC",
+            "roles": [
+                "producer"
+            ]
+        },
+        {
+            "name": "NASA EOSDIS",
+            "roles": [
+                "host"
+            ]
+        }
+    ],
+    "title": "TROPICS06\u00a0Pathfinder\u00a0L2B Instantaneous Surface Rain Rate (ISRR) V1.0",
+    "extent": {
+        "spatial": {
+            "bbox": [
+                [
+                    -180,
+                    -90,
+                    180,
+                    90
+                ]
+            ]
+        },
+        "temporal": {
+            "interval": [
+                [
+                    "2021-07-19T00:00:00Z",
+                    null
+                ]
+            ]
+        }
+    },
+    "license": "proprietary",
+    "assets": {
+        "browse": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/TROPICS01PRPSL2B_v1.0.png",
+            "type": "image/jpeg",
+            "title": "Download TROPICS01PRPSL2B_v1.0.png",
+            "roles": [
+                "browse"
+            ]
+        },
+        "thumbnail": {
+            "href": "https://docserver.gesdisc.eosdis.nasa.gov/public/project/Images/TROPICS01PRPSL2B_v1.0.png",
+            "title": "Thumbnail",
+            "roles": [
+                "thumbnail"
+            ]
+        },
+        "gov/data/TROPICS_L2B/TROPICS06PRPSL2B_1": {
+            "href": "https://disc2.gesdisc.eosdis.nasa.gov/data/TROPICS_L2B/TROPICS06PRPSL2B_1.0/",
+            "title": "Direct Download [0]",
+            "description": "Access the data via HTTPS",
+            "roles": [
+                "data"
+            ]
+        },
+        "gov/search?q=TROPICS06PRPSL2B_1": {
+            "href": "https://search.earthdata.nasa.gov/search?q=TROPICS06PRPSL2B_1.0",
+            "title": "Direct Download [1]",
+            "description": "Use the Earthdata Search to find and retrieve data sets across multiple data centers.",
+            "roles": [
+                "data"
+            ]
+        },
+        "provider_metadata": {
+            "href": "https://disc.gsfc.nasa.gov/datacollection/TROPICS06PRPSL2B_1.0.html",
+            "title": "Provider Metadata",
+            "description": "Access the dataset landing page from the GES DISC website.",
+            "roles": [
+                "metadata"
+            ]
+        }
+    }
+}
\ No newline at end of file
diff --git a/datasets/TROPICS06URADL2A_1.0.json b/datasets/TROPICS06URADL2A_1.0.json
index eabda9f8b..8a8fe9616 100644
--- a/datasets/TROPICS06URADL2A_1.0.json
+++ b/datasets/TROPICS06URADL2A_1.0.json
@@ -42,7 +42,7 @@
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@@ -53,7 +53,7 @@
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+            "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGVzcyBjcmlzLXNucHAgbDIgd2F0ZXIgZm9yIGZvcndhcmQgc3RyZWFtLCBzdGFuZGFyZCBwcm9kdWN0IHYxICh0cnBzZGwyaDJvY3JzZnMpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJQU0RMMkgyT0NSU0ZTXCIsXCIxXCIsMjA0MTk2NDk1MiwxNV0iLCJ1bW0iOiJbXCJ0cm9wZXNzIGNyaXMtc25wcCBsMiB3YXRlciBmb3IgZm9yd2FyZCBzdHJlYW0sIHN0YW5kYXJkIHByb2R1Y3QgdjEgKHRycHNkbDJoMm9jcnNmcykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUlBTREwySDJPQ1JTRlNcIixcIjFcIiwyMDQxOTY0OTUyLDE1XSJ9/TROPICS06URADL2A_1.0/items",
             "type": "application/json"
         }
     ],
diff --git a/datasets/TROPICS07ANTTL1A_0.2.json b/datasets/TROPICS07ANTTL1A_0.2.json
index aa7ad8aaa..8dc8e17f9 100644
--- a/datasets/TROPICS07ANTTL1A_0.2.json
+++ b/datasets/TROPICS07ANTTL1A_0.2.json
@@ -42,7 +42,7 @@
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index e1438a153..9c1de65c9 100644
--- a/datasets/TROPICS07BRTTL1B_0.2.json
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index 325a52e0f..81c6420a8 100644
--- a/datasets/TROPICS07URADL2A_0.2.json
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index d651640e6..0b5317a6e 100644
--- a/datasets/TROPOMAER_1.json
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index 0dddcaa44..6725d0f28 100644
--- a/datasets/TROPOMI_MINDS_NO2_1.1.json
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diff --git a/datasets/TRPSCRAERNH42H2D_1.json b/datasets/TRPSCRAERNH42H2D_1.json
index f96c60c41..70befc39c 100644
--- a/datasets/TRPSCRAERNH42H2D_1.json
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@@ -42,7 +42,7 @@
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index 08a947920..bbc94dd28 100644
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index 879b0d04f..8934cb5a9 100644
--- a/datasets/TRPSCRAERNH4M3D_1.json
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index 2d8c3ec60..8e39a6541 100644
--- a/datasets/TRPSCRAERNO32H2D_1.json
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index fae0ef2ef..0b7ee2f14 100644
--- a/datasets/TRPSCRAERNO3M3D_1.json
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@@ -42,7 +42,7 @@
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index 03b04e91d..39ec60e4e 100644
--- a/datasets/TRPSCRAERSO42H2D_1.json
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@@ -42,7 +42,7 @@
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index 63697dc07..842d3422b 100644
--- a/datasets/TRPSCRAERSO46H3D_1.json
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@@ -42,7 +42,7 @@
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index 6c9522b11..b5d01b787 100644
--- a/datasets/TRPSCRAERSO4M3D_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSCRCH2O2H2D_1.json b/datasets/TRPSCRCH2O2H2D_1.json
index e1b39c1fa..201849c23 100644
--- a/datasets/TRPSCRCH2O2H2D_1.json
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@@ -42,7 +42,7 @@
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index d9673bb09..c680181f1 100644
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index 102c9ba76..b1fcc1108 100644
--- a/datasets/TRPSCRCOM3D_1.json
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@@ -42,7 +42,7 @@
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index 0dd39bb1b..bcf4cc8af 100644
--- a/datasets/TRPSCRCOS6H3D_1.json
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@@ -42,7 +42,7 @@
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index f87e9b58c..c83879a65 100644
--- a/datasets/TRPSCRCOSM3D_1.json
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diff --git a/datasets/TRPSCRECOAM2D_1.json b/datasets/TRPSCRECOAM2D_1.json
index 2d2afd711..bd97dfdc1 100644
--- a/datasets/TRPSCRECOAM2D_1.json
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index 8480978d3..815f77d73 100644
--- a/datasets/TRPSCRECOBM2D_1.json
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index 84f338a29..ca74545fa 100644
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index daa80e6a2..7fa88cbc7 100644
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index 893fdc444..3f30a9107 100644
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index 766eb2afa..242097cea 100644
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index 7428b199f..403717c73 100644
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index 200254e1c..05de8444f 100644
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index ed54b63aa..3f8ab8eb2 100644
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index 985147f37..0410d2752 100644
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index 56a5f57d4..a1c7a11f6 100644
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index a01a48b74..a5609dcf0 100644
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index 3d7b595ab..54346e413 100644
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index ef75f8add..4db3236a1 100644
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index 73f047fba..cf4c28468 100644
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index bf480344a..864ed0c91 100644
--- a/datasets/TRPSCRO3M3D_1.json
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index d20d3848c..35f32f8a7 100644
--- a/datasets/TRPSCRO3S6H3D_1.json
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index 1008de9f8..feac4dbfd 100644
--- a/datasets/TRPSCRO3SM3D_1.json
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index bfb4622d4..e6a073573 100644
--- a/datasets/TRPSCROH2H2D_1.json
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index 9fdd72a47..f2284b553 100644
--- a/datasets/TRPSCROH6H3D_1.json
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index 410fc7931..fbe390a56 100644
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index 44b0ffc68..f72fd41fd 100644
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index 33ea00589..4a1852abd 100644
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index 225bf1543..06491ae9b 100644
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index 58723bfb6..1c8d6490b 100644
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index af1838346..132fc7981 100644
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index 0d9be1e5b..47fbacbee 100644
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index 28e2c282a..c15402e85 100644
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index 8b6282540..efd458488 100644
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index 7c9911592..b4816e51d 100644
--- a/datasets/TRPSCRT2H2D_1.json
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@@ -42,7 +42,7 @@
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index d28e628f0..b3e664498 100644
--- a/datasets/TRPSCRT6H3D_1.json
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diff --git a/datasets/TRPSCRTM3D_1.json b/datasets/TRPSCRTM3D_1.json
index 8f17d12af..0856a16b6 100644
--- a/datasets/TRPSCRTM3D_1.json
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diff --git a/datasets/TRPSCRU2H2D_1.json b/datasets/TRPSCRU2H2D_1.json
index fabaf7540..e8bbcee48 100644
--- a/datasets/TRPSCRU2H2D_1.json
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diff --git a/datasets/TRPSCRU6H3D_1.json b/datasets/TRPSCRU6H3D_1.json
index 4d16d2678..b8dc58be1 100644
--- a/datasets/TRPSCRU6H3D_1.json
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index a089453c7..70df88f01 100644
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index 92b1f1a76..0526a7049 100644
--- a/datasets/TRPSCRV2H2D_1.json
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index e4e8dbf39..153be07b0 100644
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index 2d571a38f..5f5c1935f 100644
--- a/datasets/TRPSCRVM3D_1.json
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diff --git a/datasets/TRPSDL2ALLCRSMGBEI_1.json b/datasets/TRPSDL2ALLCRSMGBEI_1.json
index 977a2ff20..1a8a56047 100644
--- a/datasets/TRPSDL2ALLCRSMGBEI_1.json
+++ b/datasets/TRPSDL2ALLCRSMGBEI_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2ALLCRSMGDEL_1.json b/datasets/TRPSDL2ALLCRSMGDEL_1.json
index c0eac7ce0..2dec2f2f5 100644
--- a/datasets/TRPSDL2ALLCRSMGDEL_1.json
+++ b/datasets/TRPSDL2ALLCRSMGDEL_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2ALLCRSMGKAR_1.json b/datasets/TRPSDL2ALLCRSMGKAR_1.json
index 323667192..346ef8db2 100644
--- a/datasets/TRPSDL2ALLCRSMGKAR_1.json
+++ b/datasets/TRPSDL2ALLCRSMGKAR_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2ALLCRSMGLAG_1.json b/datasets/TRPSDL2ALLCRSMGLAG_1.json
index f9fdc7536..8907de027 100644
--- a/datasets/TRPSDL2ALLCRSMGLAG_1.json
+++ b/datasets/TRPSDL2ALLCRSMGLAG_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2ALLCRSMGLOS_1.json b/datasets/TRPSDL2ALLCRSMGLOS_1.json
index f9c934cca..0af87f2f4 100644
--- a/datasets/TRPSDL2ALLCRSMGLOS_1.json
+++ b/datasets/TRPSDL2ALLCRSMGLOS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2ALLCRSMGMEX_1.json b/datasets/TRPSDL2ALLCRSMGMEX_1.json
index 6462c74f4..fda8fb9ce 100644
--- a/datasets/TRPSDL2ALLCRSMGMEX_1.json
+++ b/datasets/TRPSDL2ALLCRSMGMEX_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2ALLCRSMGSAO_1.json b/datasets/TRPSDL2ALLCRSMGSAO_1.json
index b83afe36f..5e3a3e0f8 100644
--- a/datasets/TRPSDL2ALLCRSMGSAO_1.json
+++ b/datasets/TRPSDL2ALLCRSMGSAO_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2ALLCRSMGTOK_1.json b/datasets/TRPSDL2ALLCRSMGTOK_1.json
index 4814b76c3..e2cf96c20 100644
--- a/datasets/TRPSDL2ALLCRSMGTOK_1.json
+++ b/datasets/TRPSDL2ALLCRSMGTOK_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2CH4AIRSFS_1.json b/datasets/TRPSDL2CH4AIRSFS_1.json
index 6beca2134..0392cba33 100644
--- a/datasets/TRPSDL2CH4AIRSFS_1.json
+++ b/datasets/TRPSDL2CH4AIRSFS_1.json
@@ -42,7 +42,7 @@
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index e5e786794..8199e56d5 100644
--- a/datasets/TRPSDL2CH4CRS1FS_1.json
+++ b/datasets/TRPSDL2CH4CRS1FS_1.json
@@ -42,7 +42,7 @@
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index d2aafbd80..750ecd0b8 100644
--- a/datasets/TRPSDL2CH4CRSAUS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2CH4CRSFS_1.json b/datasets/TRPSDL2CH4CRSFS_1.json
index 26e7ec8e0..8336e8b66 100644
--- a/datasets/TRPSDL2CH4CRSFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2COAIRSFS_1.json b/datasets/TRPSDL2COAIRSFS_1.json
index 5a917a117..88737c4b0 100644
--- a/datasets/TRPSDL2COAIRSFS_1.json
+++ b/datasets/TRPSDL2COAIRSFS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2COCRS1FS_1.json b/datasets/TRPSDL2COCRS1FS_1.json
index a95e79e98..5ee0b3989 100644
--- a/datasets/TRPSDL2COCRS1FS_1.json
+++ b/datasets/TRPSDL2COCRS1FS_1.json
@@ -42,7 +42,7 @@
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index fe74eb5b2..fcb1fb4b6 100644
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index 7b1d218b7..a50aef038 100644
--- a/datasets/TRPSDL2COCRSFS_1.json
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index 7476f5707..9b16e3c0e 100644
--- a/datasets/TRPSDL2COCRSTS1_1.json
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index 4bb1f8d2e..0b5253afb 100644
--- a/datasets/TRPSDL2COCRSTS2_1.json
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@@ -42,7 +42,7 @@
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index 1e783aac5..95021c746 100644
--- a/datasets/TRPSDL2COCRSWCFHI_1.json
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index 4cf660350..f9241033c 100644
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diff --git a/datasets/TRPSDL2H2OAIRSFS_1.json b/datasets/TRPSDL2H2OAIRSFS_1.json
index 7508a8b86..b98794878 100644
--- a/datasets/TRPSDL2H2OAIRSFS_1.json
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@@ -42,7 +42,7 @@
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index a17bfa6a9..5b0fb9566 100644
--- a/datasets/TRPSDL2H2OCRS1FS_1.json
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diff --git a/datasets/TRPSDL2H2OCRSAUS_1.json b/datasets/TRPSDL2H2OCRSAUS_1.json
index b11ef660d..72dfde952 100644
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index 4a33ab1e8..c879a05b8 100644
--- a/datasets/TRPSDL2H2OCRSFS_1.json
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index 5faf20804..31ca205a3 100644
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diff --git a/datasets/TRPSDL2HDOCRS1FS_1.json b/datasets/TRPSDL2HDOCRS1FS_1.json
index 6f243443f..b75751d5c 100644
--- a/datasets/TRPSDL2HDOCRS1FS_1.json
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index 6a7a29c82..e4d96c892 100644
--- a/datasets/TRPSDL2HDOCRSAUS_1.json
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index e52e84bae..cc9529ab7 100644
--- a/datasets/TRPSDL2HDOCRSFS_1.json
+++ b/datasets/TRPSDL2HDOCRSFS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2NH3AIRSFS_1.json b/datasets/TRPSDL2NH3AIRSFS_1.json
index 252063655..71fba39ea 100644
--- a/datasets/TRPSDL2NH3AIRSFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2NH3CRS1FS_1.json b/datasets/TRPSDL2NH3CRS1FS_1.json
index 476ad95b1..26a1dde5d 100644
--- a/datasets/TRPSDL2NH3CRS1FS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2NH3CRSAUS_1.json b/datasets/TRPSDL2NH3CRSAUS_1.json
index da8cd8ecf..0b3709c14 100644
--- a/datasets/TRPSDL2NH3CRSAUS_1.json
+++ b/datasets/TRPSDL2NH3CRSAUS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2NH3CRSFS_1.json b/datasets/TRPSDL2NH3CRSFS_1.json
index ac6d18cf8..ddf53bf10 100644
--- a/datasets/TRPSDL2NH3CRSFS_1.json
+++ b/datasets/TRPSDL2NH3CRSFS_1.json
@@ -42,7 +42,7 @@
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index d0f4db254..c4a897ef8 100644
--- a/datasets/TRPSDL2NH3CRSWCFHI_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2NH3CRSWCF_1.json b/datasets/TRPSDL2NH3CRSWCF_1.json
index 3a3aed6a8..85f8a5600 100644
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index 3a0b5dd42..7e347b725 100644
--- a/datasets/TRPSDL2O3AIRSFS_1.json
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index 3459262b4..e0227957b 100644
--- a/datasets/TRPSDL2O3AIRSOMIFS_1.json
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index c6d9162e4..340e89007 100644
--- a/datasets/TRPSDL2O3CRS1FS_1.json
+++ b/datasets/TRPSDL2O3CRS1FS_1.json
@@ -42,7 +42,7 @@
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index ffed00c50..5c0cfee76 100644
--- a/datasets/TRPSDL2O3CRSAUS_1.json
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@@ -42,7 +42,7 @@
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index f085d2acb..a23bd009c 100644
--- a/datasets/TRPSDL2O3CRSFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2O3CRSWCFHI_1.json b/datasets/TRPSDL2O3CRSWCFHI_1.json
index 7243823ae..786e1228a 100644
--- a/datasets/TRPSDL2O3CRSWCFHI_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2O3CRSWCF_1.json b/datasets/TRPSDL2O3CRSWCF_1.json
index 79793c917..af5da0105 100644
--- a/datasets/TRPSDL2O3CRSWCF_1.json
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@@ -42,7 +42,7 @@
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index 00297a420..405dedd95 100644
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diff --git a/datasets/TRPSDL2PANCRS1FS_1.json b/datasets/TRPSDL2PANCRS1FS_1.json
index 297c43501..623ef9662 100644
--- a/datasets/TRPSDL2PANCRS1FS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2PANCRSAUS_1.json b/datasets/TRPSDL2PANCRSAUS_1.json
index f108b9d98..dede15dbb 100644
--- a/datasets/TRPSDL2PANCRSAUS_1.json
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diff --git a/datasets/TRPSDL2PANCRSFS_1.json b/datasets/TRPSDL2PANCRSFS_1.json
index 4d949bd55..ad413b8d5 100644
--- a/datasets/TRPSDL2PANCRSFS_1.json
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@@ -42,7 +42,7 @@
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index 2062de07b..e2fc9b9e9 100644
--- a/datasets/TRPSDL2PANCRSWCFHI_1.json
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index 7f00814db..2c41c73df 100644
--- a/datasets/TRPSDL2PANCRSWCF_1.json
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index c373ca018..3b9c5ac61 100644
--- a/datasets/TRPSDL2TATMAIRSFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSDL2TATMCRS1FS_1.json b/datasets/TRPSDL2TATMCRS1FS_1.json
index 48d2779dc..d0df178c8 100644
--- a/datasets/TRPSDL2TATMCRS1FS_1.json
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diff --git a/datasets/TRPSDL2TATMCRSAUS_1.json b/datasets/TRPSDL2TATMCRSAUS_1.json
index 642cb8735..2a3ee75c8 100644
--- a/datasets/TRPSDL2TATMCRSAUS_1.json
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diff --git a/datasets/TRPSDL2TATMCRSFS_1.json b/datasets/TRPSDL2TATMCRSFS_1.json
index 23b8d01fe..ecf050622 100644
--- a/datasets/TRPSDL2TATMCRSFS_1.json
+++ b/datasets/TRPSDL2TATMCRSFS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGBEI_1.json b/datasets/TRPSYL2ALLCRSMGBEI_1.json
index ac26c2606..5250d7d66 100644
--- a/datasets/TRPSYL2ALLCRSMGBEI_1.json
+++ b/datasets/TRPSYL2ALLCRSMGBEI_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGDEL_1.json b/datasets/TRPSYL2ALLCRSMGDEL_1.json
index c0bf6b563..95d7ef22f 100644
--- a/datasets/TRPSYL2ALLCRSMGDEL_1.json
+++ b/datasets/TRPSYL2ALLCRSMGDEL_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGKAR_1.json b/datasets/TRPSYL2ALLCRSMGKAR_1.json
index b9ffe45fd..b9f50ba31 100644
--- a/datasets/TRPSYL2ALLCRSMGKAR_1.json
+++ b/datasets/TRPSYL2ALLCRSMGKAR_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGLAG_1.json b/datasets/TRPSYL2ALLCRSMGLAG_1.json
index ccb5206fb..0b41a659b 100644
--- a/datasets/TRPSYL2ALLCRSMGLAG_1.json
+++ b/datasets/TRPSYL2ALLCRSMGLAG_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGLOS_1.json b/datasets/TRPSYL2ALLCRSMGLOS_1.json
index 57768683e..08bcb967c 100644
--- a/datasets/TRPSYL2ALLCRSMGLOS_1.json
+++ b/datasets/TRPSYL2ALLCRSMGLOS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGMEX_1.json b/datasets/TRPSYL2ALLCRSMGMEX_1.json
index 14c7ad869..cc3e68a1a 100644
--- a/datasets/TRPSYL2ALLCRSMGMEX_1.json
+++ b/datasets/TRPSYL2ALLCRSMGMEX_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGSAO_1.json b/datasets/TRPSYL2ALLCRSMGSAO_1.json
index 94f37aeb3..c3011b45c 100644
--- a/datasets/TRPSYL2ALLCRSMGSAO_1.json
+++ b/datasets/TRPSYL2ALLCRSMGSAO_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2ALLCRSMGTOK_1.json b/datasets/TRPSYL2ALLCRSMGTOK_1.json
index faabccc6c..92a6a68cc 100644
--- a/datasets/TRPSYL2ALLCRSMGTOK_1.json
+++ b/datasets/TRPSYL2ALLCRSMGTOK_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2CH4AIRSFS_1.json b/datasets/TRPSYL2CH4AIRSFS_1.json
index ba2bc6ffb..c941121f5 100644
--- a/datasets/TRPSYL2CH4AIRSFS_1.json
+++ b/datasets/TRPSYL2CH4AIRSFS_1.json
@@ -42,7 +42,7 @@
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index 6b1b31308..f26bed2cb 100644
--- a/datasets/TRPSYL2CH4AIRSORS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2CH4CRS1FS_1.json b/datasets/TRPSYL2CH4CRS1FS_1.json
index b8b429951..afa3078e2 100644
--- a/datasets/TRPSYL2CH4CRS1FS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2CH4CRSFS_1.json b/datasets/TRPSYL2CH4CRSFS_1.json
index 0a97dcd6d..fbc7b6c55 100644
--- a/datasets/TRPSYL2CH4CRSFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2CH4CRSRS_1.json b/datasets/TRPSYL2CH4CRSRS_1.json
index f5223c606..d55b0af79 100644
--- a/datasets/TRPSYL2CH4CRSRS_1.json
+++ b/datasets/TRPSYL2CH4CRSRS_1.json
@@ -42,7 +42,7 @@
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index 3e89faa02..8ad359c48 100644
--- a/datasets/TRPSYL2COAIRSFS_1.json
+++ b/datasets/TRPSYL2COAIRSFS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2COAIRSORS_1.json b/datasets/TRPSYL2COAIRSORS_1.json
index 8b25aaa6b..1f84ffbb4 100644
--- a/datasets/TRPSYL2COAIRSORS_1.json
+++ b/datasets/TRPSYL2COAIRSORS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2COCRS1FS_1.json b/datasets/TRPSYL2COCRS1FS_1.json
index 39d9a5bb3..59d3e0b1b 100644
--- a/datasets/TRPSYL2COCRS1FS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2COCRSFS_1.json b/datasets/TRPSYL2COCRSFS_1.json
index d48067e30..87e574b35 100644
--- a/datasets/TRPSYL2COCRSFS_1.json
+++ b/datasets/TRPSYL2COCRSFS_1.json
@@ -42,7 +42,7 @@
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index d0065d0cf..024b9384e 100644
--- a/datasets/TRPSYL2COCRSRS_1.json
+++ b/datasets/TRPSYL2COCRSRS_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2HDOAIRSFS_1.json b/datasets/TRPSYL2HDOAIRSFS_1.json
index 8dfafcc9b..7cd8f4934 100644
--- a/datasets/TRPSYL2HDOAIRSFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2HDOAIRSORS_1.json b/datasets/TRPSYL2HDOAIRSORS_1.json
index bfb02c56a..9f720d24c 100644
--- a/datasets/TRPSYL2HDOAIRSORS_1.json
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@@ -42,7 +42,7 @@
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index b6547cde2..0eadc6cf9 100644
--- a/datasets/TRPSYL2HDOCRS1FS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2HDOCRSFS_1.json b/datasets/TRPSYL2HDOCRSFS_1.json
index 5a9aae313..542cde28b 100644
--- a/datasets/TRPSYL2HDOCRSFS_1.json
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index bf495f864..3e772babf 100644
--- a/datasets/TRPSYL2HDOCRSRS_1.json
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diff --git a/datasets/TRPSYL2NH3AIRSFS_1.json b/datasets/TRPSYL2NH3AIRSFS_1.json
index 7ab2700e8..4b61c2eba 100644
--- a/datasets/TRPSYL2NH3AIRSFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2NH3CRS1FS_1.json b/datasets/TRPSYL2NH3CRS1FS_1.json
index 75927cbc0..49ebbb61a 100644
--- a/datasets/TRPSYL2NH3CRS1FS_1.json
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diff --git a/datasets/TRPSYL2NH3CRSFS_1.json b/datasets/TRPSYL2NH3CRSFS_1.json
index 6cc91001a..cac7f95d5 100644
--- a/datasets/TRPSYL2NH3CRSFS_1.json
+++ b/datasets/TRPSYL2NH3CRSFS_1.json
@@ -42,7 +42,7 @@
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index 7d3282561..dc85f9ccf 100644
--- a/datasets/TRPSYL2NH3CRSRS_1.json
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@@ -42,7 +42,7 @@
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index c1852cb78..602038fa3 100644
--- a/datasets/TRPSYL2O3AIRSFS_1.json
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@@ -42,7 +42,7 @@
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index 851a6bcf5..0cfef340d 100644
--- a/datasets/TRPSYL2O3AIRSOMIFS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2O3AIRSORS_1.json b/datasets/TRPSYL2O3AIRSORS_1.json
index 4ec0b0421..a86853eb3 100644
--- a/datasets/TRPSYL2O3AIRSORS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TRPSYL2O3CRS1FS_1.json b/datasets/TRPSYL2O3CRS1FS_1.json
index ae837f4d2..2ded2f27b 100644
--- a/datasets/TRPSYL2O3CRS1FS_1.json
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index 0bb8f015c..c1c848c69 100644
--- a/datasets/TRPSYL2O3CRSFS_1.json
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index a4bd37333..cc7386911 100644
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index d8fb65c91..5df1b5b7c 100644
--- a/datasets/TRPSYL2O3OMIFS_1.json
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@@ -42,7 +42,7 @@
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index 3afac7d9f..8dbf5a7e3 100644
--- a/datasets/TRPSYL2PANCRS1FS_1.json
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diff --git a/datasets/TRPSYL2PANCRSFS_1.json b/datasets/TRPSYL2PANCRSFS_1.json
index 60d4d4709..530acb733 100644
--- a/datasets/TRPSYL2PANCRSFS_1.json
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@@ -42,7 +42,7 @@
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index 17aa8acd6..e4ec773d7 100644
--- a/datasets/TRPSYL2PANCRSRS_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/TSIS_SSI_L3_12HR_12.json b/datasets/TSIS_SSI_L3_12HR_12.json
index dcff9b49a..f2df0fe13 100644
--- a/datasets/TSIS_SSI_L3_12HR_12.json
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diff --git a/datasets/TSIS_SSI_L3_24HR_12.json b/datasets/TSIS_SSI_L3_24HR_12.json
index b17862d20..a32093d22 100644
--- a/datasets/TSIS_SSI_L3_24HR_12.json
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diff --git a/datasets/TSIS_TSI_L3_06HR_04.json b/datasets/TSIS_TSI_L3_06HR_04.json
index 1bf90b0ea..502084f0e 100644
--- a/datasets/TSIS_TSI_L3_06HR_04.json
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@@ -42,7 +42,7 @@
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index 113f7ff26..315c30aed 100644
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index 59b596704..e59ef726c 100644
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index cc3fb0541..b41e4e25b 100644
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index 7f6814328..2c36ea3af 100644
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index ee6e3983b..b19301b62 100644
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index e84d8a7ea..1db9c9f90 100644
--- a/datasets/Tree_Canopy_Cover_Mexico_2137_1.json
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index 73e971a22..acc0c5766 100644
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index b920a46ba..8812e6489 100644
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diff --git a/datasets/Tundra_Leaf_Spectra_2005_1.json b/datasets/Tundra_Leaf_Spectra_2005_1.json
index 6651c7cbd..ad3a0141c 100644
--- a/datasets/Tundra_Leaf_Spectra_2005_1.json
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index 1acd4eb52..0638bba88 100644
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index 144a6f96d..3129fe19c 100644
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index bfdaf4b34..955ae6cb2 100644
--- a/datasets/UARHA2FN_019.json
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index d21d84175..d827135da 100644
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diff --git a/datasets/UARHR3AL_011.json b/datasets/UARHR3AL_011.json
index f3e19b85a..fd6a30798 100644
--- a/datasets/UARHR3AL_011.json
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index 78b141377..8c73d9aa7 100644
--- a/datasets/UARHR3AT_011.json
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index a5f59c339..89d494c94 100644
--- a/datasets/UARIS3AL_010.json
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index 5d4cb1e68..113e847e4 100644
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diff --git a/datasets/UARML3AL_005.json b/datasets/UARML3AL_005.json
index 2997e2b68..355ea8141 100644
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index 973f655d4..e7a49a17a 100644
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index 98db985cd..a4272ef9b 100644
--- a/datasets/UARPE2AXIS1_001.json
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index 437574e35..ab05f8269 100644
--- a/datasets/UARPE2AXIS2_001.json
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index 490296828..0774ad09b 100644
--- a/datasets/UARPE2HEPSA_002.json
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index 8da952bd4..64eb35f6b 100644
--- a/datasets/UARPE2HEPSB_001.json
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index 026a852d7..a004f30f0 100644
--- a/datasets/UARPE2MEPS_001.json
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diff --git a/datasets/UARPE2VMAGAC_001.json b/datasets/UARPE2VMAGAC_001.json
index 39bbc737d..b53d4f035 100644
--- a/datasets/UARPE2VMAGAC_001.json
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index 50faeb84b..1b683163d 100644
--- a/datasets/UARPE2VMAGDC_001.json
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index ea3a6066c..9358c6db1 100644
--- a/datasets/UARPE3AT_004.json
+++ b/datasets/UARPE3AT_004.json
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index deb9b5c93..e997dae6b 100644
--- a/datasets/UARPE3TP_004.json
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diff --git a/datasets/UARSO3BS_018.json b/datasets/UARSO3BS_018.json
index 4479a1b2b..bc2a02e1b 100644
--- a/datasets/UARSO3BS_018.json
+++ b/datasets/UARSO3BS_018.json
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diff --git a/datasets/UARSU3BS_022.json b/datasets/UARSU3BS_022.json
index b2b6fbdd7..7eadac752 100644
--- a/datasets/UARSU3BS_022.json
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index a19d3e76b..faa7b7ee9 100644
--- a/datasets/UARWI3AL_011.json
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index 19006c399..5e1fdff08 100644
--- a/datasets/UARWI3AT_011.json
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index 8a73121f2..d64d70bf3 100644
--- a/datasets/UARZCNMC_001.json
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index 5dd0218ca..bdaf79cc7 100644
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index 5a614f8d6..534153134 100644
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diff --git a/datasets/UAVSAR_INSAR_AMP_GRD_1.json b/datasets/UAVSAR_INSAR_AMP_GRD_1.json
index f62c347a0..cbd7ac374 100644
--- a/datasets/UAVSAR_INSAR_AMP_GRD_1.json
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diff --git a/datasets/UAVSAR_POL_INC_1.json b/datasets/UAVSAR_POL_INC_1.json
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index 827326bdd..2cb355825 100644
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index 0d713a339..524f39999 100644
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index ba8ffad69..f765f19cb 100644
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index beec27aa2..96690e0d6 100644
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index b9b5a253b..1a3cb8dfe 100644
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diff --git a/datasets/Uncertainty_US_Coastal_GHG_1650_1.json b/datasets/Uncertainty_US_Coastal_GHG_1650_1.json
index 9c8ca148d..8c176c7ee 100644
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index a3bca2f83..a5cb9b8a1 100644
--- a/datasets/Understory_Veg_Biomass_Alaska_2340_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VIP01_004.json b/datasets/VIP01_004.json
index eb3681c05..39a30855f 100644
--- a/datasets/VIP01_004.json
+++ b/datasets/VIP01_004.json
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diff --git a/datasets/VIP07_004.json b/datasets/VIP07_004.json
index 6fa82c951..d0c1b2c35 100644
--- a/datasets/VIP07_004.json
+++ b/datasets/VIP07_004.json
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diff --git a/datasets/VIP15_004.json b/datasets/VIP15_004.json
index 5aaead4d6..25f685a1e 100644
--- a/datasets/VIP15_004.json
+++ b/datasets/VIP15_004.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/VIP30_004.json b/datasets/VIP30_004.json
index 1d94296fe..c69a40813 100644
--- a/datasets/VIP30_004.json
+++ b/datasets/VIP30_004.json
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index b3573b519..dd1579c01 100644
--- a/datasets/VIPPHEN_EVI2_004.json
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index 721078f40..c561ff9fa 100644
--- a/datasets/VIPPHEN_NDVI_004.json
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diff --git a/datasets/VISSRGOES1IMIR_001.json b/datasets/VISSRGOES1IMIR_001.json
index 88ec1eeff..b447ed31e 100644
--- a/datasets/VISSRGOES1IMIR_001.json
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index 537cc4593..68e373e5c 100644
--- a/datasets/VISSRGOES1IMVIS_001.json
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index d7d3c7463..b31e892f9 100644
--- a/datasets/VISSRGOES2IMIR_001.json
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diff --git a/datasets/VISSRGOES2IMVIS_001.json b/datasets/VISSRGOES2IMVIS_001.json
index 939f114d9..2b29e202b 100644
--- a/datasets/VISSRGOES2IMVIS_001.json
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index 71fa616d0..724ca82f9 100644
--- a/datasets/VISSRGOES3IMIR_001.json
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index cf5c650f4..0ece17c9c 100644
--- a/datasets/VISSRGOES3IMVIS_001.json
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index 46c0c7ec7..f11e5bb7a 100644
--- a/datasets/VISSRSMS1IMIR_001.json
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index b496c1b52..e26e97f5d 100644
--- a/datasets/VISSRSMS1IMVIS_001.json
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index 9dea5ded3..a983570d3 100644
--- a/datasets/VISSRSMS1L1AOIPS_001.json
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diff --git a/datasets/VISSRSMS1L1EHT_001.json b/datasets/VISSRSMS1L1EHT_001.json
index 19228c902..c52970db9 100644
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index eb82bd542..4b41f49b5 100644
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index 1ea1d6872..93c65497a 100644
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index fb0b7a84a..cb6570d2e 100644
--- a/datasets/VISSRSMS2L1AOIPS_001.json
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index 5bbe52ad7..e19d0ee9c 100644
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index cf0822254..80447b567 100644
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index 8f34182df..908084959 100644
--- a/datasets/VJ109A1_002.json
+++ b/datasets/VJ109A1_002.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/VJ109CMG_002.json b/datasets/VJ109CMG_002.json
index 28f78200a..f2a967e32 100644
--- a/datasets/VJ109CMG_002.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VJ109GA_002.json b/datasets/VJ109GA_002.json
index 1cbbab36e..b8a71c301 100644
--- a/datasets/VJ109GA_002.json
+++ b/datasets/VJ109GA_002.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/VJ109H1_002.json b/datasets/VJ109H1_002.json
index ff6f78944..36c7829e1 100644
--- a/datasets/VJ109H1_002.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VJ110A1F_2.json b/datasets/VJ110A1F_2.json
index 04f9e9f27..16d2364bd 100644
--- a/datasets/VJ110A1F_2.json
+++ b/datasets/VJ110A1F_2.json
@@ -42,7 +42,7 @@
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index 3078de514..0f85c2d55 100644
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index 7459ff13c..68e8de7f8 100644
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index f22780f40..8c7fdc950 100644
--- a/datasets/VJ113A3_002.json
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@@ -42,7 +42,7 @@
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index 23ef2ff45..777fa85a8 100644
--- a/datasets/VJ113C1_002.json
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@@ -42,7 +42,7 @@
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index 27b35d8cb..4b887211b 100644
--- a/datasets/VJ113C2_002.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VJ114A1_002.json b/datasets/VJ114A1_002.json
index 75d05071c..64925e45d 100644
--- a/datasets/VJ114A1_002.json
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@@ -42,7 +42,7 @@
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index 91c5a934a..a6242e3ab 100644
--- a/datasets/VJ114IMG_002.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VJ114_002.json b/datasets/VJ114_002.json
index 1f677c933..3e3df1a0a 100644
--- a/datasets/VJ114_002.json
+++ b/datasets/VJ114_002.json
@@ -42,7 +42,7 @@
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index 2788ba23b..40b9e9c26 100644
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index 117d7cc3d..2cadacc94 100644
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index cca21645d..a18a99271 100644
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index a12d783f8..6ad21ade9 100644
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index 30214f7db..bf7efd480 100644
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diff --git a/datasets/VJ121C2_002.json b/datasets/VJ121C2_002.json
index 1abe8d8af..974ea97e2 100644
--- a/datasets/VJ121C2_002.json
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@@ -42,7 +42,7 @@
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index 8998f69f7..8fd925883 100644
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index 258db90c2..c874f357d 100644
--- a/datasets/VJ121_002.json
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index 774735262..20fec9dfe 100644
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index 18a70330f..6890ecef1 100644
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index 6e0348505..497536ec0 100644
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diff --git a/datasets/VJ129_2.json b/datasets/VJ129_2.json
index 34710086e..672506136 100644
--- a/datasets/VJ129_2.json
+++ b/datasets/VJ129_2.json
@@ -42,7 +42,7 @@
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index 51668a5b9..6a04d0af2 100644
--- a/datasets/VJ130P1D_2.json
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@@ -42,7 +42,7 @@
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index 07ba71aa6..629673e2a 100644
--- a/datasets/VJ130P1N_2.json
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diff --git a/datasets/VJ130_2.json b/datasets/VJ130_2.json
index 3181be023..b71a85f62 100644
--- a/datasets/VJ130_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VNP03MODLL_002.json b/datasets/VNP03MODLL_002.json
index 0b7e2f56a..7f8490763 100644
--- a/datasets/VNP03MODLL_002.json
+++ b/datasets/VNP03MODLL_002.json
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index 957069fc5..ec000b21e 100644
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index 289072a80..eaed0d4e6 100644
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index 82a9001f6..e18e2c90a 100644
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index 54c135cad..97c5c8886 100644
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index 1de6ff5d8..77219db01 100644
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index d914b76c1..b80d976a6 100644
--- a/datasets/VNP10A1F_2.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VNP10A1_1.json b/datasets/VNP10A1_1.json
index 36cb33501..ebf07c5ba 100644
--- a/datasets/VNP10A1_1.json
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index a3b4d433e..276f3f13c 100644
--- a/datasets/VNP10A1_2.json
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index 8f75da6ed..921e882f7 100644
--- a/datasets/VNP10C1_2.json
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diff --git a/datasets/VNP10_1.json b/datasets/VNP10_1.json
index 5028eb3ac..7e5610187 100644
--- a/datasets/VNP10_1.json
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diff --git a/datasets/VNP10_2.json b/datasets/VNP10_2.json
index c6856f17c..67973784e 100644
--- a/datasets/VNP10_2.json
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diff --git a/datasets/VNP13A1_002.json b/datasets/VNP13A1_002.json
index 9836d11b5..be98872f5 100644
--- a/datasets/VNP13A1_002.json
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@@ -42,7 +42,7 @@
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index 8a7afef41..0549389da 100644
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index a907b27ce..03b043de7 100644
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index 2a3e09e35..ce8fcc503 100644
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index aafb4fd87..8bc0bdbef 100644
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index 95b5b38ac..cf0a82511 100644
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index c68065cf6..c88344c70 100644
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index 7938037ed..b0438ec08 100644
--- a/datasets/VNP14_002.json
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index bff0008dc..e08b64b69 100644
--- a/datasets/VNP15A2H_002.json
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index 34dc1588c..2b9ebe6c6 100644
--- a/datasets/VNP21A1D_002.json
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index da4f4d71d..b9ab2b54a 100644
--- a/datasets/VNP21A1N_002.json
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diff --git a/datasets/VNP21A2_002.json b/datasets/VNP21A2_002.json
index 730cd4124..04dff3bb4 100644
--- a/datasets/VNP21A2_002.json
+++ b/datasets/VNP21A2_002.json
@@ -42,7 +42,7 @@
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index 8b862930e..f657c93fa 100644
--- a/datasets/VNP21C1_002.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/VNP21C2_002.json b/datasets/VNP21C2_002.json
index 5b2dda913..dce6dbfd1 100644
--- a/datasets/VNP21C2_002.json
+++ b/datasets/VNP21C2_002.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/VNP21C3_002.json b/datasets/VNP21C3_002.json
index 8aa65581d..71333beea 100644
--- a/datasets/VNP21C3_002.json
+++ b/datasets/VNP21C3_002.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/VNP21_002.json b/datasets/VNP21_002.json
index fd1268bcb..280beafae 100644
--- a/datasets/VNP21_002.json
+++ b/datasets/VNP21_002.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/VNP28C2_002.json b/datasets/VNP28C2_002.json
index 70ab1ffc7..5203aa22d 100644
--- a/datasets/VNP28C2_002.json
+++ b/datasets/VNP28C2_002.json
@@ -42,7 +42,7 @@
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index 92ee1c233..ecdfa8d0d 100644
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index da3fbe75d..a060898af 100644
--- a/datasets/VNP29P1D_2.json
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diff --git a/datasets/VNP29_1.json b/datasets/VNP29_1.json
index 823aa7b85..a9176c79c 100644
--- a/datasets/VNP29_1.json
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index 97a3fb3d8..b41e7d8f6 100644
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index fed958e79..16ddfdd77 100644
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diff --git a/datasets/VNP30P1N_2.json b/datasets/VNP30P1N_2.json
index e43b24dbf..74da7517f 100644
--- a/datasets/VNP30P1N_2.json
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@@ -42,7 +42,7 @@
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index cea5bdab1..1a7c08076 100644
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index 2b9a124f0..ec6b156f2 100644
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index 61bc0f1d8..a9f482d54 100644
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index d6e7d771c..e92806bc2 100644
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index 05ef59fa2..8845ae482 100644
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index 52990912a..699959591 100644
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index d3cba390b..424e07f68 100644
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index eeed2eb00..8a9fd201c 100644
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index 5a059d547..2978d4358 100644
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index f11182efe..338a90d09 100644
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diff --git a/datasets/ZoblerSoilDerived_540_1.json b/datasets/ZoblerSoilDerived_540_1.json
index f64ed744c..65cbf49df 100644
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diff --git a/datasets/ZoblerSoil_418_1.json b/datasets/ZoblerSoil_418_1.json
index d2c293a1a..4d7b55167 100644
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index 4f9f1fbf6..250bc9521 100644
--- a/datasets/Zobler_Soil_649_1.json
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diff --git a/datasets/aerosol_properties_725_1.json b/datasets/aerosol_properties_725_1.json
index 080927294..a0fee4dec 100644
--- a/datasets/aerosol_properties_725_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/african_woody_savanna_850_1.json b/datasets/african_woody_savanna_850_1.json
index 6dd4ac6c9..a8e75a850 100644
--- a/datasets/african_woody_savanna_850_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/air_sea_gas_exchange_xdeg_1208_1.json b/datasets/air_sea_gas_exchange_xdeg_1208_1.json
index 9c5bba998..c880d8f31 100644
--- a/datasets/air_sea_gas_exchange_xdeg_1208_1.json
+++ b/datasets/air_sea_gas_exchange_xdeg_1208_1.json
@@ -42,7 +42,7 @@
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index 9e12ee5ba..9b1d3d73f 100644
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index cc22b9997..68cde7f8b 100644
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index 174e84468..91dc8288c 100644
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index 97135742a..d278d1190 100644
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index d2a4f9205..5b60609d6 100644
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index 98b164f5d..351a2c6cb 100644
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index d641bf14a..c6aa34e52 100644
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index 7682236fb..ed6255b37 100644
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index d6e000865..4ce3c5361 100644
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index a0a5161e6..b913cda9a 100644
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index 6e0e36402..b978963bf 100644
--- a/datasets/billmark_828_1.json
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index ef9bc6f7c..e4a65be16 100644
--- a/datasets/biofuel_emissions_753_1.json
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index 314862490..768b7b1d7 100644
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index 45cbba47a..2aa1af15d 100644
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diff --git a/datasets/bvoc_flux_759_1.json b/datasets/bvoc_flux_759_1.json
index ff4e5d43e..552b3663c 100644
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diff --git a/datasets/c4_percent_1deg_932_1.json b/datasets/c4_percent_1deg_932_1.json
index eeac41976..13a0df1a0 100644
--- a/datasets/c4_percent_1deg_932_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/canopychem_422_1.json b/datasets/canopychem_422_1.json
index b192a99aa..7418795db 100644
--- a/datasets/canopychem_422_1.json
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index 7cdfce540..53f2c02b8 100644
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diff --git a/datasets/century_vemap_m4_820_1.json b/datasets/century_vemap_m4_820_1.json
index c99ed0cff..e84d11b38 100644
--- a/datasets/century_vemap_m4_820_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/chem_26_1.json b/datasets/chem_26_1.json
index 72ff888fe..e220e7613 100644
--- a/datasets/chem_26_1.json
+++ b/datasets/chem_26_1.json
@@ -42,7 +42,7 @@
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index 65b978dd3..cd41be42b 100644
--- a/datasets/co2_emissions_1deg_1021_1.json
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@@ -42,7 +42,7 @@
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index 5d3738571..8103c14c0 100644
--- a/datasets/combined_ancillary_xdeg_1200_1.json
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@@ -42,7 +42,7 @@
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index acd649b6a..ecf240a20 100644
--- a/datasets/comp_runoff_monthly_xdeg_994_1.json
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index c273dd9db..802c82c18 100644
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diff --git a/datasets/cramer_leemans_637_1.json b/datasets/cramer_leemans_637_1.json
index c5552ea5a..e3b4eabee 100644
--- a/datasets/cramer_leemans_637_1.json
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index 5d82815fd..2234b6f13 100644
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index 9f4d9ce95..67f9d886f 100644
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index a4d3f81d8..6c57c77b3 100644
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diff --git a/datasets/daily_precip_est_793_1.json b/datasets/daily_precip_est_793_1.json
index 46ba890f2..effb0199b 100644
--- a/datasets/daily_precip_est_793_1.json
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diff --git a/datasets/diffuse_irradiance_791_1.json b/datasets/diffuse_irradiance_791_1.json
index b3ae2e37b..fe463142d 100644
--- a/datasets/diffuse_irradiance_791_1.json
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index 52b372e6e..fa40b72c9 100644
--- a/datasets/echidna_1045_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/ecmwf_met_1deg_1222_1.json b/datasets/ecmwf_met_1deg_1222_1.json
index b2c11e317..a545f5351 100644
--- a/datasets/ecmwf_met_1deg_1222_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/ecosystem_roots_1deg_929_1.json b/datasets/ecosystem_roots_1deg_929_1.json
index 48e7f93d0..c9d4719bd 100644
--- a/datasets/ecosystem_roots_1deg_929_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/edc_landcover_xdeg_930_1.json b/datasets/edc_landcover_xdeg_930_1.json
index b4a80939f..92d062e19 100644
--- a/datasets/edc_landcover_xdeg_930_1.json
+++ b/datasets/edc_landcover_xdeg_930_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/edgar_atmos_emissions_1deg_1022_1.json b/datasets/edgar_atmos_emissions_1deg_1022_1.json
index 28c88aa11..721fe7224 100644
--- a/datasets/edgar_atmos_emissions_1deg_1022_1.json
+++ b/datasets/edgar_atmos_emissions_1deg_1022_1.json
@@ -42,7 +42,7 @@
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index cc69cc024..523f251ec 100644
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index f0d83ce7e..f350d4df6 100644
--- a/datasets/erbe_albedo_monthly_xdeg_957_1.json
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@@ -42,7 +42,7 @@
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index 40b8dccfc..b82c316be 100644
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diff --git a/datasets/fasir_biophys_monthly_xdeg_970_1.json b/datasets/fasir_biophys_monthly_xdeg_970_1.json
index 0e3ff2a1e..e34e8460c 100644
--- a/datasets/fasir_biophys_monthly_xdeg_970_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fasir_ndvi_monthly_xdeg_972_1.json b/datasets/fasir_ndvi_monthly_xdeg_972_1.json
index e90bd5f90..4fa6fc968 100644
--- a/datasets/fasir_ndvi_monthly_xdeg_972_1.json
+++ b/datasets/fasir_ndvi_monthly_xdeg_972_1.json
@@ -42,7 +42,7 @@
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index aa585eb53..1d430cc8e 100644
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index 3328c3b9f..012e38906 100644
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index 74ee8653f..e5b6d94e8 100644
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index a289cbc78..9e60cbd0e 100644
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index 2f4ddd4da..f0dedf262 100644
--- a/datasets/ffo_Betts_1987_afd_92_1.json
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diff --git a/datasets/ffo_Betts_1988_ams_90_1.json b/datasets/ffo_Betts_1988_ams_90_1.json
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index e91633916..d5228bb60 100644
--- a/datasets/ffo_Betts_1989_afd_95_1.json
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index 31141ca35..942ea3eef 100644
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diff --git a/datasets/ffo_Betts_1989_gsm_99_1.json b/datasets/ffo_Betts_1989_gsm_99_1.json
index ee72ed4e0..5e3c8d467 100644
--- a/datasets/ffo_Betts_1989_gsm_99_1.json
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index 660a83278..775e18752 100644
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index 95bf40388..55dd76aa8 100644
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index 1985b1206..aa6284bef 100644
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index 889ebba64..e279b93d8 100644
--- a/datasets/fife_atmos_noaa_son_73_1.json
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index 08018a332..e440e20de 100644
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index 1f041a936..359fa0faf 100644
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index 57df649af..a5652e756 100644
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index 4db0673fb..22a32509c 100644
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index 3699d0fd0..7b9d7bb8d 100644
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index b2eb4b7a2..619aa824b 100644
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index aec97ae0d..e44f6195f 100644
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index 3b0deb8a8..c7f24c549 100644
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index f6dd0f5ba..82267f5d0 100644
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index 169c27a60..02d255487 100644
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index 455b38efa..7800ae615 100644
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index c994305cc..8207494f1 100644
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index 169d2cca2..11815cf04 100644
--- a/datasets/fife_hydrology_strm_st_120_1.json
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index fb5d7f501..99e0fd05d 100644
--- a/datasets/fife_optical_ot_brug_62_1.json
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index 0f46f07ff..4724a015e 100644
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index 83a4cb0ac..e7b993cba 100644
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index 9e7177da2..69f1b28a7 100644
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index 31fd57d6f..0b61dc04c 100644
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index 123919dd9..0a1143a93 100644
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index 356593948..0ddbc50d3 100644
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index d7bc0598b..62544f9cb 100644
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index 5aaadc763..379a81892 100644
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index 084ff95c6..445d98273 100644
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index ee7ce836b..abdb9877c 100644
--- a/datasets/fife_soilmstr_peck_sm_109_1.json
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index 030685a0e..eab02f06a 100644
--- a/datasets/fife_soilmstr_sm_grav_110_1.json
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@@ -42,7 +42,7 @@
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index a8e1c9d5a..aba857272 100644
--- a/datasets/fife_soilmstr_sm_neut_111_1.json
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@@ -42,7 +42,7 @@
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index c9bc54dcf..a4edf3b80 100644
--- a/datasets/fife_soilmstr_sm_tran_113_1.json
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diff --git a/datasets/fife_soilmstr_soil_imp_108_1.json b/datasets/fife_soilmstr_soil_imp_108_1.json
index ab4786fdb..5206bdba7 100644
--- a/datasets/fife_soilmstr_soil_imp_108_1.json
+++ b/datasets/fife_soilmstr_soil_imp_108_1.json
@@ -42,7 +42,7 @@
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index d6a522250..119506bbf 100644
--- a/datasets/fife_soilprop_soil_h2o_117_1.json
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index 4b732dd5b..e554400e3 100644
--- a/datasets/fife_soilprop_soil_rel_112_1.json
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index 30054a5f5..87dc83f14 100644
--- a/datasets/fife_soilprop_soildens_104_1.json
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index 4ff2f8109..9feff9e2b 100644
--- a/datasets/fife_soilprop_soilhydc_107_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fife_soilprop_soilsurv_115_1.json b/datasets/fife_soilprop_soilsurv_115_1.json
index 6cffdbaf3..8dbad7529 100644
--- a/datasets/fife_soilprop_soilsurv_115_1.json
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index 1115c8d58..4610e49a1 100644
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index d5dbe4488..6e98efeaf 100644
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index 36746b815..bef19f06d 100644
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index 46f1494a6..871915c56 100644
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index 2ce092344..afc313526 100644
--- a/datasets/fife_sur_flux_30_min_brv_23_1.json
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index d9991ea03..fd6c2ac7c 100644
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index ee9787df5..35a5d69ac 100644
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index 0fca3b03f..7be58956e 100644
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index c7b75d0fd..3a0b282fc 100644
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diff --git a/datasets/fife_sur_flux_30_min_ecv_33_1.json b/datasets/fife_sur_flux_30_min_ecv_33_1.json
index 4a94d7327..bdb784d38 100644
--- a/datasets/fife_sur_flux_30_min_ecv_33_1.json
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@@ -42,7 +42,7 @@
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index 58b175a17..98a8756c8 100644
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index 06e294c67..534280760 100644
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index be3e1c8b9..4285bd96a 100644
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index 522dea6c7..58f91da5a 100644
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index 1b7bf28ac..afa8ed9c5 100644
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index 8eca2c162..b08c1796a 100644
--- a/datasets/fife_sur_met_ncdc_sur_122_1.json
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index 5fff0075c..039bbcda9 100644
--- a/datasets/fife_sur_met_noaa_sur_58_1.json
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index 89a72a462..5c8fbc346 100644
--- a/datasets/fife_sur_met_rain_day_29_1.json
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index 363565b81..041ec333a 100644
--- a/datasets/fife_sur_refl_gem_helo_38_1.json
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index e1b057692..1c4f43cac 100644
--- a/datasets/fife_sur_refl_irt_grnd_72_1.json
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@@ -42,7 +42,7 @@
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index dc37e0411..be96d7238 100644
--- a/datasets/fife_sur_refl_irt_helo_70_1.json
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@@ -42,7 +42,7 @@
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index 1fcef2d95..0060463b6 100644
--- a/datasets/fife_sur_refl_irt_mult_71_1.json
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@@ -42,7 +42,7 @@
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index c76c87c94..c20383413 100644
--- a/datasets/fife_sur_refl_lightwnd_43_1.json
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@@ -42,7 +42,7 @@
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index f3f793366..4a2b4b1f3 100644
--- a/datasets/fife_sur_refl_ltbr_ksu_41_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fife_sur_refl_ltbr_unl_42_1.json b/datasets/fife_sur_refl_ltbr_unl_42_1.json
index 69a94f670..5f157a671 100644
--- a/datasets/fife_sur_refl_ltbr_unl_42_1.json
+++ b/datasets/fife_sur_refl_ltbr_unl_42_1.json
@@ -42,7 +42,7 @@
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index a99cb74c3..80175324e 100644
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index a930588e8..6d6f5b57c 100644
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index 70c630820..60633b680 100644
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index 995319c51..1e106aaad 100644
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diff --git a/datasets/fife_sur_refl_parabola_68_1.json b/datasets/fife_sur_refl_parabola_68_1.json
index cc3bac465..b8d510348 100644
--- a/datasets/fife_sur_refl_parabola_68_1.json
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index 86f73e684..c0f098e7c 100644
--- a/datasets/fife_sur_refl_se5_gsfc_81_1.json
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index 4a564c809..546405445 100644
--- a/datasets/fife_sur_refl_se5_helo_87_1.json
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diff --git a/datasets/fife_sur_refl_se5_leaf_85_1.json b/datasets/fife_sur_refl_se5_leaf_85_1.json
index e1e2bc15a..1696dd2c8 100644
--- a/datasets/fife_sur_refl_se5_leaf_85_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fife_sur_refl_se5_unl_82_1.json b/datasets/fife_sur_refl_se5_unl_82_1.json
index a72a0c88d..f5c856a7e 100644
--- a/datasets/fife_sur_refl_se5_unl_82_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fife_sur_refl_soilrefl_114_1.json b/datasets/fife_sur_refl_soilrefl_114_1.json
index 7de5294b3..4ae3db435 100644
--- a/datasets/fife_sur_refl_soilrefl_114_1.json
+++ b/datasets/fife_sur_refl_soilrefl_114_1.json
@@ -42,7 +42,7 @@
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index 5acab7728..e1c4a16a0 100644
--- a/datasets/fife_sur_refl_unl_long_49_1.json
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index 32decdad8..a4836419b 100644
--- a/datasets/fife_sur_refl_unl_surf_123_1.json
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diff --git a/datasets/fire_emissions_724_1.json b/datasets/fire_emissions_724_1.json
index b9c4b4b3b..1b6742058 100644
--- a/datasets/fire_emissions_724_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fire_emissions_v4_R1_1293_4.1.json b/datasets/fire_emissions_v4_R1_1293_4.1.json
index ecb8fb37f..fc77ce8a9 100644
--- a/datasets/fire_emissions_v4_R1_1293_4.1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fluxnet_point_1029_1.json b/datasets/fluxnet_point_1029_1.json
index af85ef7a2..e012af11e 100644
--- a/datasets/fluxnet_point_1029_1.json
+++ b/datasets/fluxnet_point_1029_1.json
@@ -42,7 +42,7 @@
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index c4a4c8221..34d5421a7 100644
--- a/datasets/forest_carbon_flux_949_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/fuel_load_755_1.json b/datasets/fuel_load_755_1.json
index dd4f86712..6789022be 100644
--- a/datasets/fuel_load_755_1.json
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diff --git a/datasets/gap_filled_marconi_811_1.json b/datasets/gap_filled_marconi_811_1.json
index 339864c32..fb39ee195 100644
--- a/datasets/gap_filled_marconi_811_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/gdp_xdeg_974_1.json b/datasets/gdp_xdeg_974_1.json
index b434313d2..e76eaeb6a 100644
--- a/datasets/gdp_xdeg_974_1.json
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diff --git a/datasets/geocoord_556_1.json b/datasets/geocoord_556_1.json
index 9649e9ecd..c75630107 100644
--- a/datasets/geocoord_556_1.json
+++ b/datasets/geocoord_556_1.json
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index cc5368477..a1c640715 100644
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index a8a6a58d9..c84f5196e 100644
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index 5d859f947..a16c2c8af 100644
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index 95ee6fc25..8d492e5cf 100644
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diff --git a/datasets/giss_wetlands_632_1.json b/datasets/giss_wetlands_632_1.json
index 7f92a7038..eb89c9865 100644
--- a/datasets/giss_wetlands_632_1.json
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index bb31a91de..ed26b65ea 100644
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diff --git a/datasets/globalview_co2_point_1111_1.json b/datasets/globalview_co2_point_1111_1.json
index 345e38e15..3ebb620a5 100644
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index 10c54c1dd..ee10e8678 100644
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index ae4eb4487..a8f0b67c9 100644
--- a/datasets/gpcc_precip_monthly_xdeg_995_1.json
+++ b/datasets/gpcc_precip_monthly_xdeg_995_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/gpcp_precip_monthly_xdeg_1003_1.json b/datasets/gpcp_precip_monthly_xdeg_1003_1.json
index e3d156180..074377a5d 100644
--- a/datasets/gpcp_precip_monthly_xdeg_1003_1.json
+++ b/datasets/gpcp_precip_monthly_xdeg_1003_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/gpcp_precip_pentad_xdeg_1002_1.json b/datasets/gpcp_precip_pentad_xdeg_1002_1.json
index 07493ea3d..886605379 100644
--- a/datasets/gpcp_precip_pentad_xdeg_1002_1.json
+++ b/datasets/gpcp_precip_pentad_xdeg_1002_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/gppdi_npp_gridded_xdeg_1023_1.json b/datasets/gppdi_npp_gridded_xdeg_1023_1.json
index 13f6faf8f..95c97c848 100644
--- a/datasets/gppdi_npp_gridded_xdeg_1023_1.json
+++ b/datasets/gppdi_npp_gridded_xdeg_1023_1.json
@@ -42,7 +42,7 @@
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index d041a20bc..435c3f8b0 100644
--- a/datasets/gppdi_npp_point_1033_1.json
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@@ -42,7 +42,7 @@
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index a7a3ba6d3..1b86d3c01 100644
--- a/datasets/gts_precip_daily_xdeg_1001_1.json
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diff --git a/datasets/handheld_haze_708_1.json b/datasets/handheld_haze_708_1.json
index 7bec23b78..d87e7fa6d 100644
--- a/datasets/handheld_haze_708_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/historic_cropland_xdeg_966_1.json b/datasets/historic_cropland_xdeg_966_1.json
index d48687373..ab981539d 100644
--- a/datasets/historic_cropland_xdeg_966_1.json
+++ b/datasets/historic_cropland_xdeg_966_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/historic_landcover_xdeg_967_1.json b/datasets/historic_landcover_xdeg_967_1.json
index 27d53b50d..0f96a4cb7 100644
--- a/datasets/historic_landcover_xdeg_967_1.json
+++ b/datasets/historic_landcover_xdeg_967_1.json
@@ -42,7 +42,7 @@
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index 9a741ea2b..dfa011efb 100644
--- a/datasets/historical_croplands_675_1.json
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index a7e1db27c..a4834ae47 100644
--- a/datasets/hydro1k_elevation_xdeg_1007_1.json
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index 7f1e2af6c..40a17ad99 100644
--- a/datasets/hydrographic_gghydro_636_1.json
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index 7ec3c852c..e59edfbc2 100644
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diff --git a/datasets/islscp2_soils_1deg_1004_1.json b/datasets/islscp2_soils_1deg_1004_1.json
index f78d7fbac..49120d068 100644
--- a/datasets/islscp2_soils_1deg_1004_1.json
+++ b/datasets/islscp2_soils_1deg_1004_1.json
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index 14c76224e..6e4b52e2e 100644
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index e27819f36..e901bf56a 100644
--- a/datasets/jornada_canopy_brf_668_1.json
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index 55380cea9..dc57034b9 100644
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index 16c5f3ca5..47522159e 100644
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diff --git a/datasets/kalahari_co2_heat_flux_765_1.json b/datasets/kalahari_co2_heat_flux_765_1.json
index 3740183cb..ae3063fc1 100644
--- a/datasets/kalahari_co2_heat_flux_765_1.json
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index 900405e9d..c38183acb 100644
--- a/datasets/kt_par_794_1.json
+++ b/datasets/kt_par_794_1.json
@@ -42,7 +42,7 @@
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index c89967cc4..134ef6200 100644
--- a/datasets/kt_stem_map_775_1.json
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index d541432e9..92d8c2c0e 100644
--- a/datasets/kt_veg_inventory_776_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/kt_woody_veg_777_1.json b/datasets/kt_woody_veg_777_1.json
index c279e4138..82c9eaf9f 100644
--- a/datasets/kt_woody_veg_777_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/lai_45_1.json b/datasets/lai_45_1.json
index d92a6f165..1bccdf4bd 100644
--- a/datasets/lai_45_1.json
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diff --git a/datasets/land_cover_data-1km_627_1.json b/datasets/land_cover_data-1km_627_1.json
index 2265ea2c5..a37a056ce 100644
--- a/datasets/land_cover_data-1km_627_1.json
+++ b/datasets/land_cover_data-1km_627_1.json
@@ -42,7 +42,7 @@
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index 0ada73caa..58dc7cdfa 100644
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index f7c1a963d..8d255229e 100644
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index b826d5aa4..6460bb57d 100644
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index a0da92e0a..7ebf92616 100644
--- a/datasets/lba_tree_cover-1km_686_1.json
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index a36ee220f..a4c06606c 100644
--- a/datasets/leaf_voc_emissions_763_1.json
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diff --git a/datasets/leafchem_421_1.json b/datasets/leafchem_421_1.json
index 7956db8fc..c00eba7a1 100644
--- a/datasets/leafchem_421_1.json
+++ b/datasets/leafchem_421_1.json
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index e26cb4824..c559b5569 100644
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index c02a13246..4df4a580d 100644
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index 826d6eb96..6fe476caf 100644
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index f03eb95f4..aa549d665 100644
--- a/datasets/level_1_annual_co2_895_1.json
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diff --git a/datasets/level_2_seasonal_co2_1198_1.json b/datasets/level_2_seasonal_co2_1198_1.json
index 0616db147..da951483c 100644
--- a/datasets/level_2_seasonal_co2_1198_1.json
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index 40e6ee6a5..acb1748cc 100644
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index b933b9952..95ad4b599 100644
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index cd8e334d0..a1498641d 100644
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index 1e2d80119..1914d9050 100644
--- a/datasets/mapss_modis_aerosol_814_1.json
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index 4c86eb471..c6472e461 100644
--- a/datasets/mapss_modis_watervapor_815_1.json
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index e1e8336fc..fe441805e 100644
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index 216c6f654..8543c1912 100644
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index aceda933e..82bc0586e 100644
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index 4307cd873..539cc76b5 100644
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index 890cc9190..14276bddf 100644
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index 8d798d94a..e702e9cd0 100644
--- a/datasets/modis_MOD04_aerosol_813_1.json
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index 1dac65863..49d8911a1 100644
--- a/datasets/modis_MOD05_watervapor_812_1.json
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index d6bc9a186..ce272bde5 100644
--- a/datasets/modis_albedo_2002_filled_xdeg_960_1.json
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index 781600f58..9c824f97d 100644
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index 34057ef39..91b29df08 100644
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index 7f605fe1e..d5088a814 100644
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index ed91116c9..0cd6cb4f8 100644
--- a/datasets/modis_l3_albedo_840_1.json
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diff --git a/datasets/modis_landcover_xdeg_968_1.json b/datasets/modis_landcover_xdeg_968_1.json
index fb9b04f42..32d575b53 100644
--- a/datasets/modis_landcover_xdeg_968_1.json
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diff --git a/datasets/mongu_daily_rainfall_785_1.json b/datasets/mongu_daily_rainfall_785_1.json
index 5a493ef87..656b29e32 100644
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index 0b89bd92a..137182c86 100644
--- a/datasets/mongu_fpar_trac_784_1.json
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@@ -42,7 +42,7 @@
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index 6b92e1b99..842024e54 100644
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@@ -42,7 +42,7 @@
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index b929cde0c..8d0c407f0 100644
--- a/datasets/mongu_lai-2000_781_1.json
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@@ -42,7 +42,7 @@
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index a19edbe52..f8a0faa39 100644
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@@ -42,7 +42,7 @@
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index 5279247f7..dd9600043 100644
--- a/datasets/mongu_skukuza_soil_prop_789_1.json
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diff --git a/datasets/mongu_tree_rings_788_1.json b/datasets/mongu_tree_rings_788_1.json
index a6214402d..f0ab40fb6 100644
--- a/datasets/mongu_tree_rings_788_1.json
+++ b/datasets/mongu_tree_rings_788_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/mongu_veg_structure_795_1.json b/datasets/mongu_veg_structure_795_1.json
index cb80d6ca2..b4578a2b0 100644
--- a/datasets/mongu_veg_structure_795_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/nbi_veg_maps_787_1.json b/datasets/nbi_veg_maps_787_1.json
index 66c3a40bf..a82b2d631 100644
--- a/datasets/nbi_veg_maps_787_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/ncep_met_1deg_1226_1.json b/datasets/ncep_met_1deg_1226_1.json
index 665d8fd00..494b19d31 100644
--- a/datasets/ncep_met_1deg_1226_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/net_carbon_flux_662_1.json b/datasets/net_carbon_flux_662_1.json
index d996ad456..d074fa77b 100644
--- a/datasets/net_carbon_flux_662_1.json
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@@ -42,7 +42,7 @@
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index 5a9a235b8..ffe9dd616 100644
--- a/datasets/nitrogen_deposition_730_1.json
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index 525cc03b8..c1e78360e 100644
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@@ -42,7 +42,7 @@
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diff --git a/datasets/olson_672_1.json b/datasets/olson_672_1.json
index 681f41672..ae245c88a 100644
--- a/datasets/olson_672_1.json
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index aae07a856..5d877fb06 100644
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diff --git a/datasets/ornl_lai_point_971_1.json b/datasets/ornl_lai_point_971_1.json
index 1c5f5814b..ff9ae4f4c 100644
--- a/datasets/ornl_lai_point_971_1.json
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index b26106769..32b4e3b65 100644
--- a/datasets/potential_veg_xdeg_961_1.json
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@@ -42,7 +42,7 @@
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index b06b74ea8..f5b4588e3 100644
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diff --git a/datasets/pre_post_fire_refl_757_1.json b/datasets/pre_post_fire_refl_757_1.json
index 0855a34fc..3d1e92c87 100644
--- a/datasets/pre_post_fire_refl_757_1.json
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@@ -42,7 +42,7 @@
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index e16ac6150..2464f5b46 100644
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index 936a9a308..4347bee04 100644
--- a/datasets/rivdis_199_1.json
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diff --git a/datasets/river_carbon_flux_xdeg_1028_1.json b/datasets/river_carbon_flux_xdeg_1028_1.json
index 866b3ae16..ec96513e1 100644
--- a/datasets/river_carbon_flux_xdeg_1028_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/river_discharge_cpep_640_1.json b/datasets/river_discharge_cpep_640_1.json
index 78a015ead..2f218682b 100644
--- a/datasets/river_discharge_cpep_640_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/river_routing_stn_xdeg_1005_1.json b/datasets/river_routing_stn_xdeg_1005_1.json
index cb091c61a..1328b87f7 100644
--- a/datasets/river_routing_stn_xdeg_1005_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/rlc_admin_boundaries_699_1.json b/datasets/rlc_admin_boundaries_699_1.json
index 082211bb5..37481c2ce 100644
--- a/datasets/rlc_admin_boundaries_699_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/rlc_fire_images_russia_694_1.json b/datasets/rlc_fire_images_russia_694_1.json
index 6ba469998..6155400e8 100644
--- a/datasets/rlc_fire_images_russia_694_1.json
+++ b/datasets/rlc_fire_images_russia_694_1.json
@@ -42,7 +42,7 @@
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index c0ac78b7f..2743e342b 100644
--- a/datasets/rlc_fire_sumpt_695_1.json
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index 0e0af5a75..5764c3c83 100644
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diff --git a/datasets/rlc_forest_map_1973_692_1.json b/datasets/rlc_forest_map_1973_692_1.json
index d668ee3be..a0f57333f 100644
--- a/datasets/rlc_forest_map_1973_692_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/rlc_forest_map_1990_691_1.json b/datasets/rlc_forest_map_1990_691_1.json
index f1e817d59..13cf8c419 100644
--- a/datasets/rlc_forest_map_1990_691_1.json
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diff --git a/datasets/rlc_forest_map_krasnoyarsk_693_1.json b/datasets/rlc_forest_map_krasnoyarsk_693_1.json
index 05a5c12d4..9324752ee 100644
--- a/datasets/rlc_forest_map_krasnoyarsk_693_1.json
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index 467b1e290..389260797 100644
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index 440b72305..986edb51c 100644
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index 77a24924a..95485cd49 100644
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index 24bd56ded..8a82ef8fd 100644
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index e1bdcd8d8..04305198f 100644
--- a/datasets/root_biomass_658_1.json
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diff --git a/datasets/root_nutrients_659_1.json b/datasets/root_nutrients_659_1.json
index d766fbada..3bb934181 100644
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index 406d0977e..f0965f17c 100644
--- a/datasets/root_profiles_660_1.json
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diff --git a/datasets/root_turnover_661_1.json b/datasets/root_turnover_661_1.json
index 9291d0a2d..2a00e6f31 100644
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diff --git a/datasets/root_water_storage_1deg_1006_1.json b/datasets/root_water_storage_1deg_1006_1.json
index f0c00c5d2..b4e27e60b 100644
--- a/datasets/root_water_storage_1deg_1006_1.json
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index ab1730cab..7ab830536 100644
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index 241ef4833..579acf291 100644
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index 32a23344c..89888362a 100644
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index b4f3eacbd..c72dde43c 100644
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index 531ed5ee1..2a3296ebe 100644
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index 68d750b8a..abcac17df 100644
--- a/datasets/s2k_soil_respiration_gridded_644_1.json
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index 730af3bbb..7df0bd274 100644
--- a/datasets/s2k_soller_wetlands_635_1.json
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diff --git a/datasets/s2k_zinke_soil_638_1.json b/datasets/s2k_zinke_soil_638_1.json
index fe3d7f414..ebbd700dc 100644
--- a/datasets/s2k_zinke_soil_638_1.json
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index 6e18b0ee3..e556e2e3c 100644
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index ba16fa05b..df2a8f410 100644
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index 17216bda1..b64594345 100644
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index 269fd5864..3e012d706 100644
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index cbc7af631..9e67c7c7f 100644
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index 09252d0fd..e751ecbc9 100644
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index ae9a97597..84df8bc0e 100644
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index 06515cb5b..d7342f1bd 100644
--- a/datasets/seawifs_region_625_1.json
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diff --git a/datasets/shadoz_ozonesonde_726_1.json b/datasets/shadoz_ozonesonde_726_1.json
index abc8bad89..758d1d65a 100644
--- a/datasets/shadoz_ozonesonde_726_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/smart_radiometers_727_1.json b/datasets/smart_radiometers_727_1.json
index 55871cdb2..25a6ba372 100644
--- a/datasets/smart_radiometers_727_1.json
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index d6ba98d26..0ab1d3b62 100644
--- a/datasets/snow_cover_xdeg_982_1.json
+++ b/datasets/snow_cover_xdeg_982_1.json
@@ -42,7 +42,7 @@
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index a44ac8f2a..697306af0 100644
--- a/datasets/snowfree_albedo_1deg_956_1.json
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diff --git a/datasets/soil125r_309_1.json b/datasets/soil125r_309_1.json
index 58bad4222..284338046 100644
--- a/datasets/soil125r_309_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/soil_respiration_point_645_1.json b/datasets/soil_respiration_point_645_1.json
index c2b656cea..00838fe13 100644
--- a/datasets/soil_respiration_point_645_1.json
+++ b/datasets/soil_respiration_point_645_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/soilt20r_357_1.json b/datasets/soilt20r_357_1.json
index 6e4e64688..08000ad14 100644
--- a/datasets/soilt20r_357_1.json
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index 4fb7a7c87..6a34fa10d 100644
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index 6eed53d38..22a59f2c5 100644
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index c92c2b298..c250f03f8 100644
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index ab87eafed..698c09b3a 100644
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index 7085aa454..75ed21bc5 100644
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index 2a060e4de..0e1393765 100644
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index 767643ecb..ff7f987dc 100644
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index d5081cdbd..6c3530ee3 100644
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index 113ad5efe..77f06f81e 100644
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index 195e055b3..e0a16697b 100644
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index a8dc74b0c..99c88d5d7 100644
--- a/datasets/srb_clouds_1deg_1073_1.json
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index 3a4e0b7da..624e02440 100644
--- a/datasets/srb_radiation_1deg_1201_1.json
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index 41ec93bec..0ac763de4 100644
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index fbe4b73ad..1b4da0f51 100644
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index c33576077..217ca49fc 100644
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index 8a240e141..77eff0604 100644
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index f3e15160c..d4e1082be 100644
--- a/datasets/te07sapf_334_1.json
+++ b/datasets/te07sapf_334_1.json
@@ -42,7 +42,7 @@
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index 6c2d159d5..3d9b41ad7 100644
--- a/datasets/te08bchm_335_1.json
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@@ -42,7 +42,7 @@
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index b4ef04811..0530a3d97 100644
--- a/datasets/te08bopt_336_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/te09cd_341_1.json b/datasets/te09cd_341_1.json
index 248527ae4..74c48a395 100644
--- a/datasets/te09cd_341_1.json
+++ b/datasets/te09cd_341_1.json
@@ -42,7 +42,7 @@
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index b10b947d2..63dc1783c 100644
--- a/datasets/te09gxda_337_1.json
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diff --git a/datasets/te09npd_343_1.json b/datasets/te09npd_343_1.json
index a9dcd1af7..4f8274cc8 100644
--- a/datasets/te09npd_343_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/te09pnd_342_1.json b/datasets/te09pnd_342_1.json
index 7dcdea118..01bfe271f 100644
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index 304e1085a..679c0655b 100644
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index 25c64826f..91113c414 100644
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index 03b8df48c..36785019c 100644
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index a31a3f692..34e3eb489 100644
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index 714c0223a..b9739da33 100644
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index 3829ffda4..e2e386e38 100644
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index 5bacb99f9..8309769cc 100644
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index c8430ca9e..d9665b14d 100644
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index 11cf53fec..223a785c7 100644
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index 0e5ddd116..e5a5e9dad 100644
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index 76f6d5832..260ad7476 100644
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index c5edcb83b..3606cff76 100644
--- a/datasets/te13biom_355_2.json
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index 76ef901e6..c2562bb02 100644
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diff --git a/datasets/te18geos_532_1.json b/datasets/te18geos_532_1.json
index c8824a16d..538822d59 100644
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diff --git a/datasets/te18ls30_557_1.json b/datasets/te18ls30_557_1.json
index e88e0e9f6..5e26ae677 100644
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diff --git a/datasets/te18ls60_564_1.json b/datasets/te18ls60_564_1.json
index cfce1839a..797126743 100644
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index ae8fc716d..a67e85529 100644
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index 7fc033f68..d06f71884 100644
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index 2b3b90d75..f8f5679fa 100644
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index 87bd97829..2a6a2c330 100644
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index 1173c8a42..5770ef0d2 100644
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diff --git a/datasets/te20sldn_356_1.json b/datasets/te20sldn_356_1.json
index f830b2672..e23cd127d 100644
--- a/datasets/te20sldn_356_1.json
+++ b/datasets/te20sldn_356_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/te20supp_489_1.json b/datasets/te20supp_489_1.json
index f2ad10b7b..350993366 100644
--- a/datasets/te20supp_489_1.json
+++ b/datasets/te20supp_489_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/te21smet_358_1.json b/datasets/te21smet_358_1.json
index 27ee1e244..6799b864c 100644
--- a/datasets/te21smet_358_1.json
+++ b/datasets/te21smet_358_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/te22allm_490_1.json b/datasets/te22allm_490_1.json
index b765f2342..2131cda3e 100644
--- a/datasets/te22allm_490_1.json
+++ b/datasets/te22allm_490_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/te22ring_491_1.json b/datasets/te22ring_491_1.json
index 8a5b17c6f..b1fe85a31 100644
--- a/datasets/te22ring_491_1.json
+++ b/datasets/te22ring_491_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/te23arch_492_1.json b/datasets/te23arch_492_1.json
index 34661de7b..89bfb9cf5 100644
--- a/datasets/te23arch_492_1.json
+++ b/datasets/te23arch_492_1.json
@@ -42,7 +42,7 @@
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index 20b383af0..cec731095 100644
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index 1c6890158..f29414e04 100644
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index d98ab1fd9..11e42ee3b 100644
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index 3eec27000..9156131ad 100644
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index 016bacabd..088f57198 100644
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index fb5e937dd..fd613b5d9 100644
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diff --git a/datasets/te5metd_326_1.json b/datasets/te5metd_326_1.json
index 9227b9968..b94f05b6d 100644
--- a/datasets/te5metd_326_1.json
+++ b/datasets/te5metd_326_1.json
@@ -42,7 +42,7 @@
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index 4a8d42df1..5e3028f2c 100644
--- a/datasets/te5soilr_325_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/te5treer_327_1.json b/datasets/te5treer_327_1.json
index 000ee8dd1..bef8b9b7b 100644
--- a/datasets/te5treer_327_1.json
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@@ -42,7 +42,7 @@
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index 26687f5e1..67705dd7c 100644
--- a/datasets/te6allom_329_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/te6bmflg_330_1.json b/datasets/te6bmflg_330_1.json
index c26e11f25..675dc4383 100644
--- a/datasets/te6bmflg_330_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/te6h2opd_332_1.json b/datasets/te6h2opd_332_1.json
index dcc50a1c3..83a16d825 100644
--- a/datasets/te6h2opd_332_1.json
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@@ -42,7 +42,7 @@
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diff --git a/datasets/te6mltvg_331_1.json b/datasets/te6mltvg_331_1.json
index b07635f7a..5f46f98cd 100644
--- a/datasets/te6mltvg_331_1.json
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index d32312a6f..cb5c43746 100644
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index 9e97a4564..705869689 100644
--- a/datasets/te6satns_328_1.json
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index 199586094..110be538e 100644
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index 581043ad1..91ce26b37 100644
--- a/datasets/te9biopd_340_1.json
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diff --git a/datasets/te9spref_338_1.json b/datasets/te9spref_338_1.json
index edae169b2..37df0ba01 100644
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diff --git a/datasets/tf01soil_511_1.json b/datasets/tf01soil_511_1.json
index 8119609e9..f0416496f 100644
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diff --git a/datasets/tf01tflx_512_1.json b/datasets/tf01tflx_512_1.json
index 5cc927f62..1ba53c5b2 100644
--- a/datasets/tf01tflx_512_1.json
+++ b/datasets/tf01tflx_512_1.json
@@ -42,7 +42,7 @@
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index 72aca9a28..4a0874739 100644
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index 763898713..1852b0850 100644
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index 6c87b6e87..5b11e7f47 100644
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index 83a40e93b..11bf3e86a 100644
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index e4c71d96f..f98118512 100644
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index 61da06bed..bf809831a 100644
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index f57f2aff4..47067c7be 100644
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index f11b7a0ee..9e527f78f 100644
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index 1c0eab7e4..f5230c8ce 100644
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index 8b66bde36..e7b4eb18f 100644
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index 5d86fe79b..ec6034e7b 100644
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index f6b3c2599..bee37a0b2 100644
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index c9c8db6c3..3ff8ab2d7 100644
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index 355525d7a..86b1c84ca 100644
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index c75fe8c43..82839706f 100644
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index a3fcea77f..438833464 100644
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index c43fb8935..e1b122033 100644
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index 4ad0c1be0..217c3bf20 100644
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index e749e021d..8c34ab88f 100644
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index 610f45455..3d9088c18 100644
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index b0dcd73ae..36e98d963 100644
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index 88b0dcfad..5077359e4 100644
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index 4b96d5092..3f8434f6a 100644
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index 11019713c..564ee2544 100644
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index d1de86b29..4f52ed08e 100644
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index 0f06d1069..042ac89e1 100644
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index fa940f5a5..c6a3ba3f0 100644
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diff --git a/datasets/tgb1ccfd_374_1.json b/datasets/tgb1ccfd_374_1.json
index 142dbc87e..4306c01a4 100644
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diff --git a/datasets/tgb1ccsd_377_1.json b/datasets/tgb1ccsd_377_1.json
index 20aa8b4b1..1352805d6 100644
--- a/datasets/tgb1ccsd_377_1.json
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@@ -42,7 +42,7 @@
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index dafd13dc0..86c7a4f9b 100644
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index 719c3f45f..a53894722 100644
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diff --git a/datasets/tgb3plsp_382_1.json b/datasets/tgb3plsp_382_1.json
index 6c2743b16..8aa1f3373 100644
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index 28f138bd7..641c62739 100644
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diff --git a/datasets/tgb4flux_460_1.json b/datasets/tgb4flux_460_1.json
index 13da8ac3c..8c9e99e39 100644
--- a/datasets/tgb4flux_460_1.json
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diff --git a/datasets/tgb7aaho_389_1.json b/datasets/tgb7aaho_389_1.json
index 757783f46..323c40764 100644
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index 79a3ef268..77544cb7b 100644
--- a/datasets/tgb7ddho_390_1.json
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index e58e295e7..1d8d06d26 100644
--- a/datasets/tgb7rwho_391_1.json
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index c219203c1..c70f0dd73 100644
--- a/datasets/tgb8mono_392_1.json
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index e074eb0ee..af6610996 100644
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index eb8f6c462..f5cd3b81f 100644
--- a/datasets/tgb8scds_394_1.json
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index 74b54624a..e8fe2003c 100644
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index ce7794caa..5bea051ac 100644
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index ca59723da..9cbd8cef0 100644
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diff --git a/datasets/tree_cover-1km_641_1.json b/datasets/tree_cover-1km_641_1.json
index af5028acc..5affe8eec 100644
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index a3d12a11b..3adf64293 100644
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index 15c566cf3..595a2e25b 100644
--- a/datasets/umd_landcover_xdeg_969_1.json
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index 94a89926f..6c2c28e9a 100644
--- a/datasets/veg_continuous_fields_xdeg_931_1.json
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diff --git a/datasets/vegsoils_wilhend_642_1.json b/datasets/vegsoils_wilhend_642_1.json
index bf1033bb2..83e408219 100644
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index 2bd726c84..1d8913807 100644
--- a/datasets/vemap-1_VEMAP1_CDROM_566_1.json
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index 9dd6dedd3..fc7e5fd5a 100644
--- a/datasets/vemap-1_VEMAP_Alaska_1344_1.json
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index 32a51db33..e3b2ef63e 100644
--- a/datasets/vemap-1_climate_224_1.json
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index d49ad3443..2bd1a4280 100644
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diff --git a/datasets/vemap-1_results_731_1.json b/datasets/vemap-1_results_731_1.json
index 96ef5b13f..53c392cb2 100644
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diff --git a/datasets/vemap-1_scenario_223_1.json b/datasets/vemap-1_scenario_223_1.json
index cec401bf7..d046c7fcb 100644
--- a/datasets/vemap-1_scenario_223_1.json
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@@ -42,7 +42,7 @@
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index 5819f24bf..619b668db 100644
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index f5d588ba5..db7db1adf 100644
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index c9ebbe5cc..bad6fb1d5 100644
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diff --git a/datasets/wilhend_687_1.json b/datasets/wilhend_687_1.json
index 2ae4a384f..0aed7bba5 100644
--- a/datasets/wilhend_687_1.json
+++ b/datasets/wilhend_687_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/willmott_673_1.json b/datasets/willmott_673_1.json
index 8b8ce7095..51d17b74c 100644
--- a/datasets/willmott_673_1.json
+++ b/datasets/willmott_673_1.json
@@ -42,7 +42,7 @@
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diff --git a/datasets/woody_biomass_657_1.json b/datasets/woody_biomass_657_1.json
index 8ec4c218b..9a137e4c4 100644
--- a/datasets/woody_biomass_657_1.json
+++ b/datasets/woody_biomass_657_1.json
@@ -42,7 +42,7 @@
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diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json
index 41db17482..436d2ac7c 100644
--- a/nasa_cmr_catalog.json
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         "description": "The ABLE 2A and 2B (Atmospheric Boundary Layer Experiments) data consists of  estimates of the rate of exchange of a wide variety of aerosols and gases between the Amazon Basin and its atmospheric boundary layer, and the processes by which these aerosols and gases are moved between the boundary layer and the free troposphere. The data are presented in gzipped ASCII text files in Global Tropospheric Experiment (GTE) format.The ABLE-2 project consisted of two expeditions: the first in the Amazonian dry season (ABLE-2A, July-August 1985); and the second in the wet season (ABLE-2B, April-May 1987). The ABLE-2 core research data were gathered by NASA Electra aircraft flights that stretched from Belem, at the mouth of the Amazon River, west to Tabatinga, on the Brazil-Colombia border, from a base at Manaus in the heart of the forest. See Figure 1. These observations were supplemented by ground based chemical and meteorological measurements in the dry forest, the Amazon floodplain, and the tributary rivers through use of enclosures, an instrumented tower in the jungle, a large tethered balloon, and weather and ozone sondes.This study showed air above the Amazon jungle to be extremely clean during the wet season but air quality deteriorated dramatically during the dry season as the result of biomass burning, performed mostly at the edges of the forest. Biomass burning is also a source of greenhouse gases carbon dioxide and methane, as well as other pollutants (carbon monoxide and oxides of nitrogen). Amazonian ozone deposition rates were found to be 5 to 50 times higher than those previously measured over pine forests and water surfaces. The Amazon River floodplain is a globally significant source of methane, supplying about 12% of the estimated worldwide total from all wetlands sources. Over Amazonia, carbon monoxide is enhanced by factors ranging from 1.2 to 2.7 by comparison with adjacent regions due to isoprene oxidation and biomass burning. Over the rainforest individual convective storms transport 200 megatons of air per hour, of which 3 megatons is water vapor that releases 100,000 megawatts of energy into the atmosphere through condensation into rain.The ABLE was a collaboration of U.S. and Brazilian scientists sponsored by NASA and Instituto Nacional de Pesquisas Espaciais (INPE) and supported by the Global Tropospheric Experiment (GTE) component of the NASA Tropospheric Chemistry Program.",
         "license": "proprietary"
     },
@@ -14503,7 +14503,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3255176825-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of vegetation resilience in the Arctic Boreal Vulnerability Experiment (ABoVE) core domain at annual time steps for 2000-2019 and at 300-m spatial resolution. Vegetation resilience is defined as the recovery rate from deviations, due to climate perturbations or disturbances, to the equilibrium state. It is quantified as the negative temporal lag-1 autocorrelation of Enhanced Vegetation Index (EVI). Using a time series of MODIS EVI, the vegetation resilience was estimated using a Bayesian dynamic linear model. The mapped vegetation resilience was derived from Terra EVI products (MOD13Q1v061) across 175 ABoVE B grid tiles over the ABoVE core domain. The estimated mean resilience, upper boundary, and lower boundary results are provided for each tile in cloud optimized GeoTIFF (COG) format.",
         "license": "proprietary"
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         "description": "This dataset provides gridded estimates of gross primary productivity (GPP), ecosystem respiration (Reco), net ecosystem CO2 exchange (NEE =  Reco - GPP), and methane (CH4) emissions from tundra and boreal wetland soils, across the pan-Arctic and Boreal zone (>49 degrees north) at 1-km spatial resolution. The data were produced through simulations of the Arctic Terrestrial Carbon Flux Model (TCFM-Arctic) and are provided at the daily time step for the years 2003-2015. TCFM-Arctic uses a light-use efficiency approach driven by satellite estimates of FPAR (fraction of absorbed photosynthetically active radiation) to estimate GPP, and autotrophic respiration (Rauto) is estimated as a fraction of GPP. Heterotrophic respiration (Rhetero) is estimated using decomposition rates with environmental constraints applied to three near-surface soil organic carbon (SOC) pools, and Reco is determined as the sum of Ra and Rh. Methane production is estimated using optimal CH4 production rates with environmental constraints applied to the labile carbon pool, and transfer of CH4 from the soil to the atmosphere is modeled through vegetation, soil diffusion, and water ebullition pathways. The model estimates were calibrated and evaluated using >60 tower eddy covariance (EC) sites. Baseline carbon pools were initialized by continuously cycling (spinning-up) the model for 1,000 model years using recent climatology from 1985 to 2002 to reach a dynamic steady-state between estimated net primary productivity (NPP = GPP - Rauto) and near-surface SOC pools. The TCFM-Arctic simulations were extended to the full Arctic-boreal domain at a 1-km spatial resolution using land cover maps representing high latitude vegetation communities. The data are provided in NetCDF and comma-separated values (CSV) formats.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3255116494-ORNL_CLOUD.html",
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         "description": "This dataset provides projections of land use and land cover (LULC) change within the Arctic Boreal Vulnerability Experiment (ABoVE) domain, spanning from 2015 to 2100 with a spatial resolution of 0.25 degrees. It includes LULC change under two Shared Socioeconomic Pathways (SSP126 and SSP585) derived from Global Change Analysis Model (GCAM) at an annual scale. The specific land types include: needleleaf evergreen tree-temperate, needleleaf evergreen tree-boreal, needleleaf deciduous tree-boreal, broadleaf evergreen tree-tropical, broadleaf evergreen tree-temperate, broadleaf deciduous tree-tropical, broadleaf deciduous tree-temperate, broadleaf deciduous tree-boreal, broadleaf evergreen shrub-temperate, broadleaf deciduous shrub-temperate, broadleaf deciduous shrub-boreal, C3 arctic grass, C3 grass, C4 grass, and C3 unmanaged rainfed crop. The data were generated by integrating regional LULC projections from GCAM with high-resolution MODIS land cover data and applying two alternative spatial downscaling models: FLUS and Demeter. Data are provided in NetCDF format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2787699093-ORNL_CLOUD.html",
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         "description": "This dataset contains tables containing Airborne flight metadata from synthetic aperture radar (SAR) surveys from 2012 to 2022 in Alaska and Canada. NASA's Arctic Boreal Vulnerability Experiment (ABoVE) conducted airborne SAR surveys of over 120,000 km2 in Alaska and northwestern Canada during 2017, 2018, 2019, and 2022. Legacy lines acquired between 2012 and 2015 by other projects are included for completeness and to enable longer times series creation. The data files and companion file contain L-band and P-band airborne SAR metadata acquired during the ABoVE airborne campaigns. Included are detailed descriptions of ~80 SAR flight lines and how each fits into the ABoVE experimental design. Extensive maps, tables, and hyperlinks give direct access to every flight plan as well as individual flight lines. This entry is a guide to enable interested readers to fully explore the ABoVE L- and P-band SAR data.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2600317177-ORNL_CLOUD.html",
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         "description": "This dataset provides daily SnowModel simulation outputs on a 3-km grid for the period 1 September 1980 through 31 August 2020, covering the Core ABoVE Domain. The daily outputs include: air temperature (deg C), relative humidity (%), wind speed (m/s), wind direction (deg from True North), total precipitation (rain+snow) (m), rainfall (m), snowfall (m), snow melt (m), snow sublimation (m), runoff (m), surface temperature (deg C), bulk snowpack thermal resistance (K/W), snow depth (m), snow density (kg/m3), and snow-water-equivalent (SWE) depth (m). Model data inputs included land cover and topography, ground-based observations of snow, remote sensing observations of snow from satellites and aircraft, and meteorological forcing data from weather stations and reanalysis data. The SnowModel includes the processing modules MicroMet, Enbal, SnowDunes, SnowAssin, SnowPack, and SnowTran-3D. The data are provided in NetCDF format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2254714725-ORNL_CLOUD.html",
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         "description": "This dataset provides gridded estimates of carbon dioxide (CO2) emissions from soil respiration occurring within permafrost-affected tundra and boreal ecosystems of Alaska and Northwest Canada at a 300 m spatial resolution for the period 2016-08-18 to 2018-09-12. The estimates include monthly average CO2 flux (gCO2 C m-2 d-1), daily average CO2 flux and error estimates by season (Autumn, Winter, Spring, Summer), estimates of annual offset of CO2 uptake (i.e., vegetation GPP), annual budgets of vegetation gross primary productivity (GPP; gCO2 C m-2 yr-1), and the fraction of open (non-vegetated) water within each 300 m grid cell. Belowground sources of respiration (i.e., root and microbial) are included. The gridded soil CO2 estimates were obtained using seasonal Random Forest models, information from remote sensing, and a new compilation of in-situ soil CO2 flux from Soil Respiration Stations and eddy covariance towers. The flux tower data are provided along with daily gap-filled flux observations for each Soil Respiration station forced diffusion (FD) chamber record. The data cover the NASA ABoVE Domain.",
         "license": "proprietary"
     },
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         "description": "AERONET (AErosol RObotic NETwork) is an optical ground-based aerosol monitoring network and data archive system. AERONET measurements of the column-integrated aerosol optical properties in the southern Africa region were made by sun-sky radiometers at several sites in August-September 2000 as a part of the SAFARI 2000 dry season aircraft campaign. AERONET is supported by NASA's Earth Observing System and expanded by federation with many non-NASA institutions. The network hardware consists of identical automatic sun-sky scanning spectral radiometers owned by national agencies and universities. Data from this collaboration provides globally-distributed near-real-time observations of aerosol spectral optical depths, aerosol size distributions, and precipitable water in diverse aerosol regimes.",
         "license": "proprietary"
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         "description": "This dataset provides 30 m gridded estimates of aboveground biomass density (AGBD), forest canopy height, and tree canopy coverage for the New England Region of the U.S., including the state of Maine, Vermont, New Hampshire, Massachusetts, Connecticut, and Rhode Island, for the nominal year 2015. It is based on inputs from 1 m resolution Leaf-off LiDAR data collected from 2010 through 2015, high-resolution leaf-on agricultural imagery, and FIA plot-level measurements. Canopy height and tree cover were derived directly from LiDAR data while AGBD was estimated by statistical models that link remote sensing data and FIA plots at the pixel level. Error in AGBD was calculated at the 90% confidence interval. This approach can directly contribute to the formation of a cohesive forest carbon accounting system at national and even international levels, especially via future integrations with NASA's spaceborne LiDAR missions.",
         "license": "proprietary"
     },
@@ -19573,7 +19573,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345798940-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZm9yZXN0IGFib3ZlZ3JvdW5kIGJpb21hc3MgYW5kIGNhcmJvbiBzZXF1ZXN0cmF0aW9uIHBvdGVudGlhbCBmb3IgbWFyeWxhbmQsIHVzYS5cIixcIk9STkxfQ0xPVURcIixcIkNNU19Gb3Jlc3RfQ2FyYm9uX01hcnlsYW5kXzE2NjBcIixcIjFcIiwyMzg5MDY0OTIzLDhdIiwidW1tIjoiW1wiZm9yZXN0IGFib3ZlZ3JvdW5kIGJpb21hc3MgYW5kIGNhcmJvbiBzZXF1ZXN0cmF0aW9uIHBvdGVudGlhbCBmb3IgbWFyeWxhbmQsIHVzYS5cIixcIk9STkxfQ0xPVURcIixcIkNNU19Gb3Jlc3RfQ2FyYm9uX01hcnlsYW5kXzE2NjBcIixcIjFcIiwyMzg5MDY0OTIzLDhdIn0%3D/AGB_Carbon_Sequestration_RGGI_1922_1",
         "description": "This dataset provides 90 m estimates of forest aboveground biomass (Mg/ha) for nominal 2011 and projections of carbon sequestration potential for 11 states in the Regional Greenhouse Gas Initiative (RGGI) domain. The RGGI is a cooperative, market-based effort among States in the eastern United States. Estimated biomass and sequestration potential were computed using the Ecosystem Demography (ED) model. The ED Model integrates several key data including climate variables from Daymet and MERRA2 products; physical soil and hydraulic properties from Probabilistic Remapping of SSURGO (POLARIS) and CONUS-SOIL; land cover characteristics from airborne lidar, the National Agriculture Imagery Program (NAIP), and the National Land Cover Database (NLCD); and vegetation parameters from the Forest Inventory and Analysis (FIA) Program.",
         "license": "proprietary"
     },
@@ -19599,7 +19599,7 @@
         "bbox": "-127.69, 23.19, -65.73, 50.37",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389890387-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389890387-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZm9yZXN0IGFib3ZlZ3JvdW5kIGJpb21hc3MgYW5kIGNhcmJvbiBzZXF1ZXN0cmF0aW9uIHBvdGVudGlhbCBmb3IgbWFyeWxhbmQsIHVzYS5cIixcIk9STkxfQ0xPVURcIixcIkNNU19Gb3Jlc3RfQ2FyYm9uX01hcnlsYW5kXzE2NjBcIixcIjFcIiwyMzg5MDY0OTIzLDhdIiwidW1tIjoiW1wiZm9yZXN0IGFib3ZlZ3JvdW5kIGJpb21hc3MgYW5kIGNhcmJvbiBzZXF1ZXN0cmF0aW9uIHBvdGVudGlhbCBmb3IgbWFyeWxhbmQsIHVzYS5cIixcIk9STkxfQ0xPVURcIixcIkNNU19Gb3Jlc3RfQ2FyYm9uX01hcnlsYW5kXzE2NjBcIixcIjFcIiwyMzg5MDY0OTIzLDhdIn0%3D/AGB_NEP_Disturbance_US_Forests_1829_2",
         "description": "This dataset, derived from the National Forest Carbon Monitoring System (NFCMS), provides estimates of forest carbon stocks and fluxes in the form of aboveground woody biomass (AGB), total live biomass, total ecosystem carbon, aboveground coarse woody debris (CWD), and net ecosystem productivity (NEP) as a function of the number of years since the most recent disturbance (i.e., stand age) for forests of the conterminous U.S. at a 30 m resolution for the benchmark years 1990, 2000, and 2010. The data were derived from an inventory-constrained version of the Carnegie-Ames-Stanford Approach (CASA) carbon cycle process model that accounts for disturbance processes for each combination of forest type, site productivity, and pre-disturbance biomass. Also provided are the core model data inputs including the year of the most recent disturbance according to the North American Forest Dynamics (NAFD) and the Monitoring Trends in Burn Severity (MTBS) data products; the type of disturbance; biomass estimates from the year 2000 according to the National Biomass and Carbon Dataset (NBCD); forest-type group; a site productivity classification; and the number of years since stand-replacing disturbance. The data are useful for a wide range of applications including monitoring and reporting recent dynamics of forest carbon across the conterminous U.S., assessment of recent trends with attribution to disturbance and regrowth drivers, conservation planning, and assessment of climate change mitigation opportunities within the forest sector.",
         "license": "proprietary"
     },
@@ -21445,7 +21445,7 @@
         "bbox": "-168.5, 58, -141, 71.5",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236222661-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236222661-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiY2Fub3B5IGNoZW1pc3RyeSAob3R0ZXIpXCIsXCJPUk5MX0NMT1VEXCIsXCJjaGVtXzI2XCIsXCIxXCIsMjgwNDc0NzczNiwyXSIsInVtbSI6IltcImNhbm9weSBjaGVtaXN0cnkgKG90dGVyKVwiLFwiT1JOTF9DTE9VRFwiLFwiY2hlbV8yNlwiLFwiMVwiLDI4MDQ3NDc3MzYsMl0ifQ%3D%3D/AKFED_V1_1282_1",
         "description": "This data set provides estimates of annual carbon emissions (kg carbon per square meter) from boreal fires at 450-m resolution for the state of Alaska between 2001 and 2013. To produce these data, daily burned area for 2001 to 2013 was mapped using imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) combined with perimeters from the Alaska Large Fire Database. Carbon consumption was calibrated using available field measurements from black spruce forests in Alaska. Above- and below-ground carbon consumption were modeled based on environmental variables including elevation, day of burning within the fire season, pre-fire tree cover and the differenced normalized burn ratio (dNBR). Modeled uncertainties in carbon consumption are included in the data set. The derived burn area and carbon emissions product, referred to as the Alaskan Fire Emissions Database (AKFED), provides a resource for study of the environmental controls on daily fire dynamics, boreal fire emissions in biogeochemical models, and potential feedbacks from changing fire regimes.",
         "license": "proprietary"
     },
@@ -21497,7 +21497,7 @@
         "bbox": "-169, 50, -120, 74.5",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316034-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316034-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiY2FydmU6IGwxIHNwZWN0cmFsIHJhZGlhbmNlcyBmcm9tIGFpcmJvcm5lIGZ0cywgYWxhc2thLCAyMDEyLTIwMTVcIixcIk9STkxfQ0xPVURcIixcIkNBUlZFX0wxX0ZUU19TcGVjdHJhXzE0MjZcIixcIjFcIiwyMjM2MzE2MzM2LDddIiwidW1tIjoiW1wiY2FydmU6IGwxIHNwZWN0cmFsIHJhZGlhbmNlcyBmcm9tIGFpcmJvcm5lIGZ0cywgYWxhc2thLCAyMDEyLTIwMTVcIixcIk9STkxfQ0xPVURcIixcIkNBUlZFX0wxX0ZUU19TcGVjdHJhXzE0MjZcIixcIjFcIiwyMjM2MzE2MzM2LDddIn0%3D/AK_Regional_CO2_Flux_1389_1",
         "description": "This data set provides estimates of 3-hourly net ecosystem CO2 exchange (NEE) at 0.5-degree resolution over the state of Alaska for 2012-2014. The NEE estimates are the output are from Geostatistical Inverse Modeling of a subset of CARVE aircraft CO2 data, WRF-STILT footprints, and PVPRM-SIF data from flux towers (CRV: located in Fox, AK and BRW: located just outside Barrow, AK). Daily mean NEE is also provided as calculated for all of Alaska and for four sub-regions (0.5-degree resolution) that were defined across Alaska, based on general landcover type: North Slope Tundra, South and West Tundra, Boreal Forests, and Mixed (all other). Also provided are derived annual carbon budgets for (1) all of Alaska with defined contributions from biogenic, fossil fuel, and biomass burning sources and (2) annual biogenic carbon budgets for the four landcover-type regions of Alaska. Provided for completeness are the CARVE aircraft atmospheric measurement data used in estimating NEE.",
         "license": "proprietary"
     },
@@ -21770,7 +21770,7 @@
         "bbox": "-157.27, 71.03, -155.77, 71.39",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2170969517-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170969517-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIiwidW1tIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIn0%3D/ALT_GPR_Barrow_1355_1",
         "description": "This data set provides estimates of Active Layer Thickness (ALT) determined with ground-based measurements, and calculated soil volumetric water content (VWC) at four selected sites around Barrow, Alaska in August 2013. ALT was determined using a ground-penetrating radar (GPR) system and traditional mechanical probing. Calculated uncertainties are also included. GPR measurements were taken along four transects of varying length (approx. 1 to 7 km). Mechanical probing included several high-density surveys (every 1 m within 100-m survey line) along each GPR transect. VWC of the active layer soil was calculated at 3-8 calibration points per site where the probe measurement was exactly co-located with a GPR trace.",
         "license": "proprietary"
     },
@@ -25423,7 +25423,7 @@
         "bbox": "-60, -3, -59, -2",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777403867-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777403867-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wicHJlLWRlbHRhLXg6IGF2aXJpcy1kZXJpdmVkIHRvdGFsIHN1c3BlbmRlZCBzb2xpZHMgbWFwcyBmb3IgbXJkLCBsYSwgdXNhLCAyMDE1LTIwMTZcIixcIk9STkxfQ0xPVURcIixcIlByZURlbHRhWF9MM19BVklSSVNfU2VkaW1lbnRfMTgyMlwiLFwiMVwiLDIwMjUxMjY3NzcsMTBdIiwidW1tIjoiW1wicHJlLWRlbHRhLXg6IGF2aXJpcy1kZXJpdmVkIHRvdGFsIHN1c3BlbmRlZCBzb2xpZHMgbWFwcyBmb3IgbXJkLCBsYSwgdXNhLCAyMDE1LTIwMTZcIixcIk9STkxfQ0xPVURcIixcIlByZURlbHRhWF9MM19BVklSSVNfU2VkaW1lbnRfMTgyMlwiLFwiMVwiLDIwMjUxMjY3NzcsMTBdIn0%3D/ARME_898_1",
         "description": "The Amazonian Region Micrometeorological Experiment (ARME) data contain micrometeorological data (climate, interception of  precipitation, mircometeorology and soil moisture) on the elements of the energy balance and evapotranspiration for the Amazonian forest. ASCII text data files for each of the four data types have been zipped toghether. One of the many scientific findings of this experiment was that tropical forest does not experience water stress due to the lack of precipitation, during periods when evapotranspiration is at the potential rate (Shuttleworth, 1988). ARME data types include climate (meteorological), interception of precipitation, micrometeorology, and soil moisture. These data are described in the Data Description section below. ",
         "license": "proprietary"
     },
@@ -31514,26 +31514,26 @@
     {
         "id": "ATL02_006",
         "title": "ATLAS/ICESat-2 L1B Converted Telemetry Data V006",
-        "catalog": "NSIDC_ECS STAC Catalog",
+        "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2018-10-13",
         "end_date": "",
         "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wiYXF1YXJpdXMgbDMgZ3JpZGRlZCAxLWRlZ3JlZSBkYWlseSBzb2lsIG1vaXN0dXJlIHYwMDVcIixcIk5TSURDX0VDU1wiLFwiQVEzX0RZU01cIixcIjVcIiwxNTI5NDY3NDY3LDk2XSIsInVtbSI6IltcImFxdWFyaXVzIGwzIGdyaWRkZWQgMS1kZWdyZWUgZGFpbHkgc29pbCBtb2lzdHVyZSB2MDA1XCIsXCJOU0lEQ19FQ1NcIixcIkFRM19EWVNNXCIsXCI1XCIsMTUyOTQ2NzQ2Nyw5Nl0ifQ%3D%3D/ATL02_006",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL02_006",
         "description": "This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.",
         "license": "proprietary"
     },
     {
         "id": "ATL02_006",
         "title": "ATLAS/ICESat-2 L1B Converted Telemetry Data V006",
-        "catalog": "NSIDC_CPRD STAC Catalog",
+        "catalog": "NSIDC_ECS STAC Catalog",
         "state_date": "2018-10-13",
         "end_date": "",
         "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL02_006",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wiYXF1YXJpdXMgbDMgZ3JpZGRlZCAxLWRlZ3JlZSBkYWlseSBzb2lsIG1vaXN0dXJlIHYwMDVcIixcIk5TSURDX0VDU1wiLFwiQVEzX0RZU01cIixcIjVcIiwxNTI5NDY3NDY3LDk2XSIsInVtbSI6IltcImFxdWFyaXVzIGwzIGdyaWRkZWQgMS1kZWdyZWUgZGFpbHkgc29pbCBtb2lzdHVyZSB2MDA1XCIsXCJOU0lEQ19FQ1NcIixcIkFRM19EWVNNXCIsXCI1XCIsMTUyOTQ2NzQ2Nyw5Nl0ifQ%3D%3D/ATL02_006",
         "description": "This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.",
         "license": "proprietary"
     },
@@ -31605,26 +31605,26 @@
     {
         "id": "ATL06_006",
         "title": "ATLAS/ICESat-2 L3A Land Ice Height V006",
-        "catalog": "NSIDC_CPRD STAC Catalog",
+        "catalog": "NSIDC_ECS STAC Catalog",
         "state_date": "2018-10-14",
         "end_date": "",
         "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL06_006",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2564427300-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2564427300-NSIDC_ECS.html",
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         "id": "ATL06_006",
         "title": "ATLAS/ICESat-2 L3A Land Ice Height V006",
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+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.html",
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@@ -31644,26 +31644,26 @@
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-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL07_006",
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+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.html",
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+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.html",
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         "id": "ATL11_006",
         "title": "ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006",
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     },
     {
         "id": "ATL12_006",
         "title": "ATLAS/ICESat-2 L3A Ocean Surface Height V006",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL12_006",
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         "license": "proprietary"
     },
@@ -31878,104 +31878,104 @@
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         "title": "ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003",
-        "catalog": "NSIDC_ECS STAC Catalog",
+        "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2018-10-14",
         "end_date": "",
         "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL21_003",
         "description": "ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids.",
         "license": "proprietary"
     },
     {
         "id": "ATL21_003",
         "title": "ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003",
-        "catalog": "NSIDC_CPRD STAC Catalog",
+        "catalog": "NSIDC_ECS STAC Catalog",
         "state_date": "2018-10-14",
         "end_date": "",
         "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL21_003",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.html",
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         "description": "ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids.",
         "license": "proprietary"
     },
     {
         "id": "ATL22_003",
         "title": "ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003",
-        "catalog": "NSIDC_CPRD STAC Catalog",
+        "catalog": "NSIDC_ECS STAC Catalog",
         "state_date": "2018-10-14",
         "end_date": "",
         "bbox": "-180, -88, 180, 88",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL22_003",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wiYXRsYXMvaWNlc2F0LTIgbDNhIGNhbGlicmF0ZWQgYmFja3NjYXR0ZXIgcHJvZmlsZXMgYW5kIGF0bW9zcGhlcmljIGxheWVyIGNoYXJhY3RlcmlzdGljcyB2MDA2XCIsXCJOU0lEQ19FQ1NcIixcIkFUTDA5XCIsXCI2XCIsMjYwNzAxNzExNSw2MF0iLCJ1bW0iOiJbXCJhdGxhcy9pY2VzYXQtMiBsM2EgY2FsaWJyYXRlZCBiYWNrc2NhdHRlciBwcm9maWxlcyBhbmQgYXRtb3NwaGVyaWMgbGF5ZXIgY2hhcmFjdGVyaXN0aWNzIHYwMDZcIixcIk5TSURDX0VDU1wiLFwiQVRMMDlcIixcIjZcIiwyNjA3MDE3MTE1LDYwXSJ9/ATL22_003",
         "description": "ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers.",
         "license": "proprietary"
     },
     {
         "id": "ATL22_003",
         "title": "ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003",
-        "catalog": "NSIDC_ECS STAC Catalog",
+        "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2018-10-14",
         "end_date": "",
         "bbox": "-180, -88, 180, 88",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections/ATL22_003",
         "description": "ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers.",
         "license": "proprietary"
     },
@@ -33574,7 +33574,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2788408061-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788408061-ORNL_CLOUD.html",
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         "description": "Land Surface Temperature (LST) is a key indicator of land surface states, and can provide information on surface-atmosphere heat and mass fluxes, vegetation water stress, and soil moisture. A daily, day and night, LST data set for continental Africa, including Madagascar, was derived from Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC; 4 km resolution) data for the 6-year lifetime of the NOAA-14 satellite (from 1995 to 2000) using a modified version of the Global Inventory Mapping and Monitoring System (GIMMS) (Tucker et al., 1994). The data were projected into Albers Equal Area and aggregated to 8 km spatial resolution. The data were cloud-filtered with CLAVR-1 algorithm (Stowe et al., 1999). The LST values were estimated with a split-window technique (Ulivieri et al., 1994) that takes advantage of differential absorption of the thermal infrared signal in bands 4 and 5. The emissivity of the surface was generated using a land cover classification map (Hansen et al., 2000) combined with the FAO soil map of Africa (FAO-UNESCO, 1977) and additional maps of tree, herbaceous, and bare soil percent cover (DeFries et al., 2000). Collateral products include cloud mask, time-of-scan, latitude and longitude, and land/water mask files.The data are in flat binary files. Each data file contains 1152 columns and 1152 rows, in signed integer format (2 bytes), with 8 km by 8 km spatial resolution. A unique map exists for each day and each night of the 6-year NOAA-14 lifetime. The data are best used to infer broad temporal and spatial trends rather than pixel-by-pixel values. ",
         "license": "proprietary"
     },
@@ -33743,7 +33743,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2765511853-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2765511853-ORNL_CLOUD.html",
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         "description": "This dataset provides surface reflectance measured by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) instrument during flights over research sites in Idaho and California in 2014 and 2015. AVIRIS-NG measures reflected radiance at 5-nanometer (nm) intervals in the visible to shortwave infrared spectral range between 380 and 2510 nm. Measurements are radiometrically and geometrically calibrated and provided at 1-meter spatial resolution. The data include 72 flight lines covering long-term research sites in the Reynolds Creek Experimental Watershed in southwestern Idaho and Hollister in southeastern Idaho. Several flight lines from a site in the Inyo National Forest near Big Pine, California are included.",
         "license": "proprietary"
     },
@@ -34159,7 +34159,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776874873-ORNL_CLOUD.html",
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         "description": "This data set describes rainfall distribution statistics over the African continent, including Madagascar. The rainfall estimates are based on data from the NASA Tropical Rainfall Measuring Mission (TRMM) measured between 1998 and 2012. Rainfall patterns were quantified using a gamma-based function and two Markov chain parameters with the aim to summarize the rainfall pattern to a small number of parameters and processes. These summary statistics are suitable for temporal downscaling.These data provide gridded (0.25 x 0.25-degree) estimates of 14-year mean monthly rainfall total amount (mm), frequency (count), intensity (mm/hr), and duration (hrs) of rainfall, as well as Markov chain and gamma-distribution parameters for use in temporal downscaling. The data are presented as a series of 12 netCDF (*.nc) files. ",
         "license": "proprietary"
     },
@@ -34718,7 +34718,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2170970879-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170970879-ORNL_CLOUD.html",
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         "description": "This dataset provides Stochastic Time-Inverted Lagrangian Transport model outputs for receptors located at the NOAA Barrow Alaska Observatory for 12 selected years (15 August to 15 October) across the 30-year, 1982 to 2011, study timeframe. Meteorological fields from version 3.5.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the \"receptor\" location), to create the adjoint of the transport model in the form of a \"footprint\" field. The footprint, with units of mixing ratio (ppm --- CO2; ppb --- CH4) per (umol m-2 s-1 --- CO2; nmol m-2 s-1 --- CH4), quantifies the influence of upwind surface fluxes on concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume. The simulation results included in this dataset are crucial for understanding changes in Arctic carbon cycling and are part of a retrospective analysis to link changes in atmospheric composition at Arctic receptor sites with shifts in ecosystem structure and function. Each file provides the surface influence-function footprints on a lat/lon/time grid from WRF-STILT simulations for the receptor location.",
         "license": "proprietary"
     },
@@ -34731,7 +34731,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170971482-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIiwidW1tIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIn0%3D/Alaska_L4_WRF_STILT_Particle_1571_1",
         "description": "This dataset provides Stochastic Time-Inverted Lagrangian Transport model outputs for receptors located at the NOAA Barrow Alaska Observatory for 12 selected years (15 August to 15 October) across the 30-year, 1982 to 2011, study timeframe.  Meteorological fields from version 3.5.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the \"receptor\" location), to create the adjoint of the transport model in the form of a \"footprint\" field. The footprint, with units of mixing ratio (ppm --- CO2; ppb --- CH4) per (umol m-2 s-1 --- CO2; nmol m-2 s-1 --- CH4), quantifies the influence of upwind surface fluxes on concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume. The simulation results included in this dataset are crucial for understanding changes in Arctic carbon cycling and are part of a retrospective analysis to link changes in atmospheric composition at Arctic receptor sites with shifts in ecosystem structure and function.",
         "license": "proprietary"
     },
@@ -34770,7 +34770,7 @@
         "bbox": "-147.6, 64.99, -147.6, 64.99",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236240052-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236240052-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiY2Fub3B5IGNoZW1pc3RyeSAob3R0ZXIpXCIsXCJPUk5MX0NMT1VEXCIsXCJjaGVtXzI2XCIsXCIxXCIsMjgwNDc0NzczNiwyXSIsInVtbSI6IltcImNhbm9weSBjaGVtaXN0cnkgKG90dGVyKVwiLFwiT1JOTF9DTE9VRFwiLFwiY2hlbV8yNlwiLFwiMVwiLDI4MDQ3NDc3MzYsMl0ifQ%3D%3D/Alaskan_CH4_CO2_Fluxes_1316_1",
         "description": "This data set provides hourly atmospheric concentrations of methane (CH4), carbon dioxide (CO2), and carbon monoxide (CO) as mole fractions, from January 2012 to December 2014 measured at the CARVE flux tower in Fox, Alaska (17 km north of Fairbanks) as part of NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). High-resolution meteorological fields from the Polar Weather Research and Forecasting (WRF) model coupled with the Stochastic Time-Inverted Lagrangian Transport model (WRF- STILT), along with the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM) were used to determine the influence region of the tower site and investigate the inter-annual and seasonal variability of regional fluxes of CO2 and CH4 in boreal Alaska using the tower observations. Modeled estimates of CH4, CO2, and CO background concentrations are provided. The WRF-STILT model \"footprints\" for the CARVE tower are provided with this data set.",
         "license": "proprietary"
     },
@@ -34783,7 +34783,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236279313-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236279313-ORNL_CLOUD.html",
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         "description": "This data set reports monthly averages of atmospheric CO2 concentration from satellite and airborne observations between 2009 and 2013 and simulated present and future monthly concentrations and land-atmosphere CO2 flux for periods between 1990 and 2200. Atmospheric CO2 concentration measurements were obtained from Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and NOAA Arctic Coast Guard (ACG) flights, the Greenhouse Gases Observing Satellite (GOSAT), and NOAA/ESRL vertical profile measurements at Poker Flat, Alaska (PFA). Present and future monthly CO2 concentrations and fluxes were simulated using the GEOS-Chem global tracer model and the Community Land Model, Version 4.5, for multiple regional flux and permafrost thaw scenarios.",
         "license": "proprietary"
     },
@@ -36590,7 +36590,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2756301678-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756301678-ORNL_CLOUD.html",
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         "description": "This dataset provides in situ measurements of radial tree growth of selected white spruce (Picea glauca) and black spruce (Picea mariana) trees, as well as simultaneous in situ measurements of environmental variables (air temperature, air pressure, relative humidity, soil temperature, volumetric water content, and solar irradiance) at two Arctic treeline sites: one in the Brooks Range of Alaska (AK), USA, and the other near Inuvik, Northwest Territories (NWT), Canada. In AK, 36 trees were monitored from June 7, 2016 to September 13, 2019, and in NWT, 24 trees were monitored from July 5, 2017 to July 25, 2019 with a sampling interval of 5- or 20-minutes for radial tree growth and 5-minutes for all environmental variables. The dendrometer data included in this dataset are only those gathered from 2016-2017. Dendrometer data from 2018-2019 are available from a related dataset. The data were collected to better understand the influence of environmental variables on radial tree growth dynamics. The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
@@ -36603,7 +36603,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2515313617-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515313617-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic3BhdGlvLXRlbXBvcmFsIGNoYXJhY3RlcmlzdGljcyBvZiByYWluZmFsbCBpbiBhZnJpY2EsIDAuMjUgZGVncmVlcywgZnJvbSAxOTk4LTIwMTJcIixcIk9STkxfQ0xPVURcIixcIkFmcmljYW5fUmFpbmZhbGxfUGF0dGVybnNfMTI2M1wiLFwiMVwiLDI3NzY4NzQ4NzMsMl0iLCJ1bW0iOiJbXCJzcGF0aW8tdGVtcG9yYWwgY2hhcmFjdGVyaXN0aWNzIG9mIHJhaW5mYWxsIGluIGFmcmljYSwgMC4yNSBkZWdyZWVzLCBmcm9tIDE5OTgtMjAxMlwiLFwiT1JOTF9DTE9VRFwiLFwiQWZyaWNhbl9SYWluZmFsbF9QYXR0ZXJuc18xMjYzXCIsXCIxXCIsMjc3Njg3NDg3MywyXSJ9/ArcticTreeLine_Spruce_CO2_WV_1948_1",
         "description": "This dataset provides in situ measurements of needle-level gas-exchange and leaf traits from Picea glauca (white spruce) from a field site located in the northern latitudinal forest-tundra ecotone (FTE) near the Dalton Highway in northern Alaska, and from one study site located in Black Rock Forest, New York, USA. Measurements were collected with an open flow portable photosynthesis system (Li6400XT) and custom-built temperature-controlled cuvette. Respiration as a function of leaf temperature was measured continuously as the needle temperature was ramped from approximately 5 to 65 degrees C, at a constant rate of 1 degree C per minute. Additional data include tree diameter at breast height (dbh), leaf area, photosynthetic rate, intercellular C02, conductance to H20, tree height, and data from raw temperature curves. Results are reported on both a leaf area and leaf mass basis. The data are for the period 2018-06-06 to 2018-06-23 and are provided in comma-separated (CSV) format.",
         "license": "proprietary"
     },
@@ -36629,7 +36629,7 @@
         "bbox": "-165.62, 48.22, 161.55, 82.82",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2175348008-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2175348008-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic3BhdGlvLXRlbXBvcmFsIGNoYXJhY3RlcmlzdGljcyBvZiByYWluZmFsbCBpbiBhZnJpY2EsIDAuMjUgZGVncmVlcywgZnJvbSAxOTk4LTIwMTJcIixcIk9STkxfQ0xPVURcIixcIkFmcmljYW5fUmFpbmZhbGxfUGF0dGVybnNfMTI2M1wiLFwiMVwiLDI3NzY4NzQ4NzMsMl0iLCJ1bW0iOiJbXCJzcGF0aW8tdGVtcG9yYWwgY2hhcmFjdGVyaXN0aWNzIG9mIHJhaW5mYWxsIGluIGFmcmljYSwgMC4yNSBkZWdyZWVzLCBmcm9tIDE5OTgtMjAxMlwiLFwiT1JOTF9DTE9VRFwiLFwiQWZyaWNhbl9SYWluZmFsbF9QYXR0ZXJuc18xMjYzXCIsXCIxXCIsMjc3Njg3NDg3MywyXSJ9/Arctic_Boreal_CO2_Flux_1934_1",
         "description": "This Arctic-Boreal CO2 fluxes (ABCflux) dataset contains monthly aggregates of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity (GPP) and ecosystem respiration. Over 70 supporting variables describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. The data contained in this ABCflux dataset form a standardized monthly database of Arctic-Boreal CO2 fluxes (i.e., ABCflux Database) and include 244 sites and 6,309 monthly observations; 136 sites and 2,217 monthly observations represent tundra, and 108 sites and 4,092 observations represent the boreal biome. The data are for the period 1989 to 2020.",
         "license": "proprietary"
     },
@@ -36681,7 +36681,7 @@
         "bbox": "-149.31, 62.7, -141.14, 69.81",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2732592765-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2732592765-ORNL_CLOUD.html",
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         "description": "This dataset provides lab-measured soil properties, including soil water matric potential, soil dielectric properties, soil electrical conductivity, corresponding soil moisture. The dataset also includes the basic soil physical properties such as soil organic matter, bulk density, porosity, fiber content, root biomass, and mineral texture. Soil samples were collected from August 21 to August 27, 2018, from the surface to permafrost table in soil pits at nine sites along the Dalton Highway in northern and central regions of Alaska. Permittivity and soil electrical conductivity measurements were conducted using METER TEROS 12 probes. Soil moisture measurements were made with a TEROS 21 probe. The measurements were conducted in the lab over the span of three years. The purpose of soil collection and lab measurements was to develop an integrated framework that relates the hydrological properties to dielectric properties of permafrost active layer soil in support of the NASA Arctic and Boreal Vulnerability Experiment (ABoVE) Airborne Campaign.",
         "license": "proprietary"
     },
@@ -36694,7 +36694,7 @@
         "bbox": "-180, 55.8, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2170968604-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170968604-ORNL_CLOUD.html",
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         "description": "This data set provides the spatial distributions of vegetation types, geobotanical characteristics, and physiographic features for the circumpolar Arctic tundra biome for the period 1982-2003. Specific attributes include dominant vegetation, bioclimate subzones, floristic subprovinces, landscape types, lake coverage, Arctic treeline, elevation, and substrate chemistry data. Vegetation indices, trends, and biomass estimate products for the circumpolar Arctic through 2010 are also provided.",
         "license": "proprietary"
     },
@@ -36707,7 +36707,7 @@
         "bbox": "-147.05, 68.9, -140.32, 70.71",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2170970821-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170970821-ORNL_CLOUD.html",
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         "description": "This data set provides a landcover map with 16 landcover classes for the northern coastal plain of the the Arctic National Wildlife Refuge (ANWR) on the North Slope of Alaska. The map was derived from Landsat Thematic Mapper (Landsat TM) data, Digital Elevation Models (DEMs), aerial photographs, existing maps, and extensive ground-truthing. The data used to derive the map cover the period 1982 to 1993.",
         "license": "proprietary"
     },
@@ -36746,7 +36746,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389075963-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389075963-ORNL_CLOUD.html",
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         "description": "This dataset provides measurements of atmospheric CO2 concentrations, carbon isotopes d13C and D14C, and fossil fuel CO2 (ffCO2) estimates from nine observation sites in California over three month-long campaigns in separate seasons of 2014-2015. ffCO2 was quantified based on the CO2 concentration and D14C. Simulations of ffCO2 at the sites and times of the observations were conducted with the Vulcan v2.2 fossil fuel emissions estimate for 2002 and the Weather Research and Forecasting - Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) atmospheric model. The observed and simulated ffCO2 were incorporated into Bayesian inverse estimates of ffCO2 to calculate California's ffCO2 emissions during the campaign period.",
         "license": "proprietary"
     },
@@ -38826,7 +38826,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316019-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316019-ORNL_CLOUD.html",
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         "description": "This data set provides measurements of the isotopic composition of black carbon and organic carbon aerosols collected at two locations in interior Alaska during the summer of 2013, as part of NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The delta14C end member of fire aerosol was derived and linked to soil elemental and isotopic composition in Alaskan boreal forests. Soil and aerosol measurements were used to estimate average depth of burn in Alaska during the summer of 2013.",
         "license": "proprietary"
     },
@@ -39489,7 +39489,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2767504386-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2767504386-ORNL_CLOUD.html",
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         "description": "This data set provides Boreal Ecosystem-Atmosphere Study (BOREAS) project information and data collected at selected sites in the boreal forest of Saskatchewan and Manitoba, Canada from 1993 through 1996. The data include surface, airborne, and satellite-based observations. Note that all of the data products on these CDs have been archived as separate BOREAS data sets by the ORNL DAAC and in many cases the published data are later versions. Users should search for BOREAS data among these individual data sets. These data were originally distributed on 12 CD-ROMs, but are now archived as 12 zip files to ensure historical completeness of the BOREAS data record.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2761666619-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761666619-ORNL_CLOUD.html",
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         "description": "Scanning Lidar Imager of Canopies by Echo Recovery (SLICER) data were acquired in support of BOReal Ecosystem-Atmosphere Study (BOREAS) at all of the Tower Flux (TF) sites in the Southern and Northern Study Areas (SSA and NSA, respectively) and along transects between the study areas.  Data were acquired on 5 days between 18 and 30 July 1996. Each coverage of a tower site is typically 40 km in length, with a minimum of 3 and a maximum of 10 lines across each tower oriented in a variety of azimuths. The SLICER data were acquired simultaneously with Advanced Solid-State Array Spectroradiometer (ASAS) hyperspectral, multiview angle images. The SLICER Level 3 products consist of binary files for each flight line with a data record for each laser shot composed of 13 parameters and a 600-byte waveform that is the raw record of the back scatter laser energy reflected from Earth's surface.",
         "license": "proprietary"
     },
@@ -40178,7 +40178,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2515937777-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515937777-ORNL_CLOUD.html",
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         "description": "This dataset contains estimates of biogenic CO2 flux components at 0.05 degree resolution from the Solar-Induced Fluorescence (SIF) for Modeling Urban biogenic Fluxes (SMUrF) model. Estimates were produced for the following regions and periods: eastern and western CONUS (2010-2019), western Europe (2010-2014 and 2017-2018), eastern Asia, eastern China, eastern Australia, South America, and Central Africa (2017-2018). Modeled CO2 flux components include gross primary production (GPP), ecosystem respiration (Reco), and net ecosystem exchange (NEE). Four-day means of GPP are estimated from solar-induced fluorescence (SIF) and biome-specific GPP-SIF relationships. Daily estimates of Reco are included. In addition, GPP and Reco were downscaled to hourly estimates and used to generate hourly NEE. Uncertainties for 4-day GPP and daily Reco estimates are provided. The input data streams included 500 m MODIS-based annual land cover classification, 0.05 degree spatiotemporally contiguous SIF, above-ground biomass (AGB) from GlobBiomass, eddy-covariance (EC) flux measurements, and gridded products of air and soil temperatures.",
         "license": "proprietary"
     },
@@ -40984,7 +40984,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2767484391-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2767484391-ORNL_CLOUD.html",
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         "description": "This data set provides products characterizing immediate and longer-term ecosystem changes from fires in the circumpolar boreal forests of Northern Eurasia and North America. The data include fire intensity (fire radiative power; FRP), increase in spring albedo, decrease in tree cover, normalized burn ratio, normalized difference vegetation index, and land surface temperature, as well as three derived fire metrics: crown scorch, vegetation destruction, and fire-induced tree mortality. Longer-term changes are indicated by mean albedo determined 5-12 years after fires, mean percent decrease in tree cover 5-7 years after fires, and mean annual burned percentage. The data cover the period 2001-2013 and are provided at quarter, half, and one degree resolutions for boreal forests within the 40 to 80 degree North circumpolar region. The data were derived from a variety of sources including MODIS products, climate reanalysis data, and forest inventories. A data file with identified boreal forest area (pixels), as defined by climate and vegetation type, and a file with the defined North American and Eurasian boreal forest study regions are included.",
         "license": "proprietary"
     },
@@ -41114,7 +41114,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777741206-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777741206-ORNL_CLOUD.html",
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         "description": "Surface parameter digital maps of vegetation, soil, and topography were obtained for Rondonia, Brazil, covering the 5x5 degree region bounded by 13-8 degrees S and 65-60 degrees W. Numerical maps of the natural landscape structure were prepared by digitizing existing 1:1,000,000 maps. Satellite data give information about the most recent modifications of the surface due to human activities. This mapping work was the first step of a mesoscale meteorological modeling program (Calvet et al., 1997) in forested and deforested Southwestern Amazonia (Rondonia, Brazil). This work was performed in the framework of a research program (CABARE) supported by the European Union, CEC Environment Program.Data are provided in ArcGIS ArcInfo grid ascii format for the following surface parameters:Elevation of terrain of the Rondonia region (altitude.txt)LANDSAT-derived vegetation classification of the Rondonia region in 1993-1994 (classify.txt)Soil classification of the Rondonia region (soil.txt)Sand and Clay of the Rondonia region (sand.txt and clay.txt)Vegetation classification of the Rondonia region from RADAMBRASIL (Macedo et al., 1979) (vegetation.txt)",
         "license": "proprietary"
     },
@@ -42427,7 +42427,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777405728-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777405728-ORNL_CLOUD.html",
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         "description": "The objective of CAMREX (Carbon in the Amazon River Experiment) project which was conducted from 1982 through 1991, was been to define by mass balances and direct measurements those processes which control the distribution of bioactive elements (C, N, P and O) in the mainstem of the Amazon River in Brazil. The CAMREX dataset represents a time series unique in its length and detail for very large river systems. The central sampling strategy has been to obtain representative flux-weighted water samples for comprehensive chemical analysis and to make rate measurements over 18 different sites within a 2000 km reach of the Brazilian Amazon mainstem, including major intervening tributaries. Samples have now been collected on 13 different cruises (1982-1991) during contrasting hydrographic stages. Data or images are provided for (1) water chemistry, (2) daily river discharge, (3) monthly estimates for 1989 of some model drivers and structure including NPP, Evapotranspiration, Precipitation, Temperature, and AVHRR data, (4) daily precipitation, and (5) air temperature anomalies.The processed, quality controlled and integrated data in the documented Pre-LBA Data sets were originally published as a set of three CD_ROMs (Marengo and Victoria, 1998) but are now archived individually.  ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736709887-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736709887-ORNL_CLOUD.html",
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         "description": "This dataset provides airborne eddy covariance (EC) fluxes of carbon dioxide, methane, sensible heat, and latent heat at high spatial resolution collected during the NASA Carbon Airborne Flux Experiment (CARAFE) airborne 2016 and 2017 campaigns. CARAFE utilized the NASA C-23 Sherpa aircraft with a suite of commercial and custom instrumentation. Deployment occurred across the Mid-Atlantic Region for the period 2016-09-07 through 2016-09-26 and 2017-05-03 through 2017-05-26. The data also include downwelling radiation, water vapor, pressure, temperature, wind, and aircraft navigation data. Airborne EC can quantify surface fluxes at local to regional scales, potentially helping to bridge gaps between top-down and bottom-up flux estimates and offering novel insights into biophysical and biogeochemical processes.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316723-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316723-ORNL_CLOUD.html",
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         "description": "This dataset provides methane flux estimates derived from airborne measurements collected over Alaska and the western Yukon Territory during the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) between 2012 and 2014. The state-scale methane fluxes were calculated using a combination of atmospheric profiles and lagrangian transport modeling. The methane flux estimates were used in a simple linear regression model to estimate the fluxes from the tundra and boreal ecosystems. Methane fluxes were also used with a combination of environmental variables to derive a statistical relationship between domain-wide flux and soil temperature. Soil temperature products from North American Regional Reanalysis and derived parameters from a Boltmann-Arrhenius model were used to model methane flux and related uncertainties within the domain at monthly and daily frequencies.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316336-ORNL_CLOUD.html",
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         "description": "This data set contains Level 1 spectral radiance data collected using the Fourier Transform Spectrometer (FTS) during airborne campaigns over the Alaskan and Canadian Arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316271-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316271-ORNL_CLOUD.html",
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         "description": "This data set provides high-frequency geolocation, time, height, pitch, roll, and heading information for the C-23 Sherpa aircraft during airborne campaigns over the Alaskan and Canadian Arctic as part of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The data were collected in situ using the Digital Air Data System (DADS) onboard the aircraft and are presented at 1-second intervals throughout each flight. Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are useful for matching aircraft position with the scientific data collected by other CARVE airborne instruments.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316359-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316359-ORNL_CLOUD.html",
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         "description": "This data set provides high-frequency wind speed and direction data for the C-23 Sherpa aircraft during airborne campaigns over the Alaskan and Canadian Arctic as part of the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The data were collected in situ using the Aventech AIMMS-30 Airborne Wind Sensor onboard the aircraft and are presented at 1-second intervals throughout each flight. The Winds instrument was available for flights in year 2015 only. The measurements included in this data set are most useful when paired with the scientific data collected by other CARVE airborne instruments.",
         "license": "proprietary"
     },
@@ -42544,7 +42544,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316255-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316255-ORNL_CLOUD.html",
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         "description": "This data set provides ground in situ flux and meteorological science data from fixed instruments at three eddy covariance tower sites located in the Alaskan Arctic tundra. Real and gap-filled observations of carbon dioxide, methane, water vapor, and latent energy flux in addition to standard meteorological and environmental variables are reported at half-hourly intervals between 2011 and 2015 for sites at Atqasuk, Barrow, and Ivotuk, Alaska. The three sites form a 300-km north-south transect on the North Slope of Alaska, each site representing distinct Arctic vegetation communities. These tower measurements create a long-term record of one of the largest, most volatile carbon stocks on the planet. Observations from these towers are being used to determine the seasonal and inter-annual patterns of CO2 and CH4 flux, and their relationship to changes in environmental factors.",
         "license": "proprietary"
     },
@@ -42557,7 +42557,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316372-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316372-ORNL_CLOUD.html",
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         "description": "This data set provides earth referenced radiance counts measured by the Forward Looking Infrared (FLIR) camera aboard the CARVE aircraft between April 2013 and November 2015 for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The FLIR camera records images of the surface temperature while measuring concentrations of atmospheric carbon dioxide, methane, and ozone. Thermal images from the FLIR camera will be used to characterize land surfaces underlain by permafrost during specific phases in the freeze-thaw cycle. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
     },
@@ -42570,7 +42570,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316247-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316247-ORNL_CLOUD.html",
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         "description": "This data set provides atmospheric methane (CH4), carbon dioxide (CO2), and carbon monoxide (CO) dry air mole fractions and water vapor mole fractions (H2O) from continuous in situ measurements at the CARVE flux tower in Fox, Alaska between October 2011 and May 2015 for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Air was drawn from three different heights above the base of the tower (31.7 m, 17.1 m, and 4.9 m) and analyzed using a Picarro cavity ring-down spectrometer (CRDS). Measurements of ambient and sonic temperature, vertical and horizontal velocity, and atmospheric pressure are also included in the data set.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316143-ORNL_CLOUD.html",
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         "description": "This data set provides atmospheric carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) concentrations from airborne campaigns over the Alaskan and Canadian arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The data were collected in situ using a four-species cavity ring-down spectrometer system (CRDS; Picarro Inc.) provided by Harvard University and are presented at 5-second intervals throughout each flight. The Harvard CRDS instrument only collected data in 2012-2014; no Harvard data are available for year 2015. Aircraft latitude, longitude, and altitude are also provided. CARVE flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
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         "description": "This data set provides atmospheric carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), ozone (O3), and water vapor (H2O) concentrations from airborne campaigns over the Alaskan and Canadian arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). These data are merged and gap-filled outputs from two different cavity ring-down spectrometers (CRDS; Picarro Inc.) flown aboard the CARVE aircraft and are presented at 5-second intervals throughout each flight. Aircraft latitude, longitude, and altitude are also provided. Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
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         "description": "This data set provides atmospheric carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and water vapor (H2O) concentrations from airborne campaigns over the Alaskan and Canadian arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The data were collected in situ using a cavity ring-down spectrometer (CRDS; Picarro Inc.) and are presented at 2-second intervals throughout each flight. Aircraft latitude, longitude, and altitude are also provided. Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
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         "description": "This data set provides total vertical column O2, CO2, CH4, CO, and H2O, as well as dry-air columns of CO2, CH4, CO, and H2O from airborne campaigns over the Alaskan and Canadian Arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The data represent the Level 2 Quick Retrieval (L2QR) data product collected using the CARVE Fourier Transform Spectrometer (FTS). Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
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         "description": "This data set provides atmospheric carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), molecular hydrogen (H2), nitrous oxide (N2O), sulfur hexafluoride (SF6), and other trace gas mole fractions (i.e. \"concentrations\") from airborne campaigns over the Alaskan and Canadian Arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The CARVE flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas abundances. The data were derived from laboratory measurements of whole air samples collected by a Programmable Flask Package (PFP) onboard the CARVE aircraft. Air samples were collected at strategic intervals to coincide with the overflight of a ground site of interest, or when interesting geophysical conditions were encountered. While most of these samples were collected near the surface in the planetary boundary layer (PBL), on almost every flight samples were also collected in the free troposphere. A minimum of 12 flask samples were collected per flight. Whole air samples collected in the PFPs were analyzed on automated systems at the NOAA Earth System Research Laboratory (ESRL) Global Monitoring Division in Boulder, CO, which also analyzes samples from the NOAA/ESRL Global Greenhouse Gas Reference Network. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
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         "description": "This data set provides atmospheric carbon dioxide, methane, carbon monoxide, molecular hydrogen, nitrous oxide, sulfur hexafluoride, and other trace gas mole fractions (i.e. \"concentrations\") from a flask sampling system at the CARVE flux tower in Fox, Alaska for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The data were derived from laboratory measurements of whole air samples collected by a Programmable Flask Package (PFP) from the top of the tower at 32 m above ground level during late evening multiple times per month since January 2012. Whole air samples collected in the PFPs were analyzed on automated systems at the NOAA Earth System Research Laboratory (ESRL) Global Monitoring Division in Boulder, CO, which also analyzes samples from the NOAA/ESRL Global Greenhouse Gas Reference Network. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
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@@ -42661,7 +42661,7 @@
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         "description": "This data set provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) Footprint data products for particle receptors located at positions along Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) flight paths (2012 - 2015) and various meteorological stations in Alaska and the Canadian Arctic. Each product consists of multiple NetCDF footprint files packaged as a TAR/GZIP file. These aircraft and station positions were treated as receptors in the WRF-STILT model in order to simulate the land surface influence on observed atmospheric constituents. The measurements included in this data set are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236316466-ORNL_CLOUD.html",
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         "description": "This data set provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) model inputs for particle receptors located at positions along Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) flight paths (2012 - 2015) and various meteorological stations in Alaska and the Canadian Arctic. Each product consists of multiple NetCDF files packaged as a TAR/GZIP file. These data correspond to WRF-STILT model footprint data also generated by the CARVE science team.",
         "license": "proprietary"
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         "description": "This data set provides daily 10 km resolution maps of the Alaskan and Arctic Boreal land surface state as either frozen, melting, or thawed. These data are generated from passive microwave radiometer observations made from 2003 through 2014 by the Advanced Microwave Scanning Radiometer (AMSR-E) and the Special Sensor Microwave Imager (SSM/I). Data products overlap with science data collections carried out during the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE).",
         "license": "proprietary"
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         "description": "This dataset contains photos taken by scientists aboard the CARVE aircraft during airborne campaigns over the Alaskan and Canadian Arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content.",
         "license": "proprietary"
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         "description": "This dataset includes detailed daily flight reports from each of the airborne campaigns over the Alaskan and Canadian Arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). The reports include plots of the flight path, altitude, wind and weather conditions, IR and visible light images, and initial analysis of the atmospheric gas concentrations encountered along the flight. Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content. The CARVE measurements are crucial for understanding changes in Arctic carbon cycling and the potential threats posed by thawing of Arctic permafrost.",
         "license": "proprietary"
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         "description": "This dataset contains videos captured by a camera mounted on the CARVE aircraft during airborne campaigns over the Alaskan and Canadian Arctic for the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE). Flight campaigns took place from 2012 to 2015 between the months of March and November to enable investigation of both seasonal and inter-annual variability in atmospheric gas content.",
         "license": "proprietary"
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         "description": "The Cloud Absorption Radiometer (CAR) is an airborne multi-wavelength scanning radiometer that can perform several functions including determining the single scattering albedo of clouds at selected wavelengths in the visible and near-infrared; measuring the angular distribution of scattered radiation; measuring bidirectional reflectance of various surface types; and acquiring imagery of cloud and Earth surface features.",
         "license": "proprietary"
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         "description": "This data set consists of a single NetCDF file containing simulated three dimensional winds and CO2 concentrations centered on the Tapajos National Forest in Brazil in August 2001. Winds (u, v, and w  components) and CO2 concentrations were generated at 31 vertical levels at 1 km grid increment with the Brazilian version of Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS). The simulation ran from the 1st through the 15th of August 2001, which was concurrent with the Santarem Mesoscale Campaign. The data file is in NetCDF format.Mesoscale circulations and atmospheric CO2 variations were investigated over a heterogeneous landscape of forests, pastures, and large rivers during the Santarem Mesoscale Campaign (SMC) of August 2001 (Silva Dias et al., 2004). The atmospheric CO2 concentration variations were simulated using the Colorado State University Regional Atmospheric Modeling System with four nested grids that included a 1-km finest grid centered on the Tapajos National Forest. Surface CO2 fluxes were prescribed using idealized diurnal cycles over forest and pasture that derived from flux tower observations; while surface water CO2 efflux was prescribed using a value suggested by in situ measurements in the Amazon region (Lu et al., 2005). Simulation ran from 1 August through 15 August 2001, which was concurrent with the SMC. Evaluation against flux tower observations and Belterra meteorological tower measurements showed that the model captured the observed 2-m temperatures and 10-m winds reasonably well. At 57 m the model reproduced the daytime CO2 concentration better than the nighttime concentration but missed the observed early morning CO2 maxima, in part because of the difficulties of simulating stable nocturnal boundary conditions and subgrid-scale intra-canopy processes. The results also suggested that the topography, the differences in roughness length between water and land, the shape juxtaposition of Amazon and Tapajos Rivers, and the resulting horizontal and vertical wind shears all facilitated the generation of local mesoscale circulations. Possible mechanisms producing a low-level convergence (LLC) line near the east bank of the Tapajos River were explored. Under strong trade wind conditions, mechanical forcing is more important than thermal forcing in LLC formation. Persistent clouds near the east side of the Tapajos River may have a significant impact on observed ecosystem carbon flux and should be taken into account if tower fluxes are to be generalized to a larger region. ",
         "license": "proprietary"
     },
@@ -43558,7 +43558,7 @@
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         "description": "This data set contains meteorological data collected around the confluence of the Tapajos River with the Amazon River in the Amazon Basin near Santarem, Brazil, in July and August 2001. Boundary layer and upper air measurements were collected with an acoustic sounder-sodar instrument, pilot balloons with optical theodolites, and radiosondes. Radiosondes also measured pressure, temperature, and relative humidity in addition to wind speed and direction. Measurements were made from five local stations at varying frequencies. There are 41 comma-delimited data files with this data set. Supporting information provided with the data set as companion files include: Weather forecasts: Weather forecasts were used to determine the presence of favorable conditions for the balloon flights during the CIRSAN experiment, as well as to help decide the radiosonde launch frequency. The daily observed and forecast weather descriptions for the study period (Weather_forecasts_Santarem.txt) are included. Satellite images: All the satellite images during the CIRSAN period are provided. This is a compilation of images from various instruments and satellite platforms. (See readme_sat.txt). There are 42 images in .gif format. CPTEC Analysis files: The CIRSAN measurement data were used in the CPTEC Global Analysis modeling activity. Model output results for the Pacific and South American region are provided in GRIB format. (See readme_GPSA.txt) ",
         "license": "proprietary"
     },
@@ -43571,7 +43571,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777837638-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777837638-ORNL_CLOUD.html",
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         "description": "This data set reports carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) collected at several forest and pasture sites and in the free troposphere over Amazonia. There are three comma-delimited ASCII files with this data set.Atmospheric CO2 concentrations and isotope signatures were measured at ten different forest and pasture canopy sites across the states of Amazonas, Para, and Rondonia within the Brazilian Amazon between March 1999 and March 2004. Both daytime and nighttime profile samples were collected.Samples of CO2 in the troposphere were collected during aircraft flights over the Amazon/Tapajos Rivers, FLONA Tapajos, and pasture/agriculture areas during five days in May 2003 (wet season). Samples were analyzed for carbon and oxygen isotopes of atmospheric CO2. Flights ranged from low altitudes to above the diurnal tropospheric boundary layer.Measurements of carbon and oxygen stable isotope ratios of atmospheric carbon dioxide (CO2) are a powerful indicator of large-scale CO2 exchange on land across multiple spatial scales. Stable carbon isotope composition of leaf tissue and CO2 released by respiration (delta r) can be used as an estimate of changes in ecosystem isotopic discrimination that occur in response to seasonal and interannual changes in environmental conditions, and land-use change (forest-pasture conversion). Understanding of carbon dioxide stable isotope composition can play a central role in influencing our understanding of the extent to which terrestrial ecosystems are carbon sinks.",
         "license": "proprietary"
     },
@@ -43584,7 +43584,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780153068-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780153068-ORNL_CLOUD.html",
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         "description": "This data set reports delta 13C/12C results for leaf tissues and atmospheric carbon dioxide (CO2), delta 15N/14N ratios for leaf tissue, and leaf carbon and nitrogen concentrations along a topographical gradient in old-growth forests in the ZF2 Reserve (km 34), Instituto Nacional de Pesquisas da Amazonia (INPA), near Manaus, Amazonas, Brazil. During the dry seasons of 2004 and 2006, leaves were sampled at various heights within the canopy and atmospheric air flask samples were also collected at various heights at three locations along this gradient. Also included are coincident meteorological, atmospheric CO2, and CO2 flux measurements from the plateau KM34 tower. There are 3 comma-delimited data files with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777815972-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777815972-ORNL_CLOUD.html",
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         "description": "This data set reports the measurement of stable carbon, nitrogen, and oxygen isotope ratios in organic material (plant, litter and soil samples) in forest canopy profiles and pasture (grasses and shrubs) as well as corresponding carbon and nitrogen tissue concentrations in a number of different sites across Brazil. The sampling design captured the temporal variation in rainfall over the course of several years. Carbon and nitrogen isotope ratios can act as a proxy for interpreting aspects of the carbon and nitrogen cycles in Amazonian rainforests. Data are in three comma-delimited ASCII files. ",
         "license": "proprietary"
     },
@@ -43610,7 +43610,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777836456-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777836456-ORNL_CLOUD.html",
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         "description": "This data set reports on Leaf Area Index (LAI) and Specific Leaf Area (SLA) measurements collected from forest and pasture sites in or near the Tapajos National Forest (TNF), 80 km south of the city of Santarem, Para, Brazil. The collections were between October 1999 and June 2003 from tower sites accessed via the km 67 forest entrance. There are 2 comma-delimited ASCII data files with this data set, and 1 companion data file which provides site descriptions. ",
         "license": "proprietary"
     },
@@ -43623,7 +43623,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777837446-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777837446-ORNL_CLOUD.html",
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         "description": "This data set reports leaf gas flux and leaf properties from samples collected from trees, liana, pasture saplings, and pasture grass located at eight different sampling locations in the states of Para (south of Santarem) and Amazonas (near Manaus) from November 1999 through December 2003. Data are reported on photosynthesis measurements, CO2 response curves, light response curves, humidity response curves, and stomatal responses to variations of the leaf-to-air water vapor mole fraction deficit. Leaf weight, carbon and nitrogen concentrations as well as stable isotope signatures for 13C and 15N are reported for a subset of the samples. There is one comma-delimited ASCII data file with this data set. ",
         "license": "proprietary"
     },
@@ -43636,7 +43636,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780155872-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780155872-ORNL_CLOUD.html",
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         "description": "Data are reported for leaf water potential of leaves of seven species of trees and lianas from the primary forest at the km 67 Tower Site, Tapajos National Forest, and measurements of five sapling tree species and the grass Brachiaria brizantha from a pasture site located near the km 77 Pasture Tower Site, approximately 10 km from the primary forest site. The research area is situated within the Tapajos National Forest reserve, south of the city of Santarem, Para, Brazil. Measurements were made quarterly between March 2000 and March 2001. There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
@@ -43649,7 +43649,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777836092-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777836092-ORNL_CLOUD.html",
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         "description": "This data set reports the oxygen isotope signatures of water extracted from plant tissue (xylem from the stems and leaf tissue) and of atmospheric water vapor from twelve different sites (including both pasture and forest) throughout the Amazon region of Brazil. Samples were collected approximately every 4 months between 1999 and 2003 with additional samples collected monthly between January and May of 2003. In 2004 the collection of water samples from plant tissue continued at two sites, though water vapor collections were discontinued, and measurements of deuterium signatures were added to the analyses. In addition, water vapor from the troposphere was collected during a series of aircraft flights over the Tapajos National Forest in May of 2003 and analyzed for oxygen isotopes using the same methodology. There is one comma-delimited ASCII data file with this data set.",
         "license": "proprietary"
     },
@@ -43662,7 +43662,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751546-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751546-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhIHJlZ2lvbmFsIG9yZ2FuaWMgc29pbCBjYXJib24gYW5kIG5pdHJvZ2VuIGRhdGEgKHppbmtlIGV0IGFsLilcIixcIk9STkxfQ0xPVURcIixcIlppbmtlX3NvaWxfNjgzXCIsXCIxXCIsMjc3NzMyNjkyNCwyXSIsInVtbSI6IltcImxiYSByZWdpb25hbCBvcmdhbmljIHNvaWwgY2FyYm9uIGFuZCBuaXRyb2dlbiBkYXRhICh6aW5rZSBldCBhbC4pXCIsXCJPUk5MX0NMT1VEXCIsXCJaaW5rZV9zb2lsXzY4M1wiLFwiMVwiLDI3NzczMjY5MjQsMl0ifQ%3D%3D/CD03_Ceilometer_Km67_942_1",
         "description": "A Vaisala CT-25K ceilometer was installed at an old-growth forest site located at the km 67 Eddy Flux Tower site in the Tapajos National Forest, Para, Brazil, off Kilometer 67 of BR-163 south of Santarem in April 2001 and remained operational through December 2003, with reliable data being collected between May 2001 and June 2003.Annual, 2001 to 2003, 30-minute average cloud base and backscatter profile data and measurement statistics (sample count, variance, skewness, and kurtosis) are presented in 15 ASCII comma-delineated files. In addition, the cloud base values (m) and measurement statistics for the three reported cloud base levels have been consolidated in 3 annual comma-separated files.The ceilometer provides 15-second measurements of cloud base (three levels up to 7500 m), echo intensity, and a 30-m resolution backscatter profile. The ceilometer reports vertical visibility during periods when the sky is obscured but a cloud base is not detectable. The ceilometer was operational for a sufficient amount of time to examine wet-to-dry season variations in cloud cover fraction and cloud base height.",
         "license": "proprietary"
     },
@@ -43675,7 +43675,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777753467-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777753467-ORNL_CLOUD.html",
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         "description": "A mesoscale network has been set up in the Santarem region of Para, Brazil. This network consists of eight meteorological stations named Belterra, Km 117 (Fazenda Sr. Davi), Mojui, Jamaraqua, Guarana, Embrapa (Cacoal Grande), Vila Franca and Sudam (Curua Una). Belterra and Km117 stations have been almost continuously collecting data since August, 1998, respectively. Mojui, Jamaraqua, and Guarana have been collecting data since July, 2000. Embrapa, Vila Franca and Sudam stations have been collecting data since 2002. Data are presented in 52 individual comma-separated ASCII files. Each file contains data from one calendar year for one site; both site and year are identified clearly in the data file name and all files follow the same header information and organizational structure. Measurements include air temperature and pressure, wind speed and direction, relative humidity, downward solar radiation, and at some stations soil temperature and moisture.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777833070-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777833070-ORNL_CLOUD.html",
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         "description": "Eddy correlation and micrometeorological measurements began in 2001 and continued through 2005 at the pasture site at km 77 on BR-163 just south of the city of Santarem, Para, Brazil. Measurements included turbulent fluxes (momentum, heat, water vapor, and CO2) using the eddy covariance (EC) approach. Other measurements included the CO2 profile, air temperature, humidity, wind speed profile, downward and upward solar and terrestrial radiation, downward and upward photosynthetically active radiation (PAR), atmospheric pressure, rainfall, soil temperature, soil moisture, and soil heat flux. Data are presented in 5 comma-separated ASCII value (csv) files each corresponding roughly to one calendar year. At the beginning of the measurements, in September 2000, the field was a pasture. In November 2001, the pasture was burned, plowed, and planted in upland (non-irrigated) rice. Land use practices during the study period were recorded and are included in a table in Section 5 of this guide.The EC system was composed of a 3D sonic anemometer (ATI 3D) and an infrared analyzer (LICOR 6262) installed on a 20m tower in the agricultural field. The methodology to calculate the flux is described in detail in Sakai et al. (2004) and a companion file is included that describes in detail the formulae used to calculate the eddy flux variables  (CD03_Pasture_Flux_Calculations.pdf).  ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780896810-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780896810-ORNL_CLOUD.html",
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         "description": "This data set contains measurements of nocturnal meteorological profiles collected from tethered balloon platforms during July 2001, October 2001, and November 2003. Measurements were made near the pasture/agricultural tower site at km 77 on BR-163 just south of the city of Santarem, and the near the Tapajos National Forest, km 83 tower site, Santarem, Para, Brazil.  Measurements collected include air temperature, wind speed and direction, and specific humidity. The 2003 measurements also included CO2 concentrations. Sites were near enough to allow comparison between sounding profiles and tower data. There are three comma-delimited ASCII files with this data set. Profiles were obtained from sunset until the first hours after sunrise. Each sounding provided information on temperature, humidity, horizontal wind magnitude and direction as the balloon went up and down. Typical soundings went up to 300 to 400 m. During most of the night, soundings were performed hourly. The balloon rose at a rate of 0.5 m per second in the first 100 m, and 2 m per second above it. The time between successive samplings was 10 s. Intensive periods of shallow, successive soundings were performed starting at dawn, to catch the early development of the convective boundary layer (CBL). These early morning soundings went up only to the capping inversion.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777825408-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777825408-ORNL_CLOUD.html",
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         "description": "This data set contains the results of a biometric tree survey of a 19.25 ha area adjacent to the eddy flux tower at the km 83 logged forest tower site in Tapajos National Forest, Para, Brazil. The survey was done in March 2000. All measurements reported here were taken before the logging began. Diameters of all trees > 35 cm DBH within the 19.25 ha survey area were recorded and trees with DBH between 10 and 35 cm DBH were recorded along three transects with a total area of 2.3 ha (Miller et al., 2004). These data were used to calculate net ecosystem productivity (NEP) and the role of this forest as a carbon source or sink. Biometric data are reported in one comma-delimited ASCII file.       ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777776805-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777776805-ORNL_CLOUD.html",
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         "description": "Atmospheric carbon dioxide profiles were measured at 12 levels up to 64 m at the km 83 logged tower site in Tapajos National Forest, Santarem, Para, Brazil. Data were collected over 3.5 years between June 2000-March 2004. An infra-red gas analyzer sequentially measured the concentration of CO2 at 12 heights (0.1, 0.35, 0.7, 1.4, 3, 6, 10.7, 20, 35, 40, 50, 64 m above the ground) on the tower every 48 minutes. The data, reported on a 30 minute interval, are provided in one single comma separated file.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777824910-ORNL_CLOUD.html",
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         "description": "A dendrometry study was conducted at the logged forest tower site, km 83 site, Tapajos National Forest, Para, Brazil over a period of 4 years following the implementation of a reduced impact logging management regime. Dendrometer bands were installed to measure diameter growth increments for 234 trees in an 18 ha plot adjacent to the eddy flux tower at the km 83 site. In addition to trees randomly selected for measurements within the plot prior to logging, a set of smaller diameter trees within or adjacent to gaps created during the logging treatment were added to the study in 2002. Selective logging is a major land use in the Amazon Basin. An accurate accounting of the effect of logging on regional carbon balances requires better information on the rates at which the logged forest recovers biomass. There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
@@ -43753,7 +43753,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777827936-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777827936-ORNL_CLOUD.html",
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         "description": "Leaf area index was estimated in an 18 ha plot at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. The plot was adjacent to the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil.  Thirty  litter traps were placed at 25-m intervals along two east-west transects in the 18 ha block. Litter samples were collected biweekly from the traps and returned to the lab where they were sorted, air dried, and weighed. The leaf area of a subsample of air-dried leaves was determined using a computer scanner and image processing software. The subsample was then dried in an oven and the air-dried weights were corrected to oven-dried weight. The area of leaf litter collected during each sampling was calculated using the relationship between weight and area measured for the subsample (Goulden et al., 2004). There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
@@ -43766,7 +43766,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780804841-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780804841-ORNL_CLOUD.html",
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         "description": "This data set contains summary data for monthly leaf area index (LAI) and plant area index (PAI) at the km 83 Tower Site, in the Tapajos National Forest, Para, Brazil. LAI was estimated for hemispherical photographs of leaves collected between 2000 and 2003, using the histogram and gap-fraction analysis methods.There are two data files with this data set: one comma-delimited ASCII data file with this data set which contains the monthly summary LAI and PAI data, and one compressed (*.zip) file that contains hemispherical photo images (.bmp) for 2000-2001. The images include those taken pre-logging and post-logging at the measurement site for the purpose of comparing LAI. In addition, there is a companion file containing a program code developed for LAI analysis provided as an ASCII text file.",
         "license": "proprietary"
     },
@@ -43779,7 +43779,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742597-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742597-ORNL_CLOUD.html",
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         "description": "This data set reports the results of measurements of (1) leaf-level photosynthesis response curves for the effects of temperature, leaf age, warming, irradiation, and circadian rhythm and (2) leaf-level photorespiration rates at 30 and 37 degrees C. Measurements were made between June 2000 and February 2006 at the km 83 Logged Forest Tower site, the km 67 Primary Forest Tower site, and the control site at Seca Floresta, all in the Tapajos National Forest, Para, Brazil. There are 7 comma delimited ASCII data files with this data set.",
         "license": "proprietary"
     },
@@ -43792,7 +43792,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777827322-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777827322-ORNL_CLOUD.html",
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         "description": "Above-ground litter productivity was measured in a 18 ha plot adjacent to the eddy flux tower at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. Thirty litter baskets distributed within the grid were visited bi-weekly (Goulden et al., 2004). Oven dry mass of leaves, wood, reproductive parts and miscellaneous components of the collected litter was determined for each collection. Collections covered a pre-harvest period (Sept 2000 - July 2001) and a post- harvest period (Aug 2001-Mar 2003).  There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777849678-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777849678-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBjZC0wNCBjbzIgYW5kIGhlYXQgZmx1eCwga20gODMgZ2FwIHRvd2VyIHNpdGUsIHRhcGFqb3MgbmF0aW9uYWwgZm9yZXN0XCIsXCJPUk5MX0NMT1VEXCIsXCJDRDA0X1Rvd2VyX0ZsdXhfR2FwXzk3OFwiLFwiMVwiLDI3Njg5MzQxMDIsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIGNkLTA0IGNvMiBhbmQgaGVhdCBmbHV4LCBrbSA4MyBnYXAgdG93ZXIgc2l0ZSwgdGFwYWpvcyBuYXRpb25hbCBmb3Jlc3RcIixcIk9STkxfQ0xPVURcIixcIkNEMDRfVG93ZXJfRmx1eF9HYXBfOTc4XCIsXCIxXCIsMjc2ODkzNDEwMiwyXSJ9/CD04_Logging_Damage_1038_1",
         "description": "This data set contains the results of a survey of logging damage in a 18 ha plot (300 m N-S, 600 m E-W) east (upwind) of the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil. Data collected include type of damage, snap height, and log dimensions, as well as calculated biomass of stems and canopy either damaged or removed in logging. There are two comma-delimited data files with this data set.       ",
         "license": "proprietary"
     },
@@ -43818,7 +43818,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777775195-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777775195-ORNL_CLOUD.html",
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         "description": "Tower flux measurements of carbon dioxide,water vapor, heat, and meteorological variables were obtained at the Tapajos National Forest, km 83 site, Santarem, Para, Brazil. For the period June 29, 2000 through March 11, 2004, 30-minute averaged and calculated quantities of fluxes of momentum, heat, water vapor, and carbon dioxide, storage of carbon dioxide in the air column, are reported. Data are reported in three comma separated files: (1) 30 minute-averages,  (2) the daily (24 hour) averages, and (3) the monthly (calendar) averages.The variables measured on the 67 m tower relate to meteorology, soil moisture, respiration, fluxes of momentum, heat, water vapor, and carbon dioxide, and were used to calculate storage of carbon dioxide, Net Ecosystem Exchange, and Gross Primary Productivity. Most of the variables have not been gap filled. However, CO2 flux and storage have been filled to avoid biases in Net Ecosystem Exchange; a fill index flag is included to indicate which data points were filled. Variables derived from the filled variables (respiration, NEE, GPP) are essentially filled also. Net ecosystem exchange has been filtered for calm nighttime periods.",
         "license": "proprietary"
     },
@@ -43831,7 +43831,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777815106-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777815106-ORNL_CLOUD.html",
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         "description": "This data set reports continuous high-resolution frequency-domain reflectometry measurements of soil moisture to 10 m depth and precipitation data near each of the two towers located at the km 83 tower site (logged forest site) in the Tapajos National Forest in the state of Para, Brazil. Measurements were made during 2002 and 2003. Soil moisture and precipitation data are provided in two comma-delimited ASCII files.The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower) and instrumented for eddy flux and micrometerological measurements and operated 15 months prior to any logging in the area (Goulden et al., 2004; Miller et al., 2004; Rocha et al., 2004). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006).The second tower (the 'gap tower' tower) was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.Soil moisture measurements were made in 10 m deep vertical pits (1 x 1 m2) approximately 20 m from the micrometerological tower sites in undisturbed forest patches. Reflectometers were inserted horizontally into shaft walls at 0.15, 0.30, 0.60, 1, 2, 3, 4, 6, 8, and 10 meters beneath the surface. These data were used to determine how soil moisture varies on diel, seasonal and multi-year timescales and to better understand the quantitative and mechanistic relationships between soil moisture and forest evapotranspiration.",
         "license": "proprietary"
     },
@@ -43844,7 +43844,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777849870-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777849870-ORNL_CLOUD.html",
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         "description": "This data set reports on the flux of carbon dioxide from logged forest soils near the eddy flux tower at the km 83 site, Para, Brazil. The automated soil respiration measurements were collected using 15 chambers, installed August 2001 in primary forest. Data were collected between December 19, 2001 and March 1, 2002. There is one comma-delimited data file with this data set.       ",
         "license": "proprietary"
     },
@@ -43857,7 +43857,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768934102-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768934102-ORNL_CLOUD.html",
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         "description": "This data set reports 30-minute values for above-canopy meteorology and fluxes of momentum, heat, and carbon dioxide, and within-canopy carbon dioxide and water vapor concentrations collected at 12 levels between 10 cm and 64 m at the tower located within a logging gap at km 83 Tower Site in the Tapajos National Forest, Para, Brazil. Data were collected over 1.5 years between June 3, 2002 and January 30, 2004. All of the data are contained in one comma separated file.Two towers are located at the km 83 site. The first tower was installed in an intact forest area at this site in June 2000 (the 'intact' tower). In September 2001, the area adjacent to the tower was selectively logged (Bruno et al., 2006). The second tower (the 'gap tower') was installed and operating in June 2002, 400 m east of the intact tower. The gap tower was installed in the middle of a 50 m x 50 m log landing.       ",
         "license": "proprietary"
     },
@@ -43870,7 +43870,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781603191-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781603191-ORNL_CLOUD.html",
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         "description": "This data set contains estimates of understory fuel loads (forest litter) at six locations near Paragominas in Northeastern Amazonia. Samples were collected from three different forest conditions: primary forest, logged forest, and burned forest. Volumes and weights are provided by size and condition class based on the planar transect method of estimating understory fuel loads (Brown 1971). Means and standard errors are reported from 3 transects in each forest x condition class. There is one comma-delimited data file (.csv) with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781551326-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781551326-ORNL_CLOUD.html",
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         "description": "This data set reports soil moisture expressed as volumetric water content (VWC), daily precipitation, air temperature, relative humidity, and dew point measurements conducted at the Seca Floresta site, km 67, Tapajos National Forest, Brazil. The measurements were part of the Rainfall Exclusion Experiment (REE) established to study the response of a humid Amazonian forest to severe drought.VWC was measured with continuous high-resolution frequency-domain reflectometry to 11-m depth in two 1-ha plots from 1999 to 2007. One plot was subjected to ~75 percent throughfall exclusion during the rainy season (exclusion) and another monitored under normal conditions (control). Daily precipitation was measured in the control plot and in a nearby clearing between 1999 and 2006 using wedge rain gauges. Air temperature, relative humidity, and dew point were measured along the vertical forest profile of the control and dry plots of the site between 2000 and 2003.There are three comma-delimited data files (.csv) with this data set.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781602481-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781602481-ORNL_CLOUD.html",
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         "description": "This data set contains moisture content measurements for fuel sticks located in the forest understory of the rainfall exclusion experimental site, Tapajos National Forest, Para, Brazil. The mean and standard errors are reported for control and treatment plot measurements. The measurements were taken on various dates and times of day between 1998 and 2000 during the dry season.The rainfall exclusion treatment began in late January 2000 and continued through December 2004. About 60% of throughfall (equivalent to approximately half the rainfall) was diverted from a 1-hectare plot (i.e., dry) using plastic panels installed in the understory. The comparable 1-hectare control plot (i.e., wet) was unaltered. The goal of this experiment was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad et al., 2002). There is one comma-separated (.csv) data file with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781600874-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781600874-ORNL_CLOUD.html",
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         "description": "This data set provides spatially extensive and temporally intensive surveys of the river biogeochemistry of the Ji-Parana River Basin in Western Amazonia, Rondonia, Brazil. The concentrations of major nutrient ions, dissolved organic and inorganic carbon, pH, temperature, dissolved oxygen, and conductivity were measured in Ji-Parana River and tributary samples at the defined seasonal or monthly intervals. Dominant landuse/landcover classes, slope, and soil cation exchange capacity are included for each of the extensive sampling locations derived from river basin and sub-basin characteristics.Water samples were collected from 1999 to 2003 along the main stem of the Ji-Parana River as well as from the major tributaries including the Urupa. Shapefiles with the boundaries of the major sub-basins of the study area as well as the location of the sample collection points are included for the intensive and extensive sampling campaigns as well as the Urupa River campaign. There are six comma-separated data files (.csv) and five compressed shapefiles (.zip) with this data set. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781384131-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781384131-ORNL_CLOUD.html",
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         "description": "This data set provides measurements of carbon dioxide flux rates (FCO2), gas transfer velocity (k), and partial pressures (pCO2) at 75 sites on rivers and streams of the Amazon River system in South America for the period beginning July 1, 2004, and ending January 23, 2007. Several fieldwork campaigns occurred between June 2004 and January 2007 in the Amazon River basin, with discharge conditions ranging from low to high flow. The sampled areas span the spectrum of chemical characteristics observed across the entire basin, including, for example, both low and high pH values and suspended sediment loads. There is one comma-delimited data file in this data set. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780934671-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780934671-ORNL_CLOUD.html",
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         "description": "This data set includes measurements of standard geochemical variables, dissolved CO2, dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), fine particulate organic carbon (FPOC), and coarse particulate organic carbon (CPOC) in samples taken from 60 Amazonian river locations across the Amazon Basin from 1991 to 2003 (Mayorga et al., 2005). The 14C and 13C isotopic composition of DIC was measured on samples collected between 1991 and 2003. The 14C composition of organic carbon fractions was measured on samples collected from 1995 through 1996. There are four comma-delimited data files with this data set. Note that site descriptions include a categorization of each site by topography according to the percentage of the drainage area above 1,000 m elevation (Mayorga et al., 2005). Only means of geochemical and carbon-fraction results are provided. Both individual 13C and 14C measurements and mean results are provided. ",
         "license": "proprietary"
     },
@@ -43948,7 +43948,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780118467-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780118467-ORNL_CLOUD.html",
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         "description": "This data set provides high-resolution (~500 m) gridded land and stream drainage direction maps for the Amazon River basin, excluding the Rio Tocantins basin. These maps are the result of a new topography-independent analysis method (Mayorga et al., 2005) using the vector river network from the Digital Chart of the World (DCW, Danko, 1992) to create a high-resolution flow direction map. The data products include (1) a stream network coverage with stream order assigned to each reach; (2) the basin boundaries of the major tributaries to the Amazon mainstem; (3) the mouths; and (4) the source points of these tributaries.There are 7 ESRI ArcGIS shapefiles provided in compressed *.zip format and 4 GeoTiff image files with this data set. ",
         "license": "proprietary"
     },
@@ -43961,7 +43961,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780951173-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780951173-ORNL_CLOUD.html",
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         "description": "This data set provides measured and calculated variables describing the carbon pools in river waters, CO2 respired from the water and total amount of CO2 evaded, dissolved oxygen isotopes (delta 18O-O2), and concentration of bacterial cells in river water. Samples were collected from 10 white-water rivers, two clear-water streams (one each in Amazonas and Acre), and two black-water rivers in Amazonas from July to September 2005, which coincided with a severe drought in the western and southern regions of the Amazon Basin (Zeng et al. 2008). Eight of these sites were resampled during August through September 2006 of the following year (no drought).",
         "license": "proprietary"
     },
@@ -43974,7 +43974,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780118761-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780118761-ORNL_CLOUD.html",
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         "description": "This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight Landsat 7-ETM+ scenes from 1999 acquired from the Tropical Rain Forest Information Center (TRFIC) at Michigan State University. Nine land cover classes covering the Ji-Parana Basin were identified. There is one GeoTiff  file with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784832255-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784832255-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBjZC0wNiBqaS1wYXJhbmEgcml2ZXIgYmFzaW4gbGFuZCB1c2UgYW5kIGxhbmQgY292ZXIgbWFwLCBicmF6aWw6IDE5OTlcIixcIk9STkxfQ0xPVURcIixcIkNEMDZfTFVMQ19NYXBfSmlQYXJhbmFfMTA4N1wiLFwiMVwiLDI3ODAxMTg3NjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIGNkLTA2IGppLXBhcmFuYSByaXZlciBiYXNpbiBsYW5kIHVzZSBhbmQgbGFuZCBjb3ZlciBtYXAsIGJyYXppbDogMTk5OVwiLFwiT1JOTF9DTE9VRFwiLFwiQ0QwNl9MVUxDX01hcF9KaVBhcmFuYV8xMDg3XCIsXCIxXCIsMjc4MDExODc2MSwyXSJ9/CD06_Landuse_Timeseries_JiParana_844_1",
         "description": "This data set contains four land use/land cover maps (1986, 1992, 1996 and 2001) for the Ji-Parana River Basin, derived from the digital classification of 8 Landsat images obtained from The Tropical Rain Forest Information Center (TRFIC). ",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781393394-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781393394-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of monthly carbon dioxide (CO2) flux from the Amazon mainstem rivers, tributary stream networks, and their associated varzeas (floodplains). CO2 flux was calculated using two aggregation approaches: for defined river basins (data file #2) and for defined river reaches (figure 2). Flux was calculated from (1) estimated surface water area by month for the Amazon mainstem rivers, associated varzeas, and tributary stream networks, (2) mean daily partial pressures of CO2 (pCO2) concentrations for the mainstem rivers, and (3) calculated mean pCO2 values for the varzea waters. Mean monthly discharge data for 11 mainstem rivers are also included. There are five comma-delimited data files with this data set. Amazon mainstem is a region covering the Amazon/Solimoes River mainstem from 70 degrees W to 54 degrees W. Data from the Japanese Earth Resources Satellite-1 (JERS-1) L-band synthetic aperture radar were used to estimate the areal coverage and inundation status of rivers and floodplains over 100 m in width and compiled into mosaics for periods of high and low  water.  For each mosaic, the study area was classified into either flooded or non-flooded areas. Data for the seasonal and spatial distributions of pCO2 within each hydrographic region were utilized from over 1,800 samples taken on 13 Carbon in the Amazon River Experiment (CAMREX) expeditions at different water stages throughout a 2,000 km reach of the central Amazon mainstem, tributary, and floodplain waters (Degens et al., 1991, Devol et al., 1995, Richey et al., 1988).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784836951-ORNL_CLOUD.html",
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         "description": "This data set contains physical, hydrologic, political, demographic, and societal maps for the Ji-Parana River Basin, in the state of Rondonia, Brazil. These data were used as base information in subsequent investigations of land use/land cover, biogeochemistry, soils, and water balance processes (Ballester et al., 2003). This data set includes a Digital Elevation Model (DEM), river networks and morphometric characteristics of the region (derived from the DEM), and a number of social and demographic vector sets (roads as of 2001, county borders, population change from 1970-2000, and settlement projects). The DEM is provided in GeoTIFF format. Other files are provided as shapefiles. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780119012-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780119012-ORNL_CLOUD.html",
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         "description": "This data set provides a digital map of soil orders for the Ji-Parana River Basin, in the state of Rondonia, Brazil (Western Amazonia). Soil orders were manually digitized from a 1:500,000 map from EMBRAPA originally published in 1983. Oxisols and Ultisols are the predominant soil types in the basin, encompassing 47% and 24% of the total drainage area, respectively. Entisols cover 14%, Alfisols 13% and Eptisols 2% of the basin (Ballester et al., 2003). One data file is provided in ESRI ArcGIS Shapefile format compressed into a single zip file (*.zip).",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780962370-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780962370-ORNL_CLOUD.html",
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         "description": "This data set provides simulated minimum, average, and maximum monthly rainfall, potential evapotranspiration, water deficit, and water surplus values for the Ji-Parana River basin, Rondonia, Brazil. The Thornthwaite-Mather climatological model integrated into a Geographic Information System (GIS) was used to derive the data by utilizing Advanced Very High Resolution Radar (AVHRR) images for temperatures, rainfall amounts from gauges within and around the basin, soil profiles, and land cover maps as model inputs. The monthly water balance for the Ji-Parana river basin is simulated from February 1995 through December 1996 (Victoria et al., 2007). Data are also provided from the Ji-Parana subbasin stations for total basin rainfall, basin discharge and basin evapotranspiration. This data was used to check the results of the water balance model. There are 2 comma-delimited data files with this data set.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777335210-ORNL_CLOUD.html",
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         "description": "The LBA-Ecology CD-07 team collected and processed GOES-8 imager data over the LBA region to characterize the incoming radiation and precipitation rates at regional scales. This data set contains surface down-welling solar radiation, photosynthetically active radiation (PAR) and infrared radiation, as well as precipitation rates at 8x8-km and half-hourly resolutions. The data cover the time periods: 01Mar99-30Apr99 and 01Sep99-31Oct99. The data missing from the temporal series was filled using interpolation to create a continuous sequence of data for carbon modeling studies.",
         "license": "proprietary"
     },
@@ -44065,7 +44065,7 @@
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         "description": "This data sets contains data on coarse wood density, moisture content, respiration rates and decomposition rate constants in csv format from Manaus Brazil measured from 1/1/1996 through 12/31/1997. The data for respiration reports CO2 flux from coarse litter (trunks and large branches > 10 cm diameter) that was studied in central Amazon forests (Chambers et al. 2001). The respiration study took place during the transition from wet to dry season of 1997 (June-August),and sampling from the decomposition study (Chambers et al. 2000) was carried out during both the dry and wet seasons of 1996-97 (see below). Respiration rates varied over almost two orders of magnitude (1.003-0.014 micro g C g-1 C min-1, n=61), and were significantly correlated with wood density (r2adj = 0.42), and moisture content (r2adj = 0.39). Additional samples taken from a nearby pasture indicated that wood moisture content was the most important factor controlling respiration rates across sites (r2adj = 0.65). Based on average coarse litter wood density and moisture content, the mean long-term carbon loss rate due to respiration was estimated to be 0.13 yr-1 (range of 95% prediction interval (PI) = 0.11-0.15 yr-1).Decomposition rate constants are reported as mass loss fraction per year, for boles of 155 large dead trees (> 10 cm diameter) in central Amazon forests (Chambers et al. 2000). The measurements were carried out over a 2-year period (1996-1997) on permanent plots monitored by the Biological Dynamics of Forest Fragments Project (BDFFP) of the Smithsonian Institution (Lovejoy and Bierregaard 1990; Rankin-De Merona et al. 1992) and the Biomass and Nutrient Experiment (BIONTE) of the National Institute for Amazon Research (Instituto Nacional de Pesquisas da Amazonia-INPA). Mortality data from 21 hectares of permanent inventory plots, monitored for 10-15 years, were used to select dead trees for sampling. A single csv formatted data file includes dates when trees died, their diameter and breast height (DBH, i.e., at 1.3 m) and taxonomic information.Measured rate constants varied by over 1.5 orders of magnitude (0.015-0.67 /yr), averaged 0.19 /yr with predicted error averaging 0.026 /yr. Wood density and bole diameter were significantly and inversely correlated with rate constants. A tree of average biomass was predicted to decompose at 0.17 /yr.Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control respiratory variability. These data, along with estimates of ecosystem leaf, live wood and soil respiration, were used to estimate total carbon balance as described in Chambers et al (2004).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777845734-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777845734-ORNL_CLOUD.html",
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         "description": "This data set contains carbon isotope signatures from soil organic matter collected from the following sites: the forests of the ZF-2 INPA reserve approximately 80 km north of the city of Manaus, Amazon; the Tapajos National Forest approximately 83 km south of the city of Santarem, Para; and the Fazenda Vitoria, a ranch near the city of Paragominas, Para. Samples from the Fazenda Vitoria were from degraded and managed pasture sites as well as mature and secondary forests. In addition,carbon isotope signatures from roots sorted by size class, hand-picked from soil pits in the Flona Tapajos and Fazenda Vitoria, are included, as are carbon isotope signatures from soil gases from samples collected at the Fazenda Vitoria. There are 4 ASCII data files with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2762266449-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2762266449-ORNL_CLOUD.html",
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         "description": "Leaf, live wood (tree stem), and soil respiration were measured along with additional environmental factors over a 1-yr period in a Central Amazon terra firme forest and are provided in this data set as three comma delimited data files. Investigations were carried out at an INPA reserve located along the ZF2 road at km 34 [LBA 34] on two 20 x 2500 m permanent forest inventory plots referred to as the Jacaranda plots (-2.6091 degrees S, -60.2093 degrees W). These long and narrow plots capture ecosystem variation associated with the undulating local topography. Leaf respiration measurements were also made at the tower located at ZF-2 road (km 14 [LBA 14]. Leaf respiration was measured during July and August 2001, woody respiration in August 2000 and June 2001, and soil respiration between July 2000 and June 2001 at 4 to 6-wk intervals.Understanding how tropical forest carbon balance will respond to global change requires knowledge of individual heterotrophic and autotrophic respiratory sources, together with factors that control respiratory variability. These data were used to estimate ecosystem leaf, live wood and soil respiration with detailed information provided in Chambers et al. (2004).",
         "license": "proprietary"
     },
@@ -44104,7 +44104,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781611232-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781611232-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBjZC0wNiBqaS1wYXJhbmEgcml2ZXIgYmFzaW4gbGFuZCB1c2UgYW5kIGxhbmQgY292ZXIgbWFwLCBicmF6aWw6IDE5OTlcIixcIk9STkxfQ0xPVURcIixcIkNEMDZfTFVMQ19NYXBfSmlQYXJhbmFfMTA4N1wiLFwiMVwiLDI3ODAxMTg3NjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIGNkLTA2IGppLXBhcmFuYSByaXZlciBiYXNpbiBsYW5kIHVzZSBhbmQgbGFuZCBjb3ZlciBtYXAsIGJyYXppbDogMTk5OVwiLFwiT1JOTF9DTE9VRFwiLFwiQ0QwNl9MVUxDX01hcF9KaVBhcmFuYV8xMDg3XCIsXCIxXCIsMjc4MDExODc2MSwyXSJ9/CD08_Leaf_Isotopes_Manaus_1245_1",
         "description": "This data set provides measurements for carbon (C), nitrogen (N), leaf area index (LAI), and carbon isotope ratio data (13C and 14C) of leaves sampled at the Manaus ZF2 Jacaranda transect area, Amazonas, Brazil, in 2001. Leaf tips and the petioles from the youngest and oldest leaves from a sampled branch were analyzed for nine different species. There is one  comma-delimited data file (.csv) with this data set.",
         "license": "proprietary"
     },
@@ -44117,7 +44117,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777829923-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777829923-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBjZC0wNiBqaS1wYXJhbmEgcml2ZXIgYmFzaW4gbGFuZCB1c2UgYW5kIGxhbmQgY292ZXIgbWFwLCBicmF6aWw6IDE5OTlcIixcIk9STkxfQ0xPVURcIixcIkNEMDZfTFVMQ19NYXBfSmlQYXJhbmFfMTA4N1wiLFwiMVwiLDI3ODAxMTg3NjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIGNkLTA2IGppLXBhcmFuYSByaXZlciBiYXNpbiBsYW5kIHVzZSBhbmQgbGFuZCBjb3ZlciBtYXAsIGJyYXppbDogMTk5OVwiLFwiT1JOTF9DTE9VRFwiLFwiQ0QwNl9MVUxDX01hcF9KaVBhcmFuYV8xMDg3XCIsXCIxXCIsMjc4MDExODc2MSwyXSJ9/CD08_Radiocarbon_Dates_997_1",
         "description": "This data set reports the ages and growth rates of trees determined by radiocarbon dating (14C) in three Amazonia forests. Tree samples were collected from permanent research plots at ZF2 km 34, Manaus, Amazonas, the Catuaba Experimental Farm, Acre, and the km 83 tower site (logged forest site) in the Tapajos National Forest, Para, between 2001-2003.Samples from 97 individual trees were either tree cores (Manaus and Acre) or a combination of tree cores and slabs cut from stems as part of the logging in the Tapajos National Forest (Para). Radiocarbon dating(14C)was used to determine the age and the mean diameter growth increment of samples from individual trees in various diameter size classes.  These measurements can be used to verify and extend short-term diameter increment measurements done with dendrometers and to constrain models of tree demography.There is one comma-separated ASCII  data file with this data set.",
         "license": "proprietary"
     },
@@ -44130,7 +44130,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777829322-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777829322-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBjZC0wNiBqaS1wYXJhbmEgcml2ZXIgYmFzaW4gbGFuZCB1c2UgYW5kIGxhbmQgY292ZXIgbWFwLCBicmF6aWw6IDE5OTlcIixcIk9STkxfQ0xPVURcIixcIkNEMDZfTFVMQ19NYXBfSmlQYXJhbmFfMTA4N1wiLFwiMVwiLDI3ODAxMTg3NjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIGNkLTA2IGppLXBhcmFuYSByaXZlciBiYXNpbiBsYW5kIHVzZSBhbmQgbGFuZCBjb3ZlciBtYXAsIGJyYXppbDogMTk5OVwiLFwiT1JOTF9DTE9VRFwiLFwiQ0QwNl9MVUxDX01hcF9KaVBhcmFuYV8xMDg3XCIsXCIxXCIsMjc4MDExODc2MSwyXSJ9/CD08_Radiocarbon_Dates_Manaus_996_1",
         "description": "This data set reports the ages and growth rates of trees as determined by radiocarbon dating (14C), selected from a logging operation near the city of Itacoatiara, about 250 km east of Manaus, Brazil in 1997. Samples were collected from forty-four trees from 15 species with a basal diameter greater than 100 cm and prepared for radiocarbon dating by Accelerator Mass Spectrometry (AMS) at Lawrence Livermore National Laboratory. There is one comma-separated ASCII data file with this data set. ",
         "license": "proprietary"
     },
@@ -44143,7 +44143,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781590146-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781590146-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBjZC0wNiBqaS1wYXJhbmEgcml2ZXIgYmFzaW4gbGFuZCB1c2UgYW5kIGxhbmQgY292ZXIgbWFwLCBicmF6aWw6IDE5OTlcIixcIk9STkxfQ0xPVURcIixcIkNEMDZfTFVMQ19NYXBfSmlQYXJhbmFfMTA4N1wiLFwiMVwiLDI3ODAxMTg3NjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIGNkLTA2IGppLXBhcmFuYSByaXZlciBiYXNpbiBsYW5kIHVzZSBhbmQgbGFuZCBjb3ZlciBtYXAsIGJyYXppbDogMTk5OVwiLFwiT1JOTF9DTE9VRFwiLFwiQ0QwNl9MVUxDX01hcF9KaVBhcmFuYV8xMDg3XCIsXCIxXCIsMjc4MDExODc2MSwyXSJ9/CD08_Tree_Growth_Manaus_1194_1",
         "description": "This data set provides diameter at breast height (DBH) measurements made of trees in a dense terra-firme tropical moist forest at the ZF-2 Experimental Station, 90 km north of Manaus, Brazil. DBH was measured over two transects (East to West and North to South) which were established in 1996 by the Jacaranda Project (agreement between the National Institute for Research in the Amazon (INPA) and the Japan International Cooperation Agency, JICA). For each tree, a metal dendrometer band was fixed to the trunk and growth in circumference was measured monthly with digital calipers. The transects measured 20-m x 2500-m, and were stratified by plateau, slope, and baixio (lowland areas near small streams). Topography location, distance along the transect, height at which the band was installed, local tree name, and field notes are also provided in the data files. Measurements were taken between June 1999 and December 2001.",
         "license": "proprietary"
     },
@@ -44156,7 +44156,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777408505-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777408505-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBjZC0wNiBqaS1wYXJhbmEgcml2ZXIgYmFzaW4gbGFuZCB1c2UgYW5kIGxhbmQgY292ZXIgbWFwLCBicmF6aWw6IDE5OTlcIixcIk9STkxfQ0xPVURcIixcIkNEMDZfTFVMQ19NYXBfSmlQYXJhbmFfMTA4N1wiLFwiMVwiLDI3ODAxMTg3NjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIGNkLTA2IGppLXBhcmFuYSByaXZlciBiYXNpbiBsYW5kIHVzZSBhbmQgbGFuZCBjb3ZlciBtYXAsIGJyYXppbDogMTk5OVwiLFwiT1JOTF9DTE9VRFwiLFwiQ0QwNl9MVUxDX01hcF9KaVBhcmFuYV8xMDg3XCIsXCIxXCIsMjc4MDExODc2MSwyXSJ9/CD08_Tree_Inventory_Ducke_910_1",
         "description": "This data set includes in one data file the common names, base diameters, and calculated tree masses for almost 3,000 trees on a 5 hectare plot (20 x 2,500 m) located in the Ducke Reserve near Manaus, Brazil in the central Amazon. Measurements were taken during October-December 1999. All diameter measurements were taken at 1.3 meters in height (DBH), or above the buttresses or other stem anomalies.  Forest structure characteristics such as biomass density, stem density, diameter class distribution, and taxonomic information at the family and perhaps genus level, can be derived from these data.",
         "license": "proprietary"
     },
@@ -44169,7 +44169,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780808395-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780808395-ORNL_CLOUD.html",
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         "description": "This data set reports the results of soil and vegetation surveys at four distinct areas within the Tapajos National Forest (TNF), 50 to 100 km south of Santarem, Para, Brazil, in November 1999. At 13 individual sites across the four areas, all located in primary forest, core soil samples at 10, 30 and 50 cm depths were collected and analyzed for dry mass, bulk density, texture, percentage carbon (C), percentage organic matter, and percentage nitrogen (N). At these 13 sites, vegetation was characterized for 250 m long by 10 m wide transects. Biomass was estimated for all stems over 10 cm DBH from allometric relationships for species, measured height, canopy dimension, and diameter. LAI was measured along the transect at 26 points with a LICOR LAI-2000. Canopy foliage samples were collected with a shotgun at dawn and leaf water potential was determined with a pressure chamber. Samples of foliage, wood, bark, fine roots, and litter were analyzed for %N, % C, delta 13C, and delta 15N. There are five comma-delimited ASCII data files with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777344455-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777344455-ORNL_CLOUD.html",
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         "description": "This data sets contains a single text file which reports biometry measurements of the old-growth upland forest at the Parao Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 1999 through March 2005.To monitor tree woody increment, metal dendrometer bands (Figure 1) were placed on a sub-sample of 1000 trees in December 1999. The data set contains estimates of tree diameter at breast height (cm) based on caliper measurements made approximately every six weeks. The first column of data refers to the tree identification number. For a more detailed description of the biometry study refer to Rice et al. 2004.The data file contains a time series of  DBH (cm) values from July 1999 through March 2005.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777344898-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777344898-ORNL_CLOUD.html",
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         "description": "Eddy fluxes of CO2 and H2O are measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 analyzers and Campbell CSAT3 sonic anemometers.  A third Licor gas analyzer measures (a) the CO2/H2O concentration profile (1 of 8 levels every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2/H2O, using a design pulling air simultaneously through 8 inlets (once every 20 minutes). Comprehensive meteorological data (air temperature, PAR, net radiation, etc) are also included.  Pressure and temperature of the Licor cells are controlled to 500 torr and 48 degrees C.  Eddy licors are automatically zeroed every 2 hours and the profile licor every 20 minutes.  All Licors are automatically calibrated with span gases (at 325, 400, and 475 ppm) every 6 hours.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777838049-ORNL_CLOUD.html",
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         "description": "This data set reports the concentrations of carbon monoxide (CO) and carbon dioxide (CO2), wind direction, wind speed, and air temperature measured at the Maxaranguape Atmospheric Observatory in northeast Brazil, January 4, 2003 - December 27, 2006. The data are 30-minute averages. The concentrations observed at Maxaranguape are representative of upstream atmospheric boundary conditions for the Amazon basin and could be used in conjunction with Santarem data and other data sets to estimate regional budgets for these gasses (Kirchhoff et al., 2003). There is one comma-delimited ASCII text file with this data set. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777345266-ORNL_CLOUD.umm_json",
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         "description": "This data set contains a single comma separated text file of half-hourly average CO mixing ratios measured from 2001/04/18 to 2003/08/29 in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil.CO concentrations were measured in air drawn from above the canopy top of tower (approx. 64 meters) using a TEI 48CTL instrument modified for increased stability and sensitivity. The sensor was frequently zeroed by passing ambient air over a CO oxidation catalyst. The span was checked 4 times daily by sampling calibration gases at 100 and 500 ppb. Time in the file is given in UTC (decimal date) at the start of each half hour interval.Associated meteorological parameters, CO2 concentrations and micrometerological fluxes are available in LBA-ECO CD-10 CO2 and H2O Eddy Flux Data at km 67 Tower Site, Tapajos National Forest.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777345983-ORNL_CLOUD.html",
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         "description": "This data sets reports properties of fallen course woody debris in an old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from April 2001 through July 2001.Standing and Fallen coarse woody debris (CWD), or necromass were measured in a series of ecological plots at the km 67 eddy flux tower site in the Tapajos National Forest (Figure 2). The data set includes different size classes of debris measured in different plot sizes. Size classes were: 2-10cm (in 64 m2 subplots) , 10-30cm (in 1600 m2 subplots), 30cm (in 38400 m2 subplots), standing (in entire 50m by 1000m transects).",
         "license": "proprietary"
     },
@@ -44247,7 +44247,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777347015-ORNL_CLOUD.html",
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         "description": "This data sets reports diameter at breast height (DBH) measurements in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements were made periodically from July 1999 through August 2005.Trees with DBH >35cm were measured for ~2600 trees in four 5ha transects. Trees >10cm were measured in a smaller area (Rice et al., 2004). Measurements were made in 1999, 2001, and 2005. Trees are identified by local common names.  A cross reference to scientific names is provided as a companion file.Coarse woody debris and litter samples and measurements were collected same area. See related data sets.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777348455-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777348455-ORNL_CLOUD.html",
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         "description": "This data set reports eddy flux measurements of CO2 and H2O exchange and associated meteorological measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.Eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers (Figure 1). Eddy-flux measurements were made at a sampling  rate of 8 Hz and averaged over a 1 hour interval.. A comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured.Co-located measurements included a third Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes) and (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes). See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777359356-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777359356-ORNL_CLOUD.html",
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         "description": "This data set contains a single text file which reports vertical profiles of H2O vapor concentrations measured at the Para Western (Santarem) - km 67, Primary Forest Tower Site (Figure 1). This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006.H2O concentrations were measured at 8 levels on the tower (62.2, 50, 39.4, 28.7, 19.6, 10.4, and 0.91 m). Sample air was drawn at 1000 sccm (standard cubic centimeters per minute) through 8 profile inlets in sequence (2 minutes at each level) and then a mixed air sample was simultaneously drawn from all 8 levels to obtain a total column integral (once every 20 minutes) and analyzed with an infrared gas analyzer (IRGA, LI-6262, Licor, Lincoln, NE). Data were averaged over a 1 hour interval. Calibration for H2O used two independent calibrations for the IRGA concentration measurements: (a) the nighttime relationship between ambient temperature measurements and sonic temperature measurements; (b) a chilled mirror dew point hygrometer mounted on the tower. See Appendix A of  Hutyra (2007) for addition details about calibration methods. Co-located measurements included eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. And a comprehensive set of meteorological parameters (air temperature, pressure, PAR, net radiation, precipitation, etc) were also measured. With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777363039-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777363039-ORNL_CLOUD.html",
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         "description": "This data set contains a single text file which reports litter type and mass in the old-growth upland forest at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from July 2000 through June 2005.Litter collection began in July 2000 using 40 circular, mesh screen traps (0.43 m diameter, 0.156 m2) randomly located throughout the 19.75-ha tree-survey area (Rice et al., 2004). Approximately every 14 days, litter was collected, sorted, oven dried at 60 degrees C, and weighed. The litterfall from each trap was sorted into (1) leaves, (2) fruits and flowers, (3) wood , <2 cm diameter, and (4) miscellaneous. Data values reported are the mean and standard error of the 40 mass measurements of each of the litter components and the combined total, that have been converted to the reporting units of Mg/ha/yr.",
         "license": "proprietary"
     },
@@ -44299,7 +44299,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834712-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834712-ORNL_CLOUD.html",
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         "description": "This data set contains a single text file which reports temperature measurements at the Para Western (Santarem) - km 67, Primary Forest Tower Site. This site is in the Tapajos National Forest located in north central Brazil. Measurements extend from January 2002 through January 2006 (Figure 1).Air temperature measurements were collected at 8 levels on the tower (61.9, 49.8, 39.1, 28.4, 18.3, 10.1, 2.8, and 0.6 m). Temperature measurements were made with aspirated thermistors (Met One 076B-4 aspiration with YSI 44032 thermistors) and averaged over a 1 hour interval.Co-located measurements included a Licor gas analyzer that measured (a) the CO2 and H2O concentration profiles at 8 levels in and above the canopy (1 level every 2 minutes), (b) the instantaneous integrated canopy storage of CO2 and H2O, using a design that pulled air simultaneously through all 8 inlets (once every 20 minutes), and (c) eddy fluxes of CO2 and H2O were measured at two levels (58m and 47m) using tower-mounted closed-path Licor 6262 gas analyzers and Campbell CSAT3 sonic anemometers. A comprehensive set of meteorological parameters (air pressure, PAR, net radiation, precipitation, etc) were also measured. See related data sets.With the permission of the author, Hutyra, L.R. 2007. Carbon and water exchange in Amazonian rainforests. Ph.D. Thesis, Department of Earth and Planetary Sciences, Harvard University, Cambridge, Massachusetts., is included as a companion file.",
         "license": "proprietary"
     },
@@ -44312,7 +44312,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780919500-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780919500-ORNL_CLOUD.html",
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         "description": "This data set reports the results of vegetation field surveys that measured tree height and diameter at breast height (DBH) in defined size classes at three study sites -- Santarem, Para; Paragominas, Para; and Alo Brasil, Mato Grosso, Brazil, from 2001-2003.At each site, plots and transects within plots, were defined that represented different types of logging and fire treatments, each including one primary forest plot used as a control. Along each transect all trees with more than 30 cm DBH were measured. Dead standing trees were also measured and classified in three classes of decomposition. A 4 m wide transect was used to measure individuals between 10 and 30 cm DBH. Six small subplots were set along each transect to measure regeneration individuals from 2-10 cm DBH and 0-2 cm DBH. DBH is also provided for stumps found in each of the logged forest plots. There are ten comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -44325,7 +44325,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781416738-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781416738-ORNL_CLOUD.html",
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         "description": "This data set provides mean leaf area index (LAI), dendrometry band measurements, and litterfall mass from samples collected at the km 67 research site, Topajos National Forest, Para, Brazil. Litterfall collections were from January 23, 2004 through December 3, 2004, dendrometer measurements were monthly between December 2003 and December 2004, and LAI measurements were collected from January 26, 2004 through November 3, 2004.All measurements were taken at the km 67 site in the Tapajos National Forest. This site is situated in an area of Amazonian primary tropical forest belonging to the municipality of Belterra, Para, Brazil. The forest is mostly evergreen with a few deciduous species. The canopy is characterized by large emergent trees up to 55-m tall, with a closed canopy at approximately 40-m; there are few indications of recent anthropogenic disturbance other than hunting trails. Measurement plots (50) were established along 4 transects at the site and within each plot, 5 subplots were established. The longest transect (25 m x 500 m) was the location of 20 (25 m x 25 m) plots. The other 3 transects (25 m x 250 m) contain 10 plots per transect. Note that the assignment of plots to transects is not provided.There are four comma-delimited data files (.csv) with this data set.",
         "license": "proprietary"
     },
@@ -44338,7 +44338,7 @@
         "bbox": "-63.33, -9.69, -47.75, -1.67",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781621763-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781621763-ORNL_CLOUD.html",
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         "description": "This data set provides measurements for diameter at breast height (DBH), tree height, distance from tree stems to the furthest canopy element, and a species survey of secondary forests in Para and Rondonia, Brazil, from 2002-2003. The forest areas were defined as Type A and Type B stands. Measurements were made in the overstory, understory, and midstory of each stand. Type A stands were sampled intensively, with the goal of providing high-fidelity spatial information about the 3-dimensional structure of the stand. These stands were 60 x 60-m (0.36-ha) areas divided into 10 x 10-m grids of uniform clearing and abandonment history and were identifiable from Landsat images. Type B stands were sampled extensively, with the goal of providing unbiased estimates of biomass, along with some information about the vertical structure of the stand and of spatial variability. These stands were polygons of uniform clearing and afforestation history based on multitemporal Landsat imagery, and varied in size and shape. The Landsat files provide classified land cover for each scene and can be used as a time series to evaluate land cover change over time. Each Landsat file is a geolocated land cover map based on 30-m Landsat data. NOTE: There were additional files which could not be archived due to file problems. Data Quality Statement: The Data Center has determined that this data set has missing or incomplete data, metadata, or other documentation resulting in diminished usability of this product. Known Problems: Some unresolved issues remain where data values are inconsistent with the variable descriptions provided with the data set. The site identification and plot identification values are not consistently used in all three data files. The variables are not adequately described.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2761779464-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761779464-ORNL_CLOUD.html",
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         "description": "This dataset is a compilation of carbon and energy eddy covariance flux, meteorology, radiation, canopy temperature, humidity, CO2 profiles and soil moisture and temperature profile data that were collected at nine towers across the Brazilian Amazon. Independent investigators provided the data from a variety of flux tower projects over the period 1999 thru 2006. This is Version 2 of the tower data compilation, where the data have been harmonized across projects, additional quality control checks were performed, and have been aggregated to hourly, daily, 16-day, and monthly timesteps. This integrated dataset is intended to facilitate integrative studies and data-model synthesis from a common reference point.",
         "license": "proprietary"
     },
@@ -44364,7 +44364,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781567429-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781567429-ORNL_CLOUD.html",
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         "description": "This data set provides gap-filled meteorological observations from nine Brazilian flux towers for periods between 1999 and 2006. The measurements include: air temperature, specific humidity, module of wind speed, downward long wave and shortwave radiation at the surface, surface pressure, precipitation, and carbon dioxide (CO2). These atmospheric data are provided at 1 hour time-steps. These data were used as the standardized forcing data input for the LBA Model Intercomparison Project (LBA-MIP).The LBA-MIP goal was to gain comparative understanding of ecosystem models that simulate energy, water, and CO2 fluxes over the LBA area. The task was to subject all the models to the same forcing and experimental protocol, and to compare the outputs. The protocol is provided as a companion file, lba_mip_protocol4.0_20100309.pdf.The source meteorological observations for the forcing data, from the nine Brazilian flux towers, were recently published as Saleska, et al. (2013). See related data sets. These source data were gap-filled according to the LBA-MIP standard protocol. Note that the CAX forest tower was not included in the MIP. See the companion file driver_data.pdf for additional gap-filling information.There are 34 data products with this data set and they are provided in both text (.txt) and ALMA-compliant NetCDF (.nc) formats. The files have been compressed into nine *.zip files according to site.",
         "license": "proprietary"
     },
@@ -44377,7 +44377,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751481862-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751481862-ORNL_CLOUD.html",
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         "description": "This data set contains 20 multispectral surface reflectance images collected by the EO-1 satellite Hyperion sensor at 30-m resolution and covering the entire Amazon Basin for 2002 - 2005. All images were converted to GeoTiff format for distribution. The respective ENVI *.hdr files are included as companion files and contain image projection and band information.The selected multispectral images were processed using ENVI software as described in Chambers et al. (2009). Bands with uncalibrated wavelengths and those with low spectral response were removed leaving a spectral subset of generally 196 bands (some images have fewer). A cloud mask was developed using 2-d scatter plots of variable reflectance bands to highlight clouds as regions of interest (ROIs), allowing clouds and cloud edges to be masked. A de-streaking algorithm was then applied to the image to reduce variance in balance between the vertical columns.  Apparent surface reflectance was calculated for this balanced image using the atmospheric correction algorithm ACORN in 1.5pb mode (AIG-LLC, Boulder, CO).  The images (18 of the 20) were georeferenced using the corresponding Advanced Land Imager (ALI) satellite images.",
         "license": "proprietary"
     },
@@ -44390,7 +44390,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781566910-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781566910-ORNL_CLOUD.html",
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         "description": "This data set provides the results of fractional land cover analysis for nonphotosynthetic vegetation (NPV) from two Landsat images of Manaus, Brazil, for October 14, 2004, and for July 29, 2005. Both images are from Landsat 5, path 231, row 62. The Manauas area experienced a squall line with intense downbursts from January 16-18, 2005, that resulted in widespread blowdown and tree mortality. The pre- and post-disturbance Landsat images were obtained and processed using spectral mixture analysis (SMA) in order to investigate forest disturbance and tree mortatility resulting from the downburst. SMA was based on scene-derived end-members of green vegetation (GV, photosynthetically active vegetation), NPV ( wood, dead vegetation, and surface litter), soil, and shade obtained using a pixel purity index (PPI) algorithm (Negron-Juarez et al., 2010). Changes in NPV due to disturbance were calculated by subtracting the 2004 NPV image from the 2005 NPV image. This NPV difference image is provided. There are three image files (.tif) with this data set: The two Landsat images that were georectified and converted to reflectance values and the NPV difference image. DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.KNOWN PROBLEMS: Four additional images were needed to make this data set complete but are unavailable. Specifically, the two images resulting from SMA as applied to the Landsat images collected on the 14th of October, 2004 and the 29th of July, 2005 to determine per-pixel fractional abundance of GV, NPV (wood, dead vegetation, and surface litter), soil, and shade and the 2004 NPV and 2005 NPV images that were used to derive the NPV changes image (which we do provide) (Negron-Juarez, et al., 2010).",
         "license": "proprietary"
     },
@@ -44403,7 +44403,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768946825-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768946825-ORNL_CLOUD.html",
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         "description": "This data set provides South American Land Data Assimilation System (SALDAS) forcing data including atmospheric fields necessary for land surface modeling for South America which are derived by combining modeled and observation based sources. The forcing data cover the entire continent of South America at 0.125 degree resolution and are built around the model-calculated values of air temperature, wind speed and specific humidity at two meters, surface pressure, downward shortwave and longwave surface radiation, and precipitation from the South American Regional Reanalysis (SARR). These SARR data (Aravequia et al. 2007), which were released in 2006 by INPE/CPTEC, are a medium-term, dynamically consistent, high-resolution (0.125 degree), high-frequency, atmospheric dataset covering South America. The forcing data are available at a 3-hourly time step for a 5-year period from 2000 to 2004. There are 60 monthly *.zip files with each zipped file containing ~240 3-hourly time step data files for that particular month in NetCDF format. Each zipped file is approximately one GB in size.",
         "license": "proprietary"
     },
@@ -44416,7 +44416,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781386619-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781386619-ORNL_CLOUD.html",
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         "description": "This data set provides tree age, forest formation, and  land cover classification maps, and estimates of landscape-level above-ground live woody biomass (AGLB) for secondary forests in Rondonia, Brazil. The Threshold Age Mapping Algorithm (TAMA) was applied to a densely spaced time series of Landsat images (1975 to 2003) to derive forest type and age classification maps. The AGLB of the secondary forest was estimated by combining the forest classification map with coincident biomass estimates from the Geoscience Laser Altimeter System (GLAS). There are five raster images and three comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -47380,7 +47380,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2759030200-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2759030200-ORNL_CLOUD.html",
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         "description": "This data set contains monthly temperature, precipitation, sea-level pressure, and station-pressure data for thousands of meteorological stations worldwide. The database was compiled from pre-existing national, regional, and global collections of data as part of the Global Historical Climatology Network (GHCN) project, the goal of which is to produce, maintain, and make available a comprehensive global surface baseline climate data set for monitoring climate and detecting climate change. It contains data from roughly 6000 temperature stations, 7500 precipitation stations, 1800 sea level pressure stations, and 1800 station pressure stations. Each station has at least 10 years of data, 40% have more than 50 years of data. Spatial coverage is good over most of the globe, particularly for the United States and Europe. Data gaps are evident over the Amazon rainforest, the Sahara Desert, Greenland, and Antarctica.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236223020-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236223020-ORNL_CLOUD.html",
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         "description": "This data set provides the results of (1) year-round measurements of methane (CH4) flux along with soil and air temperatures at five eddy covariance towers at sites located in the Alaskan Arctic tundra from June 2013 to December 2014 and (2) airborne CH4 and ozone (O3) measurements collected during Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) flight campaigns for years 2012 through 2014. The included site-level flux data at half-hourly intervals were calculated following standard eddy covariance data processing procedures. Also reported are daily mean methane flux, soil temperature with depth, and air temperature for each tower site. Also identified for each flux tower site were the \"zero curtain\" periods of extended cold when soil temperatures were poised near 0 degrees C. The reported CARVE airborne CH4 and O3 data were aggregated horizontally at 5 km intervals. Measurement heights are reported. These aircraft positions were treated as receptors in a Stochastic Time-Inverted Lagrangian Transport (STILT) model coupled with meteorology fields from the polar variant of the Weather and Research Forecasting model (WRF), in order to model the land surface influence on the aircraft-observed methane concentrations. The summed land surface influence on the aircraft data at each position is reported. For each airborne measurement, 2D surface influence fields (i.e. footprints) at two different spatial resolutions were derived using the WRF-STILT simulations. These gridded footprints are provided as netCDF formatted files. Regional C-CH4 fluxes were calculated from the CARVE CH4 data and footprints for the period 2012-2014 and are also included with this data set. Acknowledgements: Data collection efforts were funded by NSF ARCSS project \"Methane Loss From Arctic\" (ARCSS #1204263; http://www.nsf.gov/awardsearch/showAward?AWD_ID=1204263) and by NASA's Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE).",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2992461082-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2992461082-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of carbon dioxide (CO2) and methane (CH4) diffusive fluxes from waterbodies, and watershed landcover data for the central-interior of the Yukon-Kuskokwim Delta (YK delta), Alaska. Dissolved concentrations of methane and carbon dioxide were predicted using an integrated terrestrial-aquatic approach to scale observations based on landscape and waterbody remote sensing drivers. The observations include ~300 samples of surface water dissolved gases collected in July 2016-2019 from the central region of the YK Delta, Alaska. A machine learning model was used to generate estimated fluxes.  Model inputs include Sentinel-2 MSI with derived normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), an Arctic digital elevation model (DEM) with derived slope and flow accumulation, Sentinel-1 C-band July and December VV and VH composites, and a landcover map. Waterbody size, shape, and reflectance were determined using object-based image analysis in Google Earth Engine. Landscape-level input data were averaged in non-nested sub-basins calculated using the System for Automated Geoscientific Analyses (SAGA) \"channel network\" algorithm at three threshold sizes. Cross validation was used to tune and select variables for gradient boosting models. The trained gradient boosting models were then used to predict dissolved methane and carbon dioxide in all waterbodies (~17,000) in the region. These aquatic concentrations were converted to fluxes using an average gas transfer velocity from observations (0.33 m/d). The data are provided in GeoTIFF and shapefile formats.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2192619099-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2192619099-ORNL_CLOUD.html",
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         "description": "This dataset provides methane fluxes from hot-spot and non-hot spot differing surfaces at Big Trail Lake (BTL) in the Goldstream Valley near Fairbanks, AK, USA. Measurements were taken at a remotely-sensed methane hotspot on the shoreline of a pond, adjacent to BTL with a Los Gatos Ultra-Portable Greenhouse Gas Analyzer (UGGA), and from various non-hotspot surfaces representative of the broader thermokarst lake ecosystem with bucket chambers. All data were collected between 2019-07-04 and 2019-12-04 during the daytime hours of 09:35-17:32 local time. A ground-based CH4 enhancement survey was performed on 2019-07-06 between 13:25-17:15 Alaska Daylight Time (AKDT), approximately two hours following an AVIRIS-NG overflight and hotspot detection at the Eastside Pond. Methane flux is reported in units of both mmol CH4 m-2 hr-1 and mg CH4 m-2 d-1. Flux errors are quantified for each",
         "license": "proprietary"
     },
@@ -50370,7 +50370,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389764676-ORNL_CLOUD.html",
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         "description": "This dataset provides maps of methane (CH4) plumes along flight lines over identified methane point-source emitting infrastructure across the State of California, USA collected during 2016 and 2017. Methane plume locations were derived from Next-Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG) overflights during the California Methane Survey. The survey was designed to cover at least 60% of the methane point source infrastructure in California guided by the Vista-CA dataset of identified locations of potential methane emitting facilities and infrastructure in three primary sectors (energy, agriculture, and waste). The purpose of the survey was to detect, quantify, and attribute point source emissions to specific infrastructure elements to improve the scientific understanding of regional methane budgets and to inform policy and planning activities that reduce methane emissions.",
         "license": "proprietary"
     },
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         "description": "This model product provides source code, input data files, and example model outputs for a new mechanistic soil nitrogen (N) module in-line with the Community Multiscale Air Quality (CMAQ) model 5.1 to simulate nitric oxide (NO), nitrous acid (HONO), nitrous oxide (N2O), and ammonia (NH3) soil emissions. The modeling domain covers the continental USA plus portions of northern Mexico and southern Canada, extending from 25 degrees north to 52 degrees north.The simulations use a 12-km spatial grid resolution. Input data are from high-quality reference sources for year 2011. Example model output data are provided for one day, April 21, 2011.",
         "license": "proprietary"
     },
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         "description": "This data set provides global, gridded, model-derived net ecosystem exchange (NEE) of CO2 flux between the land and atmosphere at 3-hourly time steps over seven years (2004-2010) at three different spatial resolutions: 0.5 x 0.5 degree, 2.0 x 2.5 degrees, and 4.0 x 5.0 degrees (latitude/longitude). The 3-hourly data were derived from monthly NEE outputs of 15 global land surface models and four ensemble products in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP).",
         "license": "proprietary"
     },
@@ -55362,7 +55362,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389289428-ORNL_CLOUD.html",
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         "description": "This dataset provides annual estimates of six carbon pools, including forest aboveground live biomass, belowground biomass, aboveground dead biomass, belowground dead biomass, litter, and soil organic matter, across the conterminous United States (CONUS) for 2005, 2010, 2015, 2016, and 2017. Carbon stocks were estimated using a modified MaxEnt model. Measurements of pixel-specific site conditions from remote sensing data were combined with field inventory data from the U.S. Forest Service Forest Inventory and Analysis (FIA). Remote sensing data inputs included Thematic Mapper on Landsat 5, Operational Land Imager on Landsat 8, Moderate Resolution Imaging Spectroradiometer (MODIS) on Aqua, microwave radar measurements from Phased Array type L-band Synthetic Aperture Radar (PALSAR) on Advanced Land Observation Satellite (ALOS) and PALSAR-2 ALOS-2, airborne imagery from National Agriculture Imagery Program (NAIP), and the digital elevation model from the Shuttle Radar Topography Mission (SRTM). Data from satellite and airborne sources were co-registered on a common 100 m (1 ha) grid.",
         "license": "proprietary"
     },
@@ -55427,7 +55427,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345893268-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345893268-ORNL_CLOUD.html",
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         "description": "This dataset provides information about the resilience of tidal wetlands to sea-level rise under three scenarios of global change. With rising seas, regularly inundated tidal wetlands may persist by vertical accretion of sediments (vertical resilience) and/or by migrating inland (lateral resilience), but local and regional conditions constrain these options. This dataset provides a vertical resilience index (VR) for coastal wetlands at 30 m resolution across the continental US predicted for 2100. The VR index was computed for current sea levels, local tidal dynamics, and coastal topography. It was also calculated for future sea levels predicted for 2100 by three IPCC Realized Concentration Pathway (RCP) scenarios: 2.5, 4.5, and 8.5. Moreover, the VR index incorporates estimated rates of sediment accretion. Relevant to lateral resiliency, the data include current and future tidal areas identified by mapping mean higher high water spring tide locations under the RCP scenarios. A shapefile outlining watershed units with tidal wetlands is included along with land cover classes for these areas for 1996 and 2011.",
         "license": "proprietary"
     },
@@ -55440,7 +55440,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389100132-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389100132-ORNL_CLOUD.html",
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         "description": "This data set provides a 38-year, 1-km resolution inventory of annual on-road CO2 emissions for the conterminous United States based on roadway-level vehicle traffic data and state-specific emissions factors for multiple vehicle types on urban and rural roads as compiled in the Database of Road Transportation Emissions (DARTE). CO2 emissions from the on-road transportation sector are provided annually for 1980-2017 as a continuous surface at a spatial resolution of 1 km.",
         "license": "proprietary"
     },
@@ -55453,7 +55453,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343140450-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343140450-ORNL_CLOUD.html",
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         "description": "This data set provides daily average observations for evapotranspiration (measured and gap-filled), precipitation, net radiation, soil water content, air temperature, vapor pressure deficit, and normalized vegetation index (NDVI) from two water-limited shrubland sites for years 2008-2010. Both sites are located in the northwest part of Mexico and are part of the MexFlux network.",
         "license": "proprietary"
     },
@@ -55466,7 +55466,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389022246-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389022246-ORNL_CLOUD.html",
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         "description": "This dataset provides maps of the distribution of ecosystem functional types (EFTs) and the interannual variability of EFTs at 0.05 degree resolution across the conterminous United States (CONUS) for 2001 to 2014. EFTs are groupings of ecosystems based on their similar ecosystem functioning that are used to represent the spatial patterns and temporal variability of key ecosystem functional traits without prior knowledge of vegetation type or canopy architecture. Sixty-four EFTs were derived from the metrics of a 2001-2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) product MOD13C2. EFT diversity was calculated as the modal (most repeated) EFT and interannual variability was calculated as the number of unique EFTs for each pixel.",
         "license": "proprietary"
     },
@@ -55479,7 +55479,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2391444072-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2391444072-ORNL_CLOUD.html",
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         "description": "This dataset provides daily fire weather indices for interior Alaska during the active fire seasons from 2001 to 2010. Data are gridded at 60-m resolution. The active fire season is defined as May 24-September 18 (days of the year 144-261) in this dataset. Fire weather is the use of meteorological parameters such as relative humidity, wind speed and direction, cloud cover, mixing heights, and soil moisture to determine whether conditions are favorable for fire growth and smoke dispersion. The six indices provided in this dataset are defined and produced following the methodology of the Canadian Forest Fire Weather Index System: Fine Fuel Moisture Code, Duff Moisture Code, Drought Code, Initial Spread Index, Buildup Index, Fire Weather Index. The dataset was developed following point source data interpolation from weather station observations.",
         "license": "proprietary"
     },
@@ -55492,7 +55492,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2954648832-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2954648832-ORNL_CLOUD.html",
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         "description": "This dataset provides gridded surface-atmosphere CO2 fluxes over North America from April 8 to November 18 during 2018 and 2019. Net ecosystem exchange (NEE) was estimated  by the CMS-Flux-NA CO2 inversion system by assimilating in situ CO2 measurements and/or Orbiting Carbon Observatory (OCO-2) column-averaged CO2 retrievals. These data, along with imposed diurnal NEE variations, fossil fuel emissions, biomass burning, and biofuel emissions, are provided at 3-hour temporal resolution. The modeled co-samples of CO2 observed for aircraft flights are included for model evaluation. The data are provided in NetCDF version 4 format.",
         "license": "proprietary"
     },
@@ -55505,7 +55505,7 @@
         "bbox": "-136.15, 19.29, -55.85, 50",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343141629-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343141629-ORNL_CLOUD.html",
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         "description": "This data set provides maps of estimated carbon in forests of the 48 continental states of the US for the years 2005-2010. Carbon (termed committed carbon) stocks were estimated for forest aboveground biomass, belowground biomass, standing dead stems, and litter for the year 2005. Carbon emissions were estimated from land use conversion to agriculture, insect damage, logging, wind, and weather events in the forests for the years 2006 - 2010. Committed net carbon flux was estimated as the sum of carbon emissions and sequestration. The maps are provided at 100-m spatial resolution in GeoTIFF format. Average annual carbon estimates, by US county, for (1) emissions for the multiple disturbance sources, (2) sequestration, and (3) the committed net carbon flux are provided in an ESRI shapefile.",
         "license": "proprietary"
     },
@@ -55518,7 +55518,7 @@
         "bbox": "-79.52, 37.83, -75.05, 39.81",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389064923-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389064923-ORNL_CLOUD.html",
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         "description": "This dataset provides 90-m resolution maps of estimated forest aboveground biomass (Mg/ha) for nominal year 2011 and projections of carbon sequestration potential for the state of Maryland. Estimated biomass and sequestration potential were computed using the Ecosystem Demography (ED) model, which integrates data from multiple sources, including: climate variables from the North American Regional Reanalysis (NARR) Product, soil variables from the Soil Survey Geographic Database (SSURGO), land cover variables from airborne lidar, the National Agriculture Imagery Program (NAIP) and the National Land Cover Database (NLCD), and vegetation parameters from the Forest Inventory and Analysis (FIA) Program.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2395540148-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2395540148-ORNL_CLOUD.html",
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         "description": "Notice: This data set and guide were updated on June 30, 2014 to correct an error in the reported units. The data values were not changed.Spatially-gridded estimates of above ground biomass (AGB), net primary productivity (NPP), and net ecosystem productivity (NEP) are provided for forested areas of the conterminous United States (CONUS). Estimates of uncertainty are also provided for AGB and NEP. These data were derived by using Forest Inventory and Analysis (FIA) data to constrain forest growth rates in a Carnegie-Ames-Stanford Approach (CASA) carbon-cycle process model. Note that the data set does not include data for forests in the Northern Prairie States region (NPS; see Figure 3). These data provide a detailed estimate of carbon sources and sinks from recent forest disturbance and recovery across regions and forest types of the US.The data are presented as a series of ten NetCDF v4 (*.nc4) files at two spatial scales (1-degree and 5-km spatial resolution) for the nominal year of 2005.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2395542240-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2395542240-ORNL_CLOUD.html",
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         "description": "This data set provides global estimates of carbon fluxes associate with annual crop net primary production (NPP) and harvested biomass, annual uptake and release by humans and livestock, and the total annual estimate of net carbon exchange (NCE) derived from these carbon fluxes. NCE estimates are for the combined crop plant harvest and consumption/expiration of fodder by livestock and of food by humans. Estimation of carbon uptake and release from global agricultural production and consumption required compilation and analysis of inventory data from various sources for the years 2005-2011. The flux estimates were spatially distributed to a global 0.05-degree resolution grid using MODIS land cover data. The quantities of carbon flux in each gridcell are represented in two ways: (1) where the quantities of carbon distributed to each gridcell were divided by the total gridcell area, resulting in average carbon fluxes per unit of total area (g C/m2/yr), and (2), where annual carbon fluxes associated with a source were summed over all types for the gridcell (Mg C/yr). The total surface area of the grid cells is provided.There are eight data files in netCDF format (.nc4) with this data set -- two files (per area and per gridcell) for each of the four flux source types. Data for all years are in each *.nc4 file.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389158955-ORNL_CLOUD.html",
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         "description": "The Global Fire Atlas is a global dataset that tracks the day-to-day dynamics of individual fires to determine the timing and location of ignitions, fire size, duration, daily expansion, fire line length, speed, and direction of spread. These individual fire characteristics were derived based on the Global Fire Atlas algorithm and estimated day of burn information at 500-m resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 MCD64A1 burned area product. The algorithm identified 13.3 million individual fires (>=21 ha or 0.21 km2; the size of one MODIS pixel) over the 2003-2016 study period.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756296671-ORNL_CLOUD.html",
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         "description": "This dataset provides global gridded estimates of forest aboveground carbon stocks and potential fluxes at a 0.01-degree resolution. It was derived by initializing a newly developed global Ecosystem Demography model (ED v3.0) with novel remote sensing observations of tree canopy height collected by GEDI and ICESat-2, two NASA spaceborne lidar missions. A total of 3.77 billion lidar samples were used to generate gridded canopy height histograms that were then linked to ED simulations of canopy height and carbon dynamics during ecosystem succession. This process constrained representation of contemporary forest conditions and associated carbon stocks and fluxes in the model. Inputs that drove these simulations included meteorology, carbon dioxide levels, and soil properties. The data are provided in cloud-optimized GeoTIFF format.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3091153379-ORNL_CLOUD.html",
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         "description": "This dataset provides classes of global forests delineated by status/condition in 2020 at approximately 30-m resolution. The data support generating Tier 1 estimates for Aboveground dry woody Biomass Density (AGBD) in natural forests in the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Forest classes include primary, young secondary (<=20 years), and old secondary forests (>20 years). Classification was based on a Boolean combination of a suite of existing Earth Observation (EO) products of forest tree cover, height, age, and land use classification layers representing years 2000 to 2020. This forest status/condition classification prioritizes the reduction of potential errors of commission in the delineations by minimizing the inclusion of ambiguous pixels. Hence, it provides a conservative estimate of global forest area, identifying approximately 3.26 billion ha of forests worldwide. The classification was created on the collaborative open-science cloud-computing system, the ESA-NASA Multi-mission Analysis and Algorithm Platform (MAAP). The data are provided in cloud-optimized GeoTIFF format.",
         "license": "proprietary"
     },
@@ -55609,7 +55609,7 @@
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         "description": "This data set provides global annual carbon flux estimates, at 0.05-degree resolution, associated with livestock feed intake, manure, manure management, respiration, and enteric fermentation, summed over all livestock types. These fluxes can be summed across multiple grid cells to obtain totals for any given areas. These 2000-2013 flux estimates were based on livestock populations reported by the Food and Agriculture Organization (FAO) and the United States Department of Agriculture National Agricultural Statistics Service (USDA NASS), on coefficients provided by the Intergovernmental Panel on Climate Change (IPCC), and on additional coefficients developed by the authors.",
         "license": "proprietary"
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@@ -55622,7 +55622,7 @@
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         "description": "This dataset characterizes canopy heights of mangrove-forested wetlands globally for 2015 at 12-m resolution. Estimates of maximum canopy height (height of the tallest tree) were derived from the German Space Agency's TanDEM-X data that produced global digital surface models. Also provided are Lidar estimates of canopy height based on the GEDI instrument, which were used for training and validation of the TanDEM-X estimates of forest height. The coverage of these data follows Global Mangrove Watch's mangrove extent maps. These spatially explicit maps of mangrove canopy height can be used to assess local-scale geophysical and environmental conditions that may regulate forest structure and carbon cycle dynamics. Maps revealed a wide range of canopy heights, including maximum values (>60 m) that surpass maximum heights of other forest types. Maps are provided in cloud optimized GeoTIFF format, and mangrove heights for individual GEDI tiles are compiled in a comma separated values (CSV) files.",
         "license": "proprietary"
     },
@@ -55635,7 +55635,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389103604-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389103604-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of the extent of mangrove loss, land cover change, and its anthropogenic or climatic drivers in three time periods: 2000-2005, 2005-2010, and 2010-2016. Landsat-based Normalized Difference Vegetation Index (NDVI) anomalies were used to determine loss extent in each period. The drivers of mangrove loss were determined by examining land cover changes using a random forest machine learning technique that considered change from mangrove to wet soil, dry soil, and water at each loss pixel. A series of decision trees used several global-scale land-use datasets to identify the ultimate driver of the mangrove loss. Loss drivers include commodity production (agriculture, aquaculture), settlement, erosion, extreme climatic events, and non-productive conversion. Maps of loss extent per period, mangrove land cover changes, and loss drivers are provided for each of 39 mangrove holding nations.",
         "license": "proprietary"
     },
@@ -55648,7 +55648,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389107206-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389107206-ORNL_CLOUD.html",
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         "description": "This dataset characterizes the global distribution, biomass, and canopy height of mangrove-forested wetlands based on remotely sensed and in situ field measurement data. Estimates of (1) mangrove aboveground biomass (AGB), (2) maximum canopy height (height of the tallest tree), and (3) basal-area weighted height (individual tree heights weighted in proportion to their basal area) for the nominal year 2000 were derived across a 30-meter resolution global mangrove ecotype extent map using remotely-sensed canopy height measurements and region-specific allometric models. Also provided are (4) in situ field measurement data for selected sites across a wide variety of forest structures (e.g., scrub, fringe, riverine and basin) in mangrove ecotypes of the global equatorial region. Within designated plots, selected trees were identified to species and diameter at breast height (DBH) and tree height was measured using a laser rangefinder or clinometer. Tree density (the number of stems) can be estimated for each plot and expressed per unit area. These data were used to derive plot-level allometry among AGB, basal area weighted height (Hba), and maximum canopy height (Hmax) and to validate the remotely sensed estimates.",
         "license": "proprietary"
     },
@@ -55661,7 +55661,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389102945-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389102945-ORNL_CLOUD.html",
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         "description": "This data set provides global monthly wetland methane (CH4) emissions and uncertainty data products derived from an ensemble of multiple terrestrial biosphere models, wetland extent scenarios, and CH4:C temperature dependencies. The data are at 0.5 by 0.5-degree resolution. Two model output data products are included in WetCHARTs v1.0: an output from the full ensemble for 2009-2010 and an output from a limited subset for 2001-2015. The intended use of the products is as a process-informed wetland CH4 emission and uncertainty data set for atmospheric chemistry and transport modelling (WetCHARTs).",
         "license": "proprietary"
     },
@@ -55674,7 +55674,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389104778-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389104778-ORNL_CLOUD.html",
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         "description": "This dataset provides six global gridded products at 1-km resolution of predicted annual soil respiration (Rs) and associated uncertainty, maps of the lower and upper quartiles of the prediction distributions, and two derived annual heterotrophic respiration (Rh) maps. A machine learning approach was used to derive the predicted Rs and uncertainty data using a quantile regression forest (QRF) algorithm trained with observations from the global Soil Respiration Database (SRDB) version 3 spanning from 1961 to 2011. The two Rh maps were derived from the predicted Rs with two different empirical equations. These products were produced to support carbon cycle research at local- to global-scales, and highlight the immense spatial variability of soil respiration and our ability to predict it across the globe.",
         "license": "proprietary"
     },
@@ -55687,7 +55687,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389194355-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389194355-ORNL_CLOUD.html",
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         "description": "This dataset provides annual maps of live aboveground tree biomass (Mg/ha) for pinyon-juniper forests across the Great Basin of the Western USA for the years 2000-2016 at a spatial resolution of 30 meters. Biomass estimates are limited to areas of the Great Basin defined as a pinyon-juniper ecosystem type by the 2016 Landfire Existing Vegetation Type map. The estimates of biomass were based on a linear relationship with pinyon-juniper canopy cover and crown-based allometrics developed from field data in Nevada and Idaho. Canopy cover was estimated from remote sensing by using annual composites of Landsat imagery, which were temporally segmented with the LandTrendr algorithm, along with biologically-relevant climate variables, and topographic indices in a Random Forest regression model. Models of canopy cover were trained from semi-automatic extraction of tree crowns from 2011 - 2013 high resolution imagery (1 m) from the National Agriculture Imagery Program, which were validated with photo interpretation.  Maps of the standard deviation of biomass estimates from decision trees in the Random Forest model are provided as an indicator of uncertainty. Biomass estimates were calibrated to estimates from the Forest Inventory and Analysis program (FIA) on an annual basis and corrections applied.",
         "license": "proprietary"
     },
@@ -55713,7 +55713,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345896026-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345896026-ORNL_CLOUD.html",
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         "description": "This dataset contains annual land use/cover (LUC) maps at 30 m resolution across Mawas, Central Kalimantan, Indonesia. There are six files, each representing a five-year interval over the period 1994-2019. An additional file for 2015 was created for accuracy assessment. A high-quality and low-cloud coverage image from Landsat 5 or Landsat 8 over each 5-year period was selected or composited for the January-August timeframe. Investigators used their knowledge to manually identify training polygons in these images for five LUC classes: peat swamp forest, tall shrubs/ secondary forest, low shrubs/ferns/grass, urban/bare land/open flooded areas, and river. Pixel values of Landsat Tier 1 surface reflectance products and selected indices were extracted for each LUC and used to predict LUC classes across the Mawas study area using the Classification and Regression Trees (CART) method. These data can be used to evaluate the relationship between fire occurrence and land cover type in the study site.",
         "license": "proprietary"
     },
@@ -55726,7 +55726,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343139758-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343139758-ORNL_CLOUD.html",
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         "description": "This data set provides measurements for diameter at breast height (DBH), commercial tree height, and total tree height for forest inventories taken at the Fazenda Cauaxi and the Fazenda Nova Neonita, Paragominas municipality, Para, Brazil. Also included for each tree are the common, family, and scientific name, coordinates, canopy position, crown radius, and for dead trees the decomposition status. These biophysical measurements were made at Fazenda Cauaxi during 2012 and 2014 and at the Fazenda Nova Neonita during 2013.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389137421-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389137421-ORNL_CLOUD.html",
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         "description": "This data set provides raw LiDAR point cloud data and derived Digital Terrain Models (DTMs) for five forested areas in the municipality of Paragominas, Para, Brazil, for the years 2012, 2013, and 2014. Data are included for two areas in Paragominas for 2013 and 2014, two areas for the Fazenda Cauaxi for 2012 and 2014, and for the Fazenda Andiroba for 2014. Shapefiles showing the LiDAR/DTM coverage areas are also provided for each of the areas.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2398118307-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of aboveground biomass and spatially explicit uncertainty from 53 airborne LiDAR surveys of locations throughout California between 2005 and 2014. Aboveground biomass was estimated by performing individual tree crown detection and applying a customized \"remote sensing aware\" allometric equation to these individual trees. Aboveground biomass estimates and their uncertainties for each study area are provided in per-tree and gridded format. The canopy height models used for the tree detection and biomass estimation are also provided.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343142998-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343142998-ORNL_CLOUD.html",
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         "description": "This data set includes estimates of aboveground biomass (AGB) in 2012 from the Penobscot Experimental Forest (PEF) in Bradley, Maine. The AGB was modeled using LiDAR data gathered with the LiDAR Hyperspectral and Thermal Imager (G-LiHT) operated by Goddard Space Flight Center and field inventory data from 604 permanent Forest Inventory and Analysis (FIA) plots within the PEF. The estimates were produced through a novel modeling approach that accommodates temporal misalignment between field measurements and remotely sensed data by including multiple time-indexed measurements at plot locations to estimate changes in AGB.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082431-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082431-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of above-ground biomass (AGB), canopy height, and percent tree cover at 30-m spatial resolution for Sonoma County, California, USA, for the nominal year 2013. Biomass estimates, megagrams of biomass per hectare (Mg/ha) were generated using a combination of LiDAR data, field plot measurements, and random forest modeling approaches. Estimates of AGB uncertainty are also provided. Maximum canopy height and tree cover were derived from LiDAR data and high-resolution National Agriculture Imagery Program (NAIP) images.",
         "license": "proprietary"
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         "description": "This dataset provides 30-meter gridded estimates of aboveground biomass (AGB), forest canopy height, and canopy coverage for Maryland, Pennsylvania, and Delaware in 2011. Leaf-off LiDAR data were combined with high-resolution leaf-on agricultural imagery in a model-based stratification that was used to select 848 sampling sites for AGB estimation. Field-based estimates were then related to LiDAR height and volume metrics through random forest regression models across three physiographic regions. Spatial errors were estimated at the pixel level using standard prediction intervals to assess the accuracy of the modeling approach. Estimates of biomass were further validated against the permanent network of FIA plots and compared with existing coarse resolution national biomass maps.",
         "license": "proprietary"
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         "description": "This dataset provides airborne LiDAR data collected over 90 sites totaling approximately 100,000 hectares of forested land in Kalimantan, Indonesia on the island of Borneo in late 2014. The data were collected as part of an effort to establish a national forest monitoring system for Indonesia that uses a combination of remote sensing and ground-based forest carbon inventory approaches.",
         "license": "proprietary"
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@@ -55817,7 +55817,7 @@
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         "description": "This data set provides high-resolution LiDAR point cloud data collected during surveys over mangrove forests in the Zambezi River Delta in Mozambique in May 2014. The data are arranged into 144 1- by 1-km tiles.",
         "license": "proprietary"
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@@ -55830,7 +55830,7 @@
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         "description": "This dataset provides canopy height and elevation data products derived from airborne LiDAR data collected over 90 sites on the island of Borneo in late 2014. The sites cover approximately 100,000 hectares of forested land in Kalimantan, Indonesia. The data were produced as part of an effort to improve a national forest monitoring system for Indonesia that uses a combination of remote sensing and ground-based forest carbon inventory approaches.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082586-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082586-ORNL_CLOUD.html",
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         "description": "This dataset provides several estimates of aboveground biomass from various regressions and allometries for mangrove forest in the Zambezi River Delta, Mozambique. Plot level estimates of aboveground biomass are based on extensive tree biophysical measurements from field campaigns conducted in September and October of 2012 and 2013. Aboveground biomass estimates for the larger area of mangrove coverage within the delta are based on (1) the plot level data and (2) canopy structure data derived from airborne LiDAR surveys in 2014. The high-resolution canopy height model for the delta region derived from the airborne LiDAR data is also included.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343165627-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343165627-ORNL_CLOUD.html",
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         "description": "This data set provides canopy height, land cover change, and stand age estimates for mangrove forests in the Rufiji River Delta in Tanzania. The estimates were derived from a canopy height model (CHM) using TanDEM-X imagery and Polarimetric SAR interferometry (Pol-InSAR) techniques. Landsat imagery circa 1990 and circa 2014 was used to estimate stand age between 1994 and 2014 and for forest land cover change modeling.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343144278-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343144278-ORNL_CLOUD.html",
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         "description": "This data set provides canopy height estimates for mangrove forests at 0.6 x 0.6 m resolution in three study sites located in southeastern Mozambique, Africa: two sites on Inhaca Island and one in the Maputo Elephant Reserve, located in the southern province of Maputo for September, 2012. The estimates were derived from WorldView1 (WV-1) very high resolution (VHR) stereo images processed using the Ames Stereo Pipeline (ASP) digital surface model (DSM) tool.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343163771-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343163771-ORNL_CLOUD.html",
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         "description": "This data set provides high resolution canopy height estimates for mangrove forests in the Zambezi Delta, Mozambique, Africa. The estimates were derived from three separate canopy height models (CHM) using airborne Lidar data, stereophotogrammetry with WorldView 1 imagery, and Interferometric-Synthetic Aperture Radar (In-SAR) techniques with TanDEM-X imagery. The data cover the period 2011-10-14 to 2014-05-06.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389022166-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389022166-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of mangrove extent for 2016, and mangrove change (gain or loss) from 2000 to 2016, in major river delta regions of eight countries: Bangladesh, Gabon, Jamaica, Mozambique, Peru, Senegal, Tanzania, and Vietnam. For mangrove extent, a combination of Landsat 8 OLI, Sentinel-1 C-SAR, and Shuttle Radar Topography Mission (SRTM) elevation data were used to create country-wide maps of mangrove landcover extent at a 30-m resolution. For mangrove change, the global mangrove map for 2000 (Giri et al., 2010) was used as the baseline. Normalized Difference Vegetation Indices (NDVI) were calculated for every cloud- and shadow-free pixel in the Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI collection and used to create an NDVI anomaly from 2000 to 2016. Areas of change (loss or gain) occurred at the extremes of the cumulative anomalies.",
         "license": "proprietary"
     },
@@ -55908,7 +55908,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343143567-ORNL_CLOUD.html",
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         "description": "This data set provides 30-meter gridded estimates of aboveground biomass (AGB), canopy height, and canopy coverage for the state of Maryland in 2011. Leaf-off LiDAR data were combined with high-resolution leaf-on agricultural imagery to select 848 field sampling sites for biomass measurements. The field-based estimates were related to LiDAR height and volume metrics through random forests regression models across three physiographic regions of Maryland.",
         "license": "proprietary"
     },
@@ -55921,7 +55921,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343105668-ORNL_CLOUD.html",
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         "description": "This data set provides average hourly measured, modeled enhancements, and background methane (CH4) concentrations, atmospheric ethane (C2H6) measurements, prior CH4 flux fields by sector, and a spatial reconstruction of natural gas (NG) consumption in Boston, Massachusetts and the surrounding region. Atmospheric CH4 concentrations were measured continuously from September 2012 through August 2013 at four locations and atmospheric ethane was measured continuously for several months during 2012-2014 at one location. Spatial models of prior CH4 emissions and natural gas consumption are given for an ~18,000 km^2 area centered on Boston, MA.",
         "license": "proprietary"
     },
@@ -55934,7 +55934,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389022189-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389022189-ORNL_CLOUD.html",
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         "description": "This dataset provides 1 km gridded monthly estimates of surface ocean partial pressure of CO2 (pCO2) and air-sea flux of CO2 (CO2 flux) for the northern Gulf of Mexico for the period 2006 through 2010. Estimates of pCO2 were derived from MODIS/Aqua satellite imagery in combination with ship-based observations. Estimates of CO2 flux were derived from estimates of seawater pCO2, wind fields, and atmospheric pCO2.",
         "license": "proprietary"
     },
@@ -55960,7 +55960,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343159253-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343159253-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of pre-deforestation aboveground live woody biomass (AGLB) at 30-m resolution for deforested areas of tropical America, tropical Africa, and tropical Asia for the year 2000. The biomass estimates are only for areas where deforestation occurred during the period 2000 through 2012. These estimates represent biomass loss over this time period and can be used to derive average annual carbon emissions from tropical deforestation.",
         "license": "proprietary"
     },
@@ -55973,7 +55973,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343154679-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343154679-ORNL_CLOUD.html",
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         "description": "This data set provides high-resolution (1-m) tree canopy cover for states in the Northeast USA. State-level canopy cover data are currently available for Pennsylvania (data for nominal year 2008), Delaware (2014), and Maryland (2013). The data were derived with a rules-based expert system which facilitated integration of leaf-on LiDAR and imagery data into a single classification workflow, exploiting the spectral, height, and spatial information contained in the datasets. Additional states will be added as data processing is completed.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2395541013-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2395541013-ORNL_CLOUD.html",
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         "description": "These data consist of high-resolution maps of aboveground biomass at four forested sites in the US: Garcia River Tract in California, Anne Arundel and Howard Counties in Maryland, Parker Tract in North Carolina, and Hubbard Brook Experimental Forest in New Hampshire. Biomass maps were generated using a combination of field data (forest inventory and Lidar) and modeling approaches. Estimates of uncertainty are also provided for the Maryland site using two different modeling methodologies.These data provide estimates of aboveground biomass for the nominal year of 2011 at 20-50 meter resolution in units of megagrams of carbon per hectare (or acre for the Garcia Tract site).The data are presented as a series of 11 GeoTIFF (*.tif) files.",
         "license": "proprietary"
     },
@@ -55999,7 +55999,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082819-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082819-ORNL_CLOUD.html",
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         "description": "This dataset contains monthly mean ocean surface physical and biogeochemical data for the Gulf of Mexico simulated by the South Atlantic Bight and Gulf of Mexico (SABGOM) model on a 5-km grid from 2005 to 2010. The simulated data include ocean surface salinity, temperature, dissolved inorganic nitrogen (DIN), dissolved inorganic carbon (DIC), partial pressure of CO2 (pCO2), air-sea CO2 flux, surface currents, and primary production. The SABGOM model is a coupled physical-biogeochemical model for studying circulation and biochemical cycling for the entire Gulf of Mexico to achieve an improved understanding of marine ecosystem variations and their relations with three-dimensional ocean circulation in a gulf-wide context.",
         "license": "proprietary"
     },
@@ -56012,7 +56012,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389083479-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389083479-ORNL_CLOUD.html",
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         "description": "This dataset provides an estimate of soil organic carbon (SOC) in the top one meter of soil across Mexico at a 90-m resolution for the period 1999-2009. Carbon estimates (kg/m2) are based on a field data collection of 2852 soil profiles by the National Institute for Statistics and Geography (INEGI). The profile data were used for the development of a predictive model along with a set of environmental covariates that were harmonized in a regular grid of 90x90 m2 across all Mexican states. The base of reference was the digital elevation model (DEM) of the INEGI at 90-m spatial resolution. A model ensemble of regression trees with a recursive elimination of variables explained 54% of the total variability using a cross-validation technique of independent samples. The error associated with the predictive model estimates of SOC is provided. A summary of the total estimated SOC per state, statistical description of the modeled SOC data, and the number of pixels modeled for each state are also provided.",
         "license": "proprietary"
     },
@@ -56025,7 +56025,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389105307-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389105307-ORNL_CLOUD.html",
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         "description": "This dataset provides two sets of gridded estimates of estimated soil organic carbon (SOC) and associated uncertainties for 0-30 cm topsoil layer in kg SOC/m2 at 250-m resolution across Mexico and the conterminous USA (CONUS). The first set of gridded SOC estimates, for the period 1991-2010, were derived using multi-source SOC field data and multiple environmental variables representative of the soil forming environment coupled with a machine learning approach (i.e., simulated annealing) and regression tree ensemble modeling for optimized SOC prediction. Predictions of gridded SOC and uncertainty based on multiple bulk density (BD) pedotransfer functions (PFTs) are also included. The second set of gridded SOC estimates, for the period 2009-2011, were derived from two fully independent validation field datasets from across both countries. Note that the same environmental variables and modeling approach used for the first set of estimates were applied to the second set to assess the models' sensitivity to multiple SOC data sources. The SOC field data for the first set of estimates are provided in this dataset and the other data sources, including the two independent validation field datasets, are referenced.",
         "license": "proprietary"
     },
@@ -56038,7 +56038,7 @@
         "bbox": "-117, 22.77, -108, 32.64",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2343141032-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343141032-ORNL_CLOUD.html",
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         "description": "This data set provides data for MODIS-derived (1) gross primary productivity (GPP) for the years 2000-2010, (2) fraction of photosynthetically active radiation (fPAR) for the years 2003-2013, (3) sea surface temperature (SST) for the years 2003-2013, and (4) the NOAA-source Multivariate ENSO Index (MEI) data for the years 2003-2013 (as a measure of the El Nino/Southern Oscillation). The study areas were three transects on the Baja California Peninsula, Mexico, and the adjacent Pacific Ocean. The terrestrial transects, in order from North to South, West to East included Punta Colonet (three sites-PC1, PC2, PC3), Punta Abreojos (two sites-PA1, PA2), and Magdalena Bay (three sites-MB1, MB2, MB3).",
         "license": "proprietary"
     },
@@ -56051,7 +56051,7 @@
         "bbox": "-105.55, 40.03, -105.55, 40.03",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389021661-ORNL_CLOUD.html",
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         "description": "This dataset provides results for simulations of solar-induced chlorophyll fluorescence (SIF) implemented within the terrestrial biosphere Community Land Model (CLM 4.5) for Niwot Ridge, Colorado, USA, from 1998-2018. The data include outputs from three model simulations designed to test the importance of non-photochemical quenching (NPQ), that is, the absorbed light energy dissipated as heat, in determining seasonal SIF.",
         "license": "proprietary"
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         "description": "This data set provides the results of (1) monthly measurements of soil CO2 efflux, volumetric water content, and temperature, and (2) seasonal measurements of soil (porosity, bulk density, nitrogen (N) and carbon (C) content) and vegetation (leaf area index (LAI), litter and fine root biomass) properties in a water-limited ecosystem in Baja California, Mexico.  Measurements and samples were collected from August 2011 to August 2012.",
         "license": "proprietary"
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         "description": "This data set provides estimated CO2 emission signals for 16 regions (air quality basins) in California, USA, during the individual months of November 2010 and May 2011. The CO2 signals were predicted from simulated atmospheric CO2 observations and modeled fossil fuel emissions and biosphere CO2 fluxes. Data is also provided for the land surface in the larger modeling domain outside California. CO2 signals refer to the local enhancement or depletion in atmospheric CO2 concentration caused by fossil fuel emissions or biospheric exchange occurring within the region.",
         "license": "proprietary"
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         "description": "This data set contains estimated hourly CO2 atmospheric mole fractions and meteorological observations over North America for the year 2010 at a horizontal grid resolution of 27 km and vertical resolution from the surface to 50 hPa. The data are output from the Penn State WRF-Chem version of the Weather Research and Forecasting (WRF) model using lateral boundary conditions and surface fluxes from the CMS-Flux Inversion system.",
         "license": "proprietary"
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         "description": "This dataset provides information to access NASA Earthdata published flight data and flight information collected by the Alpha Jet Atmospheric eXperiment (AJAX) and associated with the COMEX project in 2014-2015. The file lists information for COMEX-related datasets that has been subsetted from AJAX collections archived through NASA's Atmospheric Science Data Center.  AJAX data are not otherwise replicated in this dataset. AJAX is a partnership between NASA's Ames Research Center and H211, L.L.C., which conducted in-situ measurements over California, Nevada, and the coastal Pacific in support of satellite validation. During COMEX data collection, a Picarro greenhouse gas (GHG) sensor was mounted on an Alpha Jet, a tactical strike fighter developed by Dassault-Breguet and Dornier through a German-French NATO collaboration. The GHG sensor made repeat measurements in California and Nevada. In situ data included measurements of CO2, CH4, and H2O at 2 Hz or CH4 and H2O at 10 Hz with a strategy of characterizing atmospheric structure over ocean and land, and vertical profiles to at least 5000 m.  Ancillary data, including O3, formaldehyde, and meteorological profiles, were also collected. This dataset provides filenames, spatiotemporal bounds, and download URLs for accessing these in situ data. This information is provided in comma separated values (CSV) format.",
         "license": "proprietary"
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         "description": "This dataset lists flight lines and provides data access links and contextual flight information for a subset of the AVIRIS-Classic Facility Instrument Collection that are associated with the CO2 and MEthane eXperiment (COMEX) Project.  The COMEX Project was carried out May through September, 2014. AVIRIS-Classic Facility Instrument data are otherwise not replicated in this dataset. The COMEX Project utilized several measurement capabilities including the AVIRIS-Classic airborne facility instrument data to demonstrate that methane emissions associated with fossil fuel production activities in the Los Angeles, California area were of sufficient magnitude and size for space-based observations.  These lists of the associated COMEX flights from the AVIRIS-Classic Facility Instrument provide flight lines and access information for the Level 1B Calibrated Radiance data and the Level 2 Calibrated Reflectance data.",
         "license": "proprietary"
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         "description": "This dataset lists flight lines and provides data access links and contextual flight information for a subset of the AVIRIS-NG Facility Instrument Collection that are associated with the CO2 and MEthane eXperiment (COMEX) Project.  The COMEX Project was carried out May through September, 2014. AVIRIS-NG Facility Instrument data are otherwise not replicated in this dataset. The COMEX Project utilized several measurement capabilities including the AVIRIS-NG airborne facility instrument data to demonstrate that methane emissions associated with fossil fuel production activities in the Los Angeles, California area were of sufficient magnitude and size for space-based observations.  These lists of the associated COMEX flights from the AVIRIS-NG Facility Instrument provide flight lines and access information for the Level 1B Calibrated Radiance data and the Level 2 Calibrated Reflectance data.",
         "license": "proprietary"
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@@ -56324,7 +56324,7 @@
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         "description": "This dataset provides calibrated at-sensor radiance, retrieved surface brightness temperature, and adaptive coherence estimator (ACE) detection imagery of methane, and a limited number of auxiliary gases collected with the Aerospace Corporation's Mako airborne longwave-IR hyperspectral imager flown during July 22-25, 2014 over a variety of methane generating sites in southern and central California (CA), U.S. These sites included animal husbandry and oil/gas production facilities. Specific study areas included the Coal Oil Point marine seep field off of Goleta, CA, the Kern River oil field complex at Bakersfield, CA, and the extensive stockyards in Chino, CA. The Kern River complex was acquired at 1-m ground sampling distance (GSD), while the other study areas were at 2-m GSD. Levels 1-3 data include single whisk data cubes (L1); at-sensor radiance and sensor performance (L2); surface brightness temperature and ACE detections for specific gases (L3). The data were collected in support of the NASA/ESA COMEX (CO2 and Methane EXperiment) campaign. The data are provided in ENVI and comma separated values (CSV) formats. Quicklook images are included for flight lines and molecule specific detections.",
         "license": "proprietary"
     },
@@ -56766,7 +56766,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345881744-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345881744-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of greenness trends, above- and belowground carbon stocks, and climate variables of the persistent mangrove forests on the coasts of Mexico (PMFM) at a 1 km resolution from 2001 through 2015. Data are available as one-time estimates or across the temporal range; typically as monthly summaries. One-time estimates of aboveground carbon and soil organic carbon stocks for the PMFM derived from existing sources are provided. Also included are the monthly mean normalized difference vegetation index (NDVI) from MOD13A3 used to derive greenness trends, monthly mean air temperature, and total monthly precipitation from Daymet for 2001-2015 across the PMFM. Other files include the distribution and coverage of PMFM across Mexico. Distributions are provided as four categories of PMFM: (1) Arid mangroves with Surface Water as main input, along the Gulf of California and Pacific Coast (ARsw); (2) humid mangroves with surface water input along the Pacific Coast (HUsw-Pa); (3) humid mangroves with surface water input along the coast of the Gulf of Mexico (HUsw-Gf); (4) humid mangroves with groundwater input along the Gulf of Mexico and Caribbean Sea (HUgw). These data provide a baseline for national monitoring programs, carbon accounting models, and greenness trends in coastal wetlands.",
         "license": "proprietary"
     },
@@ -56792,7 +56792,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2788380380-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788380380-ORNL_CLOUD.html",
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         "description": "The Cloud and Aerosol Research Group (CARG) of the University of Washington participated in the SAFARI-2000 Dry Season Aircraft campaign with their Convair-580 research aircraft. This campaign covered five countries in southern Africa from 10 August through 18 September 2000. Various types of measurements were obtained on the thirty-one research flights of the Convair-580 in SAFARI-2000, to study their relationships to simultaneous measurements from satellites (particularly Terra), other research aircraft, and SAFARI-2000 ground-based measurements and activities.",
         "license": "proprietary"
     },
@@ -57624,7 +57624,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389230395-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389230395-ORNL_CLOUD.html",
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         "description": "This dataset provides monthly estimates of biomass stocks and land-atmosphere carbon exchange across the western United States at 0.95 degrees longitude x 1.25 degrees latitude grid resolution from 1998 through 2010. The data include outputs from two types of model simulations: (1) a \"free\" simulation which used Community Land Model (CLM5.0) simulations forced with meteorology appropriate for complex mountainous terrain, and (2) \"assimilation\" runs using the land surface data assimilation system (CLM5-DART). In assimilation runs, the CLM5 vegetation state is constrained by remotely sensed observations of leaf area index and aboveground biomass, which influenced biomass stocks and carbon fluxes.",
         "license": "proprietary"
     },
@@ -57637,7 +57637,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345896855-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345896855-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of carbon pools, fluxes, and associated uncertainties across the contiguous USA (CONUS) at 0.5-degree resolution for all terrestrial land cover types. Carbon pools include labile carbon, foliar carbon, fine root, woody carbon, litter carbon, and soil organic carbon. Carbon fluxes include gross primary production (GPP), net primary production (NPP), net biome exchange, autotrophic respiration, and heterotrophic respiration. The modeled estimates are provided as monthly averages over the 16-year period, 2001 through 2016. The data were derived from the CARbon DAta MOdel fraMework (CARDAMOM) that included climate data, and above and below ground biomass maps of CONUS for the years 2005, 2010, 2015 and 2016 as input data sources to this model-data fusion framework.  The input data were integrated into the CARDAMOM model to constrain on the terrestrial carbon and to specifically attribute changes of forest carbon stocks and spatial distributions of carbon emissions and removals across forested lands. United States Forest Service's Forest Inventory and Analysis (FIA) plot data were used to train models for the prediction of forest above-ground biomass (AGB).",
         "license": "proprietary"
     },
@@ -57962,7 +57962,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2883645605-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2883645605-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of trends in temperature, moisture, and vegetation changes over the circumpolar Arctic. Time series trends were measured by the Theil-Sen slope and associated p-values for a variety of variables including 2-meter air temperature, precipitation, soil moisture, non-frozen season days, permafrost active layer thickness, snow cover, vapor pressure deficit, land surface water fraction, normalized difference vegetation index (NDVI), and vegetation optical depth. Trends were measured annually and over specific seasons of spring (March to May), summer (June to August), autumn (September to November) and winter (December to February), and for the 1980-2020 and 1997-2020 time periods, depending on the variable and original data availability. Emerging hotspots of change were identified for the same variables and seasons, but only over the 1997-2020 period. In addition, a multivariate ranking was used to create combined hotspot layers to show areas of substantial changes in the thermal environment, moisture, and vegetation; these themes reflect landscape changes considered to be detrimental (e.g., a threat) to ecosystems and human populations. Ancillary files provide the boundaries of study regions, Brown permafrost regions, and a land cover product.  The data are provided in cloud optimized GeoTIFF (COG) and shapefile formats.",
         "license": "proprietary"
     },
@@ -57988,7 +57988,7 @@
         "bbox": "-178.24, 47.74, -106.93, 74",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764862016-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764862016-ORNL_CLOUD.html",
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         "description": "This dataset provides two 30-year climate normal data products for conditions during the last glacial maximum (LGM; ~18,000 years ago) and a modern time period (1975-2005) for the entire state of Alaska. The first set of products are monthly climate variable averages at 60 m resolution, including: minimum, maximum, and average temperatures, total precipitation, total surface radiation, rain, snow, potential evapotranspiration (PET), actual evapotranspiration (AET), and water deficit. The second set of products are annual summary climate variable averages for the same variables (excepting average temperature and rain) at 60m, 120m, 240m, 800m, 1km, 2km, 3km, 4km, 5km, 10km and 12km resolutions. The 30-year climate normal monthly averages were derived by topographically downscaling climate variables from existing coarse-resolution general circulation model outputs combined with local weather station data and digital surface models for Alaska for both the LGM and modern time periods at 60 m resolution. From this baseline, monthly averages for total surface radiation, rain, snow, potential evapotranspiration, actual evapotranspiration, and water deficit were also modeled. The annual averages are coarser resolution upsampled versions of the 60 m resolution monthly average data.",
         "license": "proprietary"
     },
@@ -58053,7 +58053,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517679850-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517679850-ORNL_CLOUD.html",
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         "description": "This dataset contains best estimates and uncertainties for mean annual fluxes of inorganic, organic, and total (organic + inorganic) carbon in tidal wetlands, estuaries and shelf waters of eastern North America, which is defined by the coastline running between the tip of the Scotian Peninsula (Canada) and the southern tip of Florida (USA). The data are provided on a per-unit-area basis and as spatially integrated values for each of the three ecosystem types (tidal wetlands, estuaries, and shelf waters) and the entire coastal ecosystem (tidal wetlands + estuaries + shelf waters) as well as for three geographic subregions (the Gulf of Maine, the Mid-Atlantic Bight, and the South Atlantic Bight) and the entire Eastern North America domain (Gulf of Maine + Mid-Atlantic Bight + South Atlantic Bight). The data include the net uptake from the atmosphere by the three ecosystems; burial in tidal wetland soils, estuarine sediments, and continental shelf sediments; riverine input from land to estuaries; and the net lateral advective transports from ecosystem to ecosystem. In addition, heterotrophic respiration (HR), net primary production (NPP), and net ecosystem production (NEP) estimates were computed for each ecosystem. The fluxes were derived using a variety of sources and are estimates for average conditions over the past decades from data covering roughly the period 1976-01-01 to 2017-12-31.",
         "license": "proprietary"
     },
@@ -58066,7 +58066,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345888313-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345888313-ORNL_CLOUD.html",
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         "description": "This dataset provides maps of the elevation of coastal wetlands relative to tidal ranges for the conterminous United States (CONUS) at 30 m resolution for 2010. It also includes maps of tidal amplitude, relative sea-level rise for the period 1983-2001, and maps for coastal lands and low marsh areas based on the probability of being below the mean higher high tide water line for spring tides (MHHWS). Uncertainty layers for elevation maps are also provided.",
         "license": "proprietary"
     },
@@ -58118,7 +58118,7 @@
         "bbox": "-126.71, 23.27, -65.06, 50.66",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2398099021-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2398099021-ORNL_CLOUD.html",
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         "description": "This dataset contains estimates of percent cover of tree, shrub, herb, and other (non-vegetation) lifeform classes and uncertainties for the conterminous U.S. (CONUS). The estimates were derived using quantile regression forest models and indicate the percent of ground covered by a vertical projection of each lifeform class ranging from 0 to 100 percent. Model input data included Landsat surface reflectance (SR) data and 165 airborne LiDAR datasets covering eight of the eleven terrestrial biomes of the conterminous U.S. and Alaska. Eighty-six of the LiDAR acquisitions are part of the NASA Goddard's LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) airborne imager data collection; the remaining 79 sites were acquired by the National Science Foundation's National Ecological Observatory Network Airborne Observation Platform (NEON AOP). Acquisitions were selected based on the availability of the SR data for each G-LiHT and NEON dataset. The data are annual estimates from 1984 to 2018 and were tiled (425 tiles) using the CONUS Landsat Analysis Ready Data (ARD) grid scheme. Data are provided in GeoTIFF format.",
         "license": "proprietary"
     },
@@ -58222,7 +58222,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389081666-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389081666-ORNL_CLOUD.html",
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         "description": "This dataset provides 5 x 5 km gridded estimates of soil organic carbon (SOC) across Latin America that were derived from existing point soil characterization data and compiled environmental prediction factors for SOC. This dataset is representative for the period between 1980 to 2000s corresponding with the highest density of observations available in the WoSIS system and the covariates used as prediction factors for soil organic carbon across Latin America. SOC stocks (kg/m2) were estimated for the SOC and bulk density point measurements and a spatially explicit measure of the SOC estimation error was also calculated. A modeling ensemble, using a linear combination of five statistical methods (regression Kriging, random forest, kernel weighted nearest neighbors, partial least squared regression and support vector machines) was applied to the SOC stock data at (1) country-specific and (2) regional scales to develop gridded SOC estimates (kg/m2) for all of Latin America. Uncertainty estimates are provided for the two model predictions based on independent model residuals and their full conditional response to the SOC prediction factors.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780740663-ORNL_CLOUD.html",
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         "description": "This database is a major update of the Leemans and Cramer database.  It currently contains monthly averages of mean temperature, temperature range, precipitation, rain days and sunshine hours for the terrestrial surface of the globe, gridded at 0.5 degree longitude/latitude resolution.  It was generated from a large data base, using the partial thin-plate splining algorithm.",
         "license": "proprietary"
     },
@@ -58248,7 +58248,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2732596448-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2732596448-ORNL_CLOUD.html",
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         "description": "This dataset contains daily estimates of carbon fluxes in croplands derived from the \"ecosys\" model covering a portion of the Midwestern US (Illinois, Indiana, and Iowa) at county-level resolution from 2001-2018. Ecosys simulates water, energy, carbon, and nutrient cycles simultaneously for various ecosystems, including agricultural systems at up to hourly resolution. Estimates include: gross primary productivity (GPP), net primary productivity (NPP), autotrophic respiration (Ra), heterotrophic respiration (Rh), or net ecosystem exchange (NEE). Data were generated by the ecosys model constrained by observational data, including USDA crop yield from USDA National Agricultural Statistics Service, and a remote-sensing-based SLOPE GPP product. Model performance was evaluated using observations from AmeriFlux towers at agricultural sites within the study area. Agriculture in the US Midwest produces significant quantities of corn and soybeans, which are key elements to the global food supply. The data are provided in shapefile format.",
         "license": "proprietary"
     },
@@ -58261,7 +58261,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2636355304-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2636355304-ORNL_CLOUD.html",
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         "description": "This dataset contains half-hourly ground solar-induced chlorophyll fluorescence (SIF) and vegetation indices including NDVI, EVI, Red edge chlorophyll index, green chlorophyll index, and photochemical reflectance index at seven crop sites in Nebraska and Illinois for the period 2016-2021. Four sites were located at Eddy Covariance (EC) tower sites (sites US-Ne2, US-Ne3, US-UiB, and US-UiC), and three sites were located on private farms (sites Reifsteck, Rund, and Reinhart). The sites were either miscanthus, corn-soybean rotation or corn-corn-soybean rotation. The spectral data for SIF retrieval and hyperspectral reflectance for vegetation index calculation were collected by the FluoSpec2 system, installed near planting, and uninstalled after harvest to collect whole growing-season data. Raw nadir SIF at 760 nm from different algorithms (sFLD, 3FLD, iFLD, SFM) are included. SFM_nonlinear and SFM_linear represent the Spectral fitting method (SFM) with the assumption that fluorescence and reflectance change with wavelength non-linearly and linearly, respectively. Additional data include two SIF correction factors including calibration coefficient adjustment factor (f_cal_corr_QEPRO) and upscaling nadir SIF to eddy covariance footprint factor (ratio_EC footprint, SIF pixel), and measured FPAR from quantum sensors and Rededge NDVI calculated FPAR. The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
@@ -58287,7 +58287,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2162186248-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2162186248-ORNL_CLOUD.html",
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         "description": "This dataset provides near-daily lake area timeseries for 85,358 lakes across four study areas in Northern Canada and Alaska, USA, between May 1 and October 1, 2017. These lake area estimates were produced using digital images from newly developed Planet Labs CubeSats, small satellites with a 4-band (blue, green, red, near-infrared) camera payload. In constellation, CubeSats collected imagery at very high spatial (3-5m) and temporal (near-daily) resolution. From the imagery, each lake's mean, minimum, and maximum areas and seasonal dynamism were derived. The dataset covers four Arctic-Boreal regions: the Yukon Flats Basin (YFB) in eastern interior Alaska, and the Mackenzie River Valley (MRV), Canadian Shield Transect (CST), and Hudson Bay Lowland (HBL) in Canada.",
         "license": "proprietary"
     },
@@ -59899,7 +59899,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777325823-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777325823-ORNL_CLOUD.html",
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         "description": "This data set is a subset of the IGBP DISCover data set, which was derived from the Global Land Cover Characteristics database. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 deg N to 25 deg S, longitude 30 to 85 W). The data are at 1-km resolution in ASCII GRID format.",
         "license": "proprietary"
     },
@@ -59925,7 +59925,7 @@
         "bbox": "-126, 24.5, -62, 53",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389021952-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389021952-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates for export and leaching of dissolved inorganic carbon (DIC), dissolved organic carbon (DOC), total organic carbon (TOC), particulate organic carbon (POC), ammonium (NH4+), nitrate (NO3-), and total organic nitrogen (TON) from the Mississippi River Basin (MRB) to the Gulf of Mexico. The estimates are provided for a historical period of 1901-2014, and a future period of 2010-2099 (carbon estimates only) under two scenarios of high and low levels of population growth, economy, and energy consumption, respectively. The estimates are from the Dynamic Land Ecosystem Model 2.0 (DLEM 2.0). These data are applicable to studying how changes in multiple environmental factors (e.g., fertilizer application, land-use changes, climate variability, atmospheric CO2, and N deposition) affect the dynamics of leaching and export to the Gulf of Mexico.",
         "license": "proprietary"
     },
@@ -60367,7 +60367,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2951624721-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2951624721-ORNL_CLOUD.html",
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         "description": "The dataset provides simulated PM2.5 concentration estimates over Alaska, U.S. PM2.5 (particulate matter with diameter <= 2.5 microns) concentrations  in air (micrograms m-3) are gridded at 0.1-degree resolution for May to September for the years 2001 through 2015. The data were created in a modeling process utilizing the Wildland Fire Emissions Inventory System (WFEIS), the Arctic-Boreal Vulnerability Experiment (ABoVE) Wildfire Date of Burning (WDoB) dataset,  and multiple models including the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The data are provided in GeoTIFF format.",
         "license": "proprietary"
     },
@@ -60380,7 +60380,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2515935936-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515935936-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of methane (CH4) emissions from dairies in California at a resolution of 0.1 degrees (~ 10 km x 10 km) for the year 2019. The mapped sources of dairy CH4 emissions are enteric fermentation and manure management reported in gigagrams per square km per year (Gg km-2 y-1). The sum of the two sources is also provided. These data are in the succession of Vista California (Vista-CA) spatial datasets that have identified and classified potential methane source emitters in California and were created utilizing an assortment of publicly available data sources from local, state, and federal agencies. This dataset can serve as a planning tool for mitigation, a prior for atmospheric observation-based emissions estimates, attribution of emissions to a specific facility, and to validate CH4 emissions reductions from management changes.",
         "license": "proprietary"
     },
@@ -60666,7 +60666,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2531982907-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2531982907-ORNL_CLOUD.html",
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         "description": "This dataset provides annual climate summaries derived from Daymet Version 4 R1 daily data at a 1 km x 1 km spatial resolution for five Daymet variables: minimum and maximum temperature, precipitation, vapor pressure, and snow water equivalent. Annual averages are provided for minimum and maximum temperature, vapor pressure, and snow water equivalent, and annual totals are provided for the precipitation variable. Each data file is provided as a single year by variable and covers the same period of record as the Daymet V4 R1 daily data. The annual climatology files are derived from the larger datasets of daily weather parameters produced on a 1 km x 1 km grid for North America (including Canada, the United States, and Mexico), Hawaii, and Puerto Rico. Separate annual files are provided for the land areas of continental North America, Hawaii, and Puerto Rico. Data are distributed in standardized Climate and Forecast (CF)-compliant netCDF (*.nc) and Cloud Optimized GeoTIFF (*.tif) file formats. In Version 4 R1, all 2020 and 2021 files (60 total) were updated to improve predictions especially in high-latitude areas. It was found that input files used for deriving 2020 and 2021 data had, for a significant portion of Canadian weather stations, missing daily variable readings for the month of January. NCEI has corrected issues with the Environment Canada ingest feed which led to the missing readings. The revised 2020 and 2021 Daymet V4 R1 files were derived with new GHCNd inputs. Files outside of 2020 and 2021 have not changed from the previous V4 release.",
         "license": "proprietary"
     },
@@ -60679,7 +60679,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2532426483-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2532426483-ORNL_CLOUD.html",
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         "description": "This dataset provides Daymet Version 4 R1 data as gridded estimates of daily weather parameters for North America, Hawaii, and Puerto Rico. Daymet variables include the following parameters: minimum temperature, maximum temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length. The dataset covers the period from January 1, 1980, to December 31 (or December 30 in leap years) of the most recent full calendar year for the Continental North America and Hawaii spatial regions. Data for Puerto Rico is available starting in 1950. Each subsequent year is processed individually at the close of a calendar year. Daymet variables are provided as individual files, by variable and year, at a 1 km x 1 km spatial resolution and a daily temporal resolution. Areas of Hawaii and Puerto Rico are available as files separate from the continental North America. Data are in a North America Lambert Conformal Conic projection and are distributed in a standardized Climate and Forecast (CF)-compliant netCDF file format. In Version 4 R1, all 2020 and 2021 files were updated to improve predictions especially in high-latitude areas. It was found that input files used for deriving 2020 and 2021 data had, for a significant portion of Canadian weather stations, missing daily variable readings for the month of January. NCEI has corrected issues with the Environment Canada ingest feed which led to the missing readings. The revised 2020 and 2021 Daymet V4 R1 files were derived with new GHCNd inputs. Files outside of 2020 and 2021 have not changed from the previous V4 release.",
         "license": "proprietary"
     },
@@ -60692,7 +60692,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2532007210-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2532007210-ORNL_CLOUD.html",
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         "description": "This dataset provides Daymet Version 4 R1 monthly climate summaries derived from Daymet Version 4 R1 daily data at a 1 km x 1 km spatial resolution for five Daymet variables: minimum and maximum temperature, precipitation, vapor pressure, and snow water equivalent. Monthly averages are provided for minimum and maximum temperature, vapor pressure, and snow water equivalent, and monthly totals are provided for the precipitation variable. Each data file is yearly by variable with 12 monthly time steps and covers the same period of record as the Daymet V4 R1 daily data. The monthly climatology files are derived from the larger datasets of daily weather parameters produced on a 1 km x 1 km grid for North America, Hawaii, and Puerto Rico. Separate monthly files are provided for the land areas of continental North America (Canada, the United States, and Mexico), Hawaii, and Puerto Rico. Data are distributed in standardized Climate and Forecast (CF)-compliant netCDF (*.nc) and Cloud-Optimized GeoTIFF (*.tif) formats. In Version 4 R1 (ver 4.1), all 2020 and 2021 files (60 total) were updated to improve predictions especially in high-latitude areas. It was found that input files used for deriving 2020 and 2021 data had, for a significant portion of Canadian weather stations, missing daily variable readings for the month of January. NCEI has corrected issues with the Environment Canada ingest feed which led to the missing readings. The revised 2020 and 2021 Daymet V4 R1 files were derived with new GHCNd inputs. Files outside of 2020 and 2021 have not changed from the previous V4 release.",
         "license": "proprietary"
     },
@@ -60705,7 +60705,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751553403-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751553403-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic3BhdGlvLXRlbXBvcmFsIGNoYXJhY3RlcmlzdGljcyBvZiByYWluZmFsbCBpbiBhZnJpY2EsIDAuMjUgZGVncmVlcywgZnJvbSAxOTk4LTIwMTJcIixcIk9STkxfQ0xPVURcIixcIkFmcmljYW5fUmFpbmZhbGxfUGF0dGVybnNfMTI2M1wiLFwiMVwiLDI3NzY4NzQ4NzMsMl0iLCJ1bW0iOiJbXCJzcGF0aW8tdGVtcG9yYWwgY2hhcmFjdGVyaXN0aWNzIG9mIHJhaW5mYWxsIGluIGFmcmljYSwgMC4yNSBkZWdyZWVzLCBmcm9tIDE5OTgtMjAxMlwiLFwiT1JOTF9DTE9VRFwiLFwiQWZyaWNhbl9SYWluZmFsbF9QYXR0ZXJuc18xMjYzXCIsXCIxXCIsMjc3Njg3NDg3MywyXSJ9/Daymet_SubDaily_Puerto_Rico_1977_1",
         "description": "To support high spatial- and temporal-resolution land surface modeling, this dataset provides 3-hourly time step historic weather forcing at 1-km spatial resolution for Puerto Rico and surrounding islands. The latest Daymet V4 data provides gridded historic daily weather observation at 1-km spatial resolution from 1950 to present. Using sub-daily temporal information from two meteorological reanalysis datasets (GSWP3 and NARR), Daymet was further temporally downscaled to 3-hourly time steps and provided in the format required for land surface model simulations. The process of temporal downscaling preserves the relative magnitude in each sub-daily time step from GSWP3 and NARR while maintaining the total and average values from Daymet at each day. These result in two blended datasets: 1950-2014 Daymet-GSWP3 and 1979-2019 Daymet-NARR. Available variables include surface air temperature, precipitation, specific humidity, shortwave and longwave radiation, wind speed, and pressure. These data can be used as a high-resolution meteorological forcing dataset to support high-resolution land surface modeling where accurate meteorological forcing datasets built from historic observations and/or reanalysis datasets are desirable.",
         "license": "proprietary"
     },
@@ -60718,7 +60718,7 @@
         "bbox": "-178.13, 14.07, -53.06, 83.2",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2992264879-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2992264879-ORNL_CLOUD.html",
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         "description": "This dataset provides Daymet Version 4 daily data on a monthly cycle as 1-km gridded estimates of daily weather variables for minimum temperature (tmin), maximum temperature (tmax), precipitation (prcp), shortwave radiation (srad), vapor pressure (vp), snow water equivalent (swe), and day length. Data are derived from the Daymet version 4 software where the primary inputs are daily observations of near-surface maximum and minimum air temperature and daily total precipitation from weather stations. The main algorithm to estimate primary Daymet variables (tmax, tmin, and prcp) at each Daymet grid is based on a combination of interpolation and extrapolation, using inputs from multiple weather stations and weights that reflect the spatial and temporal relationships between a Daymet grid and the surrounding weather stations. Secondary variables (srad, vp, and swe) are derived from the primary variables (tmax, tmin, and prcp) based on atmospheric theory and empirical relationships. The day length (dayl) estimate is based on geographic location and time of year. Data are available for the Continental North America, Puerto Rico, and Hawaii as separate spatial layers in a Lambert Conformal Conic projection and are distributed in standardized Climate and Forecast (CF)-compliant netCDF file formats.",
         "license": "proprietary"
     },
@@ -60731,7 +60731,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2531991823-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2531991823-ORNL_CLOUD.html",
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         "description": "This dataset reports the station-level daily weather observation data and the corresponding cross-validation results for three Daymet model parameters: minimum temperature (tmin), maximum temperature (tmax), and daily total precipitation (prcp) across continental North America (including Canada, the United States, and Mexico), Hawaii, and Puerto Rico. Each data file contains the daily observations and cross-validation results for one parameter for each modeled region and each year, that is, from 1980 to the current calendar year for stations across continental North America and Hawaii and from 1950 to the current year for Puerto Rico. Also included are corresponding station metadata files listing every surface weather station used in Daymet processing for each parameter, region, and year and containing the station name, station identification, latitude, and longitude. The data are provided in netCDF and text formats.  In Version 4 R1, all 2020 and 2021 files were updated to improve predictions especially in high-latitude areas. It was found that input files used for deriving 2020 and 2021 data had, for a significant portion of Canadian weather stations, missing daily variable readings for the month of January. NCEI has corrected issues with the Environment Canada ingest feed which led to the missing readings. The revised 2020 and 2021 Daymet V4 R1 files were derived with new GHCNd inputs. Files outside of 2020 and 2021 have not changed from the previous V4 release.",
         "license": "proprietary"
     },
@@ -60744,7 +60744,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773245356-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773245356-ORNL_CLOUD.html",
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         "description": "This data set provides land use and land cover (LULC) classification products at 100-m resolution for India at decadal intervals for 1985, 1995 and 2005. The data were derived from Landsat 4 and 5 Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Multispectral (MSS) data, India Remote Sensing satellites (IRS) Resourcesat Linear Imaging Self-Scanning Sensor-1 or III (LISS-I, LISS-III) data, ground truth surveys, and visual interpretation. The data were classified according to the International Geosphere-Biosphere Programme (IGBP) classification scheme.",
         "license": "proprietary"
     },
@@ -60770,7 +60770,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2787699948-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2787699948-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZGF5bWV0OiBkYWlseSBzdXJmYWNlIHdlYXRoZXIgZGF0YSBvbiBhIDEta20gZ3JpZCBmb3Igbm9ydGggYW1lcmljYSwgdmVyc2lvbiA0IHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJEYXltZXRfRGFpbHlfVjRSMV8yMTI5XCIsXCI0LjFcIiwyNTMyNDI2NDgzLDEwXSIsInVtbSI6IltcImRheW1ldDogZGFpbHkgc3VyZmFjZSB3ZWF0aGVyIGRhdGEgb24gYSAxLWttIGdyaWQgZm9yIG5vcnRoIGFtZXJpY2EsIHZlcnNpb24gNCByMVwiLFwiT1JOTF9DTE9VRFwiLFwiRGF5bWV0X0RhaWx5X1Y0UjFfMjEyOVwiLFwiNC4xXCIsMjUzMjQyNjQ4MywxMF0ifQ%3D%3D/DeciduousFractionl_CanopyCover_2296_1",
         "description": "This dataset holds deciduous fraction and tree canopy cover at 30-m resolution over the North American boreal domain for 1992 to 2015. Deciduous fraction is the areal percentage of deciduous trees relative to all tree canopy cover within a pixel, and tree canopy cover is the areal percentage of a pixel that is covered by tree canopy.  Deciduous fraction values are valid only for pixels with tree canopy cover >25 percent. Normalized difference vegetation index (NDVI)-based median-value image composites were derived from Landsat 5, 7, and 8 Collection 1 surface reflectance datasets for years 1987-1997, 1998-2002, 2003-2007, 2008-2012, and 2013-2018 to create composites for nominal years 1992, 2000, 2005, 2010, and 2015, respectively. These image composites were prepared for early spring, mid-summer, and mid-to-late fall seasons to identify key differences in deciduous and evergreen green-up amplitudes. Random Forest (RF) regression models were used to derive deciduous fraction and tree canopy cover from the image composites. These models were trained with data from in-situ samples across Alaska and Canada from a variety of studies. Seventy percent of the in-situ samples were used for training and 30% for validation. Per-pixel uncertainty for both deciduous fraction and tree canopy cover are included and were based on one standard deviation of output values across all decision trees in the RF regression. These datasets were developed as part of NASA's ABoVE project to capture forest composition changes over the North American boreal domain across the last several decades. The data are provided in GeoTIFF format.",
         "license": "proprietary"
     },
@@ -60822,7 +60822,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2484970169-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2484970169-ORNL_CLOUD.html",
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         "description": "This dataset provides river discharge measurements collected at selected locations in the Atchafalaya and Terrebonne Basins within the Mississippi River Delta (MRD) floodplain in coastal Louisiana, USA. The measurements were made during the Delta-X 2021 field efforts from 2021-03-25 to 2021-04-11 (spring) and 2021-08-16 to 2021-09-25 (fall). Channel surveys were conducted with a Teledyne RiverPro acoustic doppler current profiler (ADCP) or a Sontek M9 RiverSurveyor ADCP on selected wide channels (>100 m wide) and a few selected narrow channels (approximately 10 m wide) near the Delta-X intensive study sites. River discharge was measured on cross-channel transects. Reported data include bathymetry, discharge (m3 s-1), and flow velocity.",
         "license": "proprietary"
     },
@@ -60835,7 +60835,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2795126898-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2795126898-ORNL_CLOUD.html",
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         "description": "This dataset contains total aboveground biomass (AGB) and necromass (AGN), and total carbon, total nitrogen, and total phosphorus content of aboveground biomass (AGB) and necromass (AGN) samples collected from herbaceous wetlands in the Atchafalaya and Terrebonne basins in southeastern coastal Louisiana during 2021. Field measurements were conducted at three sites in the Atchafalaya basin and three sites in the Terrebonne basin. Five of the sites are adjacent to sites from the Coastwide Reference Monitoring System (CRMS). The other site is located in Wax Lake Delta (WLD) without appropriate adjacent CRMS sites. All AGB and AGN plant material within each plot was clipped at soil level, stored in plastic bags, and transported to the laboratory for further analyses. Herbaceous wetland sites in both basins were chosen to represent a salinity gradient including freshwater, brackish, and saline ecosystems. These data cover the period 2021-03-19 to 2021-03-31 (spring) and 2021-08-19 to 2021-08-27 (fall).",
         "license": "proprietary"
     },
@@ -60848,7 +60848,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3091330782-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3091330782-ORNL_CLOUD.html",
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         "description": "This dataset provides ANUGA hydrodynamic modeling results and input run-scripts for the Atchafalaya basin in the Mississippi River Delta in southern Louisiana, USA, during three windows of time corresponding to the Delta-X and Pre-Delta-X field campaigns in fall 2016, spring 2021, and fall 2021. ANUGA is a 2D depth-integrated hydrodynamic model which uses the Finite Volume Method (FVM) to numerically solve the shallow water momentum and continuity equations for fluid flow in broad-scale geophysical systems. Each iteration of the model was extensively calibrated using a database of in-situ and remotely-sensed observations, including about 54 water level gauges, numerous water surface profiles collected by AirSWOT or lidar, and water level change measurements derived from UAVSAR. The model was forced using observational data collected from NOAA and USGS, and the model mesh was specifically designed to capture channel-island connectivity using high-resolution Planet Labs imagery spanning over a decade. In total, over a month of simulation outputs are included in this dataset, covering different seasons and hydrological conditions in the Atchafalaya and Wax Lake Delta systems. These model outputs can be leveraged with other Delta-X datasets to provide contextual information about water levels or flow velocities at different times or locations within the Atchafalaya basin, and the model codes provided can be used to simulate additional time periods for further analysis in this region. Model outputs are presented in NetCDF (*.nc) format and run-scripts are in Python (*.py) or contained in compressed (*.zip) file format.",
         "license": "proprietary"
     },
@@ -60861,7 +60861,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3091322507-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3091322507-ORNL_CLOUD.html",
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         "description": "This dataset comprises the primary inputs and outputs from the ANUGA hydrodynamic model for spring 2021 (2021-03-20 to 2021-04-04). These dates align with the 2021 Delta-X Spring Campaign. Data cover the Atchafalaya and Terrebonne basins of the Mississippi River Delta in southern Louisiana, USA. ANUGA is a 2D depth-integrated hydrodynamic model which uses the Finite Volume Method (FVM) to numerically solve the shallow water momentum and continuity equations for fluid flow in broad-scale geophysical systems. The inputs consist of a modified digital elevation (DEM) model, a spatial classification of the friction coefficient modified, and the model's unstructured grid with boundary condition locations. The model's outputs include two weeks of predictions of water levels and mean horizontal velocities at each mesh node at a 30-minute time step. Outputs are provided in NetCDF format, and inputs are provided in GeoTIFF and comma separated values (CSV) format. Also included are MP4 videos (*.mp4) that provide visual summaries of the outputs.",
         "license": "proprietary"
     },
@@ -60874,7 +60874,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2795127798-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2795127798-ORNL_CLOUD.html",
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         "description": "This dataset contains total belowground biomass (BGB) and necromass (BGN), and total carbon, total nitrogen, and total phosphorus content of  samples collected from herbaceous wetlands in the Atchafalaya and Terrebonne basins of the Mississippi River Delta in southeastern coastal Louisiana, U.S., during March and August 2021. The data were collected during the Delta-X Spring and Fall deployments. Field measurements were conducted at three sites in the Atchafalaya basin and three sites in the Terrebonne basin. Five of the sites are adjacent to sites from the Coastwide Reference Monitoring System (CRMS). The other site is located in Wax Lake Delta (WLD) without appropriate adjacent CRMS sites. Herbaceous wetland sites in both basins were chosen to represent a salinity gradient including freshwater, brackish, and saline ecosystems. Root biomass samples were collected using a gouge soil auger.",
         "license": "proprietary"
     },
@@ -60887,7 +60887,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2769454572-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2769454572-ORNL_CLOUD.html",
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         "description": "This dataset contains carbon-13 (13C) and nitrogen-15 (15N) isotopic signatures of belowground root biomass samples from herbaceous wetlands in the Atchafalaya and Terrebonne basins of the Mississippi River Delta in coastal Louisiana, U.S., during August 2021. The data were collected during the Delta-X Fall deployment. Field measurements were conducted at three sites in the Atchafalaya basin and three sites in the Terrebonne basin. Five of the sites are adjacent to sites from the Coastwide Reference Monitoring System (CRMS). The other site is located in Wax Lake Delta (WLD) without appropriate adjacent CRMS sites. Herbaceous wetland sites in both basins were chosen to represent a salinity gradient including freshwater, brackish, and saline ecosystems. Root biomass samples were collected using a gouge soil auger. Bulk isotopic signatures in living fine roots were measured with a mass spectrometer coupled to an elemental analyzer.",
         "license": "proprietary"
     },
@@ -60900,7 +60900,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776378726-ORNL_CLOUD.html",
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         "description": "This dataset provides an updated digital elevation model (DEM) for the Atchafalaya and Terrebonne basins in coastal Louisiana, USA. The DEM is updated from the Pre-Delta-X DEM and extended to the full Delta-X study area. This DEM was developed from multiple data sources, including sonar data collected during Pre-Delta-X and Delta-X campaigns, bathymetric data from the Coastal Protection and Restoration Authority System-Wide Assessment and Monitoring System (CPRA SWAMP), and NOAA, and topography from the National Elevation Dataset and LiDAR from US Geological Survey (USGS). The provided data layers include the DEM, a binary water/land mask, data source flags, and eight layers with analysis weighting factors for each pixel. Elevation values are provided in meters with respect to the North American Vertical Datum of 1988 (NAVD88). The weighting factors indicate how each data source contributed to this multisource DEM. The data are provided in cloud-optimized GeoTIFF (CoG) format.",
         "license": "proprietary"
     },
@@ -60913,7 +60913,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2857067302-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857067302-ORNL_CLOUD.html",
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         "description": "This dataset contains the Delft3D model of the intensive site 294 in the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall deployments in 2021 and include hydrodynamics and sediment transport. All files required to run the simulations are included. The model's output of water velocity and depth-averaged sediment concentrations are provided for both deployments. The dataset includes annual inorganic mass accumulation rates derived through modelling intra-annual variability in water levels and suspended sediment concentrations. The data are provided in netCDF format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857070149-ORNL_CLOUD.html",
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         "description": "This dataset contains the Delft3D model of the intensive site 322 in the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall deployments in 2021 and include hydrodynamics and sediment transport. All files required to run the simulations are included. The model's output of water velocity and depth-averaged sediment concentrations are provided for both deployments. The dataset includes annual inorganic mass accumulation rates derived through modelling intra-annual variability in water levels and suspended sediment concentrations. The data are provided in netCDF and ENVI formats.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857072572-ORNL_CLOUD.html",
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         "description": "This dataset contains the Delft3D model of the intensive site 396 in the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall deployments in 2021 and include hydrodynamics and sediment transport. All files required to run the simulations are included. The model's output of water velocity and depth-averaged sediment concentrations are provided for both deployments. The dataset includes annual inorganic mass accumulation rates derived through modelling intra-annual variability in water levels and suspended sediment concentrations. The data are provided in netCDF format.",
         "license": "proprietary"
     },
@@ -60952,7 +60952,7 @@
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         "description": "This dataset contains the Delft3D model of the intensive site 399 in the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall deployments in 2021 and include hydrodynamics and sediment transport. All files required to run the simulations are included. The model's output of water velocity and depth-averaged sediment concentrations are provided for both deployments. The dataset includes annual inorganic mass accumulation rates derived through modelling intra-annual variability in water levels and suspended sediment concentrations. The data are provided in netCDF format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2857068056-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857068056-ORNL_CLOUD.html",
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         "description": "This dataset contains the Delft3D model of the intensive site 421 in the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall deployments in 2021 and include hydrodynamics and sediment transport. All files required to run the simulations are included. The model's output of water velocity and depth-averaged sediment concentrations are provided for both deployments. The dataset includes annual inorganic mass accumulation rates derived through modelling intra-annual variability in water levels and suspended sediment concentrations. The data are provided in netCDF format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2857065166-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857065166-ORNL_CLOUD.html",
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         "description": "This dataset contains the Delft3D model of the Atchafalaya Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall campaigns in 2021 and include hydrodynamics, waves, and sediment transport. Bottom friction was calibrated using AirSWOT water elevation data, while sediment parameters were calibrated using AVIRIS-NG Total Suspended Solids (TSS) data. All files required to run the simulations are included. Model output of water levels, velocity, and depth-averaged sediment concentration are provided for both campaigns as netCDF files. The dataset includes a netCDF file containing the annual inorganic mass accumulation rates derived from simulations.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2857063249-ORNL_CLOUD.html",
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         "description": "This dataset contains the Delft3D model of the Terrebonne Basin along the Mississippi River Delta (MRD) in coastal Louisiana. Simulations cover the Delta-X Spring and Fall campaigns in 2021 and include hydrodynamics, waves, and sediment transport. Bottom friction was calibrated using AirSWOT water elevation data, while sediment parameters were calibrated using AVIRIS-NG Total Suspended Solids (TSS) data. All files required to run the simulations are included. The model's output of water levels, velocity, and depth-averaged sediment concentrations are provided for both campaigns as netCDF files. The dataset includes a netCDF file containing the annual inorganic mass accumulation rates derived through a storms analysis and modelling.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2550501926-ORNL_CLOUD.html",
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         "description": "This product delineates the Mississippi River Delta (MRD) landscape into distinct ecogeomorphic cells, which are small contiguous areas of land with similar ecological and geomorphological characteristics. The study area is the Atchafalaya and Terrebonne basins of the MRD in southern Louisiana, U.S., which was the focus of NASA's 2021 Delta-X campaign. Each ecogeomorphic cell is a small homogeneous area of similar vegetation and elevation (or bathymetry). A \"cell\" typically consists of a cluster of contiguous pixels in a raster image, although cells of single pixels are present. The elevation was derived from the USGS Digital Elevation Model, and the vegetation was characterized by its spectral signature as measured by near infrared (NIR) reflectance and normalized difference vegetation index (NDVI). NIR and NDVI were computed from Sentinel-2 images acquired January through September 2021. The data are provided in shapefile and GeoTIFF formats. The vector shapefiles contain the distinct ecogeomorphic cells as polygons with unique labels (i.e., ID number). A raster image of these ecogeomorphic cells provided wherein the pixel values are the polygon labels from the shapefiles. The GeoTIFFs hold the mean and standard deviations of bathymetry, NIR, and NDVI spectral indices within each ecogeomorphic region (polygon). The raster data are provided with a spatial resolution of 0.000045 degrees (approximately 5 meters).",
         "license": "proprietary"
     },
@@ -61017,7 +61017,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2840822190-ORNL_CLOUD.html",
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         "description": "This dataset provides elevation, hydrogeomorphic zone classification, soil carbon content, bulk density, organic matter content, and sediment accretion measurements collected at feldspar stations established near Louisiana's Coastwide Reference Monitoring Systems (CRMS) sites and on Mike Island in Wax Lake Delta (WLD). Feldspar stations were established to capture recent sediment deposition rates across hydrogeomorphic zones defined as discrete surface elevation ranges relative to NAVD88 (e.g., subtidal < -0.04 m, intertidal -0.04 m to 0.30 m, and supratidal > 0.30 m). Hydrogeomorphic zones classification was based on marsh surface elevations extracted from the U.S. Geological Survey (USGS) Atchafalaya 2 project LiDAR Survey 2012 digital elevation model and field GPS measurements in November - December 2020. Between two and three feldspar stations were deployed approximately 25 and 50 meters from the main channel to represent existing hydrogeomorphic zones in brackish and saline emergent marsh vegetation, tidal freshwater emergent marshes, and forested swamps. Cryocore technique was used to determine recent sediment deposition. Soil samples were collected to determine organic and inorganic fractions and organic carbon content. This dataset is from the Delta-X field studies conducted during Fall 2020, Spring 2021, Fall 2021, Spring 2022, Fall 2022, and Spring 2023.  The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
@@ -61030,7 +61030,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2769434781-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZGVsdGEteDogY2FsaWJyYXRlZCBhbnVnYSBoeWRyb2R5bmFtaWMgb3V0cHV0cyBmb3IgdGhlIGF0Y2hhZmFsYXlhIGJhc2luLCBtcmQsIGxhXCIsXCJPUk5MX0NMT1VEXCIsXCJEZWx0YVhfQU5VR0FfQXRjaGFmYWxheWFCYXNpbl8yMzA2XCIsXCIxXCIsMzA5MTMzMDc4MiwyXSIsInVtbSI6IltcImRlbHRhLXg6IGNhbGlicmF0ZWQgYW51Z2EgaHlkcm9keW5hbWljIG91dHB1dHMgZm9yIHRoZSBhdGNoYWZhbGF5YSBiYXNpbiwgbXJkLCBsYVwiLFwiT1JOTF9DTE9VRFwiLFwiRGVsdGFYX0FOVUdBX0F0Y2hhZmFsYXlhQmFzaW5fMjMwNlwiLFwiMVwiLDMwOTEzMzA3ODIsMl0ifQ%3D%3D/DeltaX_Foliar_Stable_Isotopes_2194_1",
         "description": "This dataset contains foliar tissue C and N bulk isotopic signatures (delta 13C, delta 15N) of dominant wetland herbaceous species collected at six sites in the Atchafalaya (N = 3) and Terrebonne (N = 3) basins in coastal Louisiana. Five of the sites are from the Coastwide Reference Monitoring System (CRMS) and one site is the Mike Island Site in the Wax Lake Delta (WLD). For the herbaceous wetland sites, Aboveground biomass (AGB) was harvested inside duplicate plots (0.25 m2), located 5 m apart at each sampling station. All plant material within each plot was clipped at soil level, stored in plastic bags, and transported to the laboratory for further analyses. In the lab, plant tissue (foliar) C and N bulk isotopic signatures were analyzed for two dominant plant species from each site using a Thermo Scientific Delta V Plus CF-IRMS coupled to a Carlo-Erba 1108 elemental analyzer via a ConFlo IV interface (Thermo Fisher Scientific, Waltham, MA, USA). The data were collected during 2021-08-19 to 2021-08-27 during the Delta-X Fall 2021 deployment.",
         "license": "proprietary"
     },
@@ -61043,7 +61043,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2633820146-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2633820146-ORNL_CLOUD.html",
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         "description": "This dataset contains water surface elevations collected from boat surveys performed on August 24 and September 22-25, 2021, across the Atchafalaya and Terrebonne basins in the Mississippi River Delta (MRD) floodplain, during the Delta-X Fall 2021 deployment. To perform the surveys, a Global Navigation Satellite System (GNSS) antenna (Septentrio receiver) was mounted on the side of the boat on a pole directly above the depth sounder. This GNSS antenna recorded observations of elevation continuously at 1 Hz on all field days. These data were post-processed using precise point positioning (PPP) and converted to water surface elevation by subtracting the height of the antenna above the water surface when it was mounted on the boat to provide an estimate of water surface elevation.The data are limited to times when the boat was moving slowly enough such that its speed didn't affect the height of the antenna above the water. The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
@@ -61056,7 +61056,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2772852265-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2772852265-ORNL_CLOUD.html",
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         "description": "This dataset contains properties of soil core samples for herbaceous wetlands collected in the Atchafalaya and Terrebonne basins in southeastern coastal Louisiana for the period 2021-03-21 to 2021-04-02 and on 2021-08-19. Field measurements were conducted at six sites in the Atchafalaya (N = 3) and Terrebonne (N = 3) basins. Five sites were adjacent to sites from the Coastwide Reference Monitoring System (CRMS). The other site is in the Wax Lake Delta (WLD) without appropriate adjacent CRMS sites. Herbaceous wetland sites in both basins were chosen to represent a salinity gradient including freshwater, brackish and saline ecosystems. Soil properties include bulk density, organic matter content, total densities of carbon, nitrogen, phosphorus, along with 13C and 15N isotopic signatures. The data are provided in comma-separated values (.csv) format.",
         "license": "proprietary"
     },
@@ -61069,7 +61069,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2482186619-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2482186619-ORNL_CLOUD.html",
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         "description": "This dataset provides measurements of particulate organic carbon (POC) concentrations made on water samples collected during 2021 in surface waters of the Atchafalaya River and Terrebonne Basins, portions of the Mississippi River Delta in coastal Louisiana. Water samples were collected at ~0.5 m depth from surface during the spring (2021-03-25 to 2021-04-22) and fall (2021-08-14 to 2021-09-24) field efforts. Field sampling was paused on August 25 and resumed on September 13 due to the landfall of Hurricane Ida on 2021-08-26 approximately 70 km east of the study sites. Water quality changes in this dataset caused by the hurricane are expected to be minimal. Samples were collected in multiple channels of varying width (from a few meters to >100 m) near Delta-X intensive study sites, in open bays and lakes, and a few locations in the nearshore Gulf of Mexico. For each sample, the water sample volume was filtered (in triplicate) through 25-mm glass microfiber (GF/F) filters to retain the suspended particles. The amount of organic carbon retained on each filter was measured using an elemental carbon, hydrogen and nitrogen (CHN) analyzer and normalized by the volume of sample water filtered. The reported values in this dataset include the mean and standard deviation of POC measurements from three replicate samples collected at each site.",
         "license": "proprietary"
     },
@@ -61082,7 +61082,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2772847105-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2772847105-ORNL_CLOUD.html",
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         "description": "This dataset includes above water measurements of remote-sensing reflectance measured in situ at field sampling stations during the Delta-X 2021 field efforts. Measurements were collected in the Atchafalaya River and Terrebonne Basins on the southern coast of Louisiana from 2021-03-25 to 2021-04-22 (spring) and from 2021-08-14 to 2021-09-24 (fall). Field sampling was paused on 2021-08-25 and resumed on 2021-09-13 due to the landfall of Hurricane Ida on 2021-08-26 approximately 70 km east of the study site. Water quality changes caused by the hurricane were expected to be minimal. Reflectance was measured near-simultaneously with collection of field samples and in-water sediment parameters in multiple channels of varying width (from a few meters to >100 m), near Delta-X intensive study sites, in open bays and lakes, and at a few locations in the nearshore Gulf of Mexico. For each in situ collection, a handheld Portable SpectroRadiometer (PSR-1100f, Spectral Evolution) was used to measure radiance from: (a) a highly reflective (>99% reflectance) Lambertian Spectralon panel (b) from the sky, measured at 40 degrees from the solar zenith and at 135 degrees from the sun azimuthal plane, (c) from the water, measured at 40 degrees from nadir and at 135 degrees from the sun azimuthal plane. These measurements were used to calculate remote-sensing reflectance and the water-leaving radiance relative to downwelling irradiance, including a correction for the influence of reflected skylight. In Version 3, the data files with this dataset replace and update the data files in Version 2. A minor update was made to the code used to calculate the remote sensing reflectance (Rrs). These data are provided in comma-separated values (.csv) format.",
         "license": "proprietary"
     },
@@ -61095,7 +61095,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2482190536-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2482190536-ORNL_CLOUD.html",
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         "description": "This dataset provides in situ measurements of water temperature (degrees C), salinity (PSU), turbidity (FNU), and chlorophyll-a fluorescence (RFU) in surface of the Atchafalaya River and Terrebonne Basins during the Spring (2021-03-25 to 2021-04-22) and Fall (2021-08-14 to 2021-09-24) field efforts by the Delta-X project. Field sampling was paused on August 25 and resumed on September 13, 2021, due to the landfall of Hurricane Ida on 2021-08-26 approximately 70 km east of the study site. Water quality changes caused by the hurricane were expected to be minimal. Measurements were collected in multiple channels of varying width (from a few meters to >100 m), near Delta-X intensive study sites, in open bays and lakes, and at a few locations in the nearshore Gulf of Mexico using either a YSI ProDSS water quality probe or a YSI EXO3 water quality probe.",
         "license": "proprietary"
     },
@@ -61108,7 +61108,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2428215662-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2428215662-ORNL_CLOUD.html",
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         "description": "This dataset includes model code and output for a model that simulates changes in islands and small water channels of river delta systems in response to dynamics of sediment deposit, erosion, and changing water levels. Simulations demonstrate developmental cycles of secondary channels and how sediment dynamics can allow islands to build land vertically to keep pace with rising sea levels rather than passively drowning. The model was applied to the Mississippi River Delta as part of NASA's Delta-X project. Simulations were run for other river deltas, including the Amazon, Brahmputra, Danube, Magdalena, Nile, Orinoco, Parana, Rhine-Meuse, and Rhone rivers. The model code is provided in text format for MATLAB software. Files demonstrating initial model conditions and outputs are provided in binary MATLAB as well as NetCDF version 4 format.",
         "license": "proprietary"
     },
@@ -61121,7 +61121,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2255219113-ORNL_CLOUD.html",
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         "description": "This dataset contains UAVSAR Level 1B (L1B) interferometric products for Delta-X flight lines acquired during the 2021 Spring (2021-03-27 to 2021-04-18) and Fall (2021-09-03 to 2021-09-13) deployments. The data were collected by Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), a polarimetric L-band synthetic aperture radar flown on the NASA Gulfstream-III (C20) aircraft as part of the Delta-X campaign. The study area includes the Atchafalaya Basin, in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Repeat pass interferometric synthetic aperture (InSAR) data are a standard UAVSAR product delivered by the UAVSAR processing team. For this dataset, a set of nearest-neighbor (NN), NN+1, and NN+2 co-registered VV-polarization interferograms were generated from the quad-polarization SLC stack level-1 (L1) product using a combination of the InSAR Scientific Computing Environment (ISCE), the statistical-cost, network-flow algorithm for phase unwrapping (SNAPHU), and previously developed python code. Data quality was assessed by comparing water elevation estimates with data from in situ water level gauges throughout the study area. The data are provided in non-georeferenced ENVI file format and include interferometric amplitude, wrapped interferometric phase, interferometric coherence, and unwrapped interferometric phase products. Geometry files for each flight line per field campaign with latitude, longitude, height and incidence angle information are also included. The goal of this campaign was to measure water-level changes throughout wetlands, and these data may be used to generate time series of water levels. The data are provided in ENVI format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2256471725-ORNL_CLOUD.html",
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         "description": "This dataset provides Level 1B (L1B) radiance products from NASA's Airborne Visible Infrared Imaging Spectrometer- Next Generation (AVIRIS-NG) instrument acquired over the Atchafalaya and Terrebonne basins of the Mississippi River Delta, Louisiana, USA during two deployments; spring and fall of 2021. All flights were flown on a Dynamic Aviation King Air B200. There are a combined 200 total flight lines for the spring and fall 2021 deployments; spring 2021 had 75 flight lines, fall 2021 had 175 flight lines.  AVIRIS-NG measures reflected radiance at 5-nanometer (nm) intervals in the visible to shortwave infrared spectral range between 380 and 2510 nm. Level 1B data are orthorectified calibrated radiance values in units of spectral radiance in which raw digital numbers (DNs) are translated to units of radiant intensity measured at the sensor. Measurements are radiometrically and geometrically calibrated and provided at approximately 5-meter spatial resolution, dependent on aircraft altitude. Additional flight line files include band information of observational geometry and illumination parameters, as well as geographic pixel locations and elevation. These L1B data are provided in ENVI file format.  AVIRIS-NG Cal/Val, Level 2 and Level 3 products for the Pre-Delta-X and Delta-X missions are provided in related datasets.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2256889308-ORNL_CLOUD.html",
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         "description": "This dataset contains UAVSAR Level 1 (L1) Single Look Complex (SLC) stack products for Delta-X flight lines acquired during 2021-03-27 to 2021-04-18 (spring) and 2021-09-03 to 2021-09-13 (fall). The data were collected by Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), a polarimetric L-band synthetic aperture radar flown on the NASA Gulfstream-III (C20) aircraft as part of the Delta-X campaign. The study area includes the Atchafalaya Basin, in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Repeat pass interferometric synthetic aperture (InSAR) data are a standard UAVSAR product delivered by the UAVSAR processing team. These repeat pass SLC stack co-registered time series data were used as the underlying data for higher level data products. These higher level products provide a time series of water level changes and address a goal of the Delta-X campaign to measure water-level changes throughout wetlands. Data quality was assessed by comparing water elevation estimates with data from in situ water level gauges throughout the study area. These L1 data contain slant range single look complex (SLC), latitude/longitude/height, look vector, doppler, and metadata files. The data are provided in SLC stack format (*.slc) with associated annotation (*.ann), latitude-longitude-height (*.llh), look vector (*.lkv), and Doppler centroid-slant range (*.dop) files.  The single look complex (SLC) stacks are in the HH, HV, VH, and VV polarizations. The same area was sampled at approximately 30-minute intervals. The SLCs are not corrected for residual baseline (BU).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2428617287-ORNL_CLOUD.html",
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         "description": "This dataset contains AirSWOT interferogram products collected during the 2021 Delta-X Campaign over the Atchafalaya and Terrebonne Basins of the Mississippi River Delta, Louisiana, USA from 2021-03-26 to 2021-04-18 (Spring) and 2021-08-21 to 2021-09-12 (Fall). AirSWOT uses near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. AirSWOT elevation data is useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions. The AirSWOT Level 1B (L1B) data products represent interferogram data in the radar coordinate system, not in georeferenced map coordinates. This is an earlier stage of data processing which is used to generate the later Level 2 and Level 3 data products which will contain georeferenced water heights and water height profiles for river channels in each basin. The data are provided in binary and text file formats.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2707162636-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2707162636-ORNL_CLOUD.html",
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         "description": "This data provides AVIRIS-NG Bidirectional Reflectance Distribution Function (BRDF) and sunglint-corrected surface spectral reflectance images over the Atchafalaya and Terrebonne basins of the Mississippi River Delta (MRD) of coastal Louisiana, USA. Flights were acquired during the Spring and Fall 2021 deployments of the Delta-X campaign. The imagery was acquired by the Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) from 2021-03-27 to 2021-04-06 and 2021-08-18 to 2021-09-25. Reflectance data are provided as file sets for each flight line. In addition, ten files of mosaicked flight lines, by time period and over four locations (labeled Terre, Atcha, TerreEast, and Bara), are included. Files are presented as compressed (*.zip) files, containing binary ENVI image and header files. Only land pixels were corrected and mask files for the mosaic file coverage showing presence/absence of water are also included. For the Delta-X mission, these data serve to better understand rates of soil erosion, accretion, and creation in the delta system, with the goal of building better models of how river deltas will behave under relative sea level rise.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2430019879-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2430019879-ORNL_CLOUD.html",
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         "description": "This dataset provides Level 2 (L2) atmospherically corrected surface reflectance data acquired from NASA's Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over regions of interest in the Atchafalaya and Terrebonne basins on the southern coast of Louisiana, United States. Data were collected as part of the Delta-X Spring and Fall 2021 deployments that occurred from 2021-03-27 to 2021-04-06 and from 2021-08-18 to 2021-08-25. Additionally, L2 data from flights flown specifically to capture the Significant Event of Hurricane Ida are provided.  This includes 56 files from flights conducted following Hurricane Ida from 2021-09-23 to 2021-09-25. Hurricane Ida made landfall over this region on 2021-08-29. AVIRIS-NG is a pushbroom spectral mapping system with a high signal-to-noise ratio (SNR) designed for high performance imaging spectroscopy. AVIRIS-NG measures the wavelength range from 380 nm to 2510 nm with 5-nm sampling resolution. For this dataset, spatial resolution varies from 3.8-5.4 meters. For this campaign, the AVIRIS-NG instrument was deployed on the Dynamic Aviation King Air B200 platform. This dataset represents one part of a multisensor airborne sampling campaign conducted by different aircraft teams for the Delta-X Campaign. Data are provided in ENVI file format.",
         "license": "proprietary"
     },
@@ -61199,7 +61199,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3235809207-ORNL_CLOUD.html",
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         "description": "This dataset contains Level 2 (L2) AirSWOT geocoded products, including estimated water surface elevation. The AirSWOT instrument is a Ka-band interferometer and for this study is flown on the King Air B200 platform. Data were collected during the DeltaX airborne campaign over the Atchafalaya and Terrebonne basins of the Mississippi River Delta, Louisiana, USA. Flights occurred during the Delta-X Spring 2021 deployment from 2021-03-26 to 2021-04-18 and the Delta-X Fall 2021 deployment from 2021-08-21 to 2021-09-12. AirSWOT is capable of producing high resolution (3.6 m) digital elevation models over land and water bodies using near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. The instrument includes six antennas that form multiple baseline pairs for along-track and across-track interferometry. AirSWOT elevation data are useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions and is an airborne calibration and validation instrument for the Surface Water and Ocean Topography (SWOT) satellite. This Version 3 dataset provides updated data files due to an updated Calumet survey that changed the water level by 0.138 m. This resulted in all the AirSWOT water levels changing by that same amount. For these L2 products, only the estimated water surface elevation in respect to the WGS84 ellipsoid surface, and estimated height above the NAVD88 (GEOID12B) vertical datum files changed. Note that data acquired on September 1 and September 5, 2021 do not meet the expected MAE in-situ comparison and should be used with caution. This dataset contains cloud optimized GeoTIFF rasters in UTM map coordinates for each flight line. In addition, a text file provides basic metadata, including flight line ID, start and end UTC times of data acquisition, processor version number, and the date and time of different processing stages.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2428388674-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2428388674-ORNL_CLOUD.html",
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         "description": "This dataset contains georeferenced UAVSAR Level 2 (L2) interferometric products for Delta-X flight lines acquired during the spring (2021-03-27 to 2021-04-18) and fall (2021-09-03 to 2021-09-13) deployments. This dataset provides water-level change observations throughout wetlands of the Atchafalaya and Terrebonne Basins, in Southern Louisiana, USA, within the Mississippi River Delta (MRD), and it may be used to generate time series analysis. The data were collected by Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), a polarimetric L-band synthetic aperture radar flown on the NASA Gulfstream-III (C20) aircraft as part of the Delta-X campaign. Water surface elevations were measured on multiple flights at 30-minute intervals. Data quality was assessed by comparing water elevation estimates with data from in situ water level gauges throughout the study area. The data include interferogram phase, interferogram amplitude, unwrapped interferogram phase, and coherence products. A series of quality assurance masks of troposphere-induced phase delay regions were generated for all SAR acquisition dates using a weather feature matching algorithm. Geometry files for each flight line per field campaign with latitude, longitude, height and incidence angle information are also included. The data are provided in ENVI format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2633820894-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2633820894-ORNL_CLOUD.html",
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         "description": "This dataset includes high-resolution (~5 m) gridded estimates of herbaceous aboveground biomass (AGB) for the Atchafalaya and Terrebonne basins of the Mississippi River Delta in coastal Louisiana, USA, for the fall and spring seasons of 2021. AGB, quantified as dry biomass in Mg per hectare, was estimated from Bidirectional Reflectance Distribution Function (BRDF)-adjusted surface reflectance products from NASA's Airborne Visible Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) acquired over the study area in April and August 2021. The BRDF-adjusted reflectance was derived from hemispherical-directional surface reflectance with atmospheric correction. A machine learning model to estimate AGB was generated by comparing local pixel reflectance spectra with coincident in-situ samples of herbaceous vegetation AGB. This model was then scaled to the AVIRIS-NG mosaic imagery to map herbaceous AGB across the Atchafalaya and Terrebonne Basins. The Delta-X campaign conducted both airborne (remote sensing) and field (in situ) measurements to measure hydrology, water quality (e.g., total suspended solids (TSS)), and vegetation structure. These data serve to better understand rates of soil erosion, accretion, and creation in the delta system, with the goal of building better models of how river deltas will behave under relative sea level rise. The data are provided in cloud optimized GeoTIFF (COG) format. This Version 2 dataset replaces the files provided in Version 1.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3255110465-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3255110465-ORNL_CLOUD.html",
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         "description": "This dataset provides maps of vegetation types for the Atchafalaya and Terrebonne basins in coastal Louisiana, U.S., derived from NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG) imagery acquired during spring and fall of 2021 for the Delta-X campaign.  Vegetation types were classified from Level-2B BRDF-adjusted surface reflectance. Local pixel reflectance spectra coincident with herbaceous vegetation field samples and vegetation plot data from Louisiana's Coastwide Reference Monitoring System were used to generate a machine learning-based model to classify vegetation types. This model was then applied to the AVIRIS-NG mosaic imagery to map vegetation types across the Atchafalaya and Terrebonne Basins. The data are provided in cloud optimized GeoTIFF (COG) format.",
         "license": "proprietary"
     },
@@ -61251,7 +61251,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2797469962-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2797469962-ORNL_CLOUD.html",
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         "description": "This dataset includes estimates of total suspended solids (TSS) concentration and turbidity for waters of the Atchafalaya River and Terrebonne Basins of the Mississippi River Delta (MRD) in coastal Louisiana. Estimates were derived from Level 2 (L2) BRDF-corrected imagery from NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG). AVIRIS-NG imagery was collected from March 27-April 6 (spring) and August 20-25 (fall), 2021, as part of the 2021 Delta-X campaign. Algorithms for TSS and turbidity estimation were developed using in-situ remote-sensing reflectance measured at field sampling stations paired with in-situ measures of turbidity from a water quality probe and TSS from water samples. Using the in-situ data, a partial least squares regression (PLSR) model was developed for each AVIRIS-NG wavelength. A subset of the in-situ data, collected during relatively clear AVIRIS-NG overflights, was held out to validate the PLSR model. The PLSR algorithm was then applied to AVIRIS-NG imagery to retrieve TSS and turbidity across the study area. The measurement units for TSS and turbidity estimates are mg L-1 and Formazin Nephelometric Units (FNU), respectively, and the spatial resolution is 3.8 to 5.4 m as determined by the AVIRIS-NG imagery. The dataset includes binary cloud and water masks. These data quantify the mesoscale (i.e., on the order of 1 ha) patterns of soil accretion that control land loss and gain and predict the resilience of deltaic floodplains under projected relative sea-level rise. Gridded estimates are provided in netCDF format, and regression coefficients are included in a comma-separated values (CSV) file. This is Version 3 of this dataset. All previously released data were updated to the latest available versions.",
         "license": "proprietary"
     },
@@ -61264,7 +61264,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3235707681-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3235707681-ORNL_CLOUD.html",
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         "description": "This dataset contains water surface elevations at selected point locations generated from the AirSWOT data collected during the Spring and Fall 2021 Delta-X deployments over the Atchafalaya and Terrebonne basins in Louisiana, USA. AirSWOT uses near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data. The Level 3 (L3) data were created by masking land areas out of the AirSWOT Level 2 products, then filtering and averaging to the AirSWOT heights to produce water surface elevations at selected points throughout the scene. The AirSWOT elevation data are useful for calibrating elevation and slopes along the main channels, as well as tying observations to open ocean tidal conditions. AirSWOT performance in the floodplain was limited by the presence of vegetation and the very small slope characteristic of two dimensional floodplain discharge. Therefore, the bulk of the AirSWOT data collections were targeted at the larger channels, since the channel discharge provides the necessary boundary conditions for potential overflow to islands and floodplains. The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2428357062-ORNL_CLOUD.html",
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         "description": "This dataset contains georeferenced InSAR-derived water level change maps for Delta-X flight lines acquired during the spring (2021-03-27 to 2021-04-18) and fall (2021-09-03 to 2021-09-13) deployments. Water-level change observations are provided throughout wetlands of the Atchafalaya and Terrebonne Basins, in Southern Louisiana, USA, within the Mississippi River Delta (MRD). The data were collected by Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), a polarimetric L-band synthetic aperture radar flown on the NASA Gulfstream-III (C20) aircraft as part of the Delta-X campaign. Water surface elevations were measured on multiple flights at 30-minute intervals. There are three types of gridded products available: temporalcoherence (which provide an index measuring quality of phase unwrapping ranging from 0 (poor) to 1 (correctly unwrapped)), waterlevelchange in centimeters (which provide cumulative changes in water levels at approximately 30-minute intervals), and waterlevelchange_ramp in centimeters (which provide a 2-dimensional linear trend in water-level estimates not related to changing water levels). The water-level change maps were estimated using the phase unwrapping corrected interferograms generated for nearest-neighbor (NN), NN+1, and NN+2 pairs for data acquired within a single flight (one day). This analysis was done for all flight lines. Water level changes are relative to the first sampling flight for that study area. Data quality was assessed by comparing water elevation estimates with data from in situ water level gauges throughout the study area. A series of quality assurance masks of troposphere-induced phase delay regions were generated for all SAR acquisition dates using a weather feature matching algorithm.",
         "license": "proprietary"
     },
@@ -61290,7 +61290,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3104728587-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3104728587-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZGVsdGEteDogY2FsaWJyYXRlZCBhbnVnYSBoeWRyb2R5bmFtaWMgb3V0cHV0cyBmb3IgdGhlIGF0Y2hhZmFsYXlhIGJhc2luLCBtcmQsIGxhXCIsXCJPUk5MX0NMT1VEXCIsXCJEZWx0YVhfQU5VR0FfQXRjaGFmYWxheWFCYXNpbl8yMzA2XCIsXCIxXCIsMzA5MTMzMDc4MiwyXSIsInVtbSI6IltcImRlbHRhLXg6IGNhbGlicmF0ZWQgYW51Z2EgaHlkcm9keW5hbWljIG91dHB1dHMgZm9yIHRoZSBhdGNoYWZhbGF5YSBiYXNpbiwgbXJkLCBsYVwiLFwiT1JOTF9DTE9VRFwiLFwiRGVsdGFYX0FOVUdBX0F0Y2hhZmFsYXlhQmFzaW5fMjMwNlwiLFwiMVwiLDMwOTEzMzA3ODIsMl0ifQ%3D%3D/DeltaX_LandAccretionMap_WLD_2308_1",
         "description": "This dataset provides sediment transport and land accretion model results at Wax Lake Delta (WLD), Atchafalaya Basin, in coastal Louisiana, USA. Data were simulated over the Delta-X Spring 2021 (2021-03-21 to 2021-04-03) and Fall 2021 (2021-08-14 to 2021-08-27) campaigns and the results are presented as annualized land accretion rate map. The model results for these two short-term campaigns are used to calculate the 1-year upscale land accretion rate at WLD in post-processing, which is also provided in this dataset. Model results for these two short-term campaigns were derived using inputs from an ANUGA hydrodynamic model. The Matlab sediment transport and land accretion model used to derive these data employs sediment transport theory that models floc behavior using a non-cohesive sediment transport framework. Data are presented in NetCDF (*.nc) format.",
         "license": "proprietary"
     },
@@ -61303,7 +61303,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3235699055-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3235699055-ORNL_CLOUD.html",
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         "description": "This dataset provides input data and model code to run the Marsh Accretion Rates (NUMAR) process model used to predict soil accretion rates and chemical properties for marsh sites in the Mississippi River Delta. NUMAR is a modification of the NUMAN model by Chen and Twilley (1999) that was developed for mangrove environments.  This dataset provides Python code, input data in comma separated values (CSV) format, and documentation for installing and running the model in Portable Document Format (PDF).",
         "license": "proprietary"
     },
@@ -61316,7 +61316,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515316269-ORNL_CLOUD.html",
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         "description": "This dataset provides in situ measurements of beam attenuation coefficient at 670 nm, average suspended particle size, particle size distribution, and water temperature in surface waters (~0.5 m) of the Atchafalaya and Terrebonne Basins on the southern coast of Louisiana. The field studies were conducted in the Spring and Fall in support of the Delta-X mission and include measurements made in 2021 during March 25 - April 22 and August 14 - September 24. Measurements were made using the Sequoia Scientific Laser In-Situ Scattering and Transmissometer instrument (LISST-200X) in multiple channels of varying width (from a few meters to >100m), near Delta-X intensive study sites and in open bays and lakes and at a few locations in the nearshore Gulf of Mexico. The data are provided in comma-separated (CSV) format.",
         "license": "proprietary"
     },
@@ -61329,7 +61329,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2432627361-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2432627361-ORNL_CLOUD.html",
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         "description": "This dataset provides real-time kinematic (RTK) GPS elevation measurements, along with horizontal and vertical precision errors, obtained along transects near Louisiana's Coastwide Reference Monitoring Systems (CRMS) sites and on Mike Island in Wax Lake Delta (WLD). The data were collected during the Delta-X Spring Campaign from 2021-03-24 to 2021-04-02. The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
@@ -61342,7 +61342,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2619216342-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2619216342-ORNL_CLOUD.html",
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         "description": "This dataset provides sediment concentration and grain size distribution measurements from suspended and bed sediment samples collected in the Atchafalaya and Terrebonne River Basins as part of the Delta-X Spring campaign between March 24 to April 2, 2021 and Delta-X Fall campaign between August 17-25, 2021. During the field campaign, samples were collected in the main distributary channels and the interior of Mike Island in the Wax Lake Delta, Louisiana and at site CRMS0421 inside the Terrebonne River Basin. Sediment samples were collected from a boat using a Van Dorn sampler (for suspended sediment samples) or a Ponar bed sampler (for bed samples). Suspended sediment samples were collected from a boat drifting at approximately the same velocity as the water flow. One sample was collected per drift. Bed samples were collected in a similar fashion. Data includes measurements of sediment grain size, total sediment concentration, as well as water temperature, velocity, salinity, and depth. This Version 2 includes the initial release of Fall 2021 data and an update to the Version 1 (Spring 2021) data file in which an error in the data was resolved.",
         "license": "proprietary"
     },
@@ -61355,7 +61355,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2435074094-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2435074094-ORNL_CLOUD.html",
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         "description": "This dataset includes bathymetry data for water channels in a portion of the Mississippi River Delta (MRD) of coastal Louisiana. The data were collected using sonar during field efforts of the Delta-X Campaign taking place during 2021. In situ continuous surveys of channel bathymetry were conducted in the Atchafalaya and Terrebonne basins using either a Lowrance HDS-Live Fish Finder with Active Imaging 3-in-1 Transducer or a SonarMite Echo Sounder mounted on the side or back of the research boat. The sounder depth observations were delineated by the date, time, and location. These bathymetry measurements were used to generate a digital elevation model (DEM) through interpolation with ancillary DEMs. The data are provided in comma-separated values (CSV) format. A map of data collection routes is provided in compressed keyhole markup language (KMZ).",
         "license": "proprietary"
     },
@@ -61368,7 +61368,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2482188997-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZGVsdGEteDogcGFydGljdWxhdGUgb3JnYW5pYyBjYXJib24gY29uY2VudHJhdGlvbiBmcm9tIHdhdGVyIHNhbXBsZXMsIG1yZCwgbGEsIDIwMjFcIixcIk9STkxfQ0xPVURcIixcIkRlbHRhWF9JbnNpdHVfUE9DXzIwNzNcIixcIjFcIiwyNDgyMTg2NjE5LDVdIiwidW1tIjoiW1wiZGVsdGEteDogcGFydGljdWxhdGUgb3JnYW5pYyBjYXJib24gY29uY2VudHJhdGlvbiBmcm9tIHdhdGVyIHNhbXBsZXMsIG1yZCwgbGEsIDIwMjFcIixcIk9STkxfQ0xPVURcIixcIkRlbHRhWF9JbnNpdHVfUE9DXzIwNzNcIixcIjFcIiwyNDgyMTg2NjE5LDVdIn0%3D/DeltaX_TSS_Concentration_V2_2075_2",
         "description": "This dataset provides measurements of total suspended solids concentrations (TSS) of surface waters in the Atchafalaya River and Terrebonne Basins during the spring (2021-03-25 to 2021-04-22) and fall (2021-08-14 to 2021-09-24) field efforts by the Delta-X project. Field sampling was paused on August 25 and resumed on September 13, 2021, due to the landfall of Hurricane Ida on 2021-08-26 approximately 70 km east of the study site. Water quality changes caused by the hurricane were expected to be minimal. Samples were collected from ~0.5 m of surface in multiple channels of varying width (from a few meters to >100 m), near Delta-X intensive study sites, in open bays and lakes, and at few locations in the nearshore Gulf of Mexico. For each collection, the water sample volume was filtered, and the suspended particles retained on the filter were weighed after drying. The TSS concentration was calculated as the difference of the filter weight (before and after filtration) divided by the volume filtered.",
         "license": "proprietary"
     },
@@ -61381,7 +61381,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2849224257-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2849224257-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZGVsdGEteDogY2FsaWJyYXRlZCBhbnVnYSBoeWRyb2R5bmFtaWMgb3V0cHV0cyBmb3IgdGhlIGF0Y2hhZmFsYXlhIGJhc2luLCBtcmQsIGxhXCIsXCJPUk5MX0NMT1VEXCIsXCJEZWx0YVhfQU5VR0FfQXRjaGFmYWxheWFCYXNpbl8yMzA2XCIsXCIxXCIsMzA5MTMzMDc4MiwyXSIsInVtbSI6IltcImRlbHRhLXg6IGNhbGlicmF0ZWQgYW51Z2EgaHlkcm9keW5hbWljIG91dHB1dHMgZm9yIHRoZSBhdGNoYWZhbGF5YSBiYXNpbiwgbXJkLCBsYVwiLFwiT1JOTF9DTE9VRFwiLFwiRGVsdGFYX0FOVUdBX0F0Y2hhZmFsYXlhQmFzaW5fMjMwNlwiLFwiMVwiLDMwOTEzMzA3ODIsMl0ifQ%3D%3D/DeltaX_TotalSubsidenceRate_MRD_2307_1",
         "description": "This dataset provides estimates of land subsidence rates for the Delta-X domain area within the Atchafalaya and Terrebonne basins for 2021. The study area is a portion of the Mississippi River Delta in coastal Louisiana, U.S. The total subsidence is calculated as the sum of deep and shallow vertical elevation change rates. The deep subsidence rate is based on information from the Coastal Protection and Restoration Authority (CPRA) of Louisiana, documented in the Phase-4 subsidence trend report prepared for and provided by CPRA (2022). The shallow subsidence is calculated for the Delta-X study area by interpolation of publicly available data provided by CPRA for their coast-wide estimation of shallow subsidence in the 2023 Coastal Master Plan. The total subsidence rates and the estimated uncertainty in the total subsidence rates are provided as separate files in cloud optimized GeoTIFF (COG) format at 30-m (0.0003 decimal degrees) resolution.",
         "license": "proprietary"
     },
@@ -61394,7 +61394,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2772853528-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2772853528-ORNL_CLOUD.html",
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         "description": "This dataset provides turbidity measurements with co-located water and air pressure and temperature measurements in portions of the Mississippi River Delta, coastal Louisiana, US. Data were collected at five sites in Atchafalaya River Basin in Spring (2021-03-24 to 2021-04-02) and eight sites in the Atchafalaya River and Terrebonne Basins in Fall 2021 (2021-08-16 to 2021-08-27). In order to sample various hydrodynamic conditions, sensors were deployed at island edges, island interior, and other portions of wetlands. Sensors recorded turbidity, absolute pressure, and temperature. The Delta-X mission is a 5-year NASA Earth Venture Suborbital-3 mission to study the Mississippi River Delta in the United States, which is growing and sinking in different areas. River deltas and their wetlands are drowning as a result of sea level rise and reduced sediment inputs. The Delta-X mission will determine which parts will survive and continue to grow, and which parts will be lost. Delta-X begins with airborne and in situ data acquisition and carries through data analysis, model integration, and validation to predict the extent and spatial patterns of future deltaic land loss or gain. The data are provided in comma-separated values (CSV) files.",
         "license": "proprietary"
     },
@@ -61407,7 +61407,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3110694695-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3110694695-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZGVsdGEteDogcGFydGljdWxhdGUgb3JnYW5pYyBjYXJib24gY29uY2VudHJhdGlvbiBmcm9tIHdhdGVyIHNhbXBsZXMsIG1yZCwgbGEsIDIwMjFcIixcIk9STkxfQ0xPVURcIixcIkRlbHRhWF9JbnNpdHVfUE9DXzIwNzNcIixcIjFcIiwyNDgyMTg2NjE5LDVdIiwidW1tIjoiW1wiZGVsdGEteDogcGFydGljdWxhdGUgb3JnYW5pYyBjYXJib24gY29uY2VudHJhdGlvbiBmcm9tIHdhdGVyIHNhbXBsZXMsIG1yZCwgbGEsIDIwMjFcIixcIk9STkxfQ0xPVURcIixcIkRlbHRhWF9JbnNpdHVfUE9DXzIwNzNcIixcIjFcIiwyNDgyMTg2NjE5LDVdIn0%3D/DeltaX_UAVSAR_L3_ChannelMap_V2_2344_2",
         "description": "This dataset provides gridded estimates of water channels for the Atchafalaya and Terrebonne basins of the Mississippi River Delta in Louisiana, U.S.A. The data show channels with open water that are as narrow as 10 m. These channel estimates were generated from the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) Level 1B interferometric products in radar coordinates acquired in the Spring and Fall Delta-X deployments of 2021, which have a spatial resolution of approximately 6 m. UAVSAR is a polarimetric L-band synthetic aperture radar (SAR) flown on the NASA Gulfstream-III aircraft. The data are provided in cloud-optimized GeoTIFF format. The channel estimates can be used to define open water paths in hydrodynamic models and to evaluate model performance.",
         "license": "proprietary"
     },
@@ -61420,7 +61420,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2772852503-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2772852503-ORNL_CLOUD.html",
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         "description": "This dataset provides mean stem diameter, mean height, dominant species, hydrogeomorphic zone (HGM), and stem density for vegetation in herbaceous wetlands collected in the Atchafalaya and Terrebonne basins in southeastern coastal Louisiana. The data were collected between 2021-03-21 to 2021-03-31 during the Delta-X Spring 2021 deployment, and from 2021-08-19 to 2021-08-27 during the Fall deployment. Field measurements were conducted at six sites in the Atchafalaya (N = 3) and Terrebonne (N = 3) basins. Five of the sites were adjacent to sites from the Coastwide Reference Monitoring System (CRMS), and the other site was in the Wax Lake Delta (WLD) without appropriate adjacent CRMS sites. Sites in both basins were chosen to represent a salinity gradient including freshwater, brackish, and saline ecosystems. At each herbaceous wetland site, duplicate sampling stations (30 m apart) were established parallel to the wetland edge at 25 and 50 m within the intertidal zone to capture within site variability in vegetation dynamics and soil properties. The data are provided in comma-separated values (*.csv) format.",
         "license": "proprietary"
     },
@@ -61433,7 +61433,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517706204-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517706204-ORNL_CLOUD.html",
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         "description": "This data set provides a 30-year record of Landsat TM and ETM+ derived forest phenology and the results of tree ring analyses for annual wood production and nitrogen and carbon isotopic composition at 113 selected forested sites in the eastern United States. The sites are located in four national parks: Prince William Forest Park (PRWI), Harpers Ferry National Historical Park (HAFE), Catoctin Mountain Park (CATO), and Great Smoky Mountains National Park (GRSM). Phenology and tree ring data cover 1984-2013.",
         "license": "proprietary"
     },
@@ -61537,7 +61537,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389176598-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389176598-ORNL_CLOUD.html",
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         "description": "This dataset provides derived disturbance history and predicted annual forest biomass maps at 30-m resolution for six selected Landsat scenes across the Conterminous United States (CONUS) for the period 1985-2014. The focus sites are in the following states: Colorado, Maine, Minnesota, Oregon, Pennsylvania, and South Carolina. These scenes were selected to represent a wide range of forest ecosystems, which ensured that a diversity of forest type groups and forest change processes (e.g., harvest, fire, insects, and urbanization) were included. Disturbance history was derived from a Landsat time-series for each site. Each disturbance is represented by year of detection, duration, and magnitude. The cause of the disturbance was not identified. Forest biomass was measured at field plots within each of the six sites and combined with airborne LiDAR data from each site to create land validation maps. Site biomass at 30-m resolution was estimated by developing Random Forest models that include site disturbance history with the land validation maps.",
         "license": "proprietary"
     },
@@ -61615,7 +61615,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216862849-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216862849-ORNL_CLOUD.html",
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         "description": "Plant-extractable water capacity of soil is the amount of water that can be extracted from the soil to fulfill evapotranspiration demands. This data set provides an estimate of the global distribution of plant-extractable water capacity of soil.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2966188795-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2966188795-ORNL_CLOUD.html",
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         "description": "This model product contains the source code for the Ecosystem Demography Model (ED version 1.0) as well as model input and output data for a portion of South America including the Brazilian Amazon. The model output data are estimates of potential average live biomass (kg C/m2), potential average soil carbon (kg C/m2), and potential above-ground net primary production (NPP) (kg C/m2/yr) at 1.0 degree resolution. To produce these estimates, ED was forced with ISLSCP I data for 1987 and 1988, averaged into a single year (Moorcroft et al., 2001). Data for the three estimates are provided in both ASCII text and in NetCDF formatted files. ED is an individual-based terrestrial ecosystem model that predicts both ecosystem structure (e.g. above and below-ground biomass, vegetation height and basal area, and soil carbon stocks) and corresponding ecosystem fluxes (e.g. NPP, NEP and evapotranspiration) from climate, soil, and land-use inputs. The model consists of integrated sub-models governing processes such as leaf-level physiology, plant allocation, allometry, phenology, dispersal, the effects of fire disturbances, and below-ground sub-models for soil carbon dynamics and hydrology. Using a new method for scaling-up it is possible to predict ED's large-scale behavior without simulating the fate of every plant individually. ED is used to examine how climate and edaphic factors, natural disturbances, and human land-use practices affect ecosystem structure and fluxes. This data set contains six zip files which each uncompress into six unique subdirectories. Each subdirectory is described in detail in the Model Product Description section of this document. Installation and execution instructions are provided in the Model Documentation and User's Guide section of this document. ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2966708214-ORNL_CLOUD.html",
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         "description": "This model product contains the source code for the Ecosystem Demography Model (ED version 1.0) as well as model input and output data files for the conterminous United States. The ED is a mechanistic ecosystem model built around established sub-models of leaf level physiology, organic matter decomposition, hydrology, and functional biodiversity. It was used herein to estimate ecosystem carbon stocks and fluxes in the conterminous U.S. at 1.0 degree resolution from 1700 to 1990. Output data of carbon stocks and fluxes are stored in NetCDF format. To produce the U.S. scenario, ED was run from an estimated state of ecosystems in the year 1700 to an estimated state of ecosystems in the year 1990 for each 1 degree by 1 degree grid cell through time using ISLSCP Initiative I climate and soil data and a gridded land-use history reconstruction as inputs (Hurtt et al., 2002). The land-use history was based on several sources including: spatial distribution of potential vegetation in 1700, spatial patterns of cropland from 1700 to 1990, regional estimates of land use and logging from 1700 to 1990, and U.S. Forest Inventory and Analysis (FIA) data on the current age distribution of forest stands. The Miami Land Use History Model (Miami-LU), a far simpler empirically-based ecosystem model, was used to track the history of disturbance, land use, fire, and ecosystem recovery. The effects of fire suppression were also included. Atmospheric CO2 concentrations and climatic conditions were held constant throughout the runs to focus on the consequences of land-use and fire-management changes on carbon stocks and fluxes.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389022016-ORNL_CLOUD.html",
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         "description": "This dataset provides a map of the distribution of ecosystem functional types (EFTs) at 0.05 degree resolution across Mexico for 2001 to 2014. EFTs are groupings of ecosystems based on their similar ecosystem functioning that are used to represent the spatial patterns and temporal variability of key ecosystem functional traits without prior knowledge of vegetation type or canopy architecture. Sixty-four EFTs were derived from the metrics of a 2001-2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) product MOD13C2. EFT diversity was calculated as the modal (most repeated) EFT for each pixel.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2762258684-ORNL_CLOUD.html",
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         "description": "This dataset provides ground-based column-averaged dry mole fractions (DMFs) of CO2 (xco2), CO (xco), CH4 (xch4), and N2O (xn2o) to supplement satellite-based observations of carbon dynamics of northern boreal ecosystems. Measurements were conducted with Bruker EM27/SUN Fourier transform spectrometers (FTS) at the University of Alaska Fairbanks (UAF) and two sites on the edges of the Tanana Flats wetlands to the south from 2016-08-04 to 2019-10-31. Single detectors were used during the first campaign at UAF in 2017, then two instruments were updated to dual detectors in early 2018 to allow retrieval of xco and xn2o. Data from additional FTS instruments, operated by Los Alamos National Laboratories (LANL), Karlsruhe Institute of Technology (KIT), and Jet Propulsion Laboratory (JPL), employed in these campaigns are included.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2207986936-ORNL_CLOUD.html",
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         "description": "This dataset provides Level 2 (L2) Solar-Induced Fluorescence (SIF) of chlorophyll estimates derived from the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument on the European Space Agency's (ESA's) Environmental satellite (Envisat) with ~0.5 nm spectral resolution and wavelengths between 734 and 758 nm. SCIAMACHY covers global land between approximately 70 and -57 degrees latitude on an orbital basis at a resolution of approximately 30 km x 240 km. Data are provided for the period from 2003-01-01 to 2012-04-08. Each file contains daily raw and bias-adjusted solar-induced fluorescence along with quality control information and ancillary data.",
         "license": "proprietary"
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         "description": "This dataset provides Level 2 Solar-Induced Fluorescence (SIF) of Chlorophyll estimates derived from the Global Ozone Monitoring Experiment (GOME) instrument on the European Space Agency's (ESA's) European Remote-Sensing 2 (ERS-2) satellite. Each file contains daily raw and bias-adjusted solar-induced fluorescence on an orbital basis (land pixels only), at a resolution of 40 km x 320 km, along with quality control information and ancillary data. Data is provided for the period from 19950701 to 20030622. The GOME SIF product is inherently noisy due to low signal levels and has undergone only a limited amount of validation.",
         "license": "proprietary"
     },
@@ -66360,7 +66360,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776882677-ORNL_CLOUD.html",
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         "description": "A data set of decade-mean monthly surface climate over global land areas, excluding Antarctica.  Interpolated from station data to 0.5 degree lat/lon for a range of variables:  precipitation, wet-day frequency, mean temperature and diurnal temperature range (from which maximum temperature and and minimum temperature can be determined), vapour pressure, cloud cover, ground-frost frequency.",
         "license": "proprietary"
     },
@@ -66373,7 +66373,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776885667-ORNL_CLOUD.html",
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         "description": "A data set of 30-year mean monthly surface climate over global land areas, excluding Antarctica.  Interpolated from station data to 0.5 degree lat/lon for a range of variables:  precipitation, wet-day frequency, mean temperature and diurnal temperature range (from which maximum temperature and and minimum temperature can be determined), vapour pressure, cloud cover, ground-frost frequency.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776876780-ORNL_CLOUD.html",
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         "description": "A data set of mean monthly surface climate over global land areas, excluding Antarctica. Interpolated from station data to 0.5 degrees lat/lon for a range of variables: precipitation and wet-day frequency, mean temperature and diurnal temperature range (from which maximum temperature and minimum temperature can be determined), vapour pressure, sunshine, cloud cover, ground-frost frequency and windspeed.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776827920-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776827920-ORNL_CLOUD.html",
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         "description": "An historical monthly precipitation data set for global land areas from 1900 to January 1, 1999, gridded at two different resolutions (2.5 degrees latitude by 3.75 degrees longitude and 5 degrees latitude/longitude).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2408633153-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2408633153-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of forest aboveground biomass for three study areas and the entire Paragominas municipality, in Para, Brazil, in 2012. Aboveground biomass (in megagrams of carbon per hectare) was measured for inventory plots within the study (focal) areas, and then assimilated and modeled with LiDAR and PALSAR metrics using gradient boosting machines (GBM) to predict spatially explicit forest aboveground biomass and uncertainties for the entire focal areas. The PALSAR data across the three focal areas was combined and used in a GBM model to predict forest aboveground biomass across the entire Paragominas municipality.",
         "license": "proprietary"
     },
@@ -66581,7 +66581,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784385784-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784385784-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of aboveground biomass (AGB) for defined land cover types within World Wildlife Fund (WWF) ecoregions across the boreal biome of eastern and western Eurasia, roughly between 50 and 70 degrees N. The study focused on within-growing-season data, i.e. leaf-on conditions.The AGB estimates were derived from a series of models that first related ground-based measured biomass to airborne data collected with an Optech Airborne Laser Terrain Mapper (ALTM) 3100, and a second set of models that related the airborne estimates of biomass to Geoscience Laser Altimeter System (GLAS) LiDAR canopy structure measurements. The ground, airborne, and GLAS measurements were used to formulate the models needed to generate biomass predictions for western Eurasia. Eastern Eurasia employed a two-phase approach relating field measurements directly to the GLAS measurements without the airborne intermediary. The GLAS LiDAR biomass estimates were extrapolated by land cover types and ecoregions across the entire biome area.The study compiled remotely sensed forest structure data collected in June of 2005 and 2006 from the GLAS LiDAR instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite and from an Optech Airborne Laser Terrain Mapper (ALTM) 3100 airborne instrument flown in Southeast Norway over both the ground plots and the ICESat GLAS flight path. For a consistent biome-level analysis, ecoregions contained within the boreal forest biome were identified by the World Wildlife Fund's (WWF) ecoregion map of the world (Olson et al., 2001). MODIS MOD12Q1 land cover products (2004) were used to identify land cover types for stratification purposes within eco-regions. The ground-based measurements are not provided with this data set.",
         "license": "proprietary"
     },
@@ -66763,7 +66763,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2788383221-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788383221-ORNL_CLOUD.html",
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         "description": "The U.S. Agency for International Development (USAID) Famine Early Warning System (FEWS) has been supporting the production of 10-day Rainfall Estimate (RFE) data for Africa since 1995. The FEWSNET project was established with the goal of reducing the incidence of drought- or flood-induced famine by providing decision makers with timely and accurate information on conditions that may require intervention. RFE data for continental Africa for 1999, 2000, and 2001 were downloaded the from the African Data Dissemination Service (ADDS) site and were subset for southern Africa by the SAFARI 2000 data group. The RFE 1.0 algorithm, implemented from 1995 to 2000, uses an interpolation method to combine Meteosat and Global Telecommunication System (GTS) data, and warm cloud information for the 10-day estimations. The 30-minute geostationary Meteosat-7 satellite infrared data are used to estimate convective rainfall from areas where cloud top temperatures are less than 235K. The RFE 2.0 algorithm, implemented as of January 1, 2001, uses additional techniques to better estimate precipitation while continuing the use of cold cloud duration and station rainfall data.",
         "license": "proprietary"
     },
@@ -66776,7 +66776,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345878726-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345878726-ORNL_CLOUD.html",
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         "description": "This dataset provides forest biomass estimates for the conterminous United States based on data from the USDA Forest Inventory and Analysis (FIA) program. FIA maintains uniformly measured field plots across the conterminous U.S. This dataset, derived from field survey data from 2009-2019, includes statistical estimates of biomass at the finest scale (64,000-hectare hexagons) allowed by FIA's sample density. Estimates include the mean (and standard error of the mean) biomass for both live and dead trees, calculated using three sets of allometric equations. There is also an estimate of the area of forestland in each hexagon. These data can be useful for assessing the accuracy of remotely sensed biomass estimates.",
         "license": "proprietary"
     },
@@ -66789,7 +66789,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2758951357-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2758951357-ORNL_CLOUD.html",
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         "description": "This data set provides aircraft-based NS001 Thematic Mapper Simulator (TMS) images of the study area associated with The First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE) project conducted on the Konza Prairie in Kansas. The images were acquired during June 1987 to August 1989. The images in this data set were originally provided on the FIFE CD-ROM Volume 3.",
         "license": "proprietary"
     },
@@ -69012,7 +69012,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2677230198-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2677230198-ORNL_CLOUD.html",
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         "description": "This dataset contains a set of Lagrangian particle dispersion simulations of carbon dioxide concentrations using the FLEXible PARTicle (FLEXPART) model. FLEXPART quantified the source-receptor relationships, so-called \"influence functions\", in a backward mode. The simulations were constructed for five Atmospheric Carbon and Transport America (ACT-America) deployments over the eastern U.S. that occurred in 2016-2019. Each receptor of the influence function is the 30-second or 10-minute interval along flight tracks, characterized by a box with boundaries between the maximum and minimum latitude/longitude as well as between the maximum and minimum altitudes during the interval. Each receptor box released 5,000 particles and simulated their transport and dispersion backward for 10 or 20 days. The simulations were driven by 27-km meteorology provided by the WRF-Chem simulation or by ERA-Interim data from the European Centre for Medium-Range Weather Forecasts (ECMWF). Background levels of carbon dioxide were obtained from CarbonTracker and OCO-2 v9 MIP. The data are provided in netCDF and FLEXPART binary formats.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777404781-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777404781-ORNL_CLOUD.html",
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         "description": "This data set provides a digital mosaic of the Amazon River floodplain that was compiled using Landsat TM images. This mosaic was planned in July 1995 as an activity of the EOS-IDS Project that was developed with cooperation among INPE, CENA, University of Washington in Seattle (UW), University of California in Santa Barbara (UCSB), and NASA. The mosaic is composed by 29 Landsat TM images covering a period from 1986 to 1995 that were selected with minimum cloud cover and within the July to September high water season of the Amazon River. These images were geometrically corrected using ground control points extracted from topographic charts and image charts at the 1:250,000 scale. In addition, these images were radiometrically rectified to 231/062 (Manaus region) TM image using the method developed by Hall et al. (1991). The radiometric rectification applied had a good performance for bands 3, 5, and 7, for most of the scenes. For bands 1 and 2 the radiometric rectification was limited, especially for scenes with intense haze. Nevertheless, the overall performance of radiometric normalization allowed the production of a uniform data set for the entire Brazilian Amazon River mainstem floodplain. The mosaic was then built using the best bands (rectified or non-rectified) of the TM images with 90 meter spatial resolution. The mosaic data are provided in geoTIFF-formatted files, rectified and geocoded, for six TM bands (1 to 5 and 7) with 90-meter spatial resolution. The mosaic is divided in two parts: Part 1, from the mouth of the Amazon river in Brazil to the Brazil/Peru boundary and Part 2, from the Brazil/Peru boundary to its spring.There is also a 500-meter resolution mosaic covering all the Amazon river (from spring to the mouth) with geoTIFF-formatted data files for TM bands 3, 4, and 5. The processed, quality controlled and integrated data in the documented Pre-LBA Data sets were originally published as a set of three CD_ROMs (Marengo and Victoria, 1998) but are now archived individually.  ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804820806-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804820806-ORNL_CLOUD.html",
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         "description": "The FLUAMAZON Experiment data set includes meteorological data collected with radiosondes to examine the moisture flux from the northern coast of South America (near the mouth of the Amazon River) into central Amazonia.  The measurements were collected from November 23, to December 21, 1989 during the period of transition between the dry and humid seasons in the region.   Some of the studies performed with data from FLUAMAZON were related to the atmospheric thermodynamic structure over Amazonia.  During FLUAMAZON, radiosonde measurements were made simultaneously in five different locations: Alcantara, Belem, Oiapoque, Manaus, and Alta Floresta. ASCII text data files for each location have been compiled and compressed into site-specific zipped files.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773250697-ORNL_CLOUD.html",
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         "description": "FLUXNET Canada is a Fluxnet research network comprised of the Fluxnet-Canada Research Network (FCRN) and the Canadian Carbon Program (CCP) operating from 1993 through 2014. It was a national research network of university and government scientists studying the influence of climate and disturbance on carbon cycling along an east-west transect of Canadian forest and peat land ecosystems. The data provided are measured and modeled results as obtained from the site investigators. They were not standardized and quality-controlled. Data include: atmospheric carbon dioxide (CO2) and water vapor fluxes and many ancillary meteorological variables; soil CO2 efflux and soil moisture; stable carbon isotopes; site soil and vegetation characteristics, plus documentation and descriptions for the 32 tower sites across 12 flux research stations. The time period is from 1993 - 2014; most reported data for a site does not cover the entire period.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756289636-ORNL_CLOUD.html",
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         "description": "This dataset, titled the Synthesized Alaskan Tundra Field Database (SATFiD), provides a comprehensive collection of in-situ field data compiled from 37 existing datasets resulting from field surveys conducted at Alaska tundra sites between 1972 to 2020. The data were harmonized prior to being included in this dataset. The variables include active layer thickness, vegetation cover (by plant functional types), soil moisture and temperatures, as well as the wildfire history. SATFiD provides a unique lens into various long-term ecological processes within the tundra (such as the fire-permafrost-vegetation interactions) under a rapidly changing climate.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2600303267-ORNL_CLOUD.html",
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         "description": "This dataset provides 10-minute fire emissions within 0.1-degree regularly spaced intervals across Indonesia from July 2015 to December 2020. The dataset was produced with a top-down approach based on fire radiative energy (FRE) and smoke aerosol emission coefficients (Ce) derived from multiple new-generation satellite observations. Specifically, the Ce values of peatland, tropical forest, cropland, or savanna and grassland were derived from fire radiative power (FRP) and emission rates of smoke aerosols based on Visible Infrared Imaging Radiometer Suite (VIIRS) active fire and aerosol products. FRE for each 0.1-degree interval was calculated from the diurnal FRP cycle that was reconstructed by fusing cloud-corrected FRP retrievals from the high temporal-resolution (10 mins) Himawari-8 Advanced Himawari Imager (AHI) with those from high spatial-resolution (375 m) VIIRS. This new dataset was named the Fused AHI-VIIRS based fire Emissions (FAVE). Fire emissions data are provided in comma-separated values (CSV) format with one file per month from July 2015 to December 2020. Each file includes variables of fire observation time, fire geographic location, classification, fire radiative energy, various fire emissions and related standard deviations.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764707175-ORNL_CLOUD.html",
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         "description": "This dataset provides global gridded daily estimates of gross primary production (GPP) and uncertainties at 0.05-degree resolution for the period 2000-03-01 to the recent past. The GPP was derived from the MODerate-resolution Imaging Spectroradiometer (MODIS) instruments on the NASA Terra and Aqua satellites using the MCD43C4v006 Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectances (NBAR) product as input to neural networks that were used to globally upscale GPP estimated from selected FLUXNET 2015 eddy covariance tower sites. Additional data will be added periodically.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2767479901-ORNL_CLOUD.html",
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         "description": "FLUXNET is a global network of micrometeorological tower sites that use eddy covariance methods to measure the exchanges of carbon dioxide, water vapor, and energy between terrestrial ecosystems and the atmosphere. This dataset provides information from the ORNL DAAC-hosted FLUXNET site database which was discontinued in 2016. The files provided contain a list of investigators associated with each tower site, site locations and environmental data, and a bibliography of papers that used FLUXNET data. For more up to date information on FLUXNET sites, see http://fluxnet.fluxdata.org/.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764885202-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764885202-ORNL_CLOUD.html",
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         "description": "This dataset contains an archived copy of the fluxnet.ornl.gov website as of September 2017. This archived website is provided for informational purposes only. The last updates to the website and the underlying database were made in October 2016. Support for the Fluxnet project and website was transitioned to http://fluxnet.fluxdata.org in September 2017. Please see http://fluxnet.fluxdata.org/ for information on site locations, data availability, and to add or update a flux tower site.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2883623174-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2883623174-ORNL_CLOUD.html",
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         "description": "This dataset includes maps of canopy height and aboveground biomass at spatial resolutions of 25 m and 100 m for Mexico, Gabon, French Guiana, and the Amazon Basin. The GEDI-TanDEM-X (GTDX) fusion maps were created by combining data from NASA's Global Ecosystem Dynamics Investigation (GEDI) Version 2 footprint data (from 2019-04-18 to 2021-08-18) and TanDEM-X (abbreviated as TDX) Interferometric Synthetic Aperture Radar (InSAR) images (from 2011-01-06 to 2020-12-31). The GTDX canopy height maps were generated by using the TDX coherence maps to invert the TDX height and subsequently using GEDI canopy height as reference data to calibrate the inverted height. The GTDX aboveground biomass maps were produced based on a generalized hierarchical model-based (GHMB) framework that utilizes GEDI biomass as training data to establish models for estimating biomass based on the GTDX canopy height. The dataset also includes maps of canopy height uncertainty, biomass uncertainty,  and ancillary data including a regional modeling parameter and forest disturbance. The uncertainty of GTDX canopy height was estimated for each pixel by propagating the GEDI-TDX model error to each GTDX pixel prediction. The uncertainty of GTDX aboveground biomass was estimated by considering the error in both the GEDI footprint biomass data and the GEDI-TDX model, and then applying it to each GTDX biomass pixel prediction. The regional model parameter indicates the size of the analysis window (2 to 50 km or country wide) used for each pixel. The forest disturbance information identifies pixels where disturbance occurred between 2011 and 2020, and provides the year of last disturbance.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389020423-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389020423-ORNL_CLOUD.html",
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         "description": "This dataset provides maps of aboveground forest biomass (AGB) of living trees and standing dead trees in Mg/ha across portions of Northwestern United States, including Washington, Oregon, Idaho, and Montana, at a spatial resolution of 30 m. Forest inventory data were compiled from 29 stakeholders that had overlapping lidar imagery. The collection totaled 3805 field plots with lidar imagery for 176 collections acquired between 2002 and 2016. Plot-level AGB estimates were calculated from tree measurements using the default allometric equations found in the Fire Fuels Extension (FFE) of the Forest Vegetation Simulator (FVS). The random forest algorithm was used to model AGB from lidar height and density metrics that were generated from the lidar returns within fixed-radius field plot footprints, gridded climate metrics obtained from the Climate-FVS Ready Data Server, and topographic estimates extracted from Shuttle Radar Topography Mission (SRTM) 1 Arc-Second Global elevation rasters. AGB was then mapped from the same lidar metrics gridded across the extent of the lidar collections at 30-m resolution. The standard deviation of estimated AGB of the terminal nodes from the random forest predictions was also mapped to show pixel-level model uncertainty. Note that the AGB estimates are, for the most part, a single snapshot in time and that the forest conditions are not necessarily representative of the larger study area.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517278605-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517278605-ORNL_CLOUD.html",
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         "description": "This dataset provides related gridded outputs of future modeled forest carbon sequestration priority and related species richness and habitat suitability for the western United States. The primary dataset is of the ranking of forest lands in the western U.S. for preservation based on the ability of these lands to sequester carbon over the coming century. The preservation ranking was derived from the results of simulations of future potential forest net ecosystem productivity (NEP) and vulnerability to drought and wildfire, as modeled from 2020 to 2099 at 4 km x 4 km resolution using a modified version of the Community Land Model (CLM 4.5). In addition, data files of potential forest NEP ranking and the forest vulnerability ranking are also provided. Co-located data of species richness for amphibians, birds, mammals, and reptiles are included to illustrate habitat suitability in relation to forest carbon preservation rankings. There are two files for each vertebrate class, one reflecting all western U.S. species included in the USGS GAP Analysis Project and a second for the subset of species listed as threatened or endangered by the U.S. Fish and Wildlife Service. Establishing this forest carbon preservation priority ranking for forest lands in the western U.S. will help guide the conservation of land for climate change mitigation activities and improved harvest management in the region.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2642587660-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2642587660-ORNL_CLOUD.html",
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         "description": "This dataset contains estimates of forest disturbance intensity for the conterminous United States from 1986 to 2015. It quantifies the severity/intensity of forest disturbances at 30 m resolution using time series Landsat observations and the vegetation change tracker algorithm. For each disturbance event mapped at a pixel location, the percentage of basal area removal (PBAR) after the disturbance event was estimated based on spectral changes derived from Landsat data and Random Forest models calibrated using field measurements collected by the US Forest Service Forest Inventory and Analysis (FIA) Program. This dataset complements and extends the North American Forest Dynamics-NASA Earth eXchange (NAFD-NEX) US Forest Disturbance History dataset and the NAFD-ATT Forest Canopy Cover Loss dataset from 1986-2010 to 1986-2015. Data are provided in Cloud Optimized GeoTIFF (*.tif) format.",
         "license": "proprietary"
     },
@@ -69324,7 +69324,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764878430-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764878430-ORNL_CLOUD.html",
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         "description": "This data set provides measurements of diameter at breast height (DBH) and species identification at four forest sites in the eastern side of Acre, Brazil including Bonal (A), Catuaba (B), Humaita (C) and Transacreana (D). The inventory locations include forests burned in 2005 and 2010 and nearby unburned areas. Inventory surveys were conducted in October and December 2017.",
         "license": "proprietary"
     },
@@ -69337,7 +69337,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2515314177-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515314177-ORNL_CLOUD.html",
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         "description": "This dataset provides the complete catalog of forest inventory and biophysical measurements collected over selected forest research sites across the Amazon rainforest in Brazil between 2009 and 2018 for the Sustainable Landscapes Brazil Project. This dataset includes measurements for diameter at breast height (DBH), commercial tree height, and total tree height for forest inventories. Also included for each tree are the family, common and scientific names, coordinates, canopy position, crown radius, and for dead trees, the decomposition status. Aboveground biomass estimate is available for selected sites. The data are provided in comma-separated values (CSV) and shapefile formats. Sampling methodology for each site and year is described in companion files.",
         "license": "proprietary"
     },
@@ -69350,7 +69350,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764882625-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764882625-ORNL_CLOUD.html",
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         "description": "This dataset provides measurements for diameter at breast height (DBH) and species identification of trees for inventories taken at five tropical forest sites in Acre state, Brazil, in the southwestern Amazon region. The sites included one in a forest reserve (Reserva Bonal) and four within forest fragments situated on private property. The inventory sites included forests burned in 2005 and 2010 and also unburned forests. Surveys were conducted in July and August 2014.",
         "license": "proprietary"
     },
@@ -69363,7 +69363,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764883885-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764883885-ORNL_CLOUD.html",
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         "description": "This dataset provides tree inventory, tree height, diameter at breast height (DBH), and estimated crown measurements from 30 plots located in the Tapajos National Forest, Para, Brazil collected in September 2010. The plots were located in primary forest, primary forest subject to reduced-impact selective logging (PFL) between 1999 and 2003, and secondary forest (SF) with different age and disturbance histories. Plots were centered on GLAS (the Geoscience Laser Altimeter System) LiDAR instrument footprints selected along two sensor acquisition tracks spanning a wide range in vertical structure and aboveground biomass.",
         "license": "proprietary"
     },
@@ -69376,7 +69376,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3012482048-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3012482048-ORNL_CLOUD.html",
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         "description": "This data set provides LiDAR point clouds and digital terrain models (DTM) from surveys over the K34 tower site in the Cuieiras Biological Reserve, over forest inventory plots in the Adolpho Ducke Forest Reserve, and over sites of the Biological Dynamics of Forest Fragments Project (BDFFP) in Rio Preto da Eva municipality near Manaus, Amazonas, Brazil during June 2008. The surveys encompass the K34 eddy flux tower managed through the Large-scale Biosphere-Atmosphere Experiment in Amazonia, forest inventory plots managed by the Programa de Pesquisa em Biodiversidade (PPBio), and sites managed by the BDFFP. The LiDAR data was collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.",
         "license": "proprietary"
     },
@@ -69389,7 +69389,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2992471915-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2992471915-ORNL_CLOUD.html",
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         "description": "This data set provides LiDAR point clouds and digital terrain models (DTM) from surveys over the Tapajos National Forest in Belterra municipality, Para, Brazil during late June and early July 2008. The surveys encompass the K67 and K83 eddy flux towers and a deforestation chronosequence managed through the Large-Scale Biosphere-Atmosphere Experiment in Amazonia providing long-term flux measurements of carbon dioxide. The LiDAR data was collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.",
         "license": "proprietary"
     },
@@ -69415,7 +69415,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2953939783-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2953939783-ORNL_CLOUD.html",
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         "description": "This dataset provides a probabilistic freeze/thaw (FT) data record from 2016 to 2020 for the Northern Hemisphere derived using a deep learning model (U-Net). The model was informed by satellite multi-frequency microwave brightness temperature retrievals from the NASA SMAP (Soil Moisture Active Passive) and JAXA AMSR2 (Advanced Microwave Scanning Radiometer 2) radiometers, and trained using daily soil temperature observations from Northern Hemisphere weather stations and global reanalysis data (ERA-5). Unlike other available FT data records that provide only a binary classification of frozen or non-frozen conditions, this product includes both binary FT and continuous variable estimates of the probability of thawed conditions. This product is designed to complement other established binary FT data records, including the NASA FT Earth System Data Record and SMAP Level 3 FT operational products, by providing a probabilistic FT variable with enhanced accuracy and sensitivity to near-surface (<=5 cm depth) soil FT condition. The data are provided in cloud optimized GeoTIFF (COG) format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2395504063-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2395504063-ORNL_CLOUD.html",
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         "description": "The data provided are annual land cover projections for years 2005 through 2095 generated by the Global Change Assessment Model (GCAM) Version 3.1. For the conterminous USA, the GCAM global gridded results were downscaled to ~5.6 km (0.05 degree) resolution. For each 5.6 x 5.6 km area, the annual land cover percentage comprised by each of the nineteen different land cover classes/plant functional types (PFTs) of the Community Land Model (CLM) (Table 1) are provided.Results are reported for GCAM runs of three scenarios of future human efforts towards climate mitigation as related to global carbon emissions, radiative forcing, and land cover change. Specific scenario conditions were 1) a reference scenario with no explicit climate mitigation efforts that reaches a radiative forcing level of over 7 W/m2 in 2100, 2) the 2.6 mitigation pathway (MP) scenario which is a very low emission scenario with a mid-century peak in radiative forcing at ~3 W/m2, declining to 2.6 W/m2 in 2100, and 3) the 4.5 MP scenario which stabilizes radiative forcing at 4.5 W/m2 (~ 650 ppm CO2-equivalent) before 2100.These downscaled land cover projections can be used to derive spatially explicit estimates of potential shifts in croplands, grasslands, shrub lands, and forest lands in each future climate scenario.Data are presented as three NetCDF v4 files (.nc4), one for each future climate scenario -- 2.6 MP, 4.5 MP, and GCAM reference). ",
         "license": "proprietary"
     },
@@ -78606,7 +78606,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2408633818-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2408633818-ORNL_CLOUD.html",
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         "description": "This dataset contains four alternative digital elevation models (DEMs) at 1 m resolution and model performance statistical metrics for the Global Change Research Wetland (GCReW) site on the Rhode River, a tributary of the Chesapeake Bay in Maryland, USA, for the year 2016. Three DEMs were created by using different strategies for correcting positive biases in Light Detection and Ranging (LiDAR)-based DEMs that are common in tidal wetlands. These included (1) applying a single average offset based on a literature review, (2) using the LiDAR Elevation Correction with NDVI (LEAN)-method, and (3) applying plant community-specific offsets using a local vegetation cover map. Existing LiDAR data at 1 m resolution collected in 2011 was the basis for these DEMs. The fourth DEM was created by using Empirical Bayesian Kriging to extrapolate between measured ground points. The elevation is provided in meters relative to the North American Vertical Datum of 1988 (NAVD 88). To calibrate the four approaches, the elevation of the entire marsh complex was surveyed at 20 m x 20 m resolution to document the distribution of elevation relative to tidal datums from a single year. Two Trimble R8 real-time kinematic (RTK) GPS receivers were used to survey 525 points over the complex from July 26, 2016, to August 15, 2016. Relative plant cover was also documented. Tidal datums were calculated from the nearby Annapolis, MD tidal gauge located 13 km from GCReW.",
         "license": "proprietary"
     },
@@ -78684,7 +78684,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3126327092-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3126327092-ORNL_CLOUD.html",
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         "description": "This dataset provides eight GEDI forest structure metrics relevant to wildlife habitat modeling and biodiversity assessments at 30-m resolutions across Washington, Oregon, Idaho, Montana, Wyoming, and Colorado. The metrics characterize canopy height, strata densities, and canopy cover. The data were derived using random forest modeling and prediction frameworks. The models created were also hindcasted using 2019 and 2020 GEDI footprints back to 2016 on annual time steps leveraging continuous Landsat spectral and disturbance information, Sentinel-1 backscatter metrics and ratios, topographic information, and bioclimatic variables. Machine learning data fusion approaches were used to scale-up structure information provided by the novel space-borne Global Ecosystems Dynamics Investigation (GEDI) waveform lidar sensor to continuous extents using additional satellite-based continuous earth observation data. GEDI provides a consistent sample of forest structure information at 25-m diameter footprints at near-global extents, providing a valuable source of reference information to drive continuous mapping efforts.",
         "license": "proprietary"
     },
@@ -78697,7 +78697,7 @@
         "bbox": "-180, -52.2, 180, 52.2",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3043630107-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3043630107-ORNL_CLOUD.html",
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         "description": "This dataset consists of near-global, analysis-ready, multi-resolution gridded vegetation structure metrics derived from NASA Global Ecosystem Dynamics Investigation (GEDI) Level 2 and 4A products associated with 25-m diameter lidar footprints. This dataset provides a comprehensive representation of near-global vegetation structure that is inclusive of the entire vertical profile, based solely on GEDI lidar, and validated with independent data. The GEDI sensor, mounted on the International Space Station (ISS), uses eight laser beams spaced by 60 m along-track and 600 m across-track on the Earth surface to measure ground elevation and vegetation structure between approximately 52 degrees North and South latitude. Between April 17th 2019 and March 16th 2023, GEDI acquired 11 and 7.7 billion quality waveforms suitable for measuring ground elevation and vegetation structure, respectively. This dataset provides GEDI shot metrics aggregated into raster grids at three spatial resolutions: 1 km, 6 km, and 12 km. In addition to many of the standard L2 and L4A shot metrics, several additional metrics have been derived which may be particularly useful for applications in carbon and water cycling processes in earth system models, as well as forest management, biodiversity modeling, and habitat assessment. Variables include canopy height, canopy cover, plant area index, foliage height diversity, and plant area volume density at 5 m strata. Eight statistics are included for each GEDI shot metric: mean, bootstrapped standard error of the mean, median, standard deviation, interquartile range, 95th percentile, Shannon's diversity index, and shot count. Quality shot filtering methodology that aligns with the GEDI L4B Gridded Aboveground Biomass Density, Version 2.1 was used. In comparison to the current GEDI L3 dataset, this dataset provides additional gridded metrics at multiple spatial resolutions and over several temporal periods (annual and the full mission duration). Files are provided in cloud optimized GeoTIFF format.",
         "license": "proprietary"
     },
@@ -78710,7 +78710,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2889522012-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2889522012-ORNL_CLOUD.html",
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         "description": "This dataset provides global rasters of relative height metrics for vegetation from Global Ecosystem Dynamics Investigation (GEDI) L2A data and Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) L3A ATL08 data at 100-, 200-, 500-, and 1000-m spatial resolutions. The metrics include the relative heights RH98, RH90, RH75, and RH50, corresponding to the height at which the respective 98th, 90th, 75th, and 50th percentile of returned energy is reached relative to the ground. These metrics provide measures of vegetation canopy height and structure. The different relative height metrics were intercalibrated over the overlap area (50 - 52 degrees N). GEDI data were collected from 2019-2022, and ICESat2 data were from 2019-2021. The data are provided in cloud optimized GeoTIFF format.",
         "license": "proprietary"
     },
@@ -78723,7 +78723,7 @@
         "bbox": "-180, -52, 180, 52",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153683336-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153683336-ORNL_CLOUD.html",
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         "description": "This dataset provides Global Ecosystem Dynamics Investigation (GEDI) Level 3 (L3) gridded mean canopy height, standard deviation of canopy height, mean ground elevation, standard deviation of ground elevation, and counts of laser footprints per 1-km x 1-km grid cells globally within -52 and 52 degrees latitude. These L3 gridded products were derived from Level 2 (L2) geolocated laser footprint return profile metrics from the GEDI instrument onboard the International Space Station (ISS). Canopy height is provided as the mean height (in meters) above the ground of the received waveform signal that was the first reflection off the top of the canopy (RH100). Ground elevation is provided as the mean elevation (in meters) of the center of the lowest waveform mode relative to the WGS84 reference ellipsoid. L3 gridded products can be used to characterize important carbon and water cycling processes, biodiversity, habitat and can also be of immense value for climate modeling, forest management, snow and glacier monitoring, and the generation of digital elevation models. This dataset version uses Version 2 of the input L2 data, which includes improved geolocation of the footprints as well as a modified method to predict an optimum algorithm setting group.",
         "license": "proprietary"
     },
@@ -78736,7 +78736,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2734289572-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2734289572-ORNL_CLOUD.html",
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         "description": "This dataset contains Global Ecosystem Dynamics Investigation (GEDI) Level 4A (L4A) predictions of the aboveground biomass density (AGBD; in Mg/ha) and estimates of the prediction standard error within each sampled geolocated laser footprint. The footprints are located within the global latitude band observed by the International Space Station (ISS), nominally 51.6 degrees N and S and reported for the mission weeks 19, 32, 34 and 38 (a.k.a. Golden Weeks). These weeks cover the range of instrument operating conditions important for calibration and validation of geolocation algorithms, and also include GEDI orbits that are coincident with underflights acquired by the LVIS (Land, Vegetation, and Ice Sensor) airborne lidar instrument. The GEDI instrument consists of three lasers producing a total of eight beam ground transects, which instantaneously sample eight ~25 m footprints spaced approximately every 60 m along-track. The GEDI beam transects are spaced approximately 600 m apart on the Earth's surface in the cross-track direction, for an across-track width of ~4.2 km. Footprint AGBD was derived from parametric models that relate simulated GEDI Level 2A (L2A) waveform relative height (RH) metrics to field plot estimates of AGBD. Height metrics from simulated waveforms associated with field estimates of AGBD from multiple regions and plant functional types (PFT) were compiled to generate a calibration dataset for models representing the combinations of world regions and PFTs (i.e., deciduous broadleaf trees, evergreen broadleaf trees, evergreen needleleaf trees, deciduous needleleaf trees, and the combination of grasslands, shrubs, and woodlands).",
         "license": "proprietary"
     },
@@ -78749,7 +78749,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2237824918-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2237824918-ORNL_CLOUD.html",
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         "description": "This dataset contains Global Ecosystem Dynamics Investigation (GEDI) Level 4A (L4A) Version 2 predictions of the aboveground biomass density (AGBD; in Mg/ha) and estimates of the prediction standard error within each sampled geolocated laser footprint. In this version, the granules are in sub-orbits. The algorithm setting group selection used for GEDI02_A Version 2 has been modified for Evergreen Broadleaf Trees in South America to reduce false positive errors resulting from the selection of waveform modes above ground elevation as the lowest mode. The footprints are located within the global latitude band observed by the International Space Station (ISS), nominally 51.6 degrees N and S and reported for the period 2019-04-18 to 2023-03-16. The GEDI instrument consists of three lasers producing a total of eight beam ground transects, which instantaneously sample eight ~25 m footprints spaced approximately every 60 m along-track. The GEDI beam transects are spaced approximately 600 m apart on the Earth's surface in the cross-track direction, for an across-track width of ~4.2 km. Footprint AGBD was derived from parametric models that relate simulated GEDI Level 2A (L2A) waveform relative height (RH) metrics to field plot estimates of AGBD. Height metrics from simulated waveforms associated with field estimates of AGBD from multiple regions and plant functional types (PFTs) were compiled to generate a calibration dataset for models representing the combinations of world regions and PFTs (i.e., deciduous broadleaf trees, evergreen broadleaf trees, evergreen needleleaf trees, deciduous needleleaf trees, and the combination of grasslands, shrubs, and woodlands). For each of the eight beams, additional data are reported with the AGBD estimates, including the associated uncertainty metrics, quality flags, model inputs, and other information about the GEDI L2A waveform for this selected algorithm setting group. Model inputs include the scaled and transformed GEDI L2A RH metrics, footprint geolocation variables and land cover input data including PFTs and the world region identifiers. Additional model outputs include the AGBD predictions for each of the six GEDI L2A algorithm setting groups with AGBD in natural and transformed units and associated prediction uncertainty for each GEDI L2A algorithm setting group. Providing these ancillary data products will allow users to evaluate and select alternative algorithm setting groups. Also provided are outputs of parameters and variables from the L4A models used to generate AGBD predictions that are required as input to the GEDI04_B algorithm to generate 1-km gridded products.",
         "license": "proprietary"
     },
@@ -78762,7 +78762,7 @@
         "bbox": "-180, -52, 180, 52",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2813390180-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2813390180-ORNL_CLOUD.html",
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         "description": "This dataset provides country-level estimates of land surface mean aboveground biomass density (AGBD), total aboveground biomass (AGB) stocks, and the associated standard errors of the mean calculated using different versions of the Global Ecosystem Dynamics Investigation (GEDI) Level-4B (L4B) product. The GEDI L4B product provides gridded (1 km x 1 km) estimates of AGBD within the GEDI orbital extent (between 51.6 degrees N and 51.6 degrees S). For comparison purposes, this dataset also includes national-scale National Forest Inventory (NFI) estimates of AGBD from the 2020 Global Forest Resources Assessment (FRA) published by the Food and Agriculture Organization (FAO, 2020) of the United Nations.The GEDI instrument produces high-resolution laser ranging observations of the 3-dimensional structure of the Earth's surface. GEDI was launched on December 5, 2018, and is attached to the International Space Station (ISS). The GEDI instrument consists of three lasers producing a total of eight beam ground transects, which consist of ~25 m footprint samples spaced approximately every 60 m along-track. The GEDI beam transects are spaced approximately 600 m apart on the Earth's surface in the cross-track direction, for an across-track width of ~4.2 km. The data are provided in comma-separated value (CSV) format.",
         "license": "proprietary"
     },
@@ -78775,7 +78775,7 @@
         "bbox": "-180, -52, 180, 52",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2792577683-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2792577683-ORNL_CLOUD.html",
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         "description": "This Global Ecosystem Dynamics Investigation (GEDI) L4B product provides 1 km x 1 km (1 km,  hereafter) estimates of mean aboveground biomass density (AGBD) based on observations from mission week 19 starting on 2019-04-18 to mission week 223 ending on 2023-03-16. The GEDI L4A Footprint Biomass product converts each high-quality waveform to an AGBD prediction, and the L4B product uses the sample present within the borders of each 1 km cell to statistically infer mean AGBD. The gridding procedure is described in the GEDI L4B Algorithm Theoretical Basis Document (ATBD). Patterson et al. (2019) describes the hybrid model-based mode of inference used in the L4B product. Corresponding 1 km estimates of the standard error of the mean are also provided in the L4B product. Uncertainty is due to both GEDI's sampling of the 1 km area (as opposed to making wall-to-wall observations) and the fact that L4A biomass values are modeled in a process subject to error instead of measured in a process that may be assumed to be error-free.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3049900163-ORNL_CLOUD.html",
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         "description": "This dataset contains Global Ecosystem Dynamics Investigation (GEDI) Level 4C (L4C) Version 2 predictions of the Waveform Structural Complexity Index (WSCI) and estimates of prediction intervals for each footprint estimate at 95% confidence. In this version, the granules are in sub-orbits. The algorithm setting group selection used for GEDI04_C is the same as in the GEDI02_A product. The footprints are located within the global latitude band observed by the International Space Station (ISS), nominally 51.6 degrees N and S and reported for the period 2019-04-17 to 2023-03-16. The GEDI instrument consists of three lasers producing a total of eight beam ground transects, which instantaneously sample eight ~25 m footprints spaced approximately every 60 m along-track. The GEDI beam transects are spaced approximately 600 m apart on the Earth's surface in the cross-track direction, for an across-track width of ~4.2 km. Footprint WSCI was derived from XGBoost regression models relating simulated GEDI Level 2A (L2A) waveform relative height (RH) metrics to a 3D structural complexity metric calculated from matched Airborne laser Scanning (ALS) point clouds. Four global WSCI models were trained on a plant functional type (PFT) basis (i.e., deciduous broadleaf trees, evergreen broadleaf trees, evergreen needleleaf trees, and the combination of grasslands, shrubs, and woodlands). For each of the eight beams, additional data are reported with the WSCI estimates, including the associated uncertainty metrics, quality flags, and other information about the GEDI L2A waveform for this selected algorithm setting group. Additional model outputs include WSCI predictions for each of the six GEDI L2A algorithm setting groups and associated prediction intervals. Providing these ancillary data products will allow users to evaluate and select alternative algorithm setting groups. The data are provided in HDF5 format.",
         "license": "proprietary"
     },
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         "description": "This data set provides normalized difference vegetation index (NDVI) data for the arctic growing season derived primarily with data from Advanced Very High Resolution Radiometer (AVHRR) sensors onboard several NOAA satellites over the years 1982 through 2012. The NDVI data, which show vegetation activity, were averaged annually for the arctic growing season (GS; June, July and August). The products include the annual GS-NDVI values and the results of a cumulative GS-NDVI time series trends analysis. The data are circumpolar in coverage at 8-km resolution and limited to greater than 20 degrees N.These normalized difference vegetation index (NDVI) trends were calculated using the third generation data set from the Global Inventory Modeling and Mapping Studies (GIMMS 3g). GIMMS 3g improves on its predecessor (GIMMS g) in three important ways. First, GIMMS 3g integrates data from NOAA-17 and 18 satellites to lengthen its record. Second, it addresses the spatial discontinuity north of 72 degrees N, by using SeaWiFS, in addition to SPOT VGT, to calibrate between the second and third versions of the AVHRR sensor (AVHRR/2 and AVHRR/3). Finally, the GIMMS 3g algorithm incorporates improved snowmelt detection and is calibrated based on data from the shorter, arctic growing season (May-September) rather than the entire year (January-December). ",
         "license": "proprietary"
     },
@@ -79971,7 +79971,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780535151-ORNL_CLOUD.html",
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         "description": "A 0.5 degree lat/lon data set of monthly surface climate over global land areas, excluding Antarctica. Primary variables are interpolated directly from station time-series: precipitation, mean temperature and diurnal temperature range.",
         "license": "proprietary"
     },
@@ -80004,26 +80004,26 @@
     {
         "id": "GLAH02_033",
         "title": "GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033",
-        "catalog": "NSIDC_CPRD STAC Catalog",
+        "catalog": "NSIDC_ECS STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.html",
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         "description": "GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.",
         "license": "proprietary"
     },
     {
         "id": "GLAH02_033",
         "title": "GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033",
-        "catalog": "NSIDC_ECS STAC Catalog",
+        "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.html",
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         "description": "GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.",
         "license": "proprietary"
     },
@@ -80056,26 +80056,26 @@
     {
         "id": "GLAH04_033",
         "title": "GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033",
-        "catalog": "NSIDC_CPRD STAC Catalog",
+        "catalog": "NSIDC_ECS STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wiYXRsYXMvaWNlc2F0LTIgbDNiIHdlZWtseSBncmlkZGVkIGF0bW9zcGhlcmUgdjAwNVwiLFwiTlNJRENfRUNTXCIsXCJBVEwxNlwiLFwiNVwiLDI3Mzc5OTcyNDMsNThdIiwidW1tIjoiW1wiYXRsYXMvaWNlc2F0LTIgbDNiIHdlZWtseSBncmlkZGVkIGF0bW9zcGhlcmUgdjAwNVwiLFwiTlNJRENfRUNTXCIsXCJBVEwxNlwiLFwiNVwiLDI3Mzc5OTcyNDMsNThdIn0%3D/GLAH04_033",
         "description": "Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing.",
         "license": "proprietary"
     },
     {
         "id": "GLAH04_033",
         "title": "GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033",
-        "catalog": "NSIDC_ECS STAC Catalog",
+        "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.html",
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         "description": "Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing.",
         "license": "proprietary"
     },
@@ -80209,19 +80209,6 @@
         "description": "GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz.  Each data granule has an associated browse product.",
         "license": "proprietary"
     },
-    {
-        "id": "GLAH10_033",
-        "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033",
-        "catalog": "NSIDC_CPRD STAC Catalog",
-        "state_date": "2003-09-25",
-        "end_date": "2009-10-11",
-        "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html",
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-        "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds.  Each data granule has an associated browse product.",
-        "license": "proprietary"
-    },
     {
         "id": "GLAH10_033",
         "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033",
@@ -80236,16 +80223,16 @@
         "license": "proprietary"
     },
     {
-        "id": "GLAH11_033",
-        "title": "GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033",
+        "id": "GLAH10_033",
+        "title": "GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033",
         "catalog": "NSIDC_CPRD STAC Catalog",
-        "state_date": "2003-02-20",
+        "state_date": "2003-09-25",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.html",
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-        "description": "GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.html",
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+        "description": "GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds.  Each data granule has an associated browse product.",
         "license": "proprietary"
     },
     {
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         "license": "proprietary"
     },
     {
-        "id": "GLAH12_034",
-        "title": "GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034",
+        "id": "GLAH11_033",
+        "title": "GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033",
         "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.html",
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+        "description": "GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.",
         "license": "proprietary"
     },
     {
@@ -80288,15 +80275,15 @@
         "license": "proprietary"
     },
     {
-        "id": "GLAH13_034",
-        "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034",
+        "id": "GLAH12_034",
+        "title": "GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034",
         "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.html",
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         "license": "proprietary"
     },
@@ -80314,15 +80301,15 @@
         "license": "proprietary"
     },
     {
-        "id": "GLAH14_034",
-        "title": "GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034",
+        "id": "GLAH13_034",
+        "title": "GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034",
         "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.html",
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         "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.",
         "license": "proprietary"
     },
@@ -80340,15 +80327,15 @@
         "license": "proprietary"
     },
     {
-        "id": "GLAH15_034",
-        "title": "GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034",
-        "catalog": "NSIDC_ECS STAC Catalog",
+        "id": "GLAH14_034",
+        "title": "GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034",
+        "catalog": "NSIDC_CPRD STAC Catalog",
         "state_date": "2003-02-20",
         "end_date": "2009-10-11",
         "bbox": "-180, -86, 180, 86",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.html",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_CPRD/collections?cursor=eyJqc29uIjoiW1wiYXRsYXMvaWNlc2F0LTIgbDNiIG1vbnRobHkgZ3JpZGRlZCBkeW5hbWljIG9jZWFuIHRvcG9ncmFwaHkgdjAwM1wiLFwiTlNJRENfQ1BSRFwiLFwiQVRMMTlcIixcIjNcIiwyNzU0OTU2Nzg2LDEyXSIsInVtbSI6IltcImF0bGFzL2ljZXNhdC0yIGwzYiBtb250aGx5IGdyaWRkZWQgZHluYW1pYyBvY2VhbiB0b3BvZ3JhcGh5IHYwMDNcIixcIk5TSURDX0NQUkRcIixcIkFUTDE5XCIsXCIzXCIsMjc1NDk1Njc4NiwxMl0ifQ%3D%3D/GLAH14_034",
         "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.",
         "license": "proprietary"
     },
@@ -80365,6 +80352,19 @@
         "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.",
         "license": "proprietary"
     },
+    {
+        "id": "GLAH15_034",
+        "title": "GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034",
+        "catalog": "NSIDC_ECS STAC Catalog",
+        "state_date": "2003-02-20",
+        "end_date": "2009-10-11",
+        "bbox": "-180, -86, 180, 86",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wiZ2xhcy9pY2VzYXQgbDFiIGdsb2JhbCBlbGV2YXRpb24gZGF0YSAoaGRmNSkgdjAzNFwiLFwiTlNJRENfRUNTXCIsXCJHTEFIMDZcIixcIjM0XCIsMTAwMDAwMDQ0NSwxNjddIiwidW1tIjoiW1wiZ2xhcy9pY2VzYXQgbDFiIGdsb2JhbCBlbGV2YXRpb24gZGF0YSAoaGRmNSkgdjAzNFwiLFwiTlNJRENfRUNTXCIsXCJHTEFIMDZcIixcIjM0XCIsMTAwMDAwMDQ0NSwxNjddIn0%3D/GLAH15_034",
+        "description": "GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (\u00b1 50\u00b0 latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.",
+        "license": "proprietary"
+    },
     {
         "id": "GLCHMK_001",
         "title": "G-LiHT Canopy Height Model KML V001",
@@ -81726,7 +81726,7 @@
         "bbox": "5, -35, 60, 5",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788385787-ORNL_CLOUD.html",
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         "description": "The Global Precipitation Climatology Project (GPCP) is an international project designed to provide improved long-record estimates of precipitation over the globe. The general approach is to combine the precipitation information available from several sources into a final merged product that takes advantage of the strengths of each data type. The GPCP has promoted the development of an analysis procedure for blending the various estimates together to produce the necessary global gridded precipitation fields. The currently operational procedure is based on Huffman et al. (1995) and has been used to produce the GPCP Version 2 Combined Precipitation Data Set, covering the period January 1979 through the present. The primary product in the Version 2 data set is a combined observation-only data set, that is, a gridded analysis based on gauge measurements and satellite estimates of rainfall.",
         "license": "proprietary"
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         "description": "This dataset includes estimates of gross primary production (GPP) for the conterminous U.S., for 2018-02-15 to 2021-10-15, based on measurements of solar-induced chlorophyll fluorescence from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5P satellite platform. GPP was estimated from rates of photosynthesis inferred from SIF using a linear model and ecosystem scaling factors from 102 AmeriFlux sites. Knowledge of the spatiotemporal patterns of GPP is necessary for understanding regional and global carbon budgets. Broad-scale estimates of GPP have typically relied upon carbon cycle models linking spatial patterns of vegetation with remotely sensed environmental data. SIF provides a means to directly estimate photosynthetic activity, and therefore, GPP. Recent deployments of satellite platforms that measure SIF provide near-real-time measurements and represent a breakthrough in measuring GPP on a global scale.   Regular SIF measurements can detect spatially explicit ecosystem-level responses to climate events such as drought and flooding. This dataset includes spatially explicit estimates of GPP (g m-2 d-1), uncertainty in GPP, and related TROPOMI SIF measurements (mW m-2 sr-1 nm-1) at 500-m resolution.  The data are provided in NetCDF format.",
         "license": "proprietary"
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         "description": "The GPROF 6.0 Pentads data set contains 5-day (pentad) averages of the GPROF 6.0 Gridded Orbits. The GPROF(Goddard Profiling Algorithm) data set contains a suite of 9 products providing instantaneous, gridded values of precipitation totals for each granule of the SSM/I (Special Sensor Microwave/Imager) data over the roughly 14-year period July 1987 through the present. Even though there have been at least two satellites for the entire period, sampling is sufficiently sparse that the data are averaged for pentads, then the pentads are smoothed with a 1-2-3-2-1 time-weighting. The last two pentads are unevenly weighted since the last (or last two) pentads in the average are not yet available. Consequently, the last two pentads must be recomputed when the next pentad becomes available.The data set prepared for SAFARI cover the years 1999, 2000, and 2001.The main refereed citations for the data set are Kummerow et al. (1996)and Olson et al. (1999)",
         "license": "proprietary"
     },
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         "description": "This dataset provides multiple-return LiDAR-derived vegetation canopy structure at 30-meter spatial resolution for the Great Smoky Mountains National Park (GSMNP). Canopy characteristics were analyzed using high resolution three-dimensional point cloud measurements gathered between February-April 2011 for Tennessee and during March-April 2005 for North Carolina sections of the park. Vegetation types were mapped by grouping areas of similar canopy structure. The map was compared and validated against existing vegetation maps for the park.",
         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Web-Enabled Landsat Data Monthly (GWELDMO) Version 3 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over monthly reporting periods for the 2010 epoch. GWELD data products are generated from all available Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provide consistent data to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics.    The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and to top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA\u2019s Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid.    Provided in the GWELDMO product are layers for surface reflectance bands 1 through 5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule.",
         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Web-Enabled Landsat Data Monthly (GWELDMO) Version 3.1 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over monthly reporting periods for the 1985, 1990, and 2000 epochs. GWELD data products are generated from all available Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provide consistent data to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics.    The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and to top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA\u2019s Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid.    Provided in the GWELDMO product are layers for surface reflectance bands 1 through 5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule.    Version 3.1 products use Landsat Collection 1 products as input and have improved per-pixel cloud mask, new quality data, improved calibration information, and improved product metadata that enable view and solar geometry calculations.",
         "license": "proprietary"
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         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Web-Enabled Landsat Data Annual (GWELDYR) Version 3.1 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over annual reporting periods for the 1985, 1990, and 2000 epochs. GWELD data products are generated from all available Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provide consistent data to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics.    The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and to top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA\u2019s Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid.    Provided in the GWELDYR product are layers for surface reflectance bands 1 through 5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule.    Version 3.1 products use Landsat Collection 1 products as input and have improved per-pixel cloud mask, new quality data, improved calibration information, and improved product metadata that enable view and solar geometry calculations.",
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         "description": "This data set provides global forest area, forest growing stock, and forest biomass data at 1-degree resolution for the period 1950-2010. The data set is based on a compilation of forest area and growing stock data reported in international assessments performed by FAO, MCPFE (now Forest Europe), and UNECE. Data of different assessments are to the extent possible harmonized to reflect both forest area and other wooded land, to be comparable between countries and assessments.",
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         "description": "This dataset provides global clumping index (CI) data for 2006 derived from the MODIS Bidirectional Reflectance Distribution Function (BRDF) data product. Clumping index is a key structural parameter of plant canopies which represents the degree of foliage grouping within distinct canopy structures relative to a random distribution. The data are provided at substantially higher resolution (500-m) than existing clumping index data products.",
         "license": "proprietary"
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         "description": "This dataset provides monthly globally gridded freshwater wetland methane emissions from 2001-2018 in nmol CH4 m-2 s-1, g C-CH4 m-2 d-1, and TgCH4 grid cell-1 month-1. The data were derived from a six-predictor random forest upscaling model (UpCH4) trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites covering bog (8), fen (8), marsh (10), swamp (6), and wet tundra (11) wetland classes and distributed across Arctic-boreal (20), temperate (16), and (sub)tropical (7) climate zones. Weekly mean CH4 fluxes were computed from half-hourly FLUXNET-CH4 Version 1.0 fluxes. Each grid cell CH4 flux prediction was weighted by fractional grid cell wetland extent to estimate CH4 emissions using the primary global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M) product and an alternate Global Inundation Estimate from Multiple Satellites GIEMS version 2 global wetland map. Both WAD2M and GIEMS-2 maps were modified with several correction data layers to represent the monthly area covered by vegetated wetlands, excluding open water and coastal wetlands. The data products are: mean daily fluxes with no adjustment for wetland area (i.e., flux densities assuming hypothetical 100% wetland cover); mean daily fluxes adjusting for WAD2M or GIEMS-2 wetland area; and by-pixel monthly sum of freshwater wetland methane emissions adjusting for WAD2M or GIEMS-2 wetland area. The data are provided in NetCDF4 format.",
         "license": "proprietary"
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         "description": "This dataset - HYSOGs250m - represents a globally consistent, gridded dataset of hydrologic soil groups (HSGs) with a geographical resolution of 1/480 decimal degrees, corresponding to a projected resolution of approximately 250-m. These data were developed to support USDA-based curve-number runoff modeling at regional and continental scales. Classification of HSGs was derived from soil texture classes and depth to bedrock provided by the Food and Agriculture Organization soilGrids250m system.",
         "license": "proprietary"
     },
@@ -85912,7 +85912,7 @@
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         "description": "This dataset provides global gridded information on lake surface area and open water CH4 emissions at a resolution of 0.25-degree x 0.25-degree for an annual climatology representative of the average conditions from 2003 to 2015. A compilation of flux data from 575 individual lake systems and 893 aggregated flux values were used, and each flux measurement was classified into one of seven ecoclimatic types. Ice-cover-regulated emission seasonality was derived from satellite microwave observations of ice cover phenology and freeze-thaw dynamics. Global lake area was determined from the merger of HydroLAKES and Climate Change Initiative Inland-Water (CCI-IW) remote-sensing data, and lakes were classified into ecoclimatic regions to facilitate linking these types with ecosystem-specific CH4 measurements in the flux compilation. Exploratory estimates of fluxes associated with ice melt and with spring and fall water-column turnover are also included. The data are provided in NetCDF format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764708636-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764708636-ORNL_CLOUD.html",
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         "description": "This dataset provides temporally consistent and harmonized global maps of aboveground and belowground biomass carbon density for the year 2010 at a 300-m spatial resolution. The aboveground biomass map integrates land-cover specific, remotely sensed maps of woody, grassland, cropland, and tundra biomass. Input maps were amassed from the published literature and, where necessary, updated to cover the focal extent or time period. The belowground biomass map similarly integrates matching maps derived from each aboveground biomass map and land-cover specific empirical models. Aboveground and belowground maps were then integrated separately using ancillary maps of percent tree cover and landcover and a rule-based decision tree. Maps reporting the accumulated uncertainty of pixel-level estimates are also provided.",
         "license": "proprietary"
     },
@@ -86003,7 +86003,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764742564-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764742564-ORNL_CLOUD.html",
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         "description": "This dataset provides global monthly average gross primary productivity (GPP; g carbon/m2/d) modeled at 8 km spatial resolution for each of the 35 years from 1982-2016. GPP is based on the well-known Monteith light use efficiency (LUE) equation but was improved with optimized spatially and temporally explicit LUE values derived from selected FLUXNET tower site data. Optimized LUE was extrapolated to a consistent 8 km resolution global grid using multiple explanatory variables representing climatic, landscape, and vegetation factors influencing LUE and GPP. Global gridded long-term daily GPP was derived using the optimized LUE, Global Inventory Modeling and Mapping Studies (GIMMS3g) canopy fraction of photosynthetically active radiation (FPAR), and Modern-Era Retrospective analysis for Research and Applications, Version 2, (MERRA-2) meteorological information. These data will improve satellite-based estimation and understanding of GPP using a refined LUE model framework.",
         "license": "proprietary"
     },
@@ -86016,7 +86016,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863372-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863372-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of different forms of naturally occurring soil phosphorus (P) including labile inorganic P, organic P, occluded P, secondary mineral P, apatite P, and total P on a global scale at 0.5-degree resolution. The data were assembled from chronosequence information and global spatial databases to develop a map of total soil P and the distribution among mineral bound, labile, organic, occluded, and secondary P forms in soils. Uncertainty was calculated for the different forms. The data set has no explicit temporal component -- data were nominally for the pre-industrial period ca. 1850.The estimated global spatial variation and distribution of different soil P forms presented in this study will be useful for global biogeochemistry models that include P as a limiting element in biological production by providing initial estimates of the available soil P for plant uptake and microbial utilization (Yang et al., 2013).There is one netCDF data file (.nc) with this data set. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2515869951-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515869951-ORNL_CLOUD.html",
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         "description": "This dataset includes global maps of methane (CH4) emissions from inland dam-reservoir systems at 0.25-degree spatial resolution. Daily emission rates (as grams of CH4 per day per total area of grid cell) were estimated for boreal, temperate, and subtropical-tropical eco-climatic domains and total emissions. The annual duration of the emission season is based on freeze-thaw cycles of these water bodies as applicable. In addition, the dataset includes the total fractional area of reservoirs in each grid cell. These estimates will promote understanding of the current and future role of reservoirs in the global CH4 budget and guide efforts to mitigate reservoir-related CH4 emissions. These emission estimates are climatological; one daily value for each day of year (n=365) is provided for each grid cell. Modeled estimates were based on daily mean inputs, averaged over 2002 to 2015.",
         "license": "proprietary"
     },
@@ -86068,7 +86068,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389020006-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389020006-ORNL_CLOUD.html",
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         "description": "This dataset provides modeled estimates of annual nitrous oxide (N2O) emissions at a coarse geographic scale (0.5 x 0.5 degree) for two sets of global rivers and streams covering the period of 1900-2016. Emissions (g N2O-N/yr) are provided for higher-order rivers and streams (>=4th order) and headwater streams (<4th order). The estimates were derived from a water transport model, the Model for Scale Adaptive River Transport (MOSART), coupled with the Dynamic Land Ecosystem Model (DLEM) to link hydrology and ecosystem processes pertaining to N2O flux and transport. Factors driving the model included climate, land use and land cover, and nitrogen inputs (i.e., fertilizer, deposition, manure, and sewage). Nitrogen discharges from streams and rivers to the ocean were calibrated from observations from 50 river basins across the globe.",
         "license": "proprietary"
     },
@@ -86081,7 +86081,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2207986708-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2207986708-ORNL_CLOUD.html",
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         "description": "This dataset provides spatially-contiguous global mean daily solar-induced chlorophyll fluorescence (SIF) estimates at 0.05 degree (approximately 5 km at the equator) spatial and 16-day temporal resolution from September 2014 through July 2020. This product was derived from Orbiting Carbon Observatory-2 (OCO-2) SIF observations and produced by training an artificial neural network (ANN) on the native OCO-2 SIF observations and MODIS BRDF-corrected seven-band surface reflectance along OCO-2's orbits. The trained ANN model was then applied to predict mean daily SIF (mW/m2/nm/sr) in OCO-2's gap regions based on MODIS reflectance and landcover. This framework was stratified by biomes and 16-day time steps. This dataset's high resolution and global contiguous coverage will greatly enhance the synergy between satellite SIF and photosynthesis measured on the ground at consistent spatial scales. Potential applications of this dataset include advancing dynamic drought monitoring and mitigation, informing agricultural planning and yield estimation, and providing a benchmark for upcoming satellite missions with SIF capabilities at higher spatial resolutions.",
         "license": "proprietary"
     },
@@ -86094,7 +86094,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2575421513-ORNL_CLOUD.html",
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         "description": "This dataset provides global salt marsh change, including loss and gain for five-year periods from 2000-2019. Loss and gain at a 30 m spatial resolution were estimated with Normalized Difference Vegetation Index (NDVI) anomaly algorithm using Landsat 5, 7, and 8 collections within the known extent of salt marshes. The data are provided in cloud-optimized GeoTIFF format.",
         "license": "proprietary"
     },
@@ -86107,7 +86107,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864025-ORNL_CLOUD.html",
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         "description": "This data set provides high-resolution estimates of the thickness of the permeable layers above bedrock (soil, regolith, and sedimentary deposits) within a global 30-arcsecond (~1-km) grid using the best available data for topography, climate, and geology as input. These data are modeled to represent estimated thicknesses by landform type for the geological present.",
         "license": "proprietary"
     },
@@ -86120,7 +86120,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2759076389-ORNL_CLOUD.html",
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         "description": "This dataset holds the Global Inventory Modeling and Mapping Studies-3rd Generation V1.2 (GIMMS-3G+) data for the Normalized Difference Vegetation Index (NDVI). NDVI was based on corrected and calibrated measurements from Advanced Very High Resolution Radiometer (AVHRR) data with a spatial resolution of 0.0833 degree and global coverage for 1982 to 2022. Maximum NDVI values are reported within twice monthly compositing periods (two values per month). The dataset was assembled from different AVHRR sensors and accounts for various deleterious effects, such as calibration loss, orbital drift, and volcanic eruptions. The data are provided in NetCDF format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2762262652-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2762262652-ORNL_CLOUD.html",
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         "description": "This dataset provides maps of woody (tree and shrub) cover and biomass across Sub-Saharan Africa at a resolution of 1 km for the period 2000-2004. Canopy cover observations and remote-sensing data related to woody vegetation were used to predict woody cover across Africa. Predicted woody cover, canopy height, and tree allometry were used to estimate woody biomass for Sub-Saharan Africa. Canopy cover observations were assembled from field measurements and Google Earth imagery collected from 2000-2004. Remote-sensing data related to the structural attributes of woody vegetation were derived from MODIS optical data and Q-SCAT (Quick Scatterometer) microwave measurements. Canopy height estimates were derived from spaceborne lidar and tree allometry equations were retrieved from GlobAllomeTree.",
         "license": "proprietary"
     },
@@ -86939,7 +86939,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2756285170-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756285170-ORNL_CLOUD.html",
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         "description": "Time series of monthly minimum and maximum temperature, precipitation, and potential evapotranspiration were derived for 1,469 watersheds in the conterminous United States for which stream flow measurements were also available from the national streamflow database, termed the Hydro-Climatic Data Network (HCDN), developed by Slack et al. (1993a,b). Monthly climate estimates were derived for the years 1951-1990.The climate characteristic estimates of temperature and precipitation were estimated using the PRISM (Daly et al. 1994, 1997) climate analysis system as described in Vogel, et al. 1999.Estimates of monthly potential evaporation were obtained using a method introduced by Hargreaves and Samani (1982) which is based on monthly time series of average minimum and maximum temperature data along with extraterrestrial solar radiation. Extraterrestrial solar radiation was estimated for each basin by computing the solar radiation over 0.1 degree grids using the method introduced by Duffie and Beckman (1980) and then summing those estimates for each river basin. This process is described in Sankarasubramanian, et al. (2001). Revision Notes: This data set has been revised to update the number of watersheds included in the data set and to updated the units for the potential evapotranspiration variable.  Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
@@ -88213,7 +88213,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863856-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863856-ORNL_CLOUD.html",
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         "description": "This data set describes select global soil parameters from the Harmonized World Soil Database (HWSD) v1.2, including additional calculated parameters such as area weighted soil organic carbon (kg C per m2), as high resolution NetCDF files. These data were regridded and upscaled from the Harmonized World Soil Database v1.2 The HWSD provides information for addressing emerging problems of land competition for food production, bio-energy demand and threats to biodiversity and can be used as input to model global carbon cycles. The data are presented as a series of 27 NetCDF v3/v4 (*.nc4) files at 0.05-degree spatial resolution, and one NetCDF file regridded to the Community Land Model (CLM) grid cell resolution (0.9 degree x 1.25 degree) for the nominal year of 2000.",
         "license": "proprietary"
     },
@@ -88460,7 +88460,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517357574-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517357574-ORNL_CLOUD.html",
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         "description": "This dataset provides sub-daily, high-resolution, climate data inputs including temperature, precipitation, near surface specific humidity, incoming short-wave radiation, and near-surface wind speed over 11 states of the western USA. States included are Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. These data were derived for use in the Community Land Model (CLM v4.5) and are at 3-hourly temporal and 4 x 4 km spatial resolutions for the 1979 through 2015 time period. The source for observational data was METDATA (now called GRIDMET), at a daily resolution. Modeling efforts using these data estimated annual carbon stocks, fluxes, and productivity across the western United States.",
         "license": "proprietary"
     },
@@ -88473,7 +88473,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389081763-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389081763-ORNL_CLOUD.html",
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         "description": "This dataset provides maps of tidal marsh green vegetation, non-vegetation, and open water for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD, Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Maps were derived from current National Agriculture Imagery Program data (2013-2015) using object-based classification for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program (C-CAP) map. These 1m resolution maps were used to calculate the fraction of green vegetation within 30m Landsat pixels for the same tidal marsh regions and these data are provided in a related dataset.",
         "license": "proprietary"
     },
@@ -88499,7 +88499,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810678638-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810678638-ORNL_CLOUD.html",
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         "description": "Leaf Area Index (LAI) data from the scientific literature, 1932-2000, have been compiled at the ORNL DAAC to support model development and EOS MODIS product validation. Like net primary productivity (NPP), leaf area index (LAI) is a key parameter for global and regional models of biosphere/atmosphere exchange.",
         "license": "proprietary"
     },
@@ -88551,7 +88551,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515903145-ORNL_CLOUD.html",
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         "description": "This dataset provides hourly urban greenhouse gas measurements for cities in the CO2 Urban Synthesis and Analysis (CO2-USA) Data Synthesis Network for 2000 to 2019. Measurements include carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) concentrations measured at hourly intervals at multiple sites within the U.S. cities of Boston, Indianapolis, Los Angeles, Portland, Salt Lake City, San Francisco, and Washington DC/Baltimore, and Toronto, Canada.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216880820-ORNL_CLOUD.html",
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         "description": "This dataset contains global data on soil properties, global maps of soil distributions, and the SoilData System developed by the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS). These data were originally distributed on CD-ROM, but are provided here as a single zip file. The SoilData System allows users to generate soil information and maps for geographic regions at soil depths and resolutions selected by the user. Derived surfaces of carbon density, nutrient status, water-holding capacity, and heat capacity are provided for modeling and inventory purposes.",
         "license": "proprietary"
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         "description": "Global data-surfaces pre-generated by  SoilData, at a resolution of 5x5 arc-minutes, in ASCII GRID format for ARC INFO, and for the soil depth interval 0-100 cm.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777741360-ORNL_CLOUD.html",
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         "description": "This data set contains hydrology, soils, radiation, cloud, and vegetation data from the International Satellite Land Surface Climatology Project (ISLSCP) Initiative I. The ISLSCP data sets should provide LBA modelers with many of the fields required to describe boundary conditions, and to initialize and force a wide range of land-biosphere-atmosphere models.  All of the data have been processed to the same global spatial resolution (1 deg. x 1 deg.), using the same land/sea mask and steps have been taken to ensure spatial and temporal continuity of the data. The data sets cover the period 1987-1988 at 1-month time resolution for most of the seasonally varying quantities. For this pre-LBA data set, the ISLSCP I data are provided as global coverages. The companion file illustrations were subset over the LBA study area, from 35-85 deg. W longitude and 20 deg. S to 10 deg. N latitude, as shown in Figure 1.The data files and illustrations are organized into the three groups listed below.1. Hydrology and Soils2. Radiation and Clouds3. VegetationThe data within each of these areas were acquired from a variety of sources including model output, satellites, and ground measurements. The individual data sets were provided in a variety of forms. In some cases, this required the data publication team to regrid and reformat data sets and in others to produce monthly averages from finer resolution data. The specific processing for each data set is detailed in the documentation. The processed, quality controlled and integrated data in the documented Pre-LBA Data sets were originally published as a set of three CD-ROMs (Marengo and Victoria, 1998) but are now archived individually.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2767495334-ORNL_CLOUD.html",
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         "description": "This dataset provides the results of the characterization of shrubland vegetation at two study areas in southern Idaho, USA: the Reynolds Creek Experimental Watershed (RCEW) and Hollister. Data were collected in September and October 2014. In each study area, several 10-m x 10-m plots were randomly established that are representative of the local dominant vegetation types. Measurements are reported for both plot and individual shrub attributes. Plot measurements include shrub density and biometric data, percent shrub cover derived from line intercept transects, percent plant species and bare ground cover derived from photo analysis, and average LAI. Measurements for selected individual shrubs include height, width, length, number of stems, and LAI. Leaf samples were collected for determining LAI, specific leaf area (SLA), carbon and nitrogen concentrations, and isotopic nitrogen and carbon.",
         "license": "proprietary"
     },
@@ -91086,7 +91086,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2162118945-ORNL_CLOUD.html",
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         "description": "This dataset provides the spatial distribution of vegetation types, soil carbon, and physiographic features in the Imnavait Creek area, Alaska. Specific attributes include vegetation, percent water, glacial geology, soil carbon, a digital elevation model (DEM), surficial geology and surficial geomorphology. Data are also provided on the research grids for georeferencing. The map data are from a variety of sources and encompass the period 1970-06-01 to 2015-08-31.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170968546-ORNL_CLOUD.html",
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         "description": "Active layer thickness (ALT) is a critical parameter for monitoring the status of permafrost that is typically measured at specific locations using probing, in situ temperature sensors, or other ground-based observations. The thickness of the active layer is the average annual thaw depth, in permafrost areas, due to solar heating of the surface. This data set includes the mean Remotely Sensed Active Layer Thickness (ReSALT) over years 1992 to 2000 for an area near Prudhoe Bay, Alaska. The data were produced by an Interferometric Synthetic Aperture Radar (InSAR) technique that measures seasonal surface subsidence and infers ALT. ReSALT estimates were validated by comparison with ground-based ALT measurements at multiple sites. These results indicate remote sensing techniques based on InSAR could be an effective way to measure and monitor ALT over large areas on the Arctic coastal plain.These data provide gridded (100-m) estimates of active layer thickness (cm; ALT), seasonal subsidence (cm) and subsidence trend (mm/yr), as well as calculated uncertainty in each of these parameters. This data set was developed in support  of NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) field campaign.The data are presented in one netCDF (*.nc) file. ",
         "license": "proprietary"
     },
@@ -91190,7 +91190,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216862923-ORNL_CLOUD.html",
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         "description": "The World Inventory of Soil Emission Potentials (WISE) database was used to generate a series of uniform data sets of derived soil properties for each of the 106 soil units considered in the Soil Map of the World. These data sets were then used to generate GIS raster image files for the following variables: total available water capacity (mm water per 1 m soil depth); soil organic carbon density (kg C/m**2 for 0-30cm depth range); soil organic carbon density (kg C/m**2 for 0-100cm depth range); soil carbonate carbon density (kg C/m**2 for 0-100cm depth range); soil pH (0-30 cm depth range); and soil pH (30-100 cm depth range).",
         "license": "proprietary"
     },
@@ -91203,7 +91203,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216862983-ORNL_CLOUD.html",
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         "description": "The ISRIC-WISE International soil profile data set consists of a homogenized, global set of 1,125 soil profiles for use by global modelers. These profiles provided the basis for the Global Pedon Database (GPDB) of the International Geosphere-Biosphere Programme (IGBP) - Data and Information System (DIS). The data set includes information on soil classification, site data, soil horizon data, source of data, and methods used for determining analytical data.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781648517-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781648517-ORNL_CLOUD.html",
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         "description": "This data set provides ~100-m resolution image mosaics of South America acquired during the low flood season between September and December 1995 and during the high flood season between May and July of 1996. The images cover the same areas during both seasons and were obtained from the Japanese Earth Resources Satellite 1 (JERS-1) Synthetic Aperture Radar (SAR) of the National Space Development Agency of Japan (NASDA). The data were mosaicked into 34 tiles for each season, each consisting of about 50 JERS-1 scenes. This data set constitutes the first-ever high-resolution and single season coverage of the entire Amazon River Basin, made possible by the cloud penetrating properties of the radar sensor. The images are from the original JERS-1 SAR Global Rain Forest Mapping Project. This data set contains 66 files in GeoTIFF (.tiff) format. There are 32 files for the low flood season and 34 files for the high flood season. ",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773214672-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773214672-ORNL_CLOUD.html",
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         "description": "This data set provides high-resolution surface reflectance, thermal imagery, burn severity metrics, and LiDAR-derived structural measures of forested areas in the Sierra Nevada Mountains, California, USA, collected before and after the August 2013 Rim and September 2014 King mega forest fires. Pre-fire data were paired with post-fire collections to assess pre- and post-fire landscape characteristics and fire severity. Field estimates of fire severity were collected to compare with derived remote sensing indices. Reflectance measurements for the spectroscopic AVIRIS and MASTER sensors are distributed as multi-band geotiffs for each megafire and acquisition date. Derived operational metric products for each sensor are provided in individual GeoTIFFs. GeoTIFFs produced from LiDAR point data depict first order topographic indices and summary statistics of vertical vegetation structure.",
         "license": "proprietary"
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         "description": "This data set provides a collection of vegetation, landscape, geobotanical, elevation, hydrology, and geologic maps for the Kuparuk River Basin, North Slope, Alaska. The maps cover either (1) the entire Kuparuk River Basin, from the headwaters on the north side of the Brooks Range to the Beaufort Sea coast, or (2) the selected Upper Kuparuk River Region including the Toolik Lake and Imnavait Creek research areas. The maps were produced from imagery and existing geobotanical maps covering the period 1976-08-04 to 2008-12-31.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2954717391-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2954717391-ORNL_CLOUD.html",
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         "description": "This dataset provides leaf area index (LAI) estimates for Sub-Saharan Africa for woody, herbaceous, and aggregate vegetation types.  The estimates were derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Level 4 and the native MODIS LAI product (MCD15A2H Version 6.1), which provides LAI measurements every 8 days at 500-m pixel size. Data from the MCD15A2H product were processed further to generate three layers including: a smoothed and gap filled LAI layer referred to as aggregate leaf area index and two additional layers processed to separate woody LAI (tree and shrubs) and herbaceous LAI (grass and forbs). The data include 31 MODIS 10-degree tiles and cover 2002 to 2022. The data are provided in NetCDF format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2737900059-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2737900059-ORNL_CLOUD.html",
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         "description": "This data set provides local LAI maps for the selected measured sites in Canada. These derived maps may also be useful for validating other LAI maps over these same sites given that the areas are protected from disturbance. The maps should be used for the given period of validity. The LAI data are suitable for use in modeling the carbon, water, energy, energy and trace gas exchange between the land surface and the atmosphere at regional scales. The data set may also be useful for monitoring changes in the land surface.The Leaf Area Index (LAI) maps are at 30-m resolution for the selected sites. LAI is defined here as half the total (all-sided) live foliage area per unit horizontal projected ground surface area. Overstory LAI corresponds to all tree foliage except for treeless areas where it corresponds to total foliage. The algorithms were developed from ground measurements and Landsat TM and ETM+ images (Fernandes et. al., 2003). A mask was developed using the Landsat ETM+/TM5 image and available land cover map to identify only those areas with land cover belonging to the sample land cover classes and with Landsat ETM+/TM5 spectral reflectance values that fell within the convex hull of the spectral reflectance values over the plots. LAI was mapped within the masked region using the Landsat ETM+/TM5 image and the developed transfer function. The final LAI map was scaled by a factor of 20 (offset 0). The LAI maps are in Tagged Image File Format (TIFF).",
         "license": "proprietary"
     },
@@ -117710,7 +117710,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2737900380-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2737900380-ORNL_CLOUD.html",
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         "description": "This data set provide local LAI maps for the Larose (Ontario) site in Canada. These derived maps may also be useful for validating other LAI maps over this same site given that the area is protected from disturbance. The maps should be used for the given period of validity. The LAI data are suitable for use in modeling the carbon, water, energy, energy and trace gas exchange between the land surface and the atmosphere at regional scales. The dataset may also be useful for monitoring changes in the land surface. A complete description of producing the maps for the Larose site and the ground measurement campaign is provided in the companion document Larose2003FTReport.pdf.",
         "license": "proprietary"
     },
@@ -118100,7 +118100,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779741852-ORNL_CLOUD.html",
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         "description": "This data set contains the national and provincial boundaries of Ecuador as well as the boundaries of two national parks: the Cuyabeno Wildlife Reserve and the Yasuni National Park. There are four data files in ESRI ARCGIS Shapefile format within this data set. Each shape file has been compressed into a single compressed file (*.zip).",
         "license": "proprietary"
     },
@@ -118113,7 +118113,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779741949-ORNL_CLOUD.html",
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         "description": "This data set contains the boundaries of the four major cities in the Northern Ecuadorian Amazon, the locations of primary communities in the colonist settlement area, and the locations of the road network, circa 2002. This area in northeastern Ecuador, know as the northern Oriente of Ecuador, borders the Andes Mountains and contains the headwaters of the Amazon River.The road network was originally digitized from 1:50,000 scale topographic maps from 1990. The surface attributes for the majority of the roads have been updated based on later remote sensing and field observations from 1999 and 2002. There are three compressed (*.zip) files with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779740390-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779740390-ORNL_CLOUD.html",
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         "description": "This data set reports summary statistics from socioeconomic and demographic surveys administered to the male and female heads of household on 767 farm plots. The surveys were performed in the provinces of Sucumbios and Napo/Orellana, in the northern Ecuadorian Amazon colonist settlements (Oriente) in 1999 (Pan and Bilsborrow, 2005). In addition, perception of, and opinions about local climate, soil quality, and environmental contamination were assessed for both the male and female heads of household. There are two comma-delimited (csv) ASCII data files. One file provides summary data from male respondents; the other data file provides summary responses from the female household survey (generally the spousal respondent). The original questionnaire forms are included as companion files (PDF format).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835833-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835833-ORNL_CLOUD.html",
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         "description": "This data set provides map images of hydrographic, morphologic, and edaphic features for the northern Amazon Basin in eastern Ecuador. The hydrographic data are available at two scales based on the 1:50,000 and 1:250,000-scale topographic source maps that were generated in 1990 and 1993, respectively. Morphological and edaphological data were digitized from a 1:500,000 map published in 1983. There are 3 compressed (*.zip) data files with this data set.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780116888-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780116888-ORNL_CLOUD.html",
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         "description": "This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest, Non-Forest Vegetation, Urban/Barren, and Water; and a fifth class of Clouds/Shadows. The areas of interest were the four Intensive Study Areas (ISA) of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects: Eastern Intensive Study Area; Northern Intensive Study Area; Southern Intensive Study Area, and Southwestern Intensive Study Area. These areas are in the Northern Ecuadorian Amazon, in the area known as the northern Oriente of Ecuador. The resolution of the data is 30 meters. There are 12 image files (.tif) with this data set. ",
         "license": "proprietary"
     },
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         "description": "This data set contains a time series of early Landsat-4 MSS satellite imagery as well as Landsat-5 TM and Landsat-7 ETM+ satellite imagery of the northern Ecuadorian Amazon. Some of the TM and ETM images have been georectified to UTM Zone 18 South, WGS84 Datum. Not all of the images have been georectified. ",
         "license": "proprietary"
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@@ -118178,7 +118178,7 @@
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         "description": "This data set provides 90-meter resolution Digital Elevation Model data used in the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects. The topographic data were derived from Shuttle Radar Topography Mission (SRTM) C-band and X-band interferometric synthetic aperture radars (IFSARs) data that were acquired over 80% of Earth's land mass in February 2000. This data set includes one image in GeoTiff format that is a subset for the Northern Ecuadorian Amazon region.",
         "license": "proprietary"
     },
@@ -118191,7 +118191,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780112688-ORNL_CLOUD.html",
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         "description": "This data set contains topographic/geomorphological data associated with the four Intensive Study Areas (ISAs) in the Northern Ecuadorian Amazon (northern Oriente) that are part of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects study. Study area boundaries were developed directly from 1:50,000 topographical maps. Point elevation features and 20-meter elevation contours were digitized from these same maps. Digital elevation models (DEMs) were derived from these elevation data and, in turn, terrain aspect and terrain slope were derived from the digital elevation models. Only boundary data were provided for the southwestern ISA. These data are provided in ESRI shapefile format and GeoTiff. There are six compressed (*.zip) data files with this data set.",
         "license": "proprietary"
     },
@@ -118204,7 +118204,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780119221-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780119221-ORNL_CLOUD.html",
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         "description": "This data set provides the results of controlled burns conducted to assess the flammability of mature forests on the Catuaba Experimental Farm of the Federal University of Acre - Rio Branco, Acre, Brazil. Controlled burns were conducted in 1998, and the rate of fire spread was calculated based on the duration of the fire and the measured extent of the burned area. Environmental variables measured included type of forest, canopy openness, leaf area index, number of days without rainfall, precipitation, height of litter, litter humidity, brushwood humidity, amount of water in the ground, air temperature, and relative humidity. Results from 50 fires set in 1998 are reported. There is one comma-delimited data file with this data set.These data are part of a larger study reported in the thesis by Elsa Renee Huamon Mendoza, Susceptibility of primary forest to fire in 1998 and 1999: A case study in Acre, south-eastern Amazonia, Brazil. The thesis, in Portuguese, is included as a companion file with this data set.",
         "license": "proprietary"
     },
@@ -118217,7 +118217,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780128083-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780128083-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC02_GOES8_Hotpixel_Acre_1092_1",
         "description": "This data set provides hot pixel data, as an indicator of fires that were detected by the GOES-8 satellite for the state of Acre, Brazil. Image data were collected for extended periods over the course of 3 years (1998, 2000 and 2001). Data were filtered to select only pixels identified and processed by the GOES-8 Automated Biomass Burning Algorithm (ABBA), where estimates of sub-pixel fire characteristics including size and temperature were able to be determined. There are three comma-delimited ASCII data files with this data set.",
         "license": "proprietary"
     },
@@ -118230,7 +118230,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777854088-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777854088-ORNL_CLOUD.html",
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         "description": "This data set provides hot pixel data, as an indicator of fires, that were detected by various satellites in the tri-national MAP region (Madre de Dios-Peru, Acre-Brazil, and Pando-Bolivia) in 2003, 2004, 2005, and 2006. Data from the following satellites/sensors were compiled: NOAA-12, NOAA-14, NOAA-15, and NOAA-16, which transports the AVHRR sensor; GOES-8 and GOES- 12, which transports the GOES Imager; and AQUA and TERRA, both which transport the MODIS sensor. These data were made available by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC) of the Instituto Nacional de Pesquisas Espaciais (INPE) via the internet (http://sigma.cptec.inpe.br/queimadas/). This data set contains 12 comma-delimited ASCII data files.Hot pixel data from satellites can be used as an indicator of fires and for the understanding of fire frequency in remote areas. The publication by Vasconcelos and Brown, 2007, which has been included as a companion file, describes the application of these data in the MAP region. In addition to the the hot pixel data, each observation has a derived vegetation type, susceptibility to fire, recent and past precipitation amounts, and a calculated fire risk value. These data are described in the Fire Risk Factor companion file, by Alberto W. Setzer and Raffi A. Sismanoglu, Version 5, February 2006. ",
         "license": "proprietary"
     },
@@ -118243,7 +118243,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780126918-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780126918-ORNL_CLOUD.html",
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         "description": "This data set provides meteorological measurements collected from 3 different meteorological stations within a radius of 8 km in Rio Branco, Acre  Brazil, for  the periods of  June of 1970 to 1974, December of 1974 to 1980, and  May of 1980 thru May 31, 2001. Daily average values for rainfall, relative humidity, evapotranspiration, maximum and minimum temperature, pressure, wind direction and speed, solar radiation, and cloud cover are reported.  There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
@@ -118256,7 +118256,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781607419-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781607419-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC02_PermPlot_Acre_1237_1",
         "description": "This data set provides diameter at breast height (DBH) measurements for 1,063 trees located at the Catuaba Experimental Farm, and 812 trees located in the Humaita Forest Reserve. Both sites are in the state of Acre, southwest Amazonia, Brazil. Measurements were made on individuals with DBH between 10 and 35 cm and individuals with DBH > 35 cm.  The Catuaba Experimental Farm is part of a forest fragment of approximately 800 ha. The Humaita Forest Reserve is located in a 1,500-ha forest band with dominant bamboo characteristic. Ten-ha areas were inventoried at both sites. There is one data file in comma-delimited (.csv) format with this data set. There is also one companion data file with supplemental Catuaba site tree height and biomass data.",
         "license": "proprietary"
     },
@@ -118269,7 +118269,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781610793-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781610793-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC02_Streams_Acre_1243_1",
         "description": "This data set provides coordinates for points at the mouth of tributaries of the Acre River in the Tri-national River Basin in South America. Three Global Positioning System (GPS) readings were made at the outlet of each tributary and the average of the three readings is reported. The Tri-national River Basin is located in the tri-national frontier region of Madre de Dios, Peru, Acre, Brazil, and Pando, Bolivia (known as the MAP region). The MAP region is approximately 300,000 km2. The Acre River flows through Brazil, Bolivia, and Peru. Data on the basin drainage network from the Digital Elevation Model (DEM) Shuttle Radar Topography Mission (SRTM) was obtained as a source of information for the border areas. The GPS readings were part of an assessment of the reliability of the DEM/SRTM drainage network data (Maldonado and Brown, 2003). There is one data file in comma-delimited (.csv) format and one compamion file (.pdf) with this data set.  DATA QUALITY STATEMENT: This data set provides GPS coordinates only and is not associated with any additional measurements. There is no associated research documentation. ",
         "license": "proprietary"
     },
@@ -118282,7 +118282,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742942-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742942-ORNL_CLOUD.html",
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         "description": "This data set reports bi-weekly or monthly depth-to-water measurements for three wells located in a ~1,500 ha forest fragment on the Catuaba Experimental Farm, which is the property of the Federal University of Acre, Brazil. Data were collected between February 1999 and December 2004. There is one comma-delimited ASCII data file with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS: The depth-to-water measurements for the three wells lack ground surface elevation reference points, therefore, the groundwater table elevation for the site cannot be determined.  The depth-to-water measurements are of limited use unless paired with other site data for precipitation, tree growth, etc.",
         "license": "proprietary"
     },
@@ -118295,7 +118295,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780129237-ORNL_CLOUD.html",
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         "description": "This data set provides four related spatial data products for four study areas across the Brazilian Amazon: Manaus, Amazonas; Tapajos National Forest, Para Western (Santarem); Rio Branco, Acre; and Rondonia, Rondonia. Products include vector data showing (1) roads, (2) rivers, and (3) hypsography and (4) digital elevation model (DEM) images that were encoded from the hypsography vectors. There are 15 data files with this data set which includes 12 compressed *.zip files containing ArcInfo shape files and 3 GeoTIFFS.This data set contains vector data showing roads, rivers, and hypsography for each study area in ESRI ArcGIS shapefile format. The vectors were hand-digitized by the Images Company in Brazil from paper maps produced by the Brazilian government. Depending on the scale of the original maps, the digitization errors vary. For some maps, some vectors are missing. Data were manually checked for duplicate or extra vectors. These data sets were derived from several map sheets produced from aerial coverages dating from 1974 to 1978.The DEM images were encoded from the hypsography vectors and are provided in GeoTIFF format. The attribute value associated with each line and point in the vector segment is encoded into the image channel; the image channel is then filled in by interpolating image data between encoded vector data.  For each DEM:  1 image channel with pixel resolution = 25m x 25m.  DEM images are provided for Manaus, Tapajos National Forest, and Rondonia.  The files for Rio Branco were unusable due to a documentation error.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS:The data providers note that due to limited resources, these data have been neither validated nor quality-assured for general use. For that reason, extreme caution is advised when considering the use of these data. - Any use of the derived data is not recommended because the results have not been validated.- However, the DEM, vectors, and orthorectified SAR data (related data set) can be used if the user understands how these were produced and accepts the limitations.",
         "license": "proprietary"
     },
@@ -118308,7 +118308,7 @@
         "bbox": "-68.5, -10.5, -54.5, -2",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780128555-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780128555-ORNL_CLOUD.html",
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         "description": "This data set provides three related land cover products for four study areas across the Brazilian Amazon: Manaus, Amazonas; Tapajos National Forest, Para Western (Santarem); Rio Branco, Acre; and Rondonia, Rondonia. Products include (1) orthorectified JERS-1 and RadarSat images, (2) land cover classifications derived from the SAR data, and (3) biomass estimates in tons per hectare based on the land cover classification. There are 12 image files (.tif) with this data set.Orthorectified JERS-1 and RadarSat images are provided as GeoTIFF images - one file for each study area.For the Manaus and Tapajos sites: The images are orthorectified at 12.5-meter resolution and then re-sampled at 25-meter resolution.For the Rondonia and Rio Branco sites: The images from 1978 are orthorectified at 25-meter resolution and then re-sampled at 90-meter resolution. Each GeoTIFF file contains 3 image channels: - 2 L-band JERS-1 data in Fall and Spring seasons and - 1 C-band RadarSat data.Land cover classifications are based on two JERS-1 images and one RadarSat image and provided as GeoTIFFs - one file for each study area. Four major land cover classes are distinguished: (1) Flat surface; (2) Regrowth area; (3) Short vegetation; and (4) Tall vegetation. The biomass estimates in tons per hectare are based on the land cover classification results and are reported in one GeoTIFF file for each study area.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.KNOWN PROBLEMS: The data providers note that due to limited resources, these data have been neither validated nor quality-assured for general use. For that reason, extreme caution is advised when considering the use of these data.Any use of the derived data is not recommended because the results have not been validated. However, the DEM and vectors (related data set), and orthorectified SAR data can be used if the user understands how these were produced and accepts the limitations. ",
         "license": "proprietary"
     },
@@ -118321,7 +118321,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777289829-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777289829-ORNL_CLOUD.html",
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         "description": "The provided data were generated by the Integrated BIosphere Simulator (IBIS) terrestrial ecosystem model using data from the East Anglia Climate Research Unit climate record for the years 1921-1998. Data are included for the annual net ecosystem exchange of the surface, microbial respiration, root respiration, total soil respiration, soil moisture, leaf area index, drainage, and surface and subsurface runoff, for the entire Amazon and Tocantins basins. The data files are provided in netCDF format and standard ESRI ARCGIS ARC/INFO ASCIIGRID format. The netCDF files consist of either annual or monthly means from 1921 to 1998. The ASCII files are available only for the annual mean files.",
         "license": "proprietary"
     },
@@ -118334,7 +118334,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777285487-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777285487-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC04_Land_Use_5min_906_1",
         "description": "This data set contains 5-minute land use maps for agricultural activity in Amazonia. The data set was produced by the statistical fusion of agricultural census data from Brazil,Columbia, Bolivia, and Peru with the land cover data product from the Global Land Cover Facility. These land use maps indicate the estimated total amount of cropland and pasture (natural and planted) for the Amazon and Tocantins River basins in 1995 and 1980 and are suitable for use in models or other similar purposes. Data are provided in the netCDF format and the ARC/INFO GRID ASCII format.The 1995 data were generated from a fusion of agricultural census data and a satellite classification, and are described in Cardille, Foley, and Costa (2002).  The fusion technique merges agricultural census data from Brazil, Columbia, Peru, and Bolivia with land cover data from the University of Maryland Global Land Cover Facility 1-km classification. This technique was used to derive an estimate of the mid-1990s total agriculture surface for the region, which was then apportioned according to agriculture census data into cultivated area, natural pasture, and planted pasture.The 1980 maps, including only the Brazilian portion of the Amazon/Tocantins river drainage basins, were created by scaling the mid-1990s snapshots backward in time using the relative increase or decrease in agriculture, as derived from mid-1980s census data and United Nations Food and Agriculture Organization (FAO) data (Cardille and Foley, 2003).",
         "license": "proprietary"
     },
@@ -118347,7 +118347,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779736297-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779736297-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC04_Macrohydrology_1048_1",
         "description": "This data set provides continental-scale hydrological river flow routing parameter data for the Amazon and Tocantins River basins at 5 minute (~9 km) resolution (Costa et al., 2002). The data set includes four geospatial data files (in standard ESRI Arc/Info ASCII Grid format): (1) the river network (flow direction); (2) sinuosity of each of the main rivers, measured at 111 river sections in the basins; (3) depth to the water table; and (4) transmissivity of the aquifer. The latter two parameters were derived from measurements taken at 81 wells located throughout the basins. There is also a compressed file (*.zip) which contains the time series of monthly mean river discharge and long-term climatology (monthly mean) for the period of record at each of 122 fluviometric stations located throughout the basin. These files are provided in ASCII common-separated (.csv) format. Also included in this data set are two data files in *.csv format; one containing river discharge station location and drainage area information and one containing original well data.",
         "license": "proprietary"
     },
@@ -118360,7 +118360,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777288274-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777288274-ORNL_CLOUD.html",
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         "description": "The model output data provided were generated by the THMB 1.2 (Terrestrial Hydrology Model with Biogeochemistry) model which simulates the flow of water through groundwater systems, rivers, lakes and wetlands. The model operates at a 5-minute latitude-by-longitude grid with a 1-hour time step and requires as boundary conditions: topography, evaporation from water surfaces, surface runoff, base flow, and precipitation. Data are included for the mean monthly simulated water height above flood stage, mean monthly simulated river discharge, and mean monthly inundated area for the period 1939-1998 for the entire Amazon and Tocantins River basins. There are three netCDF files (.nc) with this data set.",
         "license": "proprietary"
     },
@@ -118373,7 +118373,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777849985-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777849985-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC05_BDFF_Biomass_Soils_1040_1",
         "description": "This data set reports (1) total aboveground dry biomass based on detailed estimates of all live and dead plant material, (2) results from repeated surveys of aboveground biomass allowing the calculation of above-ground productivity, and (3) soil chemical and physical characteristics for 50 1-ha plots of undisturbed and fragmented central Amazonian rainforest within the Biological Dynamics of Forest Fragments Project (BDFFP) study area. The reported data are plot-level summaries based on plant and soil samples and measurements obtained over the 1997 to 2001 timeframe. The BDFFP study area is an experimentally fragmented landscape spanning 1,000 km2 located 70-90 km north of Manaus, Amazonas, Brazil. For additional information about the BDFFP and research conducted at the site, please visit their web site at http://pdbff.inpa.gov.br/index.html.There are six comma-separated ASCII data files with this data set.",
         "license": "proprietary"
     },
@@ -118386,7 +118386,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773207594-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773207594-ORNL_CLOUD.html",
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         "description": "This data set includes high-resolution geocoded mosaics derived from the Validation Overflight for Amazon Mosaics (VOAM) aerial video surveys as part of the Large-Scale Biosphere-Atmosphere (LBA) Experiment in the Amazon. The VOAM flights were carried out in the wet-season (June) 1999 in the Brazilian Amazon to provide ground verification for mapping of wetland cover in the Amazon Basin conducted by the Global Rain Forest Mapping (GRFM) Project JERS-1 (Japanese Earth Remote Sensing Satellite). Digital camcorder systems were installed in a Bandeirante survey plane operated by Brazil's National Institute for Space Research. The VOAM99 surveys circumscribed the Brazilian Amazon, documenting ground conditions at resolutions on the order of 1-m resolution for wetlands, forests, savannas, and human-impacted areas. Geocoded mosaics were generated by processing the aerial videography into GeoTIFF format, maximizing its usefulness for environmental monitoring applications. Other applications of the VOAM99 videography include acquisition of ground control points for image geolocation, forest biomass estimation, and rapid assessment of fire damage. Geocoded digital videography provides a cost-effective means of compiling a high-resolution validation data set for land cover mapping in remote, cloud-covered regions. ",
         "license": "proprietary"
     },
@@ -118399,7 +118399,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777292705-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777292705-ORNL_CLOUD.html",
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         "description": "This data set presents georeferenced digital video files from Validation Overflight for Amazon Mosaics (VOAM) aerial video surveys as part of the Large-Scale Biosphere-Atmosphere Experiment in the Amazon. The VOAM flights were carried out in the wet-season (June) 1999 in the Brazilian Amazon to provide ground verification for mapping of wetland cover with the Global Rain Forest Mapping (GRFM) Project JERS-1 (Japanese Earth Remote Sensing Satellite) mosaics of the Amazon basin. Digital camcorder systems were installed in a Bandeirante survey plane operated by Brazil's National Institute for Space Research. The VOAM99 surveys circumscribed the Brazilian Amazon, documenting ground conditions at resolutions on the order of 1-m (wide-angle format) and 10-cm (zoom format) for wetlands, forests, savannas, and human-impacted areas. Other applications of the VOAM videography include acquisition of ground control points for image geolocation, creation of a high-resolution geocoded mosaic of a forest study area, forest biomass estimation, and rapid assessment of fire damage. Geocoded digital videography provides a cost-effective means of compiling a high-resolution validation data set for land cover mapping in remote, cloud-covered regions.",
         "license": "proprietary"
     },
@@ -118412,7 +118412,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781649041-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781649041-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wNyBsYWtlIHNlZGltZW50IG51dHJpZW50IGRhdGEsIGxhZ28gY2FsYWRvLCBicmF6aWw6IDE5ODItMTk4NFwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwN19MYWtlX051dHJpZW50X1NlZGltZW50c18xMDUwXCIsXCIxXCIsMjc3OTczODI5OCwyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMDcgbGFrZSBzZWRpbWVudCBudXRyaWVudCBkYXRhLCBsYWdvIGNhbGFkbywgYnJhemlsOiAxOTgyLTE5ODRcIixcIk9STkxfQ0xPVURcIixcIkxDMDdfTGFrZV9OdXRyaWVudF9TZWRpbWVudHNfMTA1MFwiLFwiMVwiLDI3Nzk3MzgyOTgsMl0ifQ%3D%3D/LC07_Amazon_Wetlands_1284_2",
         "description": "This data set provides a map of wetland extent, vegetation type, and dual-season flooding state of the entire lowland Amazon basin. As described in Hess et al. (2015), the classified image was derived from the Global Rain Forest Mapping Project (GRFM) Amazon mosaics (Rosenqvist et al 2000; Siqueira et al. 2002) acquired during Oct.-Nov. 1995 and May-June 1996, corresponding to the low-flood and high-flood seasons for much of the central Amazon. Hess et al. (2003) mapped wetland extent, vegetative cover, and flooding state for an 18 degree \u00d7 8 degree portion of the central Amazon using the dual-season GRFM mosaics. This study extends the previous wetlands mapping to report the first validated estimate of wetland extent, cover, and flooding for the lowland Amazon basin. A wetlands mask was created by segmentation of the mosaics and clustering of the resulting polygons; a rules set was then applied to classify wetland areas into five land cover classes and two flooding classes using dual-season backscattering values. The mapped wetland area of 8.4 \u00d7 105 km2 is equivalent to 14 % of the total basin area (5.83 \u00d7 106 km2) and 17% of the lowland basin (5.06 \u00d7 106 km2). The mapped flooding extent is representative of average high and low-flood conditions for latitudes north of 6 degrees S; flooding conditions were less well captured for the southern part of the basin. The wetlands map is provided in GeoTIFF format using two coordinate systems: unprojected (Geographic) with pixel size of 3 arcseconds, and Albers Conical Equal Area with pixel size of 100 m.",
         "license": "proprietary"
     },
@@ -118425,7 +118425,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777830431-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777830431-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC07_Bathymetry_Curuai_999_1",
         "description": "The bathymetry data provided represent a continuous surface of interpolated point measurements of depth values of Lago Curuai, an Amazon River floodplain lake, upstream from Santarem, Para, Brazil, from measurements made in June of 2004. The first product contains the actual depth values (in meters) of the interpolated continuous surface saved as real numbers in both ENVI and GeoTIFF formats. Also available is a color scaled depth GeoTIFF image which has an embedded color scale bar. This secondary file is meant only for viewing but has the unique advantage of being a GeoTIFF file. Therefore, this map can be a background image with other projected files of interest in the area. Data provided in this data set were used to develop a methodology for processing and applying high resolution bathymetric data acquired with a Lowrance-480M ecosounder in the Amazon floodplain. This research was supported by the addition of Landast/TM images for planning and executing the survey. 4600 km of transects were processed semi-automatically and integrated into a georeferenced database. A digital elevation model with 15 m horizontal resolution and 1 cm vertical resolution was generated for the floodplain. The changes in inundated area and volume of water on the floodplain were estimated. Regression models were constructed to predict flood area and water stored volume from water level. The results of this research show that water level and flooded area mapped from images are good enough for estimating water stored volume in the Lago Grande de Curuai (Barbosa et al., 2006).",
         "license": "proprietary"
     },
@@ -118438,7 +118438,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780955074-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780955074-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC07_Biomass_LGrande_1127_1",
         "description": "This data set reports measurements of aquatic macrophyte biomass, phenology, leaf characteristics, and length and diameter of stems of both submerged and unsubmerged macrophytes. Data were collected from sites in the Monte Alegre Lake region on the eastern Amazon River floodplain in Para, Brazil. Ten field surveys were made at approximately monthly intervals from December 2003 to November 2004. There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
@@ -118451,7 +118451,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780968798-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780968798-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wNyBsYWtlIHNlZGltZW50IG51dHJpZW50IGRhdGEsIGxhZ28gY2FsYWRvLCBicmF6aWw6IDE5ODItMTk4NFwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwN19MYWtlX051dHJpZW50X1NlZGltZW50c18xMDUwXCIsXCIxXCIsMjc3OTczODI5OCwyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMDcgbGFrZSBzZWRpbWVudCBudXRyaWVudCBkYXRhLCBsYWdvIGNhbGFkbywgYnJhemlsOiAxOTgyLTE5ODRcIixcIk9STkxfQ0xPVURcIixcIkxDMDdfTGFrZV9OdXRyaWVudF9TZWRpbWVudHNfMTA1MFwiLFwiMVwiLDI3Nzk3MzgyOTgsMl0ifQ%3D%3D/LC07_Curuai_chl_1134_1",
         "description": "This data set reports (1) concentrations of total, organic, and inorganic suspended solids; dissolved inorganic, and organic carbon; chlorophyll-a and (2) measurements of turbidity, ph, temperature, transparency, conductivity, and calculated carbon dioxide (CO2) in water samples collected from Lago Curuai (Lake Curuai), in the floodplain of the Amazon River south of Obidos, Para, Brazil. Approximately 70 stations were sampled during four phases of the hydrological cycle: receding (September 2003), low (November 2003), rising (February 2004), and high water (June 2004). There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
@@ -118464,7 +118464,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777830478-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777830478-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC07_Lake_Chlorophyll_MODIS_1000_1",
         "description": "This data set contains chlorophyll concentration maps of the Amazon River floodplain region from Parintins (Amazonas) to Almeirim (Para). These chlorophyll fraction maps were derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance product (MOD09) for 19 months from April 2002 to December 2003. The study was conducted in a floodplain reach upstream from Santarem, Para, in order to assess seasonal changes in phytoplanktonic chlorophyll-a distributions in the floodplain Lake Curuai. MODIS reflectance data were acquired at four river stages: rising (April), high (June), decreasing (September), and low (November). Chlorophyll maps were derived and used to compute the weighted average of chlorophyll concentration from MODIS images in the region. Field measurements of suspended inorganic matter and chlorophyll-a in Lake Curuai were made almost concurrently with satellite overpasses (Barbosa, 2005). The images and the estimated chlorophyll concentrations were compared to measured chlorophyll concentrations at control points for different hydrological states. This data set may be applied to better understand the seasonal dynamics of primary production of the Amazon floodplains. The maps of chlorophyll-a concentration may be used to model spatial and temporal variations of primary production in this region.The monthly chlorophyll-a maps are provided as GeoTIFF files. There are two formats: (1) color-mapped pixels and (2) pixels as chlorophyll-a concentrations. These latter images are not intended for browsing. These images have pixel values that are the chlorophyll-a concentration in mg/m3 and need to be download and opened in GIS software.",
         "license": "proprietary"
     },
@@ -118477,7 +118477,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779738298-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779738298-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC07_Lake_Nutrient_Sediments_1050_1",
         "description": "This data set reports lake sediment texture and porosity, carbon (C), nitrogen (N), and phosphorus (P) content of surficial sediments, 210Pb-derived nutrient accumulation rates in sediments, and burial rates of C, N, and P in sediments at eleven locations in Lake Calado, Amazonas, Brazil. Field samples were collected between February 1982 and August 1984. There are eight comma-delimited ASCII data files with this data set. ",
         "license": "proprietary"
     },
@@ -118490,7 +118490,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779737265-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779737265-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wNyBsYWtlIHNlZGltZW50IG51dHJpZW50IGRhdGEsIGxhZ28gY2FsYWRvLCBicmF6aWw6IDE5ODItMTk4NFwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwN19MYWtlX051dHJpZW50X1NlZGltZW50c18xMDUwXCIsXCIxXCIsMjc3OTczODI5OCwyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMDcgbGFrZSBzZWRpbWVudCBudXRyaWVudCBkYXRhLCBsYWdvIGNhbGFkbywgYnJhemlsOiAxOTgyLTE5ODRcIixcIk9STkxfQ0xPVURcIixcIkxDMDdfTGFrZV9OdXRyaWVudF9TZWRpbWVudHNfMTA1MFwiLFwiMVwiLDI3Nzk3MzgyOTgsMl0ifQ%3D%3D/LC07_Monthly_Inundated_Areas_1049_1",
         "description": "This data set reports monthly mean inundation areas (square kilometers) for four cover classes of Central Amazon wetlands habitat: Open water (OW),  river channel (RC) class, macrophyte (MA) class, and a flooded forest (FF) class, which also incorporates a flooded shrub class. The full study area was a 1.77 million km2 quadrant covering the Central Amazon Basin. Inundation was also calculated from three subsets of this area: (1) covering only the Amazon/Solimoes River mainstem and (2) the Eastern and (3) the Western halves of this mainstem area. There is one comma-delimited ASCII data file in this data set.",
         "license": "proprietary"
     },
@@ -118503,7 +118503,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781386124-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781386124-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wNyBsYWtlIHNlZGltZW50IG51dHJpZW50IGRhdGEsIGxhZ28gY2FsYWRvLCBicmF6aWw6IDE5ODItMTk4NFwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwN19MYWtlX051dHJpZW50X1NlZGltZW50c18xMDUwXCIsXCIxXCIsMjc3OTczODI5OCwyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMDcgbGFrZSBzZWRpbWVudCBudXRyaWVudCBkYXRhLCBsYWdvIGNhbGFkbywgYnJhemlsOiAxOTgyLTE5ODRcIixcIk9STkxfQ0xPVURcIixcIkxDMDdfTGFrZV9OdXRyaWVudF9TZWRpbWVudHNfMTA1MFwiLFwiMVwiLDI3Nzk3MzgyOTgsMl0ifQ%3D%3D/LC07_Reservoir_GHG_1143_1",
         "description": "This data set provides flux measurements of methane (CH4) and carbon dioxide (CO2) from surface waters to the atmosphere. It also provides CH4, CO2, and oxygen (O2) concentrations of surface water, and concentrations measured at several depths of the Balbina Reservoir in the central Amazon Basin, Amazonas, Brazil. The Balbina Reservoir was formed by impounding the Uatuma River in 1987.  Reservoir surface water samples, bottom water samples, and gas samples from static flux enclosures were collected at 10 to 14 sites at monthly intervals between April and November of 2005, and 6 times in February, 2006. Water samples to determine the vertical profiles of temperature, dissolved O2, CH4, and CO2 were collected during the rainy and dry seasons immediately above the dam between September 2004 and February 2006. Water samples were collected downstream from the dam from July 2004 - November 2005 for analysis of CH4 and CO2 concentrations.There are three comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -118516,7 +118516,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835418-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835418-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wNyBsYWtlIHNlZGltZW50IG51dHJpZW50IGRhdGEsIGxhZ28gY2FsYWRvLCBicmF6aWw6IDE5ODItMTk4NFwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwN19MYWtlX051dHJpZW50X1NlZGltZW50c18xMDUwXCIsXCIxXCIsMjc3OTczODI5OCwyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMDcgbGFrZSBzZWRpbWVudCBudXRyaWVudCBkYXRhLCBsYWdvIGNhbGFkbywgYnJhemlsOiAxOTgyLTE5ODRcIixcIk9STkxfQ0xPVURcIixcIkxDMDdfTGFrZV9OdXRyaWVudF9TZWRpbWVudHNfMTA1MFwiLFwiMVwiLDI3Nzk3MzgyOTgsMl0ifQ%3D%3D/LC07_Reservoir_Methane_Emissions_1047_1",
         "description": "This data set reports methane (CH4) fluxes at the water-air interface and concentrations and isotopic signals of CH4 in the bubbles stirred up from the sediment in Tucurui and Samuel reservoirs in 2000 and 2001. Tucurui (deep) reservoir is located near Belem city in the Tocantins-Araguaia basin in the eastern Amazon. Samuel (shallow) reservoir is situated near Porto Velho city in the Jamari River, a tributary of the Madeira River in the western Amazon. Field samples were collected between June 2000 and September 2001. There are two comma-delimited ASCII data files in this data set. This study was carried out to identify differences in methane cycling between deep and shallow reservoirs (Lima, 2005). Isotopic and concentration analyses of methane in bubbles, dissolved in the water column, and emitted to the atmosphere demonstrate that water depth is critical regarding methane emissions from hydroreservoirs in the Amazon. Methanotrophic activities are greater in Tucurui (deep) while light isotopic methane is directly released from Samuel (shallow). Therefore, the methanotrophic layer of the deep reservoir is more efficient in oxidizing methane before reaching the atmosphere, since the quantity of methane in the sediments of the reservoirs were equivalent.",
         "license": "proprietary"
     },
@@ -118529,7 +118529,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779739356-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779739356-ORNL_CLOUD.html",
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         "description": "This data set reports the monthly record of inundated area, in square km, for six floodplain and open water regions in South America. The following floodplains were analyzed: (1) mainstem Amazon River floodplain in Brazil; (2) Llanos de Mojos (Beni and Mamore rivers) in Bolivia; (3) Bananal Island (Araguaia River) in Brazil; (4) Roraima savannas (Branco and Rupununi rivers) in Brazil and Guyana; (5) Llanos del Orinoco (Apure and Meta rivers) in Venezuela and Colombia; and (6) Pantanal wetland (Paraguay River) in Brazil. Flooded area was estimated at monthly intervals from December 1978 through August 1987 for the Amazon mainstem region and from January 1979 through August 1987 for the other five regions. Inundated area was determined from SMMR (Scanning Multichannel Microwave Radiometer) passive microwave data. Area estimates include permanent open water as well as land subject to seasonal inundation. This data set contains five data files: two comma-delimited (.csv) ASCII data files providing the monthly inundation area values for six floodplain and open water regions in South America; a compressed (.zip) file providing seventeen ESRI Shape files for the region bounding polygons; and two .csv files providing information about the region bounding polygons and latitude/longitude verticies.",
         "license": "proprietary"
     },
@@ -118542,7 +118542,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781386478-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781386478-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wNyBsYWtlIHNlZGltZW50IG51dHJpZW50IGRhdGEsIGxhZ28gY2FsYWRvLCBicmF6aWw6IDE5ODItMTk4NFwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwN19MYWtlX051dHJpZW50X1NlZGltZW50c18xMDUwXCIsXCIxXCIsMjc3OTczODI5OCwyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMDcgbGFrZSBzZWRpbWVudCBudXRyaWVudCBkYXRhLCBsYWdvIGNhbGFkbywgYnJhemlsOiAxOTgyLTE5ODRcIixcIk9STkxfQ0xPVURcIixcIkxDMDdfTGFrZV9OdXRyaWVudF9TZWRpbWVudHNfMTA1MFwiLFwiMVwiLDI3Nzk3MzgyOTgsMl0ifQ%3D%3D/LC07_Spectroradiometry_1144_1",
         "description": "This data set includes bidirectional reflectance (BDR) spectra and water-quality data of floodplain lakes of the Solimoes and Negro Rivers in the central Amazon basin, Amazonas, Brazil. Samples and measurements were collected during July 2000 to August 2000. Bidirectional reflectance factors were recorded, at 3 nm intervals from 400 to 900 nm, concurrently with in situ measurements of water temperature and Secchi depth, and collection of samples for analysis of optically active components including total suspended solids, chlorophyll, and dissolved organic carbon (DOC).The lakes sampled were in the low-lying varzea of the Solimoes River (\"varzea\" is the local name for the floodplain formed by the overflow of white-water rivers) and igapo (\"igapo\" is the local name for the floodplain formed by the overflow of black-water rivers) of the Negro River.There are two comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -118555,7 +118555,7 @@
         "bbox": "-64.11, -1.14, -63.1, -0.29",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781598950-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781598950-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0wMSBzcnRtIDkwLW1ldGVyIGRpZ2l0YWwgZWxldmF0aW9uIG1vZGVsLCBub3J0aGVybiBlY3VhZG9yaWFuIGFtYXpvblwiLFwiT1JOTF9DTE9VRFwiLFwiTEMwMV9TUlRNX0RFTV85MG1fTkVDXzEwODNcIixcIjFcIiwyNzczMjYxMTY2LDRdIn0%3D/LC07_Wetlands_fluxes_1209_1",
         "description": "This data set provides estimates of daily and monthly carbon dioxide (CO2) and methane (CH4) diffusive and ebullitive flux for dry and flooded areas from two study sites, Cuini and Itu, in the interfluvial wetlands of the upper Negro River basin, Brazil. CO2 (ebullitive and diffusive) and CH4 diffusive flux measurements were made one day each month from February 2005 through January 2006 in both permanently and seasonally flooded areas. For the remaining days of each month, fluxes were calculated as the mean of the two measurements bracketing that time period, times the area flooded each day. Total site area, dry area, and seasonally varying flooded area estimates for the two wetlands were determined through analysis of synthetic aperture radar data from Radarsat images. From these estimates, the total flux of CO2 and CH4 for the sites was calculated. Values for CH4 ebullitive flux were determined from a constant for each area based on whether the water was rising or falling and the area flooded. Hydrologic measurements were taken from April 2004 through January, 2006.There are three comma-separated (.csv) data files with this data set.",
         "license": "proprietary"
     },
@@ -118568,7 +118568,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768945067-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768945067-ORNL_CLOUD.html",
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         "description": "This data set provides (1) soil maps for Brazil that are digital versions of the MAPA DE SOLOS DO BRASIL (EMBRAPA, 1981) classified at three levels of detail, 19-class, 70-class and 249-class; (2) vegetation maps for Brazil that are digital versions of the MAPA DE VEGETACAO DO BRASIL (IBGE, 1988) classified at three levels of detail, 13-class, 59-class, and an overprint (combination) class; and (3) a land cover map for all of South America that was derived from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data over the time period 1987 through 1991 (Stone et al., 1994).The seven soil, vegetation, and general land cover classification maps are provided as GeoTIFF files (*.tif) files. There are also three companion files (.pdf), one each, for the soil, vegetation, and land cover maps, with information on  map units, class values, codes, and descriptions.",
         "license": "proprietary"
     },
@@ -118581,7 +118581,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784856942-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784856942-ORNL_CLOUD.html",
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         "description": "This data set provides Ecosystem Demography Model (ED) estimates of potential above-ground net primary production (NPP) (kg C/m2/y), potential average live biomass (kg C/m2), and potential average soil carbon (kg C/m2) for the Brazilian Amazon at 1 degree resolution. Ecosystem Demography Model predicts both ecosystem structure (e.g. above and below-ground biomass, vegetation height and basal area, and soil carbon stocks) and corresponding ecosystem fluxes (e.g. NPP, NEP, and evapotranspiration) from climate, soil, and land-use inputs. Estimates for the Brazilian Amazon include the effects of natural disturbances such as windthrow and fire, but do not include the effects of human land use. To produce these estimates, ED was forced with ISLSCP I data for 1987 and 1988 and averaged into a single average year (Moorcroft et al., 2001).The data are provided for the three estimates in both ASCII text and in NetCDF formatted files. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780129991-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780129991-ORNL_CLOUD.html",
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         "description": "This data set reports observations of fires in the vicinity of Maraba, Para, Brazil, from November 3-5th, 2001, and in Mato Grosso, Brazil, between Cuiaba and Alta Floresta, for July 12-15th, 2002. These ground-based data were collected by visual inspection from roads primarily during daylight hours. Data include fire position and time, estimates of fire size, and type of vegetation burned. There is one comma-delimited ASCII file with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777821076-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777821076-ORNL_CLOUD.html",
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         "description": "This data set includes 16 zipped archives of shapefiles of cities, rivers and streams, roads, and study area boundaries of several Amazonian study sites: Altamira, Santarem, Bragantina, and Ponta de Pedras, in the state of Para, and 1 site at Machadinho D'Oeste, in the state of Rondonia. Data from Brazil were digitized from Instituto Nacional de Colonizacao e Reforma Agraria (INCRA) maps and other data from Instituto Brasileiro de Geografia e Estatistica (IBGE). These products were prepared in the 2000-2004 time period. The data of creation for the source material is unknown.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777823518-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777823518-ORNL_CLOUD.html",
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         "description": "This data set includes 15 zipped archives of rectified .tif format Landsat 5 TM and Landsat 7 ETM+ scenes from near the study sites of Altamira, Santarem, Ponta de Pedras, and Bragantina in the state of Para, Brazil and Machadinho D'Oeste in Rondonia, Brazil. Dates represent the most cloud-free image retrievals from 1985-2004 and are therefore not continuous. These images may be useful to evaluate potential environmental impacts resulting from the establishment of colonization projects in the Amazon. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751407-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751407-ORNL_CLOUD.html",
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         "description": "This data set reports daily total precipitation data retrieved from Brazilian National Institute of Meteorology (INMET) network for three stations near two Amazonian research sites: Altamira, and Santarem, from 1961-1998.Daily precipitation totals are provided in one comma-separated ASCII file for three stations in Para, including two sites in Altamira: Altamira City and on the Transamazon Highway at Km 100 near Medicilandia (operated by EMBRAPA); and, one site in Santarem: Taperinha. Data availability varies by station (sublocation): Altamira City from 1961-1990, Transamazon Km 100 from 1982-1998,  and Taperinha from 1983-1992.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751083-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751083-ORNL_CLOUD.html",
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         "description": "This data set reports basic soil structure and composition information for five Amazonian research sites: Altamira, Bragantina, Tome-Acu, and Ponta de Pedras, all four in the state of Para, Brazil; and one site in Yapu, Colombia. Soil characteristics reported for all five study sites include cation information (e.g., H, Al, Mg, K, Na, S), percent of soil C, N, and organic matter, soil texture/composition and color, pH, and land use history. Soil bulk density and tons of carbon/ha are reported for only three of the study sites: Altamira, Bragantina, and Tome-Acu. All of the data are provided in one comma-separated data file.The five study areas represent characteristic differences in soil fertility and a range of land uses typical of the Amazon region. One of these areas, Altamira, is characterized by above average pH, nutrients, and texture. The other four areas are more typical of the 75 percent of the Amazon that is characterized by Oxisols and Ultisols, with well-drained but low pH and low levels of nutrients. Ponta de Pedras in Marajo Island, located in the estuary, is composed of upland Oxisols and floodplain alluvial soils. Igarape-Acu in the Bragantina region is characterized by both nutrient-poor Spodosols and Oxisols. Tome-Acu, south of Igarape-Acu, represents a mosaic of Oxisols and Ultisols. Yapu, in the Colombian Vaupes, is composed of patches of Spodosols and Oxisols. Three of the areas are colonization regions at various degrees of development: Altamira is a colonization front that opened up in 1971, whereas Tome-Acu was settled by a Japanese population in the 1930s, and Bragantina was settled in the early part of the twentieth century. Marajo (Ponta de Pedras) is the home of caboclos, whereas Yapu is home to Tukanoan Native American populations. In these study areas  slash-and-burn cultivation as well as plantation agriculture and mechanized agriculture are employed. Length of fallows vary in these communities. The two indigenous areas leave their land in longer fallow than do the three colonization areas, and the proportion of land prepared from secondary forests increases with length of settlement as the stock of mature forest declines over time.",
         "license": "proprietary"
     },
@@ -118659,7 +118659,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780154255-ORNL_CLOUD.html",
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         "description": "This data set includes classified land cover transition maps at 30-m resolution derived from Landsat TM, MSS, ETM+ imagery and aerial photos of Altamira, Santarem, and Ponta de Pedras, in the state of Para, Brazil. The Landsat images were classified into several types of land use (e.g., forest, secondary succession, pasture, annual crops, perennial crops, and water) and subjected to change detection analysis to create transition matrices of land cover change. Dates of acquired images represent the most cloud-free image retrievals from 1970-2001 for each site and are therefore not continuous. There are 3 GeoTIFF files (.tif) with this data set.",
         "license": "proprietary"
     },
@@ -118672,7 +118672,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751260-ORNL_CLOUD.html",
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         "description": "This data set contains two files with vegetation data for five Amazonian sites: Altamira, Bragantina, Tome-Acu, and Ponta de Pedras, all in the state of Para, and Yapu, Colombia. One file describes vegetation composition and structure (basal area, biomass, species composition) with different land use histories for all five study sites; the second file describes more specific information about individual plant characteristics (family/species names, DBH, stem and total plant height) within each plot.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784832273-ORNL_CLOUD.html",
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         "description": "This data set includes orthorectified Landsat ETM+ scenes across the Legal Amazon region. At least one scene is provided for each spatial tile, representing the most cloud-free retrievals from mid-1999 through late 2001 (Fig. 1). Dates are therefore not continuous but include scenes from July 8, 1999 to November 13, 2001. Data have been atmospherically corrected and orthorectified. The individual images should be highly useful as they include very little cloud cover, but they should not be mosaicked together since retrieval dates vary.Data files (and format) included for each scene are: six multispectral bands (tif), two thermal bands (tif), one panchromatic band (tif), two preview files (jpg), and one metadata file (txt). The individual Geotiff files have been g-zipped and subsequently all of the files for a scene have been g-zipped together for ordering convenience.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777339420-ORNL_CLOUD.html",
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         "description": "This data set includes Landsat TM scenes from across the Legal Amazon region.  A single image is provided for each spatial tile, representing the most cloud-free retrieval from 9/21/86 to 9/17/94.  All files are in a single directory, including one band-sequential (bsq) file and one database (ddr) file for each scene.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777396961-ORNL_CLOUD.html",
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         "description": "This data set contains GIS coverage constructed from measurements taken of four logged areas in Cauaxi, Para, Brazil. Logged areas were selectively harvested either using conventional logging techniques or using reduced-impact logging (RIL) techniques (Pereira et al., 2002). Two areas were harvested with each technique in 1996 and two additional areas were harvested in 1998. Coverage includes log decks (patios), roads, skids trails, tree-fall locations, and logging area (block) boundary. These field surveys were conducted as part of an investigation of canopy damage following selective logging by two different techniques (Asner et al., 2004).Coverage is in ArcInfo interchange format (*.e00). The geographic projection of the data is UTM zone 22, South WGS84 datum.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777369863-ORNL_CLOUD.html",
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         "description": "This data set contains GIS coverages constructed from measurements taken of  logged areas in Juruena, Mato Grosso. Classes include roads, skids trails, tree crowns, tree-fall locations, and block boundary (Asner et al., 2004). Coverages are in ArcInfo SHAPE format (*.shp), UTM projection, using the WGS84 datum.",
         "license": "proprietary"
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         "description": "This data set contains GIS coverages constructed from measurements taken of logged areas in the Tapajos National Forest region of Para, Brazil in 1996 and 1998 (Asner et al., 2004). Coverages include log decks (patios), roads, skids trails, tree-fall locations, and block boundary. They are in ArcInfo SHAPE format (*.shp). The Tapajos data are in latitude/longitude using the WGS84 datum.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781593560-ORNL_CLOUD.html",
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         "description": "This data set reports forest biophysical measurements from a rainfall exclusion experiment conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil from 1998 to 2006. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002). Data are reported for stem inventory, tree diameter at breast height (DBH) and height, dendrometer measurements of tree diameter growth increments, canopy density, leaf area index (LAI), and coarse and fine litter mass.The measurements were made monthly from September 28, 1998 through November 10, 2006. There are six comma-delimited data files (.csv), one text file (.txt), and two companion files with this data set.  ",
         "license": "proprietary"
     },
@@ -118763,7 +118763,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781400209-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781400209-ORNL_CLOUD.html",
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         "description": "This data set provides the results of the two modeled scenarios for future patterns of deforestation across the Amazon Basin from 2002 to 2050. This larger defined Amazon Basin (PanAmazon area) includes the Amazon River watershed, the Legal Amazon in Brazil, and the Guiana region. The model SimAmazonia was used to simulate monthly deforestation in the Amazon Basin from 2002 to 2050 for two scenarios: (1) a \"Business-as-Usual\" scenario, which considered the deforestation trends across the basin and projected the rates by using historical images and their variations from 1997 to 2002 and then added to that the effect of paving a set of major roads, and (2) a \"Governance\" scenario, that also considered the current deforestation trends, but assumed a 50% limit  imposed for deforested land within each basin's subregion, and that existing and proposed Protected Areas (PAs), play a decisive role in limiting deforestation as well (Soares et al., 2006).The provided data products include one GeoTiff (*.tif) for each year (2002 to 2050) for both model scenarios for a total of 98 files. The files have been compressed in two *.zip files, one for each model scenario. There is also one comma-delimited file that contains the model input data derived from satellite deforestation maps. ",
         "license": "proprietary"
     },
@@ -118776,7 +118776,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773197258-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773197258-ORNL_CLOUD.html",
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         "description": "This data set provides measurements of specific leaf area and monthly phenological observations for selected tree and vine species at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The study site was part of a rainfall exclusion experiment that was conducted from 1999-2006 to develop an understanding of the physical processes driving the observed soil water dynamics at the site. Phenological observations were made from 2001-2004 in rainfall exclusion and control plots. In total, 3,224 leaves were observed across 223 individuals and 56 species. The phenological observations included the month and year when a given leaf was first observed fully expanded and last observed alive. Starting in July 2004 and continuing through January 2006, leaves that had been followed in the phenology study were sampled and leaf area and mass were determined and the specific leaf area was calculated.There are two comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -118789,7 +118789,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768944064-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768944064-ORNL_CLOUD.html",
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         "description": "A simple GIS soil-water balance model for the Amazon Basin, called RisQue (Risco de Queimadasa -- Fire Risk), was used to conduct an analysis of spatial and temporal patterns of drought in moist tropical forests and the complex relationships between patterns of drought and forest fire regimes from 1995 through 2001. The provided data products are the model output estimates of maximum plant-available soil water (PAWmax) at 10 m depth at 8 km resolution and model data inputs of monthly precipitation and evapotranspiration. RisQue estimates PAWmax at 10 m depth starting with a map of PAWmax (1-2 m depth) developed using 1,565 RADAMBRASIL soil texture profiles and empirical relationships between soil texture and critical soil water parameters and then interpolated to 8 km resolution. In RisQue, plant-available soil water (PAW) is depleted by monthly evapotranspiration estimated using the Penman Monteith equation and satellite-derived radiation and recharged by monthly precipitation.There are three data files with this data set, two *.zip, and one GeoTIFF image (.tif). The *.zip files expand to 83 *.asc files of evapotranspiration and 89 *.asc files for precipitation data. The image (.tif) is a map of  maximum percent available water at 10 m depth. All the files in this data set are in standard arc/info asciigrid format at 8 km resolution.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781644640-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781644640-ORNL_CLOUD.html",
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         "description": "This data set contains biomass estimates for coarse roots measured on the forest floor and measurements of fine root growth down to 2-m depth at the km 67 Rainfall Exclusion Experiment site, Tapajos National Forest, Brazil. The study site was part of a rainfall exclusion experiment that was conducted from 1999-2006 to develop an understanding of the physical processes driving the observed soil water dynamics at the site. All surface roots intersected along three 1000-m long x 1-m wide transects were identified to species, measured, and biomass calculated. The collections were made on January 26, 2001 during the experimental rain exclusion period.The fine root growth was measured from 0.5-m to 2-m depth with a rhizotron. The rhizotron tubes were inserted into deep soil pits in the control and treatment plots. Average root growth measurements are provided by depth interval on a monthly basis from July 25, 2000 to December 14, 2003. DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS: There are discrepancies with the documentation, collection dates reported and collection method for fine roots utilizing rhizotrons. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768932524-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768932524-ORNL_CLOUD.html",
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         "description": "This data set provides a single raster image containing the spatial distribution of aboveground live forest biomass of the Amazon basin. This product was derived using a methodology based on a combination of land cover map, remote sensing derived metrics, and more than 500 forest plots distributed over the basin (Saatchi, et al., 2007).The distributed map was produced in ENVI, in Tiff format and it contains forest biomass divided among 11 classes at 1 km spatial resolution with reasonable accuracy (better than 70%). Remote sensing and ground data used in this product were collected from 1990-2000. The Biomass map represents average biomass distribution over the Amazon basin over this period and was used to estimate the total carbon stock of the basin, including the dead and belowground biomass.",
         "license": "proprietary"
     },
@@ -118828,7 +118828,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777844591-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777844591-ORNL_CLOUD.html",
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         "description": "This data set contains two image mosaics of L-band radar backscatter and two image mosaics of first order texture. The two backscatter images are mosaics of L-band Radar Backscatter at Horizontal-Horizontal (HH) Polarization created from 1,500 images collected by the Japanese Earth Resources Satellite-1 (JERS-1) Synthetic Aperture Radar (SAR) over the Amazon River Basin as part of the Global Rainforest Mapping Project (GRMP). These backscatter image mosaics were developed using data collected over 62 days from August to November of 1995 for the peak of the dry season and for 62 days from May to June of 1996 during the peak of the wet season. The two image mosaics are at 3 arc-sec resolution. Data provided under this project are resampled images at 30 arc-sec resolution (or about 1 km resolution). For each radar backscatter image, first order texture statistical information was derived and is distributed along with the image mosaic.This data set contains four images each in both geotiff and ENVI formats, provided in eight zip files.  The four files in ENVI file format contain o_envi? in their file name and when extrapolated contain an envi image (*_envi.dat) and an envi image header file (_envi.hdr). The four files in geotiff format contain o_geotiff?  in their file name and when extrapolated contain *.tif and *.tfw file pairs. See Section 2 for more information about the characteristics of these data files.",
         "license": "proprietary"
     },
@@ -118841,7 +118841,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777847802-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777847802-ORNL_CLOUD.html",
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         "description": "This data set contains proportional estimates for the vegetative cover types of woody vegetation, herbaceous vegetation, and bare ground over the Amazon Basin for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of MODIS 32-day composites were used to create the vegetation cover types using the Vegetation Continuous Fields (VCF) (Hansen et al., 2002) approach which shows how much of a land cover such as \"forest\" or \"grassland\" exists anywhere on the land surface.  The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated.The original MODIS products are 500-m spatial resolution and are derived from 2000-2001 data products. The data were resampled to 1-km resolution for the regional study under this project, and provided as 3 separate cover type files in ENVI and GeoTIFF file formats that are provided in six zipped files. These products are registered to the rest of the regional data sets over the Amazon basin. These data are also available for download from the Global Land Cover Facility Website (http://modis.umiacs.umd.edu/). ",
         "license": "proprietary"
     },
@@ -118854,7 +118854,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781573934-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781573934-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0xMCBvcnRob3JlY3RpZmllZCBsYW5kc2F0IGV0bSsgZGF0YSBmb3IgbGVnYWwgYW1hem9uOiAxOTk5LTIwMDFcIixcIk9STkxfQ0xPVURcIixcIkxDMTBfTGFuZHNhdF9FVE1fODQ2XCIsXCIxXCIsMjc4NDgzMjI3MywyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMTAgb3J0aG9yZWN0aWZpZWQgbGFuZHNhdCBldG0rIGRhdGEgZm9yIGxlZ2FsIGFtYXpvbjogMTk5OS0yMDAxXCIsXCJPUk5MX0NMT1VEXCIsXCJMQzEwX0xhbmRzYXRfRVRNXzg0NlwiLFwiMVwiLDI3ODQ4MzIyNzMsMl0ifQ%3D%3D/LC15_Roughness_Map_1182_1",
         "description": "This data set provides physical roughness maps of vegetation canopies in the Amazon Basin. The images are estimates of aerodynamic roughness length (Z0) and zero plane displacement height (D0) at 1-km spatial resolution. The aerodynamic roughness length (Z0) is an important parameter to determine the vertical gradients of mean wind speed and the conditions for momentum transfer over a vegetated or bare rough surface.The maps were produced from a multivariate regression model algorithm developed from field-measured vegetation structure and remote-sensing data. The data input sources included Shuttle Radar Topography Mission (SRTM) (Saatchi, 2013), JERS-1, MODIS, and field data from vegetation biomass plots over the Amazon basin, as well as tower-based wind profile measurements, and roughness parameters from LBA tower sites. There are two GeoTIFF (.tif) files with this data set.  ",
         "license": "proprietary"
     },
@@ -118867,7 +118867,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781607897-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781607897-ORNL_CLOUD.html",
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         "description": "This data set provides Normalized Difference Vegetation Index (NDVI) composite images of the Amazon Basin for the years 1999-2000 at approximately1-km spatial resolution. The images were from the VEGETATION 1 sensor, aboard the SPOT 4 satellite.Ten day composite images were reprocessed through several filters for cloud removal. Monthly NDVI data were used to create five metrics: maximum NDVI, minimum of 6 greenest months, range of NDVI between min and max, mean NDVI dry months, and mean NDVI wet months. There are five GeoTIFF (.tif) files with this data set.",
         "license": "proprietary"
     },
@@ -118880,7 +118880,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768953357-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768953357-ORNL_CLOUD.html",
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         "description": "This dataset provides a subset of the SRTM30 Digital Elevation Model (DEM) elevation and standard deviation data for the Amazon Basin. SRTM30 is a near-global digital elevation model (DEM) comprising a combination of data from the Shuttle Radar Topography Mission (SRTM), flown in February, 2000, and the earlier U.S. Geological Survey's GTOPO30 data set. The SRTM30 resolution is 30 arc-sec or about 1 km. In processing the SRTM data, to combine with GTOPO30, the data were resampled from 3 arc-sec to 30 arc-sec. Provided here are the mean elevation and the standard deviation (STD) of the data points used in the averaging. The STD is thus an indication of topographic roughness useful in some applications.",
         "license": "proprietary"
     },
@@ -118893,7 +118893,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777370025-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777370025-ORNL_CLOUD.html",
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         "description": "This image was collected by the Hyperion sensor on 10-July-2004 at 13:16:16 GMT.  It was calibrated to apparent surface reflectance using the ACORN atmospheric model.The Hyperion imager has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, spatial resolution of 30 m, and a swath width of 7.8 km. Sampling is scene based (256 samples, 512 lines) (http://eo1.usgs.gov/sensors.php).  Through these large number of spectral bands, complex land ecosystems can be imaged and accurately classified.Data from the EO-1 Hyperion imaging spectrometer may greatly increase our ability to estimate the presence and structural attributes of selective logging in the Amazon Basin using four biogeophysical indicators not yet derived simultaneously from any satellite sensor: 1) green canopy leaf area index; 2) degree of shadowing; 3) presence of exposed soil and; 4) non-photosynthetic vegetation material. Airborne, field and modeling studies have shown that the optical reflectance continuum (400-2500 nm) contains sufficient information to derive estimates of each of these indicators. Our ongoing studies in the eastern Amazon basin also suggest that these four indicators are sensitive to logging intensity. Satellite-based estimates of these indicators should provide a means to quantify both the presence and degree of structural disturbance caused by various logging regimes.",
         "license": "proprietary"
     },
@@ -118906,7 +118906,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781635278-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781635278-ORNL_CLOUD.html",
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         "description": "This data set provides measurements for soil physical and chemical properties, rooting depth and weight, leaf area index (LAI), plant area index (PAI), biomass, fraction of photosynthetically active radiation (fPAR), and ground-based reflectance measurements of soil and litter samples. The samples were collected from 23 areas within the Brazilian research sites of the Brasilia National Park (BNP) and Aguas Emnendadas Ecological Station (AE), Brasilia; Cangacu Research Center, Tocantins; and Tapajos National Forest, Para.The research areas were in the most intensely stressed areas in Brazil, with rapid and aggressive land use conversions in forested and cerrado-transition areas. These field measurements were conducted from June to July 2002. There are 61 comma-delimited (.csv) data files with this data set.",
         "license": "proprietary"
     },
@@ -118919,7 +118919,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781603707-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781603707-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0xMCBvcnRob3JlY3RpZmllZCBsYW5kc2F0IGV0bSsgZGF0YSBmb3IgbGVnYWwgYW1hem9uOiAxOTk5LTIwMDFcIixcIk9STkxfQ0xPVURcIixcIkxDMTBfTGFuZHNhdF9FVE1fODQ2XCIsXCIxXCIsMjc4NDgzMjI3MywyXSIsInVtbSI6IltcImxiYS1lY28gbGMtMTAgb3J0aG9yZWN0aWZpZWQgbGFuZHNhdCBldG0rIGRhdGEgZm9yIGxlZ2FsIGFtYXpvbjogMTk5OS0yMDAxXCIsXCJPUk5MX0NMT1VEXCIsXCJMQzEwX0xhbmRzYXRfRVRNXzg0NlwiLFwiMVwiLDI3ODQ4MzIyNzMsMl0ifQ%3D%3D/LC21_Foliar_Nutrients_1234_1",
         "description": "This data set provides measurements for foliar nutrients from logging blocks in the Tapajos National Forest, Para Western Santarem, Brazil. Data are included for calcium (Ca), phosphorus (P), magnesium (Mg), nitrogen (N), and potassium (K) concentrations. In March 2003 foliar samples were collected from the cover types remaining after selective logging in 2002: forest, tree-fall gaps, skids, roads, and deck areas. Fresh foliage was also collected in March 2003, from 192 upper canopy species at an intact forest site 17 km from the logging area. There are two data files with this data set.",
         "license": "proprietary"
     },
@@ -118932,7 +118932,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777743122-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777743122-ORNL_CLOUD.html",
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         "description": "This data set provides Landsat Enhanced Thematic Mapper Plus (ETM+) imagery, derived classified land cover products, and cloud-water masks for selected Brazilian states (Acre, Amapa, Amazonas, Maranhao, Mato Grosso, Para, Rondonia, and Roraima) for the years 1999-2002. The Landsat ETM+ images were processed to derive fractional land cover types (photosynthetic vegetation [PV], non-photosynthetic vegetation [NPV], and bare substrate) by application of the Carnegie Landsat Analysis System (CLAS) methodology (Asner et al., 2005). CLAS utilizes a quantitative determination of fractional land cover at the subpixel scale (e.g., within each Landsat 30 x 30 m pixel). The resulting images display estimates of subpixel land cover fraction values including free of clouds, cloud shadows, and water. There are 584 *.zip files in this data set which when expanded, contain a total of 1,717 (*.tif) images files (GeoTiff Standard format).",
         "license": "proprietary"
     },
@@ -118945,7 +118945,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781563943-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781563943-ORNL_CLOUD.html",
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         "description": "This data set provides the results of analyses of Landsat Enhanced Thematic Mapper Plus (ETM+) images for selective logging activity in the Brazilian states of Para, Mato Gross, Rondonia, Roraima, and Acre over the years 1999 through 2001. Images were analyzed using the Carnegie Landsat Analysis System (CLAS) to detect and to quantify the amount of damage due to selective logging in the major timber-production states of the Brazilian Amazon. This approach provided automated image analysis using atmospheric modeling for detection of forest canopy openings, surface debris, and bare soil exposed by forest disturbances; and pattern-recognition techniques. CLAS provides detailed measurements of forest-canopy damage at a spatial resolution of 30 x 30m. Fifteen GeoTiff format files are included -- one for each of the three years from 1999-2001 for each of the five states. Each GeoTiff is a single band image where each pixel represents if logging activity was or was not detected. A zero (0) value indicates that no logging was detected, while a value of one (1) indicates that damage from logging was detected. The 15 GeoTiff (*.tif) files have been compressed into one *.zip file.",
         "license": "proprietary"
     },
@@ -118958,7 +118958,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781607052-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781607052-ORNL_CLOUD.html",
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         "description": "This data set provides measurements for soil nutrients from areas that were selectively logged and from control areas in the Tapajos National Forest, Para Western Santarem, Brazil. Data are included for calcium (Ca), phosphorus (P), magnesium (Mg), nitrogen (N), aluminum (Al), iron (Fe), silicon (Si), carbon 13, nitrogen 15, and potassium (K) concentrations. In addition, data are included for Phosphorus fractionation which was performed on a subset of the soils, and soil bulk density measurements. The samples were from clay-dominated (oxisols) soils.",
         "license": "proprietary"
     },
@@ -118971,7 +118971,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781643706-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781643706-ORNL_CLOUD.html",
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         "description": "This data set contains field observations, corresponding GPS points, and point and polygons of deforested areas in the state of Mato Grosso, Brazil, for the period August 2003 to July 2004. The field observations were conducted in the forested areas between Nova Mutum and Sinop, MT. These data were part of a study to validate Moderate Resolution Imaging Spectroradiometer (MODIS) data at 250-m resolution for the detection of deforested areas.There are 16 data files with this data set. This includes 10 shapefile (.shp) and six comma-separated files (.csv).",
         "license": "proprietary"
     },
@@ -118984,7 +118984,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781625095-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781625095-ORNL_CLOUD.html",
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         "description": "This data set contains field observations, corresponding GPS points, and point and polygons of deforested areas in the state of Mato Grosso, Brazil, for the period  March 17-24,2005. Fieldwork was conducted in the regions surrounding Sinop, Mato Grosso, with specific emphasis on large clearings occurring in the Xingu Basin. The field campaign was designed to validate preliminary MODIS deforestation products designed to detect deforestation during the wet season. There are five data files with this data set: four shapefiles (.shp) and one comma-separated file (.csv).",
         "license": "proprietary"
     },
@@ -118997,7 +118997,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784837251-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784837251-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0yMSBzb2lsIGNoYXJhY3RlcmlzdGljcywgbG9nZ2VkIGFyZWFzLCB0YXBham9zIGZvcmVzdCwgcGFyYSwgYnJhemlsOiAyMDAzXCIsXCJPUk5MX0NMT1VEXCIsXCJMQzIxX1NvaWxfQ2hhcmFjdGVyaXN0aWNzXzEyMzZcIixcIjFcIiwyNzgxNjA3MDUyLDJdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0yMSBzb2lsIGNoYXJhY3RlcmlzdGljcywgbG9nZ2VkIGFyZWFzLCB0YXBham9zIGZvcmVzdCwgcGFyYSwgYnJhemlsOiAyMDAzXCIsXCJPUk5MX0NMT1VEXCIsXCJMQzIxX1NvaWxfQ2hhcmFjdGVyaXN0aWNzXzEyMzZcIixcIjFcIiwyNzgxNjA3MDUyLDJdIn0%3D/LC22_MODIS_Phenology_Mato_Grosso_1185_1",
         "description": "This data set, LBA-ECO LC-22 Land Cover from MODIS Vegetation Indices, Mato Grosso, Brazil,  provides land cover classifications for Mato Grosso, Brazil, for the years 2000-2001 and 2003-2004. The classifications were derived from annual vegetation phenology information from a time series of Collection 4, 16-day MODerate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI), and the Enhanced Vegetation Index (EVI) vegetation data, at 250-m resolution. A decision tree classifier was trained using field observations and Landsat TM data of land cover from 2003-2004 to identify seven land-cover classes. The classifier was applied to the 2000-2001 and 2003-2004 MODIS ENVI and EVI data. There are two GeoTIFF (.tif) files with this data set.",
         "license": "proprietary"
     },
@@ -119010,7 +119010,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780900765-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780900765-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBsYy0yMSBzb2lsIGNoYXJhY3RlcmlzdGljcywgbG9nZ2VkIGFyZWFzLCB0YXBham9zIGZvcmVzdCwgcGFyYSwgYnJhemlsOiAyMDAzXCIsXCJPUk5MX0NMT1VEXCIsXCJMQzIxX1NvaWxfQ2hhcmFjdGVyaXN0aWNzXzEyMzZcIixcIjFcIiwyNzgxNjA3MDUyLDJdIiwidW1tIjoiW1wibGJhLWVjbyBsYy0yMSBzb2lsIGNoYXJhY3RlcmlzdGljcywgbG9nZ2VkIGFyZWFzLCB0YXBham9zIGZvcmVzdCwgcGFyYSwgYnJhemlsOiAyMDAzXCIsXCJPUk5MX0NMT1VEXCIsXCJMQzIxX1NvaWxfQ2hhcmFjdGVyaXN0aWNzXzEyMzZcIixcIjFcIiwyNzgxNjA3MDUyLDJdIn0%3D/LC22_MODIS_VCF_Tree_Cover_1112_1",
         "description": "This data set contains proportional estimates for the vegetative cover types of tree cover, herbaceous vegetation, and bare ground over South America for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of 500-m MOD09A1 Surface Reflectance 8-day minimum blue reflectance composites were used as input data. To reduce the presence of cloud shadows, The data were converted to 40-day composites using a second darkest albedo (sum of blue, green, and red bands), and the Vegetation Continuous Fields (VCF) algorithmn  was utilized (Hansen et al., 2002). The VCF shows how much of a land cover such as forest or grassland exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated. There are three images provided in GeoTIFF format.",
         "license": "proprietary"
     },
@@ -119023,7 +119023,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780155131-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780155131-ORNL_CLOUD.html",
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         "description": "This data set provides (1) areal estimates of deforestation events (>25 ha) that were identified from 2001-2004 in Mato Grosso by the Brazilian Institute for Space Research (INPE) as part of the Program for the Estimation of Deforestation in the Brazilian Amazon (PRODES) and (2) the classification of the post-deforestation land use as either cropland, cattle pasture, or not in production (deforested areas that were never fully cleared or returned immediately to secondary forest) in the years after the large deforestation events from 2002-2005. Data are provided in ESRI shapefile format. There are five compressed (*.zip) data files with this data set. Each shapefile represents one year of post-deforestation land use. Land use in the years following deforestation was estimated using annual time series of MODIS NDVI (normalized difference vegetation index) and EVI (enhanced vegetation index). Metrics of vegetation phenology derived annual time series of MODIS NDVI and EVI data were analyzed using a decision-tree classifier to characterize the major cover type in each area of new deforestation. Post-deforestation land use for each large deforestation event was classified based on the classification of MODIS phenology metrics for all years following deforestation during 2002-2005. ",
         "license": "proprietary"
     },
@@ -119036,7 +119036,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784895558-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784895558-ORNL_CLOUD.html",
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         "description": "This data set contains data associated with MODIS fire maps generated using two different algorithms and compared against fire maps produced by ASTER. These data relate to a paper (Morisette et al., 2005) that describes the use of high spatial resolution ASTER data to evaluate the characteristics of two fire detection algorithms, both applied to MODIS-Terra data and both operationally producing publicly available fire locations. The two algorithms are NASA's operational Earth Observing System MODIS fire detection product and Brazil's National Institute for Space Research (INPE) algorithm. These data are the ASCII files used in the logistic regression and error matrices presented in the paper. ",
         "license": "proprietary"
     },
@@ -119049,7 +119049,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784831948-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784831948-ORNL_CLOUD.html",
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         "description": "Satellite fire detection was determined from two sensors, the Advanced Very High Resolution Radiometer (AVHRR) on NOAA-12 and the Moderate Resolution Imaging Spectroradiometer (MODIS) on both the Terra and Aqua platforms, for 2001- 2003 to characterize fire activity in Brazil, giving special emphasis to the Amazon region. Active fire data for AVHRR/NOAA-12 was produced using a fixed threshold fire detection technique based on the algorithm developed by the Centro de Previsao do Tempo e Estudos Climaticos (CPTEC/INPE) (Setzer and Pereira, 1991; Setzer et al., 1994; Setzer and Malingreau, 1996). Active fire data for MODIS/Terra and MODIS/Aqua was produced using a contextual fire detection technique based on NASA-University of Maryland algorithm (Justice et al., 2003; Giglio et al.2003).Resulting fire counts were compared for major biomes of Brazil (Figure 1), the nine states of the Legal Amazon (e.g., Tocantins, Figure 2), and two important road corridors in the Amazon region (Figure 3). In evaluating the daily fire counts, there is a dependence on variations in satellite viewing geometry, overpass time, atmospheric conditions, and fire characteristics (Schroeder et al., 2005). The data provided are the coordinates of daily active vegetation fires in Brazil for 2001 through 2003 at 1km resolution for both AVHRR and MODIS sensors.  Data are provided in both Arcview (shape file format) and ASCII comma separated file formats. Vector files for the major biomes of Brazil, the nine states of the Legal Amazon, and two important road corridors in the Amazon region are also included.",
         "license": "proprietary"
     },
@@ -119062,7 +119062,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777369007-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777369007-ORNL_CLOUD.html",
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         "description": "This data set contains ASTER sensor Level-1B satellite imagery over controlled burns in the State of Roraima in Northern Brazil on January 19 and 28, 2003, plus simultaneously collected soil and near-surface air temperature profiles on January 28th. The ASTER imagery is provided in 14 zipped files containing HDF-EOS files (*.hdf and *.met file pairs), while the sample-based temperature profiles, one for the air the other for the ground, are provided as comma separated ASCII files.",
         "license": "proprietary"
     },
@@ -119075,7 +119075,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834773-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834773-ORNL_CLOUD.html",
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         "description": "This data set provides the number of hot spots detected across the legal Amazon Basin at 5- km resolution by the AVHRR (Advanced Very High Resolution Radiometer) on NOAA 12, 14, 15, 16, 17, and 18 satellites for the entirety of 2001 (January 1 - December 31).  Only hot spots detected at night are included. This data is useful for modeling fire events and evaluating human impacts on the Amazon Basin using fire as an indicator of anthropogenic disturbance (Arima et al., 2007).",
         "license": "proprietary"
     },
@@ -119088,7 +119088,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835245-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835245-ORNL_CLOUD.html",
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         "description": "This data set contains a shapefile of a digitized map of the land parcel information of the original properties of the Uruara colonization site, Para, Brazil, acquired from the Instituto de Colonizacao e Reforma Agraria, or the Colonization and Agrarian Reform Institute (INCRA). The Uruara settlement geometry was initially designed by INCRA, and consists of mostly 100 hectare lots (400 x 2500 meters, and 500 x 2000 meters), running north and south of the Trans-Amazon Highway, as a fine network of small, narrow rectangles. The other parcels in the landscape are the so-called glebas that range up to 3,000 hectares. The map was in the form of a paper map without a projection (a spherical geographic coordinate system) in the South American 1969 datum (SAD 1969). This paper map was digitized in Environmental Science Research Institute (ESRI) ArcInfo 8.1 using a digitizing table, and the digital cadastral data were geo-referenced and projected to match the Universal Transverse Mercator projection (Zone 22 South, World Geodetic System 1984 datum) of Landsat imagery (Landsat.org). There is one compressed (*.zip) file with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835565-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835565-ORNL_CLOUD.html",
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         "description": "This data set contains a 1999 Landsat ETM+ mosaic image land of cover classification showing forested and deforestation areas in Uruara, Para, Brazil. This image may be overlain with the cadastral property map of the same area (see related data set LBA-ECO LC-24 Cadastral Property Map of Uruara, Para, Brazil: ca.1975). This data sets contains a single geotiff image distributed as deforested_large.zip.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777853903-ORNL_CLOUD.html",
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         "description": "This data set contains ESRI shapefiles of historical roads (basin-wide federal and state roads) in nine Brazilian states for the Legal Amazon: Amazonas, Para, Acre, Rondonia, Roraima, Tocantins, Amapa, Matto Grosso, and Maranhao. There are 48 compressed (*.zip) files for the years 1968, 1975, 1981, 1985, 1987, and 1993 in GCS South American 1969 projection.  ",
         "license": "proprietary"
     },
@@ -119127,7 +119127,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779741271-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779741271-ORNL_CLOUD.html",
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         "description": "This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final classification shows five classes derived using visual comparison (Water, Clouds/Shadow, Forest, Not Forest, Background). These data were used in 2007 to illustrate the nature of deforestation in Southern Para, Brazil over the past twenty years (Simmons et al. 2007). There are four annual GeoTIFF files distributed with this data set. Each GeoTIFF file and accompanying *.tfw file have been compressed into a single *.zip file. ",
         "license": "proprietary"
     },
@@ -119140,7 +119140,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779741137-ORNL_CLOUD.html",
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         "description": "This data set provides course land cover classifications derived from Landsat TM images for 1986, 1988, and 1991 for the area surrounding the municipality of Uruara, Para, Brazil. Five land cover classes (Water, Clouds/Shadow, Forest, Not Forest, and Background) were derived (Aldrich et al. 2006). The Land Cover is in a compressed (*.zip) GeoTIFF file for each year.",
         "license": "proprietary"
     },
@@ -119153,7 +119153,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768939449-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768939449-ORNL_CLOUD.html",
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         "description": "This data set, LBA-ECO LC-24 Forest Cover Map from MODIS, 500-m, South America: 2001, contains forest cover information for 2001 for all of South America. The data were collected by the MODerate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Earth Observing System, TERRA (AM-1) satellite platform and released by the MODIS science team as an image showing percent canopy cover. This information was then reclassified so that all pixels with a percent canopy cover greater than 40% (40% after the 1973 UNESCO standard) were classified as forest (a value of 1), and all other pixels were classified as non-forest (a value of 2). Water features were given a value of 3. This data has a pixel resolution of 500 meters and is unprojected with the WGS-1984 datum (Hansen et al. 2006). There is one GeoTIFF data file for this data set.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777291261-ORNL_CLOUD.html",
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         "description": "This data set provides annual spatial patterns of cropland, natural pasture, and planted pasture land uses across Amazonia for the period 1940/1950-1995. Two series of 5-minute grid cell historical maps were generated starting from land use classification products for 1995. Annual data are the fraction of natural pasture, planted pasture, and cropland in each 5-min grid cell. The annual maps are provided in two NetCDF (.nc) format file at 5-minute resolution. The AMZ-C.nc file covers the Brazilian portion of Amazon and Tocantins Rivers basins, and is based on the 1995 land use classification of Cardille et al. (2002), generated through the fusion of remote sensing (AVHRR) and agricultural census data. The second file, AMZ-R.nc, covers the entire Legal Amazon region and adjacent areas and is based on the 1995 land use classification by Ramankutty et al. (2008). The land use classification was generated by the fusion of satellite imagery (MODIS and VEGETATION-SPOT) and data from the agricultural census. A historical land-use reconstruction algorithm was used to generate the annual spatial patterns (based on work from Ramunkutty and Foley, 1999).",
         "license": "proprietary"
     },
@@ -119179,7 +119179,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768950526-ORNL_CLOUD.html",
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         "description": "This model product provides the Fortran source code and input data for the Simple Tropical Ecosystem Model (SITE). SITE is a simplified point model of vegetation dynamics that uses an integration interval of one hour to estimate the fluxes of CO2, water, and energy. Model forcing data are hourly meteorological parameters. SITE is a simplified model of vegetation dynamics for tropical ecosystems developed by Santos and Costa (2004).Model input data measurements of temperature, wind velocity, precipitation, latent heat, sensible heat, downward incident solar flux, and downward incident infrared flux were collected at the km 67 Tapajos National Forest site, Para, Brazil, from 2002 to 2003.SITE is structured with a canopy layer and two soil layers, and incorporates the following processes:*infrared radiation balance in the canopy and balance of solar radiation*aerodynamic processes*plant physiology*transpiration*balance of water intercepted by the canopy*transport of mass and energy fluxes*soil heat flux and soil moisture*carbon balance There are five files provided with this data set: the Fortran source code (version 1.1-0d), one file for the main program that declares variables and input parameters, one file that initializes vegetation parameters, one file used to compile the SITE model, and the km 67 input data file in comma-delimited (.csv) format. The four SITE files are provided in the compressed file SITE_Model.zip.  One companion file is also provided that  describes the collection and processing of the meteorological and flux measurements at the km 67 Tapajos National Forest site and the use of the data to calibrate SITE. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768952288-ORNL_CLOUD.html",
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         "description": "This data set is an active fire detection product resulting from the application of The Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to Geostationary Environmental Operational Satellite (GOES) imager data for all of South America from 2000 through 2005. GOES imager data are available at 30 minute intervals with a nominal 4 x 4-km resolution. The data provided are the latitude/longitude, brightness temperature, estimates of sub-pixel fire size and temperature, Global Land Cover Characterization (GLCC) ecosystem type, and a pixel-fire flag (0-5, information regarding the probability of a fire or processing characteristics) for each active fire detected by WF_ABBA for a 30 minute imager interval. Spatial area coverage data files are provided as a complement to individual fire detection data files because the area of the latter varied according to the GOES imager scan mode in use. Versions 5.9 and 6.0 WF_ABBA data are provided. Differences between the two versions are assumed to be small though (typically less than 10%). An in-line temporal filter has been added to the algorithm to screen out false alarms associated with noise in the imagery and cloud edge issues in version 6.0. This is especially important for screening false alarms due to reflection off clouds at extreme view angles and at sunrise and sunset.There are nine compressed (*.zip) files with this data set which expand to the filtered ASCII text data files (.filt), and seven coverage files text (.txt).",
         "license": "proprietary"
     },
@@ -119205,7 +119205,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777803612-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777803612-ORNL_CLOUD.html",
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         "description": "This data set provides active fire detection images and associated summary information derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images for various locations in Brazilian Amazonia during 2001-2003. There are two image types: (1) GeoTiff images (masks) of active fire pixels, and (2) GeoTiff images (masks) of clustered active fire pixels where a distinct cluster identification number has been assigned to each individual group of contiguous active fire pixels. There are 122 GeoTiff format files of each type of fire mask; a total of 244 images. The spatial resolution of the fire mask images is 30 meters. ETM+ images were selected based on data quality, availability, as well as on the occurrence of vegetation fires.In addition to the two image types, there are also two types of fire pixel summary information provided in text files: (1) one file of active fire pixel summary information derived from the active fire pixel images, and (2) 122 files of clustered active fire pixel information derived from individual clustered fire pixel masks, each of which correspond to a clustered image.",
         "license": "proprietary"
     },
@@ -119218,7 +119218,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781588541-ORNL_CLOUD.html",
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         "description": "This data set contains modeled estimates of carbon flux, biomass, and annual burning emissions across the Brazilian state of Mato Grosso from 2000-2006. The model, DEforestation CArbon Flux (DECAF), was used to provide annual carbon fluxes from large deforestation events (>25 ha) based on post-deforestation land use, and the frequency and duration of active fires during the deforestation process. Carbon fluxes associated with the conversion of Cerrado to mechanized crop production, fires in Cerrado, and managed pasture cover types were also estimated. Model data outputs provided include:  * Estimated aboveground live biomass from DECAF in 2000 and 2004.* Annual biomass burning emissions estimates for 2001-2005 from low, middle, and high emissions scenarios with DECAF. There are 15 GeoTIFF files for annual emissions which represent the carbon emissions per pixel in grams of carbon per m2 (g C m-2). Model data inputs provided include: * Annual burn trajectories for 2001 - 2005, including deforestation, Cerrado land cover conversion, and fires in pasture and Cerrado ecosystems unrelated to agricultural expansion. These data were assembled from three sources: MODIS 500-m burned area maps, annual deforestation based on data from the INPE PRODES program, and the conversion of Cerrado savannah/woodland to cropland estimated from land cover information from MODIS phenology metrics.* Annual land cover data 2001-2004 for the portion of Mato Grosso covered by MODIS phenology metrics, tile h12v10, updated based on annual land cover changes in Amazon forest and Cerrado cover types.* Monthly Normalized Difference Vegetation Index (NDVI) for MODIS tile h12v10 from 10/2000 - 09/2006, based on cloud and gap-filled 16-day NDVI data from MODIS Collection 4 16-day NDVI composites  MOD13 product (Huete et al., 2002).There are six compressed (*.gz) files with this data set.",
         "license": "proprietary"
     },
@@ -119231,7 +119231,7 @@
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         "description": "This data set provides active fire locations and estimates of annual fire frequencies for South America from 2000-2007. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors aboard the Terra (2000-2007) and Aqua (2003-2007) satellite platforms were analyzed to determine spatial and temporal patterns in satellite fire detections. The analysis considered a high-confidence subset of all MODIS fire detections to reduce the influence of false fire detections over small forest clearings in Amazonia (Schroeder et al., 2008). The number of unique days on which the active fire detections were recorded within a 1 km radius was estimated from the subset of active fire detections and the ArcGIS neighborhood variety algorithm. There are 14 data files with this data set: 7 GeoTIFF (.tif) files of fire frequency at MODIS 250 m resolution, where each grid cell value represents the number of days in that year on which active fires were detected, and 7 shape files of active fire locations for the years 2001-2007.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2343105406-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of forest canopy height derived from the Geoscience Laser Altimeter System (GLAS) LiDAR instrument that was aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite. A global GLAS waveform data set (n=12,336,553) from collection periods between October 2004 and March 2008 was processed to obtain canopy height estimates.Estimates of GLAS maximum canopy height and crown-area-weighted Lorey's height are provided for 18,578 statistically-selected globally distributed forested sites in a point shapefile. Country is included as a site attribute.Also provided is the average canopy height for the forested area of each country, plus the number of GLAS data footprints (shots), number of selected sample sites, and estimates of the variance for each country.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768949725-ORNL_CLOUD.html",
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         "description": "This model product contains the source codes for version 1 of the individual-based forest ecosystem biogeochemistry model LINKAGES and two subsequent versions as well as example input and output data. LINKAGES predicts long-term structure and dynamics of forest ecosystems as constrained by nitrogen availability, climate, and soil moisture. Model simulations compare favorably to field data from different geographic areas worldwide. LINKAGES, written in FORTRAN and provided in ASCII format, simulates birth, growth, and death of all trees greater than 1.43-cm dbh. Litter fall and decomposition are also simulated. Sunlight is the driving variable. Growing season degree days, soil water availability, and AET are calculated from precipitation, temperature, soil field moisture capacity, and wilting point. Decomposition and soil N availability are calculated from organic matter quantity and carbon chemistry, evapotranspiration, and degree of canopy closure. Light availability to each tree is a function of leaf biomass of taller trees. Degree days and availabilities of light and water constrain species reproduction. These variables plus soil N constrain tree growth and carbon accumulation in biomass. Tree death probability increases with age and slow growth. Leaf, root, and woody litter are returned to the soil at the end of each year to decay the following year. Climatic and forest data for eastern North America and New South Wales are provided as example model inputs. Modelers may use their own site data within any version of LINKAGES. Example model output is also provided.",
         "license": "proprietary"
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         "description": "This model product provides the Fortran 77 source code for the Lund-Potsdam-Jena (LPJ) Wetland Hydrology and Methane Dynamic Global Vegetation Model (LPJ-WHyMe v1.3.1), auxiliary C++ routines, ASCII and NetCDF input data, and NetCDF example output data. LPJ-WHyMe v1.3.1 simulates peatland hydrology, permafrost dynamics, peatland vegetation, and methane emissions.The model processes can be simulated on an area-averaged 0.5 or 1.0 degree grid cell basis at global, regional, or site scales and on a daily, monthly, or annual time step as appropriate. Input driver data are monthly mean air temperature, total precipitation, percentage of full sunshine, annual atmospheric CO2 concentration, and soil texture class. The simulation for each grid cell begins from \"bare ground\", requiring a \"spin up\" (under non-transient climate) of ca. 1,000 years to develop equilibrium vegetation, carbon, and soil structure. Model simulations compare favorably, with some exceptions, to field observations collected from peatland sites (e.g., Degero, Sweden; Lakkasuo, Finland; BOREAS Northern Study Area, Canada; and others) and non-peatland sites (e.g., Point Barrow, Alaska, and Spasskaya, Siberia). LPJ-WHyMe is a further development of LPJ-WHy, which dealt with the introduction of permafrost and peatlands into LPJ. Implementing peatlands in LPJ required the addition of two new plant functional types (PFTs) (flood tolerant C3 graminoids and Sphagnum mosses) to the already existing ten PFTs, the introduction of inundation stress for non-peatland PFTs, a slow-down in decomposition under inundation, and the addition of a root exudates pool. LPJ-WHyMe v1.3.1 adds a methane model subroutine. This model product has one compressed data file (*.zip) and seven companion files.",
         "license": "proprietary"
     },
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         "description": "TMI/TRMM surface soil moisture (LPRM) L3 1 day 25 km x 25 km daytime V001 is a Level 3 (gridded) data set. Its land surface parameters, surface soil moisture, land surface (skin) temperature, and vegetation water content, are derived from passive microwave remote sensing data from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), using the Land Parameter Retrieval Model (LPRM). There are two files per day, one daytime and one nighttime, archived as two different products. This document is for the daytime product. The data set covers the period from December 1997 to April 2015 (when the instruments on the TRMM satellite were shut down in preparation for its reentry into the earth's atmosphere).  The LPRM is based on a forward radiative transfer model to retrieve surface soil moisture and vegetation optical depth. The land surface temperature is derived separately from TMI's Ka-band (37 GHz). A unique feature of this method is that it can be applied at any microwave frequency, making it very suitable to exploit all the available passive microwave data from various satellites.  Input data are from the TMI Brightness Temperatures (1B-11) product, daytime passes, as processed using LPRM (i.e., LPRM/TMI/TRMM Level 2 product, LPRM_TMI_SOILM2_V001).",
         "license": "proprietary"
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         "description": "TMI/TRMM surface soil moisture (LPRM) L3 1 day 25 km x 25 km nighttime V001 is Level 3 (gridded) data set. Its land surface parameters, surface soil moisture, land surface (skin) temperature, and vegetation water content, are derived from passive microwave remote sensing data from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), using the Land Parameter Retrieval Model (LPRM). There are two files per day, one daytime and one nighttime, archived as two different products. This document is for the nighttime product. The data set covers the period from December 1997 to April 2015 (when the instruments on the TRMM satellite were shut down in preparation for its reentry into the earth's atmosphere).  The LPRM is based on a forward radiative transfer model to retrieve surface soil moisture and vegetation optical depth. The land surface temperature is derived separately from TMI's Ka-band (37 GHz). A unique feature of this method is that it can be applied at any microwave frequency, making it very suitable to exploit all the available passive microwave data from various satellites.  Input data are from the TMI Brightness Temperatures (1B-11) product, nighttime passes, as processed using LPRM (i.e., LPRM/TMI/TRMM Level 2 product, LPRM_TMI_SOILM2_V001).",
         "license": "proprietary"
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         "description": "TMI/TRMM surface soil moisture (LPRM) L2 V001 is a Level 2 (swath) data set. Its land surface parameters, surface soil moisture, land surface (skin) temperature, and vegetation water content are derived from passive microwave remote sensing data from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), using the Land Parameter Retrieval Model (LPRM). Each swath is packaged with associated geolocation fields. The data set covers the period from December 1997 to April 2015 (when the instruments on the TRMM satellite were shut down in preparation for its reentry into the earth's atmosphere), at the spatial resolution (nominally 45 km) of TMI's X band (10.7 GHz).  The LPRM is based on a forward radiative transfer model to retrieve surface soil moisture and vegetation optical depth. The land surface temperature is derived separately from TMI's Ka-band (37 GHz). A unique feature of this method is that it can be applied at any microwave frequency, making it very suitable to exploit all the available passive microwave data from various satellites.  Input data are from the TMI Brightness Temperatures (1B-11) product, archived at the Goddard Earth Sciences Data and Information Services Center (GES DISC).",
         "license": "proprietary"
     },
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         "description": "WindSat/Coriolis surface soil moisture (LPRM) L3 1 day 25 km x 25 km daytime V001 is a Level 3 (gridded) data set. Its land surface parameters, surface soil moisture, land surface (skin) temperature, and vegetation water content, are derived from polarimetric microwave radiometer data from WindSat, onboard the Naval Research Laboratory's Coriolis satellite, using the Land Parameter Retrieval Model (LPRM). There are two files per day, one ascending (daytime) and one descending (nighttime), archived as two different products. This document is for the daytime product. The data set covers the period from February 2003 to July 2012.  The LPRM is based on a forward radiative transfer model to retrieve surface soil moisture and vegetation optical depth. The land surface temperature is derived separately from the WindSat's Ka-band (37.0 GHz). A unique feature of this method is that it can be applied at any microwave frequency, making it very suitable to exploit all the available passive microwave data from various satellites.    Input data are from the WindSat brightness temperatures (sdrLowRes) product, daytime passes, as processed using LPRM (i.e., LPRM/WindSat/Coriolis L2 product, LPRM_WINDSAT_SOILM2_V001).",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1488311688-GES_DISC.html",
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         "description": "WindSat/Coriolis surface soil moisture (LPRM) L3 1 day 25 km x 25 km nighttime V001 is a Level 3 (gridded) data set. Its land surface parameters, surface soil moisture, land surface (skin) temperature, and vegetation water content, are derived from polarimetric microwave radiometer data from WindSat, onboard the Naval Research Laboratory's Coriolis satellite, using the Land Parameter Retrieval Model (LPRM). There are two files per day, one ascending (daytime) and one descending (nighttime), archived as two different products. This document is for the nighttime product. The data set covers the period from February 2003 to July 2012.  The LPRM is based on a forward radiative transfer model to retrieve surface soil moisture and vegetation optical depth. The land surface temperature is derived separately from the WindSat's Ka-band (37.0 GHz). A unique feature of this method is that it can be applied at any microwave frequency, making it very suitable to exploit all the available passive microwave data from various satellites.    Input data are from the WindSat brightness temperatures (sdrLowRes) product, nighttime passes, as processed using LPRM (i.e., LPRM/WindSat/Coriolis L2 product, LPRM_WINDSAT_SOILM2_V001).",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1488311935-GES_DISC.html",
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         "description": "WindSat/Coriolis surface soil moisture (LPRM) L2 V001 is a Level 2 (swath) data set. Its land surface parameters, surface soil moisture, land surface (skin) temperature, and vegetation water content, are derived from polarimetric microwave radiometer data from WindSat, onboard the Naval Research Laboratory's Coriolis satellite, using the Land Parameter Retrieval Model (LPRM). Each swath is packaged with associated geolocation fields. The data set covers the period from February 2003 to July 2012.  The LPRM is based on a forward radiative transfer model to retrieve surface soil moisture and vegetation optical depth. The land surface temperature is derived separately from the WindSat's Ka-band (37.0 GHz). A unique feature of this method is that it can be applied at any microwave frequency, making it very suitable to exploit all the available passive microwave data from various satellites.    Input data are from the WindSat brightness temperatures (sdrLowRes) product, archived at the Goddard Earth Sciences Data and Information Services Center (GES DISC).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2956539244-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2956539244-ORNL_CLOUD.html",
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         "description": "The NCAR LSM 1.0 is a land surface model developed to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces on climate and atmospheric chemistry. It can be run coupled to an atmospheric model or uncoupled, in a stand-alone mode, if an atmospheric forcing is provided. The model runs on a spatial grid that can range from one point to global. The model was designed for coupling to atmospheric numerical models. Consequently, there is a compromise between computational efficiency and the complexity with which the necessary atmospheric, ecological, and hydrologic processes are parameterized. The model is not meant to be a detailed micrometeorological model, but rather a simplified treatment of surface fluxes that reproduces at minimal computational cost the essential characteristics of land-atmosphere interactions important for climate simulations. The model is a complete executable code with its own time-stepping driver, initialization (subroutine lsmini), and main calling routine (subroutine lsmdrv). When coupled to an atmospheric model, the atmospheric model is the time-stepping driver. There is one call to subroutine lsmini during initialization to initialize all land points in the domain; there is one call per time step to subroutine lsmdrv to calculate surface fluxes and update the ecological, hydrological, and thermal state for all land points in the domain. The model writes its own restart and history files. These can be turned off if appropriate. Available for downloading from the ORNL DAAC are the LMS Model Documentation and User's Guide, the model source code, input data set, and scripts for running the model.  Applications of the model are described in two additional companion files.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2756847743-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756847743-ORNL_CLOUD.html",
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         "description": "This dataset, referred to as LUH2-GCB2019, includes 0.25-degree gridded, global maps of fractional land-use states, transitions, and management practices for the period 0850-2019. The LUH2-GCB2019 dataset is an update to the previous Land-Use Harmonization Version 2 (LUH2-GCB) datasets prepared as required input to land models in the annual Global Carbon Budget (GCB) assessments, including land-use change data relating to agricultural expansion, deforestation, wood harvesting, shifting cultivation, afforestation, and crop rotations. Compared with previous LUH2-GCB datasets, the LUH2-GCB2019 takes advantage of new data inputs that corrected cropland and grazing areas in the globally important region of Brazil, as far back as 1950. LUH2-GCB datasets are used by bookkeeping models and Dynamic Global Vegetation Models (DGVMs) for the GCB.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736721610-ORNL_CLOUD.html",
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         "description": "This data set provides field measurements of diameter, tree height, and crown dimensions for 1,513 trees in 30 plots at the La Selva Biological Station in Costa Rica. Fourteen of these plots were in undisturbed primary forest, six were in primary forest which had been selectively logged, seven were secondary forests, and three were abandoned pastures reverting to forest. The diameter and height data were used to calculate aboveground biomass for each of the 30 plots. The crown measurements were used to estimate a vertical profile for each plot, showing the vegetation volume in 1 meter increments from the ground to the top of the canopy.There are three comma-delimited data files and two shapefiles with this data set. The files contain the measurements and calculated biomass for the individual stems as well as the summary data at the plot level.",
         "license": "proprietary"
     },
@@ -120583,7 +120583,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773258088-ORNL_CLOUD.html",
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         "description": "This data set contains land-use, canopy height, and aboveground carbon estimates derived from LiDAR data collected at La Selva Biological Station in Costa Rica in March 1998 and March 2005. The data are provided as GeoTIFFs (*.tif) of 100-m (1-ha) resolution. A look-up table is provided that relates modeled changes in height to changes in stand characteristics (including age and carbon content). The data were used to test the accuracy and scale-dependency of high-resolution predictions of vegetation dynamics and carbon flux by the Ecosystem Demography (ED). The ED model is an individual-based terrestrial ecosystem model that predicts both ecosystem structure and corresponding ecosystem fluxes from climate, soil, and land-use inputs.",
         "license": "proprietary"
     },
@@ -120622,7 +120622,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2837050574-ORNL_CLOUD.html",
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         "description": "This dataset provides lake bathymetry maps derived from Landsat surface reflectance products for a portion of the North Slope area of Alaska. A random forest regression algorithm was used to generate depths for each point identified as being part of a lake, creating depth prediction files for each Landsat scene available for the study period: 2016-07-01 to 2018-08-31. These products are fitted to the ABoVE standard projection and reference grid to make them easily scalable and geometrically compatible with other products in the ABoVE study domain. The data are provided in cloud-optimized GeoTIFF (COG) format.",
         "license": "proprietary"
     },
@@ -120765,7 +120765,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784898845-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784898845-ORNL_CLOUD.html",
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         "description": "These data represent fractional land use and land cover patterns annually for the years 1500 - 2100 for the globe at 0.5-degree (~50-km) spatial resolution. Land use categories of cropland, pasture, primary land, secondary (recovering) land, and urban land, and underlying annual land-use transitions, are included. Annual data on age and biomass density of secondary land, as well as annual wood harvest, are included for each grid cell. Historical land cover data for the years 1500 - 2005 are based on HYDE 3.1 and future land cover projections for the period 2006 - 2100 came from four Integrated Assessment Model (IAM) scenarios which reach different levels of radiative forcing by year 2100: MESSAGE (8.5 W/m2), AIM (6 W/m2), GCAM (4.5 W/m2), and IMAGE (2.6 W/m2). A key feature of these data is that historical reconstructions of land use were harmonized (computationally adjusted to minimize differences at the transition period) with modeled future scenarios, allowing for a seamless examination of historical and future land use. The output data present a single consistent, spatially gridded set of land-use change scenarios for studies of human impacts on the past, present, and future Earth system. For additional information about the algorithms, inputs, and options used in creating the land use transitions data, please refer to Hurtt et al. (2006) and Hurtt et al. (2011).Data are presented as a series of twenty (20) different data products representing different past and future model scenarios. There are a total of 560 NetCDF v4 files (*.nc4), one for each combination of data product and land use variable.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764728966-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764728966-ORNL_CLOUD.html",
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         "description": "This dataset provides 0.25-degree gridded, global, annual estimates of fractional land use and land cover patterns for the period 2015-2100, designed to support the ISIMIP2b effort to assess the impacts of 1.5 Deg Celcius global warming. Land use types, land use transitions, and cropland estimates of area fraction are provided and include detailed separation of primary and secondary natural vegetation into forest and non-forest sub-types, pasture into managed pasture and rangeland, and cropland into multiple crop functional types; all transitions between land use states per grid cell per year, including crop rotations, shifting cultivation, and wood harvest; and agriculture management including irrigation, synthetic nitrogen fertilizer, and biofuel management. The LUH2-ISIMIP2b datasets were derived using Land Use Harmonization 2 (LUH2) methodology and are based on land-use scenarios provided by the REMIND-MAgPIE Integrated Assessment Model using an SSP2 storyline along with RCP2.6 and RCP6.0 emissions scenarios. In contrast to the standard SSP scenarios, these land use changes additionally account for climate and atmospheric CO2 fertilization effects on the underlying patterns of potential crop yields, water availability, and terrestrial carbon content. This is achieved by using the LPJmL (Lund-Potsdam-Jena managed land) model forced with atmospheric CO2 concentrations and patterns of climate change generated from 4 different climate models (GFDL, HADGEM, IPSL, and MIROC) consistent with the 2 different RCP scenarios, resulting in a set of 8 different LUH2-ISIMIP2b datasets.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389083233-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389083233-ORNL_CLOUD.html",
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         "description": "This dataset provides annual maps of land cover classes for the Colombian Amazon from 2001 through 2016 that were created by classifying time segments detected by the Continuous Change Detection and Classification (CCDC) algorithm. The CCDC algorithm detected changes in Landsat pixel surface reflectance across the time series, and the time segments were classified into land cover types using a Random Forest classifier and manually collected training data. Annual maps of land cover were created for each Landsat scene and then post-processed and mosaicked. Land cover types include unclassified, forest, natural grasslands, urban, pastures, secondary forest, water, or highly reflective surfaces. The training data are not included with this dataset.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2775078742-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2775078742-ORNL_CLOUD.html",
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         "description": "This dataset provides a reference of land surface phenology (LSP) at 30-m pixels for 78 regions of 10 x 10 km2 across a wide range of ecological and climatic regions in North America during 2019 and 2020. The data were derived by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near- surface PhenoCam time series (hereafter called HP-LSP). The HP-LSP dataset consists of two parts: (1) the 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series and (2) four key phenological transition dates that are greenup onset, maturity onset, senescence onset, and dormancy onset (accuracy less than or equal to five days). The PhenoCam network offers near-surface observations via the RGB (Red, Green, and Blue) imagery every 30 minutes. Each RGB imagery enables us to calculate as many as 100 Green Chromatic Coordinate (GCC) for generating a collection of localized vegetation dynamics. The HLS EVI2 time series with frequent gaps was fused with the most comparable PhenoCam GCC temporal shape selected from the GCC collection using the Spatiotemporal Shape Matching Model (SSMM) to create the synthetic gap-free HLS-PhenoCam EVI2 time series, which was used to establish the physically-based hybrid piecewise logistic model (HPLM) for detecting phenological transition dates (phenometrics).",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2398128915-ORNL_CLOUD.html",
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         "description": "This dataset provides the complete catalog of point cloud data collected during LiDAR surveys over selected forest research sites across the Amazon rainforest in Brazil between 2008 and 2018 for the Sustainable Landscapes Brazil Project. Flight lines were selected to overfly key field research sites in the Brazilian states of Acre, Amazonas, Bahia, Goias, Mato Grosso, Para, Rondonia, Santa Catarina, and Sao Paulo. The point clouds have been georeferenced, noise-filtered, and corrected for misalignment of overlapping flight lines. They are provided in 1 km2 tiles. The data were collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2767326506-ORNL_CLOUD.html",
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         "description": "This dataset provides the point cloud data derived from small footprint waveform LiDAR data collected in August 2014 over Reynolds Creek Experimental Watershed and Hollister in southern Idaho. The LiDAR data have been georeferenced, noise-filtered, and corrected for misalignment for overlapping flight lines and are provided in 1 km tiles. High resolution digital elevation models and maps of maximum vegetation height derived from the LiDAR data are provided for each site.",
         "license": "proprietary"
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         "description": "MAPSS (Mapped Atmosphere-Plant-Soil System) is a landscape to global vegetation distribution model that was developed to simulate the potential biosphere impacts and biosphere-atmosphere feedbacks from climatic change. Model output from MAPSS has been used extensively in the Intergovernmental Panel on Climate Change's (IPCC) regional and global assessments of climate change impacts on vegetation and in several other projects.",
         "license": "proprietary"
     },
@@ -123027,7 +123027,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2731753367-ORNL_CLOUD.html",
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         "description": "This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during a single flight aboard a NASA WB-57 aircraft over California, Nevada, Oregon, and Washington, U.S., on 2003-08-27. This deployment was an instrument validation flight. Imagery was collected over the Cascade Mountains and Lake Tahoe. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 25-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight path, spectral band information, instrument configuration, ancillary notes, and summary information for the flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
     },
@@ -123040,7 +123040,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2731775161-ORNL_CLOUD.umm_json",
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during three flights aboard a NASA ER-2 aircraft over California and Nevada, U.S., from 2005-10-19 to 2005-12-09. This deployment was coordinated by NASA's Dryden Flight Research Center (DRFC), renamed Armstrong Flight Research Center in 2014, located in Edwards, California. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during five flights aboard a NASA ER-2 aircraft over southwestern U.S., from 2011-05-15 to 2011-05-23. This deployment was coordinated by NASA's Dryden Flight Research Center (DRFC), renamed Armstrong Flight Research Center in 2014, located in Edwards, California. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
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         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during two flights aboard a NASA ER-2 aircraft over California, Nevada, Wyoming, Utah, Colorado, Nebraska, South Dakota, Wisconsin, and Minnesota, U.S., from 2006-09-19 to 2006-10-13. This deployment was coordinated by NASA's Dryden Flight Research Center (DRFC), renamed Armstrong Flight Research Center in 2014, located in Edwards, California. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) program during 21 flights aboard a NASA DC-8 aircraft over the central and western U.S. from 2019-07-22 to 2019-09-03. The purpose of these flights was to measure emissions and to characterize the aerosols in the smoke plume above and downwind of the fire, and to determine the overall spatial extent of wildfires and prescribed fires. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 20-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the FireSense project during 11 flights aboard a NASA B200 aircraft over California, Nevada, Utah, and Arizona, U.S., 2023-10-16 to 2023-10-26. The FireSense project is focused on delivering NASA's unique Earth science and technological capabilities to operational agencies, striving towards measurable improvement in US wildland fire management. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset provides resources for identifying flight lines of interest for the MODIS/ASTER Airborne Simulator (MASTER) instrument based on spatial and temporal criteria. MASTER first flew in 1998 and has ongoing deployments as a Facility Instrument in the NASA Airborne Science Program (ASP). MASTER is a joint project involving the Airborne Sensor Facility (ASF) at the Ames Research Center, the Jet Propulsion Laboratory (JPL), and the Earth Resources Observation and Science Center (EROS).  The primary goal of these airborne campaigns is to demonstrate important science and applications research that is uniquely enabled by the full suite of MASTER thermal infrared bands as well as the contiguous spectroscopic measurements of the AVIRIS (also flown in similar campaigns), or combinations of measurements from both instruments. This dataset includes a table of flight lines with dates, bounding coordinates, site names, investigators involved, flight attributes, and associated campaigns for the MASTER Facility Instrument Collection. A shapefile containing flights for all years, a GeoJSON version of the shapefile, and separate KMZ files for each year allow users to visualize flight line locations using GIS software.",
         "license": "proprietary"
     },
+    {
+        "id": "MASTER_GEMx_Spring_2024_2370_1",
+        "title": "MASTER: Geological Earth Mapping Experiment (GEMx), Spring 2024",
+        "catalog": "ORNL_CLOUD STAC Catalog",
+        "state_date": "2024-04-02",
+        "end_date": "2024-06-28",
+        "bbox": "-124.26, 31.14, -108.08, 43.2",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3255928163-ORNL_CLOUD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3255928163-ORNL_CLOUD.html",
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+        "description": "This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during 30 flights aboard a NASA ER-2 aircraft over California, Oregon, Nevada, and Arizona, US, from 2024-04-02 to 2024-06-28. The Geological Earth Mapping Experiment (GEMx) research project used NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Hyperspectral Thermal Emission Spectrometer (HyTES), and MODIS/ASTER Airborne Simulator (MASTER) instruments to collect the measurements over the country's arid and semi-arid regions, including parts of California, Nevada, Arizona, and New Mexico, to map portions of southwest US for critical minerals. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file. Level 2 products from these GEMx flights will be added to this dataset when they become available.",
+        "license": "proprietary"
+    },
     {
         "id": "MASTER_GEMx_Summer_2023_2319_1",
         "title": "MASTER: Geological Earth Mapping Experiment (GEMx), California-Arizona, Summer 2023",
@@ -123326,7 +123339,7 @@
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The raw data were collected as part of the Hyperspectral Infrared Imager (HyspIRI) mission's preparatory airborne campaign during 11 flights aboard a NASA ER-2 aircraft over California and Nevada, U.S., from 2013-09-13 to 2013-12-05. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during seven flights aboard a NASA ER-2 aircraft over California, Nevada, Central America, and eastern Pacific Ocean from 2007-07-29 to 2007-08-18. This deployment supported the Tropical Composition, Cloud and Climate Coupling Campaign (TC4), which investigated the atmospheric structure, properties, and processes in the Eastern Pacific Tropics. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Western Diversity Time Series (WDTS, formerly HyspIRI) airborne campaign during five flights aboard a NASA ER-2 aircraft over California and Nevada, U.S., from 2022-09-02 to 2022-09-09. The WDTS campaign will observe California's ecosystems and provide critical information on natural disasters such as volcanoes, wildfires, and drought. MASTER products can identify vegetation type and health and provide a benchmark for the state of the ecosystems against which future changes can be assessed. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Western Diversity Time Series (WDTS, formerly HyspIRI) program during nine flights aboard a NASA ER-2 aircraft over selected areas of California, U.S, from 2020-09-17 to 2020-10-15. The WDTS program will observe California's ecosystems and provide critical information on natural disasters such as volcanoes, wildfires, and drought. MASTER products can identify vegetation type and health and provide a benchmark for the state of the ecosystems against which future changes can be assessed. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each deployment, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Western Diversity Time Series (WDTS, formerly HyspIRI) airborne campaign during nine flights aboard a NASA ER-2 aircraft over selected areas of California and Nevada, U.S., from 2021-02-09 to 2021-04-02. The WDTS campaign will observe California's ecosystems and provide critical information on natural disasters such as volcanoes, wildfires, and drought. MASTER products can identify vegetation type and health and provide a benchmark for the state of the ecosystems against which future changes can be assessed. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "description": "This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Western Diversity Time Series (WDTS, formerly HyspIRI) airborne campaign during 12 flights aboard a NASA ER-2 aircraft over California and Nevada, U.S., from 2023-03-31 to 2023-05-02. The WDTS campaign will observe California's ecosystems and provide critical information on natural disasters such as volcanoes, wildfires, and drought. MASTER products can identify vegetation type and health and provide a benchmark for the state of the ecosystems against which future changes can be assessed. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in five bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2763230127-ORNL_CLOUD.html",
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         "description": "This dataset contains the Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) multispectral data collected during the SAFARI 2000 project. The flights were undertaken over Southern Africa by the NASA ER-2 aircraft during August and September, 2000.",
         "license": "proprietary"
     },
@@ -124383,19 +124396,6 @@
         "description": "The MCD15A3H Version 6.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Level 4, Combined Fraction of Photosynthetically Active Radiation (FPAR), and Leaf Area Index (LAI) product is a 4-day composite data set with 500 meter pixel size. The algorithm chooses the best pixel available from all the acquisitions of both MODIS sensors located on NASA\u2019s Terra and Aqua satellites from within the 4-day period.  LAI is defined as the one-sided green leaf area per unit ground area in broadleaf canopies and as one-half the total needle surface area per unit ground area in coniferous canopies. FPAR is defined as the fraction of incident photosynthetically active radiation (400-700 nm) absorbed by the green elements of a vegetation canopy.  The LAI product has attained stage 2 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation and the FPAR product has attained stage 1 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation.  Improvements/Changes from Previous Versions  * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).",
         "license": "proprietary"
     },
-    {
-        "id": "MCD18A1_061",
-        "title": "MODIS/Terra+Aqua Surface Radiation Daily/3-Hour L3 Global 1km SIN Grid V061",
-        "catalog": "LPCLOUD STAC Catalog",
-        "state_date": "2000-02-24",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2484080427-LPCLOUD.umm_json",
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-        "description": "The MCD18A1 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18A1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).   * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18A1 Version 6.1 product has an improved 1 km resolution over the 5 km Version 6. * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).   ",
-        "license": "proprietary"
-    },
     {
         "id": "MCD18A1_062",
         "title": "MODIS/Terra+Aqua Surface Radiation Daily/3-Hour L3 Global 1km SIN Grid V062",
@@ -124409,19 +124409,6 @@
         "description": "The MCD18A1 Version 6.2 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).    Provided in the MOD18A1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.    Validation at stage 1 (https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site (https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).     The Version 6.2 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: 1) MODIS shortwave infrared bands are included in the retrieval algorithm, which significantly reduces estimation uncertainties in cloud- and snow-covered pixels.   2) An improved climatology of surface reflectance was produced and used in the retrieval algorithm.        ",
         "license": "proprietary"
     },
-    {
-        "id": "MCD18A2_061",
-        "title": "MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 1km SIN Grid V061",
-        "catalog": "LPCLOUD STAC Catalog",
-        "state_date": "2000-02-24",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2484080763-LPCLOUD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2484080763-LPCLOUD.html",
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-        "description": "The MCD18A2 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Photosynthetically Active Radiation (PAR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of PAR every 3 hours. PAR is incident solar radiation in the visible spectrum (400-700 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident PAR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global PAR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18A2 product are layers for instantaneous PAR array for each individual MODIS overpass and 3-hour PAR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).    * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18A2 Version 6.1 product has an improved 1 km resolution over the 5 km Version 6. * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).",
-        "license": "proprietary"
-    },
     {
         "id": "MCD18A2_062",
         "title": "MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 1km SIN Grid V062",
@@ -124435,19 +124422,6 @@
         "description": "The MCD18A2 Version 6.2 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Photosynthetically Active Radiation (PAR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of PAR every 3 hours. PAR is incident solar radiation in the visible spectrum (400-700 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident PAR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global PAR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).    Provided in the MOD18A2 product are layers for instantaneous PAR array for each individual MODIS overpass and 3-hour PAR array along with a View Zenith Angle layer.    Validation at stage 1 (https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site (https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).     The Version 6.2 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: 1) MODIS shortwave infrared bands are included in the retrieval algorithm, which significantly reduces estimation uncertainties in cloud- and snow-covered pixels.   2) An improved climatology of surface reflectance was produced and used in the retrieval algorithm.        ",
         "license": "proprietary"
     },
-    {
-        "id": "MCD18C1_061",
-        "title": "MODIS/Terra+Aqua Downward Shortwave Radiation Daily/3-Hour L3 Global 0.05Deg CMG V061",
-        "catalog": "LPCLOUD STAC Catalog",
-        "state_date": "2000-02-24",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2484081120-LPCLOUD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2484081120-LPCLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections?cursor=eyJqc29uIjoiW1wibW9kaXMvdGVycmErYXF1YSBicmRmL2FsYmVkbyB3aGl0ZSBza3kgYWxiZWRvIHNob3J0d2F2ZSBkYWlseSBsMyBnbG9iYWwgMzBhcmNzZWMgY21nIHYwNjFcIixcIkxQQ0xPVURcIixcIk1DRDQzRDYxXCIsXCI2MVwiLDI1NDAyNzU2NzIsMjBdIiwidW1tIjoiW1wibW9kaXMvdGVycmErYXF1YSBicmRmL2FsYmVkbyB3aGl0ZSBza3kgYWxiZWRvIHNob3J0d2F2ZSBkYWlseSBsMyBnbG9iYWwgMzBhcmNzZWMgY21nIHYwNjFcIixcIkxQQ0xPVURcIixcIk1DRDQzRDYxXCIsXCI2MVwiLDI1NDAyNzU2NzIsMjBdIn0%3D/MCD18C1_061",
-        "description": "The MCD18C1 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG) with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18C1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).    * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).",
-        "license": "proprietary"
-    },
     {
         "id": "MCD18C1_062",
         "title": "MODIS/Terra+Aqua Downward Shortwave Radiation Daily/3-Hour L3 Global 0.05Deg CMG V062",
@@ -124461,19 +124435,6 @@
         "description": "The MCD18C1 Version 6.2 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG) with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).    Provided in the MOD18C1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.    Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).     The Version 6.2 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: 1) MODIS shortwave infrared bands are included in the retrieval algorithm, which significantly reduces estimation uncertainties in cloud- and snow-covered pixels.   2) An improved climatology of surface reflectance was produced and used in the retrieval algorithm.        ",
         "license": "proprietary"
     },
-    {
-        "id": "MCD18C2_061",
-        "title": "MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 0.05Deg CMG V061",
-        "catalog": "LPCLOUD STAC Catalog",
-        "state_date": "2000-02-24",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2484081543-LPCLOUD.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2484081543-LPCLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections?cursor=eyJqc29uIjoiW1wibW9kaXMvdGVycmErYXF1YSBicmRmL2FsYmVkbyB3aGl0ZSBza3kgYWxiZWRvIHNob3J0d2F2ZSBkYWlseSBsMyBnbG9iYWwgMzBhcmNzZWMgY21nIHYwNjFcIixcIkxQQ0xPVURcIixcIk1DRDQzRDYxXCIsXCI2MVwiLDI1NDAyNzU2NzIsMjBdIiwidW1tIjoiW1wibW9kaXMvdGVycmErYXF1YSBicmRmL2FsYmVkbyB3aGl0ZSBza3kgYWxiZWRvIHNob3J0d2F2ZSBkYWlseSBsMyBnbG9iYWwgMzBhcmNzZWMgY21nIHYwNjFcIixcIkxQQ0xPVURcIixcIk1DRDQzRDYxXCIsXCI2MVwiLDI1NDAyNzU2NzIsMjBdIn0%3D/MCD18C2_061",
-        "description": "The MCD18C2 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Photosynthetically Active Radiation (PAR) gridded Level 3 product produced daily at 0.05 degree (5,600 meters at the equator) resolution with estimates of PAR every 3 hours. PAR is incident solar radiation in the visible spectrum (400-700 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident PAR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global PAR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18C2 product are layers for instantaneous PAR array for each individual MODIS overpass and 3-hour PAR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).    * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).",
-        "license": "proprietary"
-    },
     {
         "id": "MCD18C2_062",
         "title": "MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 0.05Deg CMG V062",
@@ -124600,7 +124561,7 @@
         "bbox": "-180, -90, 180, 90",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2565807736-LPCLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/LPCLOUD/collections?cursor=eyJqc29uIjoiW1wibW9kaXMvdGVycmErYXF1YSBicmRmL2FsYmVkbyB3aGl0ZSBza3kgYWxiZWRvIHNob3J0d2F2ZSBkYWlseSBsMyBnbG9iYWwgMzBhcmNzZWMgY21nIHYwNjFcIixcIkxQQ0xPVURcIixcIk1DRDQzRDYxXCIsXCI2MVwiLDI1NDAyNzU2NzIsMjBdIiwidW1tIjoiW1wibW9kaXMvdGVycmErYXF1YSBicmRmL2FsYmVkbyB3aGl0ZSBza3kgYWxiZWRvIHNob3J0d2F2ZSBkYWlseSBsMyBnbG9iYWwgMzBhcmNzZWMgY21nIHYwNjFcIixcIkxQQ0xPVURcIixcIk1DRDQzRDYxXCIsXCI2MVwiLDI1NDAyNzU2NzIsMjBdIn0%3D/MCD19A3CMG_061",
         "description": "The MCD19A3CMG Version 6.1 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-Angle Implementation of Atmospheric Correction (MAIAC) Vegetation Index Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The MCD19A3CMG product provides Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) at ground level in the absence of atmospheric scattering or absorption.     The MCD19A3CMG Vegetation Index data product contains the following Science Dataset (SDS) layers: NDVI, NDVI normalized to a fixed geometry of solar zenith angle at 45\u00b0 and nadir view, gap-filled NDVI, EVI, and EVI normalized to a fixed geometry of solar zenith angle at 45\u00b0 and nadir view. A low-resolution browse image is also included showing NDVI created using a composite of all available orbits. ",
         "license": "proprietary"
     },
@@ -127234,7 +127195,7 @@
         "id": "MIL2ASAF_002",
         "title": "MISR Level 2 FIRSTLOOK Aerosol parameters V002",
         "catalog": "LARC STAC Catalog",
-        "state_date": "1999-12-18",
+        "state_date": "2017-11-01",
         "end_date": "",
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1542382556-LARC.umm_json",
@@ -127247,13 +127208,13 @@
         "id": "MIL2ASLF_002",
         "title": "MISR Level 2 FIRSTLOOK Surface parameters V002",
         "catalog": "LARC STAC Catalog",
-        "state_date": "1999-12-18",
+        "state_date": "2017-11-01",
         "end_date": "",
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1542382559-LARC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1542382559-LARC.html",
         "href": "https://cmr.earthdata.nasa.gov/stac/LARC/collections?cursor=eyJqc29uIjoiW1wibWlzciBsZXZlbCAxYjIgdGVycmFpbiBkYXRhIHYwMDRcIixcIkxBUkNcIixcIk1JMUIyVFwiLFwiNFwiLDI3OTQzNzM4MDYsN10iLCJ1bW0iOiJbXCJtaXNyIGxldmVsIDFiMiB0ZXJyYWluIGRhdGEgdjAwNFwiLFwiTEFSQ1wiLFwiTUkxQjJUXCIsXCI0XCIsMjc5NDM3MzgwNiw3XSJ9/MIL2ASLF_002",
-        "description": "This Level 2 FIRSTLOOK Land Surface product contains directional reflectance properties,albedo(spectral & PAR integrated),FPAR,radiation parameters & terrain-referenced geometric parameters, produced using ancillary input from the previous time period.",
+        "description": "This Level 2 FIRSTLOOK Land Surface product contains directional reflectance properties, albedo(spectral and PAR integrated), FPAR, radiation parameters, and terrain-referenced geometric parameters produced using ancillary input from the previous time period. MIL2ASLF_002 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 FIRSTLOOK Surface parameters version 2. It contains directional reflectance properties, albedo (spectral and photosynthetically active radiation (PAR) integrated), a fraction of photosynthetically active radiation absorbed by vegetation (FPAR), radiation parameters, and terrain-referenced geometric parameters produced using ancillary input from the previous time period. Data collection for this product is ongoing. This collection contains the Leaf Area Index (LAI).\\r\\n\\r\\nMulti-angle Imaging SpectroRadiometer (MISR) Level 2 Aerosol data products contain various information on the Earth's atmosphere. The aerosol data include tropospheric aerosol optical depth on 17. 6-km centers archived with a compositional model identifier and retrieval residuals, ancillary data including relative humidity, ozone optical depth, stratospheric aerosol optical depth, and retrieval flags. MISR multi-angle imagery will be used to monitor global and regional trends radiatively significant to optical properties (optical depth, single scattering albedo, and size distribution) and amounts (mass loading) of natural and anthropogenic aerosols, including those arising from industrial and volcanic emissions, slash-and-burn agriculture, and desertification. Coupled with MISR's determinations of top-of-atmosphere and surface albedos, these data will measure the global aerosol forcing of the shortwave planetary radiation budget. \\r\\n\\r\\nThe MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four forward, and four aftward. It takes seven minutes for all nine cameras to view the exact surface location. The view angles relative to the surface reference ellipsoid are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. MISR is designed to view Earth with cameras in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successfully imaged by all nine cameras in 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the effects of sunlight on Earth and distinguish different types of clouds, particles, and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.",
         "license": "proprietary"
     },
     {
@@ -128045,7 +128006,7 @@
         "bbox": "9.08, -35, 31.49, -15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2788357139-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788357139-ORNL_CLOUD.html",
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         "description": "MISR (Multi-angle Imaging SpectroRadiometer) views the sunlit Earth simultaneously at nine widely spaced and collects global images with high spatial detail in four colors at every angle. These images are carefully calibrated to provide accurate measures of the brightness, contrast, and color of reflected sunlight. The change in reflection at different view angles affords the means to distinguish different types of atmospheric particles (aerosols), cloud forms, and land surface covers. Combined with stereoscopic techniques, this enables construction of 3-dimensional models and more accurate estimates of the total amount of sunlight reflected by Earth's diverse environments.MISR was built for NASA by the Jet Propulsion Laboratory. It is part of NASA's Terra spacecraft, launched into a polar orbit around the Earth on December 18, 1999.The Southern African Fire Atmosphere Research Initiative (SAFARI) 2000 field campaign focused on the smoke and gases released into the environment of southern Africa by industrial, biological, and man-made sources such as biomass burning. The area of study and MISR path numbers include Botswana, Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Zambia, and Zimbabwe. These MISR data cover the period August 12 through September 28, 2000.",
         "license": "proprietary"
     },
@@ -128071,7 +128032,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2515861985-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515861985-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of forest aboveground biomass (AGB; in Mg ha-1) at a resolution of 250 m for the southwestern United States over the time period 2000-2021. The AGB estimates were derived from the Jet Propulsion Laboratory Multiangle Imaging Spectro-Radiometer (MISR) Level 1B2 Terrain radiance data and a multi-angle approach that exploits the relationship between forest AGB and a suite of red band reflectance values modeled at viewing angles with respect to the direction of illumination. The year 2000 National Biomass and Carbon Dataset (NBCD 2000) AGB estimates were used to fit a model coefficient for the MISR-derived AGB estimates for the year 2000, with AGB estimates for all subsequent years dependent on both this coefficient and MISR red band bidirectional reflectance factors (BRFs). Quality assurance (QA) files are also provided that allow users to impose criteria of varying stringency. The bidirectional reflectance distribution function (BRDF) model-fitting root mean square error (RMSE) value was used as one of the criteria to determine if the AGB estimates were reasonable. This dataset is the first example of forest AGB estimation based on a multi-angle index applied using MISR data.",
         "license": "proprietary"
     },
@@ -133830,7 +133791,7 @@
         "bbox": "-180, 0, 0, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2631225371-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2631225371-ORNL_CLOUD.html",
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         "description": "This data set contains daily Moderate Resolution Imaging Spectroradiometer (MODIS) land incident photosynthetically active radiation (PAR) images over North America for the years 2003 - 2005 and was created to fill the need for daily PAR estimates. Incident PAR is the solar radiation in the range of 400 to 700 nm reaching the earth's surface and plays an important role in modeling terrestrial ecosystem productivity.  The daily images were derived by integrating MODIS/Terra and MODIS/Aqua instantaneous PAR data where the instantaneous PAR data is estimated directly from Terra or Aqua MODIS 5-min L1b swath data (Liang et al., 2006 and Wang et al., 2010). The spatial distribution of this data set includes the MODIS tile subsets covering North America, Central America, portions of South America, and Greenland, available for the years 2003 - 2005. There are 45,376 *.hdf files with a spatial resolution of 4 km x 4 km in sinusoidal projection distributed by year in three compressed data files: 2003.zip, 2004.zip, and 2005.zip. Contained within each daily file are 4 separate image files: DirectPar, DiffusePAR, TotalPAR, and Observation Count. There are 46 MODIS tiles that cover the study area extent.  ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789036254-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789036254-ORNL_CLOUD.html",
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         "description": "The recently generated MODIS burned area product over southern Africa for the month of September 2000 was used to calculate regional biomass burning emissions from grassland and woodland fires for a number of trace gases and particulates at 1 km spatial resolution. A dynamic regional fuel load model developed for southern Africa in support of SAFARI 2000 fire emissions modeling is used to compute spatially explicit southern Africa fuel load data.",
         "license": "proprietary"
     },
@@ -134623,7 +134584,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789742965-ORNL_CLOUD.html",
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         "description": "The MOPITT (Measurements Of Pollution In The Troposphere) instrument on the NASA Terra Satellite makes measurements of infrared radiation originating from the surface of the planet and isolates the energy being radiated from carbon monoxide (CO). By using appropriate data analysis techniques, concentration profiles of CO (Level-2 (L2) data) can be obtained on a global basis at a reasonably high horizontal (~22km) and vertical resolution (~3km).The MOPITT Level-3 (L3) data products provided in this data set are a subset of the daily averages from the L2 data. This subset was produced by overlaying a global 1x1-degree grid onto the L2 data, and then clipping the data to this southern Africa subset which originates at 5 degrees longitude and -35 degrees latitude and extends to 60 degrees longitude and 35 degrees latitude. Data are reported for 2 heights, 700 and 350 hPa, from daytime swaths for the period August 1-September 30, 2000, the SAFARI 2000 Dry Season Campaign.",
         "license": "proprietary"
     },
@@ -136807,7 +136768,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736724792-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736724792-ORNL_CLOUD.html",
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         "description": "This data set describes the temperature and relative humidity at 12 locations around Goddard Space Flight Center in Greenbelt MD at 15 minute intervals between November 2013 and November 2015. These data were collected to study the impact of surface type on heating in a campus setting and to improve the understanding of urban heating and potential mitigation strategies on the campus scale. Sensors were mounted on posts at 2 m above surface and placed on 7 different surface types around the centre: asphalt parking lot, bright surface roof, grass field, forest, and stormwater mitigation features (bio-retention pond and rain garden). Data were also recorded in an office setting and a garage, both pre- and post-deployment, for calibration purposes. This dataset could be used to validate satellite-based study or could be used as a stand-alone study of the impact of surface type on heating in a campus setting.",
         "license": "proprietary"
     },
@@ -136963,7 +136924,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808090466-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808090466-ORNL_CLOUD.html",
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         "description": "A global digital data base of vegetation was compiled at 1 degree latitude by 1 degree longitude resolution, drawing on approximately 100 published sources.  Vegetation data from varied sources were consistently recorded using the hierarchical UNESCO classification system.  The raw data base distinguishes about 180 vegetation types that have been collapsed to 32.",
         "license": "proprietary"
     },
@@ -137080,7 +137041,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764692443-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764692443-ORNL_CLOUD.html",
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         "description": "This dataset provides a global 0.25 degree x 0.25 degree gridded monthly mean leaf area index (LAI) climatology as averaged over the period from August 1981 to August 2015. The data were derived from the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g version 2, a bi-weekly data product from 1981 to 2015 (GIMMS-LAI3g version 2). The LAI3g version 2 (raw) data were first regridded from 1/12 x 1/12 degree to 0.25 x 0.25 degree resolution, then processed to remove missing and unreasonable values, scaled to obtain LAI values, and the bi-weekly LAI values were averaged for every month. Finally, the monthly long-term mean LAI (1981-2015) was calculated.",
         "license": "proprietary"
     },
@@ -137119,7 +137080,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2847115945-ORNL_CLOUD.html",
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         "description": "This dataset provides Level 2 (L2) Solar-Induced Fluorescence (SIF) of chlorophyll estimates derived from the Global Ozone Monitoring Experiment 2 (GOME-2) instrument on the European Meteorological Satellite (EUMETSAT) MetOp-A with ~0.5 nm spectral resolution and wavelengths between 734 and 758 nm. GOME-2 covers global land on an orbital basis at a resolution of approximately 40 km x 80 km (before 15 July 2013) or 40 km x 40 km (since 15 July 2013). Data are provided for the period from 2007-02-01 to 2018-02-01. Each file contains daily raw and bias-adjusted solar-induced fluorescence, quality control information, and ancillary data. SIF measurements can provide information on vegetation's functional status, including light-use efficiency and global primary productivity, which can be used for global carbon cycle modeling and agricultural applications. The GOME-2 SIF product is inherently noisy due to low signal levels and has undergone only a limited amount of validation. The data are provided in netCDF format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2840822442-ORNL_CLOUD.html",
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         "description": "This dataset provides Level 2 (L2) Solar-Induced Fluorescence (SIF) of chlorophyll estimates derived from the Global Ozone Monitoring Experiment 2 (GOME-2) instrument on the European Meteorological Satellite (EUMETSAT) MetOp-B with ~0.5 nm spectral resolution and wavelengths between 734 and 758 nm. GOME-2 covers global land (observations up to 75-degree solar zenith angle) at a resolution of approximately 40 km x 80. Data are provided for the period from 2013-04-01 to 2021-06-07. Each file contains daily raw and bias-adjusted solar-induced fluorescence along with quality control information and ancillary data. SIF measurements can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. The GOME-2 SIF product is inherently noisy owing to low signal levels and has undergone only a limited amount of validation. The data are provided in netCDF (*.nc) format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345793484-ORNL_CLOUD.html",
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         "description": "This dataset provides the hourly average of continuous atmospheric measurements of methane (CH4) from two urban sites and three boundary sites in and around Boston, Massachusetts, U.S., from September 2012-May 2020, measured with Picarro cavity ring down spectrometers (CRDS). Five-minute average atmospheric measurements of ethane (C2H6) and methane at Copley Square in Boston, MA, are also provided, with ethane measured with a laser spectrometer and methane measured with a Picarro CRDS. Background CH4 concentrations for the urban sites were determined using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model trajectories at the boundary of the study region based on measurements at three boundary sites and wind direction from the North American Mesoscale Forecast System (NAM) 12-kilometer meteorology.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345877554-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345877554-ORNL_CLOUD.html",
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         "description": "This dataset contains annual global flare site surveys from 2012-2019 derived from Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar Partnership (SNPP) satellite. Gas flaring sites were identified from heat anomalies first estimated by the VIIRS Nightfire (VNF) algorithm from which high-temperature biomass burning and low-temperature gas flaring were separated based on temperature and persistence. Nightly observations for each flare site were drawn to determine their activity in the given calendar year. Data include flare location, temperature, and estimated flared gas volume; flaring data summarized by country; and KMZ files for viewing flaring locations in Google Earth. This dataset is valuable for measuring the current status of global gas flaring, which can have significant environmental impacts.",
         "license": "proprietary"
     },
@@ -137223,7 +137184,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863233-ORNL_CLOUD.html",
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         "description": "The U.S. Department of Agriculture, Agriculture and Agri-Food Canada, the Russian Academy of Agricultural Sciences, the University of Copenhagen Institute of Geography, the European Soil Bureau, the University of Manchester Institute of Landscape Ecology, MTT Agrifood Research Finland, and the Agricultural Research Institute Iceland have shared data and expertise in order to develop the Northern and Mid Latitude Soil Database (Cryosol Working Group, 2001). This database was the source of data for the current product. The spatial coverage of the Northern and Mid Latitude Soil Database is the polar and mid-latitude regions of the northern hemisphere: Alaska, Canada, Conterminous United States, Eurasia (except Italy), Greenland, Iceland, Kazakstan, Mexico, Mongolia, Italy, and Svalbard. The Northern and Mid-Latitude Soil Database represents the proportion (percentage) of polygon encompassed by the dominant soil or nonsoil. Soils include turbels, orthels, histels, histosols, mollisols, vertisols, aridisols, andisols, entisols, spodosols, inceptisols (and hapludolls), alfisols (cryalf and udalf), natric great groups, aqu-suborders, glaciers, and rocklands. Also included are data on the circumpolar distribution of gelisols (turbels, orthels, and histels), and the ice content (low, medium, or high) of circumpolar soil materials (from the International Permafrost Association, 1997). The resulting maps show the dominant soil of the spatial polygon unless the polygon is over 90 percent rock or ice. Data are in the U.S. soil classification system and includes the distribution of soil types (%) within a map unit (polygon). Data are available in ESRI shapefile format and include the same attribute values with the exception of Italy, which does not contain distribution values.",
         "license": "proprietary"
     },
@@ -137249,7 +137210,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3236621594-ORNL_CLOUD.html",
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         "description": "This dataset provides global monthly wetland methane (CH4) emissions estimates at 0.5 by 0.5-degree resolution for the period 2001-01-01 to 2022-08-31 that were derived from an ensemble of multiple terrestrial biosphere models, wetland extent scenarios, and CH4:C temperature dependencies that encompass the main sources of uncertainty in wetland CH4 emissions. There are 18 model configurations. WetCHARTs v1.3.3 is an updated product of WetCHARTs v1.3.1 dataset. The intended use of this product is as a process-informed wetland CH4 emission data set for atmospheric chemistry and transport modeling. Users can compare estimates by model configuration to explore variability and sensitivity with respect to ensemble members. The data are provided in netCDF format.",
         "license": "proprietary"
     },
@@ -137834,7 +137795,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517711781-ORNL_CLOUD.html",
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         "description": "This data set provides organic soil layer characteristics, estimated carbon content, and soil depth measurements made at four black spruce stands in interior Alaska that had burned twice in the last 37-52 years (intermediate-interval fire events). The most recent fires occurred in 2004, 2005, and 2010. Measurements of soil depth and distance from the adventitious roots to the soil, and total organic matter are also included for unburned black spruce sites adjacent to the burned sites dominated by live, intermediate-aged (~37-52 years) black spruce trees.",
         "license": "proprietary"
     },
@@ -137847,7 +137808,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539900339-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of aboveground biomass (AGB) for defined land cover types within World Wildlife Fund (WWF) ecoregions across the boreal biome of Alaska and western and eastern Canada, roughly between 45 and 70 degrees N. The study focused on within-growing-season data, i.e. leaf-on conditions.The AGB estimates were derived from a series of models that first related ground-based measured biomass to Portable Airborne Laser System (PALS) LiDAR measurements, and a second set of models that related the airborne estimates of biomass to Geoscience Laser Altimeter System (GLAS) LiDAR canopy structure measurements. The GLAS LiDAR biomass estimates were extrapolated by land cover types and ecoregions across the entire biome area.The study compiled remotely sensed forest structure data collected in June of 2005 and 2006 from the GLAS LiDAR instrument aboard the NASA Ice, Cloud, and land Elevation (ICESat) satellite and from the PALS airborne instrument flown at various times from 2005-2009 over both the ground plots and the ICESat GLAS flight path. For a consistent biome-level analysis, ecoregions contained within the boreal forest biome were identified by the World Wildlife Fund's (WWF) ecoregion map of the world (Olson et al., 2001). Land cover maps were used to identify land cover types for stratification purposes within eco-regions. Land cover data for Canada were provided by the Earth Observations for Sustainable Development (EOSD) project centered on year 2000, with images from 1999 to 2002. The National Land Cover Data (NLCD) 2001 classification was used for Alaska based on data collected between 1999 and 2004. The ground-based measurements are not provided with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2552905405-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2552905405-ORNL_CLOUD.html",
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         "description": "This data set includes biophysical measurements collected in 2009 from five New England experimental forest stations: Bartlett Experimental Forest, Harvard Forest, Howland Research Forest, Hubbard Brook Experimental Forest, and the Penobscot Experimental Forest. Howland measurements were repeated in 2010 and one site in the Sierra National Forest, California, was surveyed in 2008. Biomass in respective measurement plots was calculated with allometric equations using measured diameter at breast height (DBH) for trees greater than 10 cm and species identification. Within selected subplots, the number of stems with diameters less than 10 cm were counted and classified to allow for an estimate of biomass for these stems.  There are 16 data files provided that present the biophysical measurement results and the biomass estimates in ASCII comma-separated format.  For a subset of sites and plots (Bartlett Experimental Forest, Harvard Forest and Howland Research Forest), more intensive inventories were done in coordination with Echidna lidar imaging (Strahler et al., 2008). In these intensive collections, the stem location, species, DBH and live/dead status were recorded for all stems with total stem height and canopy dimensions recorded for every tenth stem. In addition, for stems below 10 cm DBH, species and count were recorded in a subplot of each intensive inventory plot. See the related data set Strahler et al., 2011.Investigators from Federal and university laboratories conducted these field campaign to make estimates of forest biophysical attributes that will prove useful in comparisons with airborne lidar (LVIS) and UAVSAR remote sensing acquisitions. The North American Carbon Program (NACP) is a multi-disciplinary research program designed to obtain scientific understanding of North America's carbon sources and sinks and of the changes in carbon stocks needed to meet societal concerns, and to provide tools for decision makers. NACP began in 2002 and continues to date. The NACP data collection contains continental carbon budgets, dynamics, processes, and management of the sources and sinks of carbon dioxide, methane, and carbon monoxide in North America and in adjacent ocean regions. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517656499-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517656499-ORNL_CLOUD.html",
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         "description": "This dataset contains annual estimates of carbon stocks, fluxes, and productivity over forested land in 11 states of the western USA (Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming). The estimates were produced from multiple simulations using the Community Land Model (v4.5) with different climate forcing data and prescribed harvest rates. Business as usual (BAU) scenarios were run to ensure that the simulations represented present-day stand ages. The estimates span two modeled time periods, 1979-2014 and 2015-2099, at 1/24-degree (4 km x 4 km) resolution. Variables included are gross primary production (GPP), net ecosystem exchange (NEE), net ecosystem productivity (NEP), net primary production (NPP), autotrophic respiration (RA), heterotrophic respiration (RH), transpiration factor, aboveground live tree carbon, carbon loss from fire, allocation to stem carbon, and burned area fraction over forested areas of the western USA.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2539906855-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539906855-ORNL_CLOUD.html",
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         "description": "This data set is a collection of measurements of carbon dioxide (CO2) and non-CO2 greenhouse gases made across North America by nine independent atmospheric monitoring networks from 2000 - 2009. During this North American Carbon Program (NACP) sponsored activity, data were compiled from the following networks: AGAGE, COBRA, CSIRO, INTEX-A, INTEX B, Irvine Latitude Network, NOAA CMDL, SCRIPPS, and Stanley Tyler-UC Irvine. The files presented here are the products of merging multiple original measurement results files for selected sites across North America from each monitoring network. The primary focus of this effort was the compilation of non-CO2 greenhouse gases over North America, but numerous CO2 observations are also included. The data files for each network are accompanied by detailed readme documentation files prepared by the respective network investigators. Project descriptions, objectives, references, sampling and analysis methods, and data file descriptions are included in these READMEs. Table 1 in the documentation displays the monitoring network sites, sample types, analytes, and links to the detailed network README files. Network- and laboratory-specific data citations are included in the README documentation and should be used to acknowledge the use of these data as appropriate. The data files for each monitoring network and each sampling type (continuous or flasks) have been combined into one compressed (*.zip) file along with the detailed README document. There are 17 compressed files that when expanded contain data files which represent one years data for that specific campaign and sampling method. The number of annual files that were compiled from a network into this collection varies.",
         "license": "proprietary"
     },
@@ -137899,7 +137860,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2539907396-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539907396-ORNL_CLOUD.html",
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         "description": "This data set provides a bottom-up CO2 emissions inventory for the mid-continent region of the United States for the year 2007. The study was undertaken as part of the North American Carbon Program (NACP) Mid-Continent Intensive (MCI) campaign. Emissions for the MCI region were compiled from these resources into nine inventory sources (Table 1):(1) forest biomass and soil carbon, harvested woody products carbon, and agricultural soil carbon from the U.S. Greenhouse Gas (GHG) Inventory (EPA, 2010; Heath et al., 2011);(2) high resolution data on fossil and biofuel CO2 emissions from Vulcan (Gurney et al,. 2009); (3) CO2 uptake by agricultural crops, lateral transport in crop biomass harvest, and livestock CO2 emissions using USDA statistics (West et al., 2011); (4) agricultural residue burning (McCarty et al., 2011);(5) CO2 emissions from landfills (EPA, 2012);(6) and CO2 losses from human respiration using U.S. Census data (West et al., 2009). The CO2 inventory in the MCI region was dominated by fossil fuel combustion, carbon uptake during crop production, carbon export in biomass (commodities) from the region, and to a lesser extent, carbon sinks in forest growth and incorporation of carbon into timber products. ",
         "license": "proprietary"
     },
@@ -137912,7 +137873,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2539908010-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539908010-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of Net Ecosystem Exchange (NEE) flux for the U.S. Upper Midwest at 0.5-degree resolution for the year 2007. Estimates were produced by two atmospheric CO2 inversion systems (top-down), referenced as the continental Colorado State University (CSU) inversion and the mesoscale Pennsylvania State University (PSU) inversion. This modeling work was performed in support of the North American Carbon Program (NACP) Mid-Continent Intensive (MCI) experimental campaign in the U.S. Upper Midwest designed to evaluate innovative methods for CO2 flux inversion and data assimilation. The experiment was performed over a relatively flat, heavily managed agricultural landscape which features a high density of atmospheric CO2 observation measurements. Among the CO2 observations used by the inversion systems were results from a network of instrumented tall towers in the region. The NEE estimates were produced for comparison with CO2 fluxes derived from bottom-up inventory estimates.There are five data files with this data set. The NEE estimates are provided in two NetCDF files, one for each inversion system. Boundary CO2 inflow data used by each inversion system are provided in three comma-separated-format files (.csv).",
         "license": "proprietary"
     },
@@ -137925,7 +137886,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539941056-ORNL_CLOUD.html",
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         "description": "This data set provides high precision and high accuracy atmospheric CO2 data from seven instrumented communication towers located in the U.S. Upper Midwest. The overall sampling period was from January 2007 through December 2009 although actual sampling dates vary within this time period for individual towers and sampling heights above ground level. The measurements were obtained in support of the North American Carbon Program (NACP) Mid-Continent Intensive (MCI) campaign.The sampling network included: the five Ring 2 towers (Centerville (Iowa), Galesville (Wisconsin), Kewanee (Illinois), Mead (Nebraska), and Round Lake (Minnesota)) deployed and operated by PSU; the Missouri Ozarks (Missouri) co-located AmeriFlux site (PSU/Oak Ridge National Laboratory (ORNL)); and the Rosemount (Minnesota) tall tower trace gas observatory (University of Minnesota, Rosemount Research and Outreach Center (RROC)). Hourly CO2 dry mole fractions (in ppm) were averaged from measurements made at different above-ground levels on the towers and are reported in Coordinated Universal Time (UTC). For the five Ring 2 sites, daily daytime average CO2 dry mole fractions were also calculated, from hourly values between 12:00-17:00 local standard time and reported in UTC. There are seven compressed (.zip) data files and one comma-separated (.csv) file with this data set. Data quality flags are provided in each file. ",
         "license": "proprietary"
     },
@@ -137938,7 +137899,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2631228736-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2631228736-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibW93aW5nIGV4cGVyaW1lbnQgYmlvcGh5cy4gZGF0YSAoZmlmZSlcIixcIk9STkxfQ0xPVURcIixcImZpZmVfYmlvbG9neV9tb3dfYmlvcF81NVwiLFwiMVwiLDI5ODAxMTI4OTAsMl0iLCJ1bW0iOiJbXCJtb3dpbmcgZXhwZXJpbWVudCBiaW9waHlzLiBkYXRhIChmaWZlKVwiLFwiT1JOTF9DTE9VRFwiLFwiZmlmZV9iaW9sb2d5X21vd19iaW9wXzU1XCIsXCIxXCIsMjk4MDExMjg5MCwyXSJ9/NACP_MCI_Crop_GPP_1217_1",
         "description": "This data set provides an integrated collection of (1) ground-based meteorological, radiometric, and vegetation measurements, (2) flux-based estimates of gross primary production (GPP), and (3) numerous vegetation indices derived from satellite imagery for three eddy covariance flux tower locations near Lincoln, Nebraska, USA. Land use surrounding the towers is cropland with corn and soybeans. Data are reported for selected days during the growing seasons of 2001 through 2008 only when ground-based crop canopy reflectance was measured. Algorithms developed to relate ground-based and satellite spectral information to GPP of the cropland adjacent to the towers are provided. AmeriFlux tower-based Level 2 measurements included photosynthetically active radiation (PAR), heat flux, and GPP estimates; see Section 2 for specific towers.Ground-based measurements on the corn and soybean vegetation surrounding the towers included total chlorophyll content (Chl) and leaf area index (LAI). Ground-based crop canopy reflectance was measured at 5.4 m above the corn and soybean canopy using hyperspectral radiometers (range 400 to 1100 nm) during the growing season from May to October in eight different years (2001-2008). This resulted in 173 measurement campaigns (18 in 2001, 31 in 2002, 34 in 2003, 31 in 2004, 21 in 2005, 15 in 2006, 14 in 2007, and 9 in 2008). Spectral bands from Landsat TM and ETM+, MERIS , and MODIS instruments were used to calculate vegetation indices. Vegetation indices related to chlorophyll can be used as a proxy for GPP because of the observed close relationship between GPP and Chl content in crops. Algorithms developed to relate spectral information to the GPP of the cropland adjacent to the towers are provided as companion files.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2631228061-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2631228061-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibW93aW5nIGV4cGVyaW1lbnQgYmlvcGh5cy4gZGF0YSAoZmlmZSlcIixcIk9STkxfQ0xPVURcIixcImZpZmVfYmlvbG9neV9tb3dfYmlvcF81NVwiLFwiMVwiLDI5ODAxMTI4OTAsMl0iLCJ1bW0iOiJbXCJtb3dpbmcgZXhwZXJpbWVudCBiaW9waHlzLiBkYXRhIChmaWZlKVwiLFwiT1JOTF9DTE9VRFwiLFwiZmlmZV9iaW9sb2d5X21vd19iaW9wXzU1XCIsXCIxXCIsMjk4MDExMjg5MCwyXSJ9/NACP_Modeled_NEE_NEP_Fluxes_1203_1",
         "description": "This data set provides modeled carbon flux estimates at 8-km spatial resolution over North America for the year 2004 of (1) net ecosystem exchange (NEE) of carbon dioxide (CO2), (2) net ecosystem production (NEP, the balance of net primary production and heterotrophic respiration), (3) stream evasion (CO2 emitted from streams and rivers), (4) emissions from harvested forest and agricultural products, and (5) emissions from biomass burning.Annual estimates, in g C/m2/year, are provided for all five fluxes. Daily estimates, in g C/m2/day, are provided for NEP and stream evasion fluxes. Fluxes for fire emissions, harvest decomposition/respiration, stream evasion, and NEP were derived as described in Section 5.NEE fluxes were estimated using a full bottom-up accounting of NEE produced by integrating emissions from harvested forest and agricultural products, CO2 emitted from streams and rivers, and biomass burning in the CarbonTracker (version 2011_oi) modeling system. NEE estimates were run in the forward mode through the CarbonTracker inversion setup that calculates CO2 uptake and release at the Earth's surface over time. Refer to Turner et al.(2013) for details.There are seven data files in NetCDF (.nc) format with this data set, including: five annual files for fire emissions, harvest decomposition/respiration, stream evasion, NEP, and NEE fluxes; and two daily files for NEP and stream evasion fluxes.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2552206090-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2552206090-ORNL_CLOUD.html",
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         "description": "This data set provides environmental data that have been standardized and aggregated for use as input to carbon cycle models at global (0.5-degree resolution) and regional (North America at 0.25-degree resolution) scales. The data were compiled from selected sources (Table 2) and integrated into gridded global and regional collections of climatology variables (precipitation, air temperature, air specific humidity, air relative humidity (NA only), pressure, downward longwave radiation, downward shortwave radiation, and wind speed), time-varying atmospheric CO2 concentrations, time-varying nitrogen deposition, biome fraction and type, land-use and land-cover change, C3/C4 grasses fractions, major crop distribution, phenology, multiple soil characteristics, and a land-water mask. The temporal ranges of the data are sufficient for carbon cycle model simulations from 1801 to 2010. These data were compiled specifically for the North American Carbon Program (NACP) Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as the prescribed model input driver data (Huntzinger et al., 2013). The driver data were used by 22 terrestrial biosphere models to run baseline and sensitivity simulations. The standardized data provided consistent model inputs to minimize the inter-model variability caused by differences in environmental drivers and initial conditions. Together with the sensitivity simulations, the standardized input data enable better interpretation and quantification of structural and parameter uncertainties of model estimates. Data are provided in Climate and Forecast (CF) metadata convention compliant (version 1.4) netCDF-4 file formats. There are 3,152 *.nc4 data files with this data set. ",
         "license": "proprietary"
     },
@@ -137977,7 +137938,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2631229163-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2631229163-ORNL_CLOUD.html",
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         "description": "This data set provides a summary of the model structure and characteristics of participating models in the North American Carbon Program (NACP) Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP), a formal model intercomparison and evaluation effort focused on improving the diagnosis and attribution of carbon exchange at regional and global scales. Model structure refers to the types of processes considered (e.g. nutrient cycling, disturbance, lateral transport of carbon), and the specific ways these processes are represented (e.g. photosynthetic formulation, temperature sensitivity, respiration) in the models. These data are the result of a comprehensive survey of investigators responsible for each MsTMIP participating model. For a given characteristic (i.e., process/attribute), a model was assigned a binary value (0 or 1) indicating whether it included a particular characteristic; a value of one (1) was given if it considered or included that process, or a zero (0) if it did not. MsTMIP builds upon current and past synthesis activities, and has a unique framework designed to isolate, interpret, and inform understanding of how model structural differences impact estimates of carbon uptake and release. There is one data file with this data set in .csv format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2556074845-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2556074845-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibW93aW5nIGV4cGVyaW1lbnQgYmlvcGh5cy4gZGF0YSAoZmlmZSlcIixcIk9STkxfQ0xPVURcIixcImZpZmVfYmlvbG9neV9tb3dfYmlvcF81NVwiLFwiMVwiLDI5ODAxMTI4OTAsMl0iLCJ1bW0iOiJbXCJtb3dpbmcgZXhwZXJpbWVudCBiaW9waHlzLiBkYXRhIChmaWZlKVwiLFwiT1JOTF9DTE9VRFwiLFwiZmlmZV9iaW9sb2d5X21vd19iaW9wXzU1XCIsXCIxXCIsMjk4MDExMjg5MCwyXSJ9/NACP_MsTMIP_TBMO_1225_1",
         "description": "This data set provides global gridded estimates of carbon, energy, and hydrologic fluxes between the land and atmosphere from 15 Terrestrial Biosphere Models (TBMs) in a standard format. Model estimates are at monthly and yearly time steps for the period 1900 to 2010, with a spatial resolution of 0.5 degree x 0.5 degree globally, excluding Antarctica.",
         "license": "proprietary"
     },
@@ -138003,7 +137964,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2539902376-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539902376-ORNL_CLOUD.html",
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         "description": "This data set provides soil maps for the United States (US) (including Alaska), Canada, Mexico, and a part of Guatemala. The map information content includes maximum soil depth and eight soil attributes including sand, silt, and clay content, gravel content, organic carbon content, pH, cation exchange capacity, and bulk density for the topsoil layer (0-30 cm) and the subsoil layer (30-100 cm). The spatial resolution is 0.25 degree. The Unified North American Soil Map (UNASM) combined information from the state-of-the-art US General Soil Map (STATSGO2) and Soil Landscape of Canada (SLCs) databases. The area not covered by these data sets was filled by using the Harmonized World Soil Database version 1.21 (HWSD1.21). The Northern Circumpolar Soil Carbon (NCSCD) database was used to provide more accurate and up-to-date soil organic carbon information for the high-latitude permafrost region and was combined with soil organic carbon content derived from the UNASM (Liu et al., 2013). The UNASM data were utilized in the North American Carbon Program (NACP) Multi-Scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) as model input driver data (Huntzinger et al., 2013). The driver data were used by 22 terrestrial biosphere models to run baseline and sensitivity simulations. The compilation of these data was facilitated by the NACP Modeling and Synthesis Thematic Data Center (MAST-DC). MAST-DC was a component of the NACP (www.nacarbon.org) designed to support NACP by providing data products and data management services needed for modeling and synthesis activities.",
         "license": "proprietary"
     },
@@ -138016,7 +137977,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517680963-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517680963-ORNL_CLOUD.html",
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         "description": "This dataset reports continuous atmospheric measurements of CO2 from two receptor sites and three boundary sites in and around Boston, Massachusetts, USA, that were combined with high-resolution CO2 emissions estimates and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to estimate regional CO2 emissions from September 2013 to December 2014. The HYSPLIT model followed an ensemble of 1,000 particles released at the urban CO2 measurement sites backward in time based on wind fields and turbulence from the North American Mesoscale Forecast System (NAM) at 12-km resolution to the boundary CO2 measurement sites to derive footprint values and CO2 enhancements expected from the prior emissions based on the Anthropogenic Carbon Emissions System (ACES) inventory and the urban-Vegetation Photosynthesis Respiration Model (urbanVPRM). This dataset contains three sets of data products: (1) observed hourly mean CO2 observations for two urban receptor sites in Boston, MA (Boston University (BU) and Copley Square (COP)), (2) observed hourly mean CO2 and calculated vertical profiles (50 - 5000 m) for three boundary sites around Boston including Harvard Forest at Petersham, MA (HF), Canaan, NH (CA), and Martha's Vineyard, MA (MVY), and modeled mean boundary CO2 concentrations for particles released from BU and COP, and (3) particle trajectory files including footprint values and CO2 enhancements above boundary CO2 concentrations from the HYSPLIT model.",
         "license": "proprietary"
     },
@@ -138029,7 +137990,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517713672-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517713672-ORNL_CLOUD.html",
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         "description": "This data set provides Biome-BGC modeled estimates of carbon stocks and fluxes in the U.S. Pacific Northwest for the years 1986-2010. Fluxes include net ecosystem production (NEP), and net aboveground wood growth. Stocks include aboveground wood mass. Also present are mapped distributions of associated forest disturbances, distinguished by disturbance type (harvest, fire, pest/pathogen). The data are presented in a mapped form as well as in tabular summaries broken out by ownership and ecoregion. Maps of annual precipitation and temperature data are included for the years 1980-2010.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2840815089-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2840815089-ORNL_CLOUD.html",
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         "description": "This dataset from the PalEON Ecosystem Model Intercomparison Project (PEMIP) provides harmonized regional environmental and meteorological drivers at a resolution of 0.5 degrees for the North-central and Northeastern U.S. over the time period 0850-01-01 to 2010-12-31. This dataset consists of the regional environmental and meteorological drivers. The environmental drivers include (1) dominant biome type, (2) plant functional type, (3) annual carbon dioxide concentration, (4) monthly carbon dioxide concentration, (5) land use-land cover change, (6) nitrogen concentrations, and (7) soil measurements. The meteorological drivers include (1) incident longwave radiation, (2) incident shortwave radiation, (3) precipitation, (4) surface pressure, (5) specific humidity, (6) air temperature, and (7) wind speed. The PEMIP is a coordinated effort to develop a set of terrestrial ecosystem model simulations with the ability to evaluate high-resolution ecophysiological causes and consequences of forest responses to climatic variability and change over the past millennium.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2631233127-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2631233127-ORNL_CLOUD.html",
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         "description": "This data set provides landcover maps of (1) peatland type (bog, fen, marsh, swamp) with levels of biomass (open, forested) and (2) Burn Severity Index (BSI) (Dyrness and Norum, 1983) for four wildfire areas in northern Alberta, Canada. The four wildfire sites include the Utikuma fire site of 2011, Kidney Lake fire site of 2011, Fort McMurray west fire site of 2009, and Fort McMurray east fire site of 2009. The peatland classification at 12.5-m resolution (fen vs. bog including treed vs. open vs. shrubby) at each wildfire site was based on a pre-burn 2007 multi-date, multi-sensor fusion (Optical-IR, C-band and L-band SAR) approach. Over 350 field locations were sampled in central Alberta to train and validate the peatland type maps. The additional site, Wabasca, was an unburned site. Burn severity was measured in the field using the Burn Severity Index (BSI) (Dyrness and Norum 1987), a qualitative assessment of burnt moss that uses a 1-5 scale, with 1 being unburnt and 5 being severely burnt. The field data of ground consumption were correlated with Landsat pre- and post-burn imagery, specific to peatlands, to develop multivariate models for calculating burn severity and %-not-sphagnum-moss. These models were used to generate the Burn Severity Maps at 30-m resolution (percent unburned moss, and the burn severity index (BSI)). All sites were visited in 2013 for field measurements and the Utikuma site was also visited in 2012 for field measurements. Additional biophysical data for the various peatlands (aboveground biomass \u0096 tree and shrub, plant heights, density, etc. were collected and will be provided in another data set. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517704644-ORNL_CLOUD.html",
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         "description": "This dataset provides a land cover map focused on peatland ecosystems in the upper peninsula of Michigan. The map was produced at 12.5-m resolution using a multi-sensor fusion (optical and L-band SAR) approach with imagery from Landsat-5 TM and ALOS PALSAR collected between 2007 and 2011. A random forest classifier trained with polygons delineated from field data and aerial photography was used to determine pixel classes. Accuracy assessment based on field-sampled sites show high overall map accuracy (92%).",
         "license": "proprietary"
     },
@@ -138081,7 +138042,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539942542-ORNL_CLOUD.html",
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         "description": "This data set provides two products that were derived from the recently published North American Carbon Program (NACP) Regional Synthesis 1-degree terrestrial biosphere model (TBM) and inverse model (IM) outputs (Gridded 1-deg Observation Data and Biosphere and Inverse Model Outputs, Wei et al., 2013). The first product is the aggregation of the standardized gridded 1-degree TBM and IM outputs to the Greenhouse Gas (GHG) inventory zones as defined for North America (United States, Canada, and Mexico). Depending on the data availability, the monthly/yearly Net Ecosystem Exchange (NEE), Net Primary Production (NPP), Total Vegetation Carbon (VegC), Heterotrophic Respiration (Rh), and Fire Emissions (FE) outputs from the 22 TBM and 7 IM models were aggregated from the 1-degree resolution gridded format to the inventory zones and then, further divided into Forest Lands, Crop Lands, and Other Lands sectors within each inventory zone based on the 1-km resolution GLC2000 land cover map (GLC2000, 2003).The second product is the North American national GHG inventories on the scale of inventory zones which contain estimated land-atmosphere exchange of CO2 (NEE) in forest lands, crop lands, and other lands sectors. NEE estimates were synthesized from inventory-based data on productivity, ecosystem carbon stock change, and harvested product stock change, and additional information from national-level GHG inventories of the United States, Canada, and Mexico including EPA (2011) and Environment Canada (2011).An additional summary file of annual mean NEE (2000-2006)is provided for both land sectors and reporting zones in North America and was created by combining the aggregated model output and the national GHG database and is provided. The aggregated monthly and yearly model output data and the national GHG inventories data are available in comma separated value (*.csv) format files. Also provided are detailed inventory zone spatial data as an ESRI Shapefile. Included are zone names, boundaries, and zone and land cover type area attributes. For mapping convenience, the inventory zones shapefile was merged with 1-km forest, crop, and other lands masks to create a 1-km resolution reference data file that was converted to GeoTIFF format. The GeoTIFF defines to which inventory zone and land cover type each 1-km grid cell belongs.This document provides detailed information about the content, format, and processing procedures of these two data products. Detailed descriptions of the TBMs and IMs can be found in a separate companion document: NACP Regional Synthesis - Description of Observations and Models. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2555119330-ORNL_CLOUD.html",
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         "description": "This data set contains standardized gridded observation data, terrestrial biosphere model output data, and inverse model simulations of carbon flux parameters that were used in the North American Carbon Program (NACP) Regional Synthesis activities. The data set provides five observation data files (MODIS GPP, MODIS NPP, FIA forest biomass/forest area, NASS crop NPP, and NASS agricultural land fraction) and simulation results from 18 terrestrial biosphere models (TBM) (28 variables; 114 files) and seven inverse models (IM) (two variables; 8 files). To produce this data set, the NACP Modeling and Synthesis Thematic Data Center (MAST-DC) resampled original model simulation results and observation measurement data to 1-degree spatial resolution for North American region, interpolated into monthly or yearly temporal resolution, and reformatted into Climate and Forecast (CF) convention compatible netCDF format. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539941553-ORNL_CLOUD.html",
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         "description": "This data set contains the originally-submitted observation measurement data, terrestrial biosphere model output data, and inverse model simulations that various investigator teams contributed to the North American Carbon Program (NACP) Regional Synthesis activities. The data set provides nine (9) data packages of remote sensing and ground observation measurements (OM) (MODIS gross primary productivity (GPP), MODIS net primary production (NPP), MODIS fraction of photosynthetically active radiation (fPar), MODIS leaf area index (LAI), MODIS enhanced vegetation index (EVI), MODIS normalize difference vegetation index (NDVI), Forest Inventory and Analysis (FIA) forest biomass, National Agricultural Statistics Service (NASS) crop NPP, and Flux Anomaly). The data set also provides data packages of simulation results from 19 terrestrial biosphere models (TBM) and eight (8) inverse models (IM). The data packages are respectively OM, TBM, and IM data files listed in Tables 4-6. Each OM, TBM, and IM data package contains all of the original data (and documentation, if any) that the NACP Modeling and Synthesis Thematic Data Center (MAST-DC) acquired or received. These originally-submitted data were processed by the MAST-DC to produce the three standardized gridded data sets of carbon flux for inter-comparison purposes (see Related Data Products below). These original data and documentation are provided to allow users of the standardized gridded data products to be able to trace back to the data origins when needed. The Data Center (ORNL DAAC) transformed some of the originally-submitted data files to file formats that are more suitable for long-term archiving. For example, *.xlsx files were saved as *.csv, ERDAS Imagine files were converted to GeoTIFFs, and MATLAB files were converted to GeoTIFF and NetCDF formats as appropriate. Files received in NetCDF, GeoTIFF, and HDF formats were not transformed.  ",
         "license": "proprietary"
     },
@@ -138120,7 +138081,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2552200592-ORNL_CLOUD.html",
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         "description": "This data set contains standardized gridded observation data, terrestrial biospheric model output, and inverse model simulations that were compiled but not used in the North American Carbon Program (NACP) Regional Synthesis activities, thus the supplemental designation. The data set provides six (6) observation data packages (9 variables - MODIS LAI, MODIS FPAR, MODIS NDVI, MODIS EVI, FIA forest biomass, forest area, GPP Anomaly, NEE Anomaly, Reco Anomaly; 8 data files), output results from three terrestrial biosphere models (TBM) (14 variables; 214 files), and simulations from one inverse model (IM) (one variable; 1 file). To produce this data set, the NACP Modeling and Synthesis Thematic Data Center (MAST-DC) original data files were resampled to 1-degree spatial resolution for North American region (except for FIA Forest Biomass which was resampled to 0.5-degree resolution), interpolated into monthly or yearly temporal resolution, and reformatted into Climate and Forecast (CF) convention compatible netCDF format.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2631226474-ORNL_CLOUD.html",
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         "description": "This data set contains the original model output data submissions from the 24 terrestrial biosphere models (TBM) that participated in the North American Carbon Program (NACP) Site-Level Synthesis. The model teams generated estimates for, but not limited to,  a minimum of six variables, including gross primary productivity (GPP), net ecosystem exchange (NEE), leaf area index (LAI), ecosystem respiration (Re), latent heat flux (LE), and sensible heat flux (H) for each of 47 selected eddy covariance flux tower sites across North America. Participating modeling teams followed the NACP Site Synthesis Protocol (site_synthesis_protocol_v7.pdf), which covers procedures, plans, and infrastructure for the site-level analyses. File format and units conversions of several data submissions were made by the MAST-DC to produce NetCDF files of consistent content and structure for all 24 TBM outputs. The model outputs are structured as described in Appendix A: Model Output Variables, of the Site Synthesis Protocol. In addition, MAST-DC processed these original model submissions to derive uniquely processed and formatted data files for model inter-comparison and evaluation (NACP Site: Terrestrial Biosphere Model and Aggregated Flux Data in Standard Format). This related data set provides GPP, NEE, LAI, Re, LE, and sensible heat (H) model output variables at the native half-hourly time step, and in daily, monthly, and annual aggregations. The related data set also contains gap-filled observations and total uncertainty estimates at the same time steps.There are 24 compressed (*.zip) files with this data set -- one file for each model. When expanded, the .zip files contain model output data files for flux tower sites in NetCDF and some in text formats.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539942233-ORNL_CLOUD.html",
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         "description": "This data set provides standardized output variables for gross primary productivity (GPP), net ecosystem exchange (NEE), leaf area index (LAI), ecosystem respiration (Re), latent heat flux (LE), and sensible heat flux (H) from 24 terrestrial biosphere models for 47 eddy covariance flux tower sites in North America. Each model used standardized input data for each flux tower site (i.e., gap-filled, locally observed weather; land use history; and other site specific data) and followed standard model setup and spinup procedures. The files also contain gap-filled observations and total uncertainty estimates. The data set was compiled for the North American Carbon Program (NACP) Site-Level Synthesis for use in model inter-comparison and assessment of how well the models simulate carbon processes across vegetation types and environmental conditions in North America. There is one compressed (.zip) file with this data set. When expanded, the .zip file contains model output data for one variable at one site. The model output and observations are available at the native half-hourly time step, or in daily, monthly, and annual aggregations, in comma-separated text (.csv) format. ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539943609-ORNL_CLOUD.html",
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         "description": "This data set contains meteorological, carbon cycle flux, phenology, and ancillary data measured at 47 eddy covariance flux tower sites across North America. The data were used by North American Carbon Program (NACP) Site-Level Synthesis as model driver data and for assessing how well 24 Terrestrial Biosphere Models simulated carbon processes across vegetation types and environmental conditions.*The meteorology data include eight variables: air temperature (K), specific humidity (kg/kg), wind speed (m/s), precipitation (kg/m2/s), surface pressure (Pa), surface incident shortwave radiation (W/m2), surface incident longwave radiation (W/m2), and CO2 concentration (ppm). Gap-filled data were used by modeling teams as input model driver data.*Measured fluxes of net ecosystem exchange (NEE) and derived gross primary productivity (GPP) and respiration (R) and respective calculated uncertainty estimates are provided for each tower site at the native time resolution of the observations (30 or 60-minute) as well as the diurnal, seasonal, and annual time scales. The data were gap-filled following a standard protocol. Components of uncertainty include uncertainties resulting from turbulence, gap-filling, flux partitioning, and u* threshold determination. Flux observations and uncertainty data were used to assess how well models simulated carbon processes.*Remotely sensed NDVI, LAI, and fPAR phenology data were derived from the GIMMS version g NDVI data set for each flux tower site. Phenology data were used by some modeling teams as input model driver data.*Ancillary data and information describe tower location and physical characteristics, disturbance history, and biological and ecological attributes of the vegetation, litter, and soil. These ancillary data were used by modeling teams as input model driver data.The data files are in both ASCII text and NetCDF formats (ALMA standard). The compilation of these data was facilitated by the NACP Modeling and Synthesis Thematic Data Center (MAST-DC). ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539885886-ORNL_CLOUD.html",
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         "description": "This data set contains measurements and estimates of leaf, tree, and soil data from six projects conducted by the Terrestrial Ecosystem Research and Regional Analysis- Pacific Northwest (TERRA-PNW) research group between 1999 and 2014 across forests in Oregon and Northern California. Included are standardized, integrated measurements and estimates of specific leaf area, leaf longevity, leaf carbon and nitrogen for 35 tree and shrub species derived from more than 1,200 branch samples collected from over 200 forest plots, including several AmeriFlux sites. Plot-level measurements of forest composition, structure (e.g. tree biomass), and productivity estimates, as well as measurements of soil structure (e.g. bulk density) and chemistry (e.g. carbon) are also included.",
         "license": "proprietary"
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         "description": "This dataset provides spatial data products with identified and organized locations of potential methane (CH4) emitting facilities and infrastructure spanning the State of California. These data products form a GIS-based mapping database designed to address shortcomings in current CH4 source inventories and is known as Vista California (Vista-CA). Vista-CA consists of detailed spatial maps for facilities and infrastructure in California that are known or expected sources of CH4 emissions and illustrates the spatial distribution of potential CH4 sources. Vista-CA spatial data sets were created utilizing an assortment of publicly available data sources from local, state, and federal agencies for the years 2005 to 2019. The final Vista-CA database contains over 230,000 entries, which are presented as fifteen CH4 emitting infrastructure maps. The database was used to support flight planning and source attribution for the California Methane Survey project.",
         "license": "proprietary"
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         "description": "This data set provides spatial data products with identified and classified locations of potential methane (CH4) emitting facilities and infrastructure in the South Coast Air Basin (SoCAB). These data products form a GIS-based mapping database designed to address shortcomings in current urban CH4 source inventories and is known as Vista Los Angeles (Vista-LA). SoCAB is the air shed for the greater Los Angeles urban area, which includes urbanized portions of the Los Angeles, Orange, Riverside, and San Bernardino Counties, California, USA. Vista-LA consists of detailed spatial maps for facilities and infrastructure in the SoCAB that are known or expected sources of CH4 emissions and illustrates the spatial distribution of potential CH4 sources, representing a first step towards developing an urban-scale CH4 emissions gridded inventory for the SoCAB. Vista-LA spatial data sets were created utilizing an assortment of publicly available data sources from local, state, and federal agencies for the years 2012 to 2017. The final Vista-LA database contains over 33,000 entries, which are presented as thirteen CH4 emitting infrastructure maps.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2552181939-ORNL_CLOUD.html",
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         "description": "The data set provides a 30-m comprehensive fuelbed characteristics map for both the wildland and cropland areas of the conterminous United States (CONUS) for 2010. This integrated product is the result of combining the spatially discrete Fuel Characteristic Classification System (FCCS) data of the US Forest Service (USFS) with the crop-and grassland-specific information of the US Department of Agricultures (USDA's) Cropland Data Layer (CDL).  By combining the spatially discrete details of the FCCS data set with the crop-and grassland-specific information of the CDL, a more robust map of fuelbed characteristics is available. The merged product has an advantage over the original FCCS map for estimating emissions from burned areas due to the integration of the fuelbed characteristics for agricultural areas from the CDL.There are three GeoTIFF format files and three comma-separated companion files distributed with this data set. The three tif files provided are very large and exceed the size limits of a standard GeoTIFF file format (4 GB). File sizes range from 20 to 30 GB. Compressed file sizes range from 2 to 3 GB. They are in a format that is called a BigTIFF file. ArcGIS 10.0 and ERDAS Imagine are able to read these files.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517709145-ORNL_CLOUD.html",
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         "description": "This data set provides the results of (1) field measurements of woody vegetation (shrubs) at 26 diverse sites across the North Slope of Alaska during 2010 and 2011, (2) field-based statistical estimates of site shrub structural characteristics, (3) high-resolution panchromatic satellite imagery-based estimates of field site shrub characteristics using the Canopy Analysis with Panchromatic Imagery (CANAPI) model, and (4) adjusted CANAPI estimates of shrub characteristics at 1,013 selected sites widely distributed across the North Slope.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517303826-ORNL_CLOUD.html",
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         "description": "Characterizing the cause of forest canopy changes through time is fundamental to understanding current and future forest functions. A better understanding of forest dynamics can help build linkages between patterns and processes. The North American Forest Dynamics (NAFD) products provided in this dataset predict characteristics related to the cause of forest canopy cover losses for the conterminous United States (CONUS) derived from Landsat images for the period 1986-2010.  The characteristics are summarized in four separate data layers. The first layer labels the type of change event (stable-no change, removals, fire, stress, wind, conversion, other), the second labels the year of the event, the third and fourth layers measure dominance and diversity, measures of qualitative confidence metrics derived from the model predictions. For each pixel the maps depict the greatest magnitude event occurring between 1986-2010.",
         "license": "proprietary"
     },
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         "description": "The North American Forest Dynamics (NAFD) products provided in this data set consist of 25 annual and two time-integrated forest disturbance maps for the conterminous United States (CONUS) derived from Landsat images for the period 1986-2010. Each annual map has classified pixels showing water, no forest cover, forest cover, no data available (data gaps) in present year, and forest disturbances that occurred in that year. The time-integrated maps are similarly classified, but over the entire 1986-2010 period with the first and last forest disturbance years identified and provided as separate maps.",
         "license": "proprietary"
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         "description": "This data set provides the results of time-series analyses of Landsat imagery for 55 selected forested sites across the conterminous U.S.A. The output is a pair of disturbance data products for each site, one showing the first year of disturbance in the time series, the other showing the last year of disturbance. Each data pixel is labeled as either a static land class (persistent non-forest, persistent forest, or persistent water) or with the year of change for disturbed forest pixels. The time period analyzed is approximately 1984-2009.These forest disturbance data are distributed as a single band GeoTiff, with appropriate projection information defined within the file. The analyses were performed in three phases: 5 sites during the Prototype/Focal phase; 23 sites in Phase I; and 27 sites in Phase II. The spatial resolution of the Prototype/Focal and Phase I data is 28.5 meters. The spatial resolution of the Phase II data is 30 meters. The temporal resolution is nominally biennial. The mapped area for each forested site is approximately 185 km x 185 km. There are a total of 110 GeoTiff files - a first year and a last year disturbance file for each of the 55 sites.",
         "license": "proprietary"
     },
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_HGT) dataset, which provides global elevation data at 1 arc second spacing.    NASADEM data products were derived from original telemetry data from the Shuttle Radar Topography Mission (SRTM), a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA), as well as participation from the German and Italian space agencies. SRTM\u2019s primary focus was to generate a near-global DEM of the Earth using radar interferometry. It was a primary component of the payload on space shuttle Endeavour during its STS-99 mission, which was launched on February 11, 2000, and \ufb02ew for 11 days.   In addition to Terra Advanced Spaceborne Thermal and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 data, NASADEM also relied on Ice, Cloud, and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) ground control points of its lidar shots to improve surface elevation measurements that led to improved geolocation accuracy.  Other reprocessing improvements include the conversion to geoid reference and the use of GDEMs and Advanced Land Observing Satellite Panchromatic Remote-sensing instrument for Stereo Mapping (PRISM) AW3D30 DEM, and interpolation for void filling.    NASADEM are distributed in 1 degree latitude by 1 degree longitude tiles and consist of all land between 60\u00b0 N and 56\u00b0 S latitude. This accounts for about 80% of Earth\u2019s total landmass.       NASADEM_HGT data product layers include DEM, number of scenes (NUM), and an updated SRTM water body dataset (water mask). The NUM layer indicates the number of scenes that were processed for each pixel and the source of the data. A low-resolution browse image showing elevation is also available for each NASADEM_HGT granule.  ",
         "license": "proprietary"
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_NC) dataset, which provides global elevation data at 1 arc second spacing.    NASADEM data products were derived from original telemetry data from the Shuttle Radar Topography Mission (SRTM), a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA), as well as participation from the German and Italian space agencies. SRTM\u2019s primary focus was to generate a near-global DEM of the Earth using radar interferometry. It was a primary component of the payload on space shuttle Endeavour during its STS-99 mission, which was launched on February 11, 2000, and \ufb02ew for 11 days.   In addition to Terra Advanced Spaceborne Thermal and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 data, NASADEM also relied on Ice, Cloud, and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) ground control points of its lidar shots to improve surface elevation measurements that led to improved geolocation accuracy.  Other reprocessing improvements include the conversion to geoid reference and the use of GDEMs and Advanced Land Observing Satellite Panchromatic Remote-sensing instrument for Stereo Mapping (PRISM) AW3D30 DEM, and interpolation for void filling.    NASADEM are distributed in 1\u00b0 by 1\u00b0 tiles and consist of all land between 60\u00b0 N and 56\u00b0 S latitude. This accounts for about 80% of Earth\u2019s total landmass.       NASADEM_NC data product layer includes DEM. The NUM layer indicates the number of scenes that were processed for each pixel and the source of the data. The source of each elevation pixel in the corresponding NASADEM_NUMNC product.  ",
         "license": "proprietary"
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         "license": "proprietary"
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_SHHP) dataset, which provides Shuttle Radar Topography Mission (SRTM) global elevation height data at 1 arc second spacing.  NASADEM data products were derived from original telemetry data from SRTM, a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA), as well as participation from the German and Italian space agencies. SRTM\u2019s primary focus was to generate a near-global DEM of the Earth using radar interferometry. It was a primary component of the payload on space shuttle Endeavour during its STS-99 mission, which was launched on February 11, 2000, and \ufb02ew for 11 days.   In addition to Terra Advanced Spaceborne Thermal and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 data, NASADEM also relied on Ice, Cloud, and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) ground control points of its lidar shots to improve surface elevation measurements that led to improved geolocation accuracy.  Other reprocessing improvements include the conversion to geoid reference and the use of GDEMs and Advanced Land Observing Satellite Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) AW3D30 DEM, and interpolation for void filling.  NASADEM are distributed in 1 degree latitude by 1 degree longitude tiles and consist of all land between 60\u00b0 N and 56\u00b0 S latitude. This accounts for about 80% of Earth\u2019s total landmass.     NASADEM_SHHP data product layers include SRTM-only floating-point DEM and height error. A low-resolution browse image showing the SRTM-only elevation is also available for each NASADEM_SHHP granule. ",
         "license": "proprietary"
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_SIM) dataset, which provides global Shuttle Radar Topography Mission (SRTM) image mosaic data at 1 arc second spacing.    NASADEM data products were derived from original telemetry data from the Shuttle Radar Topography Mission (SRTM), a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA), as well as participation from the German and Italian space agencies. SRTM\u2019s primary focus was to generate a near-global DEM of the Earth using radar interferometry. It was a primary component of the payload on space shuttle Endeavour during its STS-99 mission, which was launched on February 11, 2000, and \ufb02ew for 11 days.   In addition to Terra Advanced Spaceborne Thermal and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 data, NASADEM also relied on Ice, Cloud, and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) ground control points of its lidar shots to improve surface elevation measurements that led to improved geolocation accuracy.  Other reprocessing improvements include the conversion to geoid reference and the use of GDEMs and Advanced Land Observing Satellite Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) AW3D30 DEM, and interpolation for void filling.    NASADEM are distributed in 1 degree latitude by 1 degree longitude tiles and consist of all land between 60\u00b0 N and 56\u00b0 S latitude. This accounts for about 80% of Earth\u2019s total landmass.       NASADEM_SIM data product layers include radar combined images and a NUM file associated with combined images. A low-resolution browse image showing the SRTM image mosaic elevation is also available for each NASADEM_SIM granule.  ",
         "license": "proprietary"
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Digital Elevation Model (DEM) version 1 (NASADEM_SSP) dataset, which provides global Shuttle Radar Topography Mission (SRTM) sub-swath elevation data at 1 arc second spacing.  NASADEM data products were derived from original telemetry data from the Shuttle Radar Topography Mission (SRTM), a collaboration between NASA and the National Geospatial-Intelligence Agency (NGA), as well as participation from the German and Italian space agencies. SRTM\u2019s primary focus was to generate a near-global DEM of the Earth using radar interferometry. It was a primary component of the payload on space shuttle Endeavour during its STS-99 mission, which was launched on February 11, 2000, and \ufb02ew for 11 days.  In addition to Terra Advanced Spaceborne Thermal and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) Version 3 data, NASADEM also relied on Ice, Cloud, and Land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) ground control points of its lidar shots to improve surface elevation measurements that led to improved geolocation accuracy.  Other reprocessing improvements include the conversion to geoid reference and the use of GDEMs and Advanced Land Observing Satellite Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) AW3D30 DEM, and interpolation for void filling.  NASADEM are distributed in 1 degree latitude by 1 degree longitude tiles and consist of all land between 60\u00b0 N and 56\u00b0 S latitude. This accounts for about 80% of Earth\u2019s total landmass.     NASADEM_SSP data product layers include radar total correlation, radar volumetric correlation, radar individual images, radar incidence angle (relative to ellipsoid), and radar incidence angle (local). A low-resolution browse image showing sub-swath elevation is also available for each NASADEM_SSP granule. ",
         "license": "proprietary"
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         "license": "proprietary"
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         "description": "This NASMo-TiAM (North America Soil Moisture Dataset Derived from Time-Specific Adaptable Machine Learning Models) dataset holds gridded estimates of surface soil moisture (0-5 cm depth) at a spatial resolution of 250 meters over 16-day intervals from mid-2002 to December 2020 for North America. The model employed Random Forests to downscale coarse-resolution soil moisture estimates (0.25 deg) from the European Space Agency Climate Change Initiative (ESA CCI) based on their correlation with a set of static (terrain parameters, bulk density) and dynamic covariates (Normalized Difference Vegetation Index, land surface temperature). NASMo-TiAM 250m predictions were evaluated through cross-validation with ESA CCI reference data and independent ground-truth validation using North American Soil Moisture Database (NASMD) records. The data are provided in cloud optimized GeoTIFF format.",
         "license": "proprietary"
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         "description": "This data set provides MODIS-derived surface biophysical climatologies of bidirectional distribution function  (BRDF), BDRF/albedo, land surface temperature (LST), leaf area index (LAI), and evapotranspiration (ET) as separate files for each of the MODIS land cover types, and four radiative forcing data files for four scenarios of potential vegetation shifts in North America. Each biophysical variable has temporal periods that represent the average of all 8-day periods from the years 2000-2012. The data have a spatial resolution of 0.05 degree (~5 km) and a temporal resolution of eight days. Additionally, a file containing diffuse fraction of surface downward solar radiation (DiffuseFraction) at a monthly scale, and a file containing snow water equivalent (SWE) are provided. The extent of the data covers the land area of North America, from 20 to 60 degrees N. The land-cover map used was synthesized from nine yearly 500-m MODIS land-cover layers (MCD12 Q1 Collection 5) for 2001-2008. These high-resolution land data were originally developed for quantifying biophysical forcing from land-use changes associated with forestry activities, such as radiative forcing from altered surface albedo. ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2556019064-ORNL_CLOUD.html",
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         "description": "This data set provides forest age map products at 1-km resolution for Canada and the United States (U.S.A.). These continental forest age maps were compiled from forest inventory data, historical fire data, optical satellite data, and the images from the NASA Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project. These input data products have various sources and creation dates as described in the source paper by Pan et al. (2011). Canadian maps were produced with data available through 2004 and U.S.A. maps with data available through 2006. A supplementary map of the standard deviations for age estimates was developed for quantifying uncertainty.Note that the Pan et al. (2011) paper is included as a companion file with this data set and was the source of descriptions in the guide.Forest age, implicitly reflecting the past disturbance legacy, is a simple and direct surrogate for the time since disturbance and may be used in various forest carbon analyses that concern the impact of disturbances. By combining geographic information about forest age with estimated carbon dynamics by forest type, it is possible to conduct a simple but powerful analysis of the net CO2 uptake by forests, and the potential for increasing (or decreasing) this rate as a result of direct human intervention in the disturbance/age status.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2539954386-ORNL_CLOUD.html",
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         "description": "The NBCD 2000 (National Biomass and Carbon Dataset for the Year 2000) data set provides a high-resolution (30 m) map of year-2000 baseline estimates of basal area-weighted canopy height, aboveground live dry biomass, and standing carbon stock for the conterminous United States. This data set distributes, for each of 66 map zones, a set of six raster files in GeoTIFF format. There is a detailed README companion file for each map zone. There is also an ArcGIS shapefile (mapping_zone_shapefile.shp) with the boundaries of all the map zones. A mosaic image of biomass at 240 m resolution for the whole conterminous U.S. is also included.Please read this important note regarding the differences of Version 2 from Version 1 of the NBCD 2000 data. With Version 1, in some mapping zones, certain land cover types (in particular Shrubs, NLCD Type 52) were missing from and unaccounted for in modeled estimates because of a lack of reference data. In Version 1, when landcover types were missing in the models, the model for the deciduous tree cover type was applied. While more woody vegetation was mapped, the authors think this had little effect on model performance as in most cases NLCD version 1 cover type was not a strong predictor of modeled estimates (See companion Mapping Zone Readme files). In Version 2, after renewed modeling efforts and user feedback, these previously unaccounted for cover types are now included in modeled estimates.All 66 mapping zones were updated with the previously unmapped land cover types now mapped. The authors recommend use of the new version for all analyses and will only support the updated version.Development of the data set used an empirical modeling approach that combined USDA Forest Service Forest Inventory and Analysis (FIA) data with high-resolution InSAR data acquired from the 2000 Shuttle Radar Topography Mission (SRTM) and optical remote sensing data acquired from the Landsat ETM+ sensor. Three-season Landsat ETM+ data were systematically compiled by the Multi-Resolution Land Characteristics Consortium (MRLC) between 1999 and 2002 for the entire U.S. and were the foundation for development of both the USGS National Land Cover Dataset 2001 (NLCD 2001) and the Landscape Fire and Resource Management Planning Tools Project (LANDFIRE). Products from both the NLCD 2001 (landcover and canopy density) and LANDFIRE (existing vegetation type) projects as well as topographic information from the USGS National Elevation Dataset (NED) were used within the NBCD 2000 project as spatial predictor layers for canopy height and biomass estimation. Forest survey data provided by the USDA Forest Service FIA program were made available to the project under a national Memorandum of Understanding. The response variables (canopy height and biomass) used in model development and validation were derived from the FIA database (FIADB). Production of the NLCD 2001 and LANDFIRE projects was based on a mapping zone approach in which the conterminous U.S. was split into 66 ecoregionally distinct mapping zones. This mapping zone approach was also adopted by the NBCD 2000 project. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781575223-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781575223-ORNL_CLOUD.html",
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         "description": "This data set provides classified land cover transition images (maps) derived from Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) imagery for Ariquemes, Luiza, and Ji-Paranao areas in Rondonia, Brazil, at 30-m resolution. Images depict the age relative to the year 2000, of cleared land from the date the land was cut, to the date when primary forests transitioned into nonforest class (for example,  25 = cut by 1975, or 25 years before the year 2000). Temporal changes in three regions are represented by 31 TM scenes acquired between 1984 and 1999, and a pair of MSS scenes from 1975 and 1978. Data are provided as three GeoTiff (*.tif) images, one for each of the three areas. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412277-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781412277-ORNL_CLOUD.html",
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         "description": "This data set provides a 27-year land cover time series of 28.5-m resolution products derived from Landsat images for 80% of Rondonia, Brazil, for the period 1984 to 2010. Selected Landsat Thematic Mapper (TM) and Landsat Multispectral Scanner (MSS) images from the years 1984 through 2010, for seven path/row scenes (PortoVelho, Ariquemes, Jiparana, Luiza (or Urupa), Cacoal, Chapuingaia, and Vilhena) were mosaicked for each year. Each mosaicked image was georectified and classified into seven land-cover classes--savanna/rock, pasture, secondary forest, primary forest, cloud, urban, or water. This 27-year time series allows the long-term assessment of land-cover variation across the state. There are 27 GeoTIFF image files (.tif) and one accompanying .xml file for each GeoTIFF file, compressed and available as *.zip files, one file for each year for the period 1984-2010, with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781624044-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781624044-ORNL_CLOUD.html",
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         "description": "This data set provides a time series of land cover classifications for Ariquemes, Ji-Parana, and Luiza, research sites in Rondonia, Brazil. The land cover classifications are derived from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) sensors.  The time period ranges from June 1975 through June 2000, but all areas do not have images for all the years. The images were classified into the following categories: 1. Primary upland forest, representing the dominant natural vegetation in the area; 2. Pasture and green pasture; 3. Second growth, dominated by small trees and shrubs with low species diversity and biomass relative to primary forest; 4. Soil/urban; 5. Rock/savanna; 6. Water;  and 7. Cloud and smoke obscured. In addition, areas covered by rock and savanna were mapped and all areas outside of the overlap zone between all dates within a scene, and scene edges, were masked.There are 75 GeoTIFF files (.tif) with this data set which includes: classified images (*ful.tif) and a corresponding image mask (*ful_mask .tif) for each date (with the exception of 1978 and 1996 images for Ji-Parana, for which there are only ful_mask.tif files), and three mask files for rock, savannah, and scene edges, for each area. By area, there are 31 images for Ariquemes, 23 images for Ji-Parana, and 21 images for Luiza. ",
         "license": "proprietary"
     },
@@ -140538,7 +140499,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781335068-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781335068-ORNL_CLOUD.html",
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         "description": "This data set provides soil physical and chemical properties, and grass nutrient measurements of samples collected from 17 pasture sites located within the state of Rondonia in the southwestern Brazilian Amazon. Soil data includes bulk density, class, texture, and measurements of carbon (C), phosphorus (P), calcium (Ca), magnesium (mg), and potassium (K) concentrations.  Foliar data includes nitrogen (N), P, Ca, Mg, and K concentrations.The 17 pasture sites were cattle ranches selected within the region between Porto Velho and Presidente Medici of Rondonia. Four of the ranches with Ultisols support dairy cattle, and the rest have beef cattle pastures dispersed across three soil orders: Oxisols, Ultisols, and Alfisols.  Nearby primary forest sites were also sampled to provide data on the original soil properties for each soil order. Soil samples were collected in May 2003, July through August 2003, and May 2004, which covered the late rainy season (May) and the dry season (July through August). Grass species sampled included Brachiaria brizantha, Brachiaria decumbens, B. brizantha, and Pennestum clandestinum, and represented three phenologically distinct grass materials: wet-season live grass, collected in May 2004, dry-season live grass and dry-season senesced grass, both collected between the end of July and the beginning of August 2003. There are 4 comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -140551,7 +140512,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781400518-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781400518-ORNL_CLOUD.html",
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         "description": "This data set provides the results of spectral reflectance (350 to 2,500 nm at 1-nm increments) and biophysical measurements on grass pastures in eight cattle ranches in the state of Rondonia, located in the southwestern Brazilian Amazon. The ranches are located near the cities of Porto Velho, Ariquemes, Ouro Preto, Ji-Parana, and Presidente Medici. Field measurements were collected in July and August 2003. The primary grass species sampled were Brachiaria brizantha and Brachiaria decumbens. Spectrometer measurements were taken at 5-m intervals along 100 m transects on the pastures - fourteen total transects. Vegetation was sampled at 20-m intervals along the transects. All standing biomass and litter on the soil surface were collected and separated into live and senesced biomass and then dried to calculate water content. Sixty-eight reflectance spectra coincided with grass biophysical samples.Note that the research was done on private lands in Rondonia, and to protect the privacy of those land owners no geographic information is associated with the reported measurements. Three data files are included: an ENVI spectral library file with reflectance data for 484 pasture sampling points, an ASCII comma-separated file with reflectance data for the 484 pasture sampling points, and an ASCII comma-separated file with the biophysical measurements.",
         "license": "proprietary"
     },
@@ -140564,7 +140525,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781593932-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781593932-ORNL_CLOUD.html",
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         "description": "This data set provides a time series of Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) scenes for five (Path/Row) areas in Rondonia, Brazil. The scenes are from the period June 1975 through June 2000, but all areas do not have scenes for all the years. The areas and Landsat Path/Rows included are as follows: Ariquemes (P232,R67), Ji-Parana (P231, R67), Luiza (P231, R68), Cacoal (P230, R68), and Porto Velho (P232, R66). TM images are available for all five areas. Because of a paucity of digital Landsat MSS imagery from the 1970s, only two scenes could be included, a 1975 scene from Ariquemes and a 1978 scene from Ji-Parana. Each of the Landsat scenes has been coregistered to a Path/Row-specific georectified PRODES Landsat file obtained from the Brazilian Government's National Institute for Space Research (INPE) program. For each scene, the coregistration is accurate to within (plus or minus)1 pixel (30-m Landsat resolution) in most places. The five INPE PRODES Landsat scenes used in the georectification process are included with this data set. There are five compressed files (tar.gz format) with this data set. When expanded, each compressed file (which corresponds to one of the five areas) contains a directory for each scene with GeoTIFF files for individual Landsat bands, a text file of tie points, and another text file of slope and intercept values for converting radiance to reflectance. There are two dates for Landsat MSS scenes, 45 dates for TM scenes, and six dates for ETM+ scenes.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781581040-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781581040-ORNL_CLOUD.html",
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         "description": "This data set provides fractional land cover type images for shade, green vegetation (GV), non-photosynthetic vegetation (NPV), and soil for the regions of JiParana, PortoVelho, Luiza, Ariquemes, and Cacoal in the state of Rondonia, Brazil, for the period 1984 to 2000. The images were derived with a spectral mixture analysis (SMA) of Landsat Thematic Mapper (TM) time series scenes for each of these areas. There were 249 TM scenes and one Landsat Multispectral Scanner (MSS) scene acquired for these analyses. The images are 30-m Landsat resolution and were georectified to the Brazilian space agency 1998 and 1999 PRODES imagery. There are 250 GeoTIIF image files (*.tif) in this data set. Files are grouped by region and year/month/day scene was taken. ",
         "license": "proprietary"
     },
@@ -140590,7 +140551,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780920003-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780920003-ORNL_CLOUD.html",
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         "description": "This data set provides the results of (1) synoptic streamwater sampling and analyses from numerous sites across Rondonia and (2) corresponding watershed characteristics derived from remote sensing and historical/available data sources. Sixty streams, in both forested and non-forested sites, were sampled once during the dry season in August of 1998 and 49 of the same streams were sampled again during the wet season in January-February of 1999. Analyses included sodium (Na), calcium (Ca), magnesium (Mg), potassium (K), silica (Si), chloride (Cl), sulfate, pH, and acid neutralizing capacity. Watershed characteristics, including soil cation content, pH, watershed lithology, area, percent deforested, and urban watershed population density, were derived and calculated from digitized soil maps and available soil profile analyses, digitized topographic maps, land use mosaics from Landsat Thematic Mapper (TM) images, and Brazilian census data. The objective of the study was to determine the relative influence of watershed soil exchangeable cation content, rock type, deforestation, and urban population density on stream concentrations of base cations, dissolved silicon, chloride and sulfate in both the dry and wet seasons in a humid tropical region undergoing regional land use transformation. There are three comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -140603,7 +140564,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781406353-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781406353-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of watershed deforestation, as a proportion of the total area of watersheds, in Rondonia, Brazil for 1999. Deforestation maps were determined for the main agricultural and surrounding forested areas of Rondonia using multiple Landsat TM scenes (Biggs et al. 2008). Cumulative deforestation estimates were derived from this time series of Landsat scenes from 1975 to 1999. To obtain watershed-level estimates of deforestation, watershed boundaries and stream networks were delineated by a flow accumulation algorithm using a 90-m resolution digital elevation model (DEM) from NASA's Shuttle Radar Topography Mission (SRTM). The results were watersheds of seven Strahler stream orders (1-7) with stream networks that closely matched those of the 1:100,000 topographic maps for the area. The watershed boundaries, classified by stream order, were overlain on the time series of deforestation maps to determine the cumulative deforestation extent in 1999. This data set contains six ESRI ArcGIS shapefiles of the watershed boundaries for streams orders 2-7, the smallest watershed (second order) to the largest inclusive watershed (seventh order). The cumulative deforestation estimates, as a proportion of total area for each watershed, are available as a comma-delimited text file that can be related to the individual watershed boundary shapefiles. Cumulative deforestation data are available for first order streams, although not as a shapefile. There are six zipped ESRI ArcGIS shapefiles (*.zip) and one ASCII comma separated file with this data set.",
         "license": "proprietary"
     },
@@ -140616,7 +140577,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777783116-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777783116-ORNL_CLOUD.html",
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         "description": "This data set contains soil emissions of nitric oxide (NO), carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) measured in plots of a secondary-growth forest fertilization experiment located 6.5-km northwest of the town of Paragominas, Para, Brazil during 1999-2001. Control, pre-, and post-treatment plot trace gas emission results are reported in a single comma-separated file.A highly degraded former pasture with secondary-growth forest (capoeira -- fallow vegetation) at Fazenda Vitoria, 6.5-km northwest of the town of Paragominas, Para, was chosen for this fertilization experiment. Twelve 20m x 20m plots were established: three were fertilized with nitrogen (only), three were fertilized with phosphorus (only), and three were fertilized with both nitrogen and phosphorus. The remaining three plots served as the control for these treatments. Application of the fertilizers occurred Jan 19, 2000 and February 2001, at the beginning of the rainy season. ",
         "license": "proprietary"
     },
@@ -140629,7 +140590,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781403604-ORNL_CLOUD.html",
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         "description": "This data set provides Landsat images of the county of Sao Francisco do Para located in the Bragantina region of Para, Brazil, the oldest agriculture frontier in Amazonia. These images are subsets for the municipio (county) and immediate region. There are seven GeoTIFF files (.tif) with this data set which includes two for July 24, 1984 multispectral scanner (MSS), one for June 21, 1994 thematic mapper Landsat 5 (TM5),  three for July 13, 1999 thematic mapper Landsat 7 (TM7), and one TM for June 21, 1994.",
         "license": "proprietary"
     },
@@ -140642,7 +140603,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777777771-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777777771-ORNL_CLOUD.html",
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         "description": "This data set reports the results of a study to measure soil emissions of the carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), and nitric oxide (NO) throughout an entire cropping cycle in (1) slash-and-burn and (2) chop-and-mulch prepared agricultural fields from 2001-2004.  An adjacent 15-year-old fallow field with secondary forest vegetation served as the control.  The study site is within the municipality of Igarape Acu, Para, Brazil, at the Experimental Farm of the Federal Rural University of Amazonia. Flux data are reported in one comma-separated file.",
         "license": "proprietary"
     },
@@ -140655,7 +140616,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780910985-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780910985-ORNL_CLOUD.html",
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         "description": "This data set reports biomass from small stems and non-woody vegetation measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment. The study location was Fazenda Vitoria, 6.5-km northwest of the town of Paragominas, Para, Brazil, in a 6-year old secondary-growth forest. Vegetation life-forms with diameters less than or equal to 2 cm (grasses, herbs, vines and dead material) were destructively sampled in November 1999, June 2000, June 2001, July 2003, July 2004, and July 2005. All data are provided in a single comma-separated file. The site was divided into three blocks with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea), three were fertilized with phosphorus (50 kg P/ha as superphosphate), three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control.",
         "license": "proprietary"
     },
@@ -140668,7 +140629,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742781-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742781-ORNL_CLOUD.html",
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         "description": "This data set reports monthly measured soil volumetric water content (VWC) from a rainfall exclusion experiment that was conducted from 1999-2001 at the km 67 Seca Floresta site, Tapajos National Forest, Brazil. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002). There are two ASCII comma delimited files with measured VWC, one for the control plot and one for the rainfall exclusion plot.These measured values were used by the authors to develop a model of daily changes in the distribution of water through the soil layers. The simulated daily VWC values are also provided in the file with the measured VWC. For comparison, results of VWC simulation for the control and treatment plots using a STELLA model which incorporates rainfall and plant water uptake are provided. There are two ASCII comma delimited files of simulated results. See Belk et. al., 2007 for details.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777785283-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777785283-ORNL_CLOUD.html",
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         "description": "This data set reports the results of a rainfall exclusion experiment in the Tapajos National Forest (Flona-Tapajos) at km 67 along the Santarem-Cuiaba BR-163 highway. From December 1999 through April 2005, following a one-year pre-treatment phase, rainfall was excluded from one of two 1-hectare plots of seasonally dry humid tropical forest. Soil emissions of carbon dioxide (CO2), nitric oxide (NO), nitrous oxide (N2O), and methane (CH4) were monitored in order to determine the likely effect of increasingly frequent El Nino drought episodes in the Amazon basin. Soil trace gas flux data are provided in one comma-separated data file.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780107886-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780107886-ORNL_CLOUD.html",
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         "description": "This data set provides a time series of calcium, magnesium, and potassium extracted from soil samples from a laboratory column extraction study conducted in 2002. Soils used in the columns were originally collected in 1998 in Fazenda Vitoria, a cattle ranch 6 km north of the town of Paragominas, Para, Brazil. The soils were from contrasting land uses of primary forest (mata), secondary forest (capoeira), or pasture (pasto). Water equilibrated with increasing concentrations of CO2 was used to extract cations from the soil columns. Data represent the time series of cation concentrations in the extract solutions as well as the total content of cations removed from the soils. There is one comma-delimited ASCII file with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780104163-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780104163-ORNL_CLOUD.html",
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         "description": "This data set reports soil CO2 flux and results of physical and chemical characterization of soils from pastures, secondary forests, and mature forests near Rio Branco, Acre, Brazil. CO2 flux measurements were made in the field on a monthly basis at 16 sites from June of 1999 to January 2001. In addition, litter was collected monthly from 2001-2002 at each of the mature forest sites and at 4 of the secondary forest sites, and mean litter mass is reported. Soil samples were collected and analyzed from several land cover types at two sites during this same time period. There are four comma-delimited ASCII data files with this data set.",
         "license": "proprietary"
     },
@@ -140720,7 +140681,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777782798-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777782798-ORNL_CLOUD.html",
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         "description": "This data set reports the results of a study to quantify the effects of moisture and substrate availability on soil trace gas fluxes in a regrowth forest in Eastern Amazonia, Apeu, Para, Brazil, from 1999-2003. The efflux of carbon dioxide (CO2), nitric oxide (NO), nitrous oxide (N2O), and methane (CH4) from soil was measured as a response to (1) increased soil moisture availability during the dry season by irrigation and (2) decreased substrate availability by continuous removal of aboveground litter and compared to (3) untreated control plots. Soil gas fluxes are reported in one comma-separated data file.",
         "license": "proprietary"
     },
@@ -140733,7 +140694,7 @@
         "bbox": "-55, -2.75, -55, -2.75",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780918831-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780918831-ORNL_CLOUD.html",
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         "description": "This data set reports soil carbon dioxide (CO2) and nitrous oxide (N2O) concentrations and soil volumetric water content (VWC) from a rainfall exclusion experiment that was conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil. Samples were collected every two to three months. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad 2002).Data provided are from December 9, 1999, and April 2, 2000-June 14, 2002. There is one comma-delimited data file with this data set.  ",
         "license": "proprietary"
     },
@@ -140746,7 +140707,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784836843-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784836843-ORNL_CLOUD.html",
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         "description": "This data set reports field estimated saturated hydraulic conductivity measurements from June 12 through June 20, 2001. This study was part of a rainfall exclusion experiment that was conducted from 1999-2001 at the km 67 Seca Floresta site, Tapajos National Forest, Para, Brazil. The objective of this component of the study was to develop an understanding of the physical processes driving the observed soil water dynamics at the site. There is one comma-delimited ASCII data file with this data set.",
         "license": "proprietary"
     },
@@ -140759,7 +140720,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777778341-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777778341-ORNL_CLOUD.html",
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         "description": "This data set provides tree diameters and heights measured from 1999 to 2005 in plots of a secondary-growth forest fertilization experiment located 6.5-km northwest of the town of Paragominas, Para, Brazil. In the 6-year old secondary-growth forest, all trees greater than 2 cm diameter at breast height (DBH) were tagged, identified, and measured for diameter and height in November 1999. Fertilizer was applied to selected plots in January 2000 and February 2001. Tree heights and diameters were remeasured in May 2000, June 2001, July 2002, July 2004, and July 2005. All data are provided in a single comma-separated file.The site was divided into three blocks, with four treatment plots (each 20m x 20m) located in each block (3 reps x 4 treatments = 12 plots). Three of the twelve plots were fertilized with nitrogen (100 kg N/ha as urea); three were fertilized with phosphorus (50 kg P/ha as superphosphate); three were fertilized with both nitrogen and phosphorus. The remaining three plots were not fertilized and served as the experimental control..",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784836379-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784836379-ORNL_CLOUD.html",
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         "description": "This data set includes measurements of dissolved nutrient and organic carbon concentrations, as well as dissolved oxygen, alkalinity, conductivity, turbidity, pH, and discharge from three streams located in mixed land use (crop fields, pastures, secondary vegetation, and forest) and two streams in entirely forested landscapes near Paragominas in the state of Para, Brazil. Stream water samples were collected during two different periods: 1) weekly from August 1999 to July 2001 at location Igarape 54, Station 5 and 2) monthly from April 2003 through October 2005 at all of the stations. The exact start date and suite of measurements vary by location. In addition, samples from precipitation collectors at the Paragominas Meteorological Station were measured for nutrient concentrations every two weeks from 1999 to 2001. There are two comma delimited ASCII data files with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780108110-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780108110-ORNL_CLOUD.html",
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         "description": "This data set consists of water chemistry data from streams, wells, rainwater, and canopy throughfall samples. The field measurements were carried out at Rancho Grande in the Brazilian state of Rondonia, in the southwestern Brazilian Amazon basin, at two adjacent watersheds, a forest (1.37 ha), and pasture (0.73 ha). Samples were collected during one entire rainy season starting in August 2004 and ending in April 2005. There is one comma-delimited data file with this data set.Ridge, Tennessee, U.S.A.",
         "license": "proprietary"
     },
@@ -140798,7 +140759,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780901460-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780901460-ORNL_CLOUD.html",
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         "description": "This data set provides the results of (1) the physical and chemical characterization of streams and (2) comparable chemical analyses of extracted soil water in the Aldeia River basin at Fazenda Nova Vida, a large cattle ranch 50 km from the city of Ariquemes, in central Rondonia, Brazil, from 1994-2001. Data are provided on the stream beds including cross-sectional depth and stream bed surface type. Stream discharge is reported. Streamwater was sampled and analyzed periodically over the eight year duration of the study at numerous steam locations. Soil solution samples were collected at the same frequency with lysimeters placed at 30 cm and 100 cm depths on the floodplain and at upland forest and pasture sites in the Aldeia River watershed. There are five comma-delimited data files in this data set. ",
         "license": "proprietary"
     },
@@ -140811,7 +140772,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804827524-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804827524-ORNL_CLOUD.html",
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         "description": "This data set reports the carbon and nutrient stocks of above-ground vegetation and soil pools at three locations where post-pasture secondary forest recovery ranged from 0 to 14 years since abandonment. These sites are located in the state of Amazonas, Brazil, along the road BR-174 north of the city of Manaus within three fazendas (cattle ranches) now in various stages of grazing, pasture abandonment, or pasture reclamation: Fazenda Rodao (km 46), Embrapa-District of SUFRAMA (DAS) pasture research site (km 53) and Fazenda Dimona (km 72). From September 2000 to July 2001, measurements were obtained for aboveground biomass (cite ND-04 Sec For Recovery), foliage and wood samples were collected and analyzed for total nutrient (C, N, P, K, Ca and Mg) concentrations, and soil samples from 0 to 45 cm depth were collected and analyzed for total nutrient (C, N, P, K, Ca and Mg) concentrations. Total carbon (C) and nutrient stocks were calculated for various vegetation and soil pools to gain an understanding of the dynamics of nutrient and C buildup in regenerating secondary forests in central Amazonia (Feldpausch et al., 2004). There are 2 comma-delimited ASCII data files with this data set.",
         "license": "proprietary"
     },
@@ -140824,7 +140785,7 @@
         "bbox": "-60.03, -2.57, -59, -2",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804826978-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804826978-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND04_Secondary_Forest_Recovery_1068_1",
         "description": "This data set reports measurements of the canopy and structure of secondary forests regenerating from abandoned pastures. These secondary forests are located in the state of Amazonas, Brazil, along the road BR-174 north of the city of Manaus within three fazendas (cattle ranches) now in various stages of grazing, pasture abandonment, or pasture reclamation: Fazenda Rodao (km 46), Embrapa-District of SUFRAMA (DAS) pasture research site (km 53), and Fazenda Dimona (km 72). Ten secondary forest study sites were selected within the three fazendas where post-pasture forest recovery ranged from 0 to 14 years since abandonment.From 2000-2001 estimates of leaf area index (LAI) and canopy cover were derived from hemispherical canopy digital photographs, and estimates of aboveground biomass and basal area were derived utilizing allometric equations from diameter at breast height (DBH) measurements. Estimates were classified by growth-form and diameter class. See Feldpausch et al. (2005) for more information. There are four comma-delimited data files with this data set and one companion file with information regarding the allometric equations relating diameter at breast height (for dbh > 5 cm) to dry weight for biomass calculations. ",
         "license": "proprietary"
     },
@@ -140837,7 +140798,7 @@
         "bbox": "-60.03, -2.52, -60.03, -2.52",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781618453-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781618453-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND04_Soil_H2O_Manaus_1246_1",
         "description": "This data set contains soil water measurements to a depth of 3 meters for the years 1999, 2000, and 2001, and total monthly precipitation data for 1999-2000. The data were collected from a pasture site located at the Embrapa Pasture Research Site, a former cattle research station 54 km north of Manaus on the highway BR 174 Manaus-Boa Vista, Brazil. There are three comma-separated data files (.csv) with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS: There is no associated research documentation and the units were not provided with the data. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780106713-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780106713-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND04_Termite_Mounds_1072_1",
         "description": "This data set reports the results of a comprehensive study of mound building termites at the Embrapa research station in the Distrito Agropecuario da SUFRAMA, located at km 53 of the federal highway BR 174 outside Manaus, Amazonas, Brazil. Study areas included a primary forest site, an adjacent 7-8 year old secondary forest site, and two abandoned pasture sites which were being used for agroforest purposes.Reported are (1) the termite species occurrence and areal abundance of mounds, (2) characterization of the mound soil microbiological community, root biomass, seedling emergence success, soil respiration, nitrogen mineralization, and (3) the characterization of the termite mound soil physical, chemical, and hydraulic properties. Analyses were also performed on samples from adjacent control soils for comparison. This data set contains 15 comma-delimited data files.",
         "license": "proprietary"
     },
@@ -140863,7 +140824,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780960821-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780960821-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND06_LandUse_Studies_1130_1",
         "description": "This data set provides measurements of soil properties compiled from 39 studies on nutrient dynamics in natural forests and forest-derived land uses (pasture, shifting cultivation and tree plantations) conducted in Amazonia over the period of 1950-2001. The initial literature survey for the data consisted of more than 100 studies conducted during this period.The objectives of this project were to compare soil data from major land uses across Amazonia and identify gaps in present knowledge that offer direction for future research. Five widely cited hypotheses were tested concerning the effects of land-use change on soil properties by analyzing data compiled from 39 studies in multi-factorial ANOVA models:-- effective cation exchange capacity (ECEC), and exchangeable calcium (Ca) concentrations rise and remain elevated following the slash-and-burn conversion of forest to pasture or crop fields soil contents of total carbon (C), nitrogen (N), and inorganic readily (i.e., Bray, Mehlich I or resin) extractable phosphorus (Pi) decline following forest-to-pasture conversion-- soil concentrations of total C, N, and Pi increase in secondary forests with time since abandonment from agricultural activities-- soil nutrient conditions under all tree-dominated land-use systems (natural or not) remain the same-- higher efficiencies of nutrient utilization occur where soil nutrient pools are lower There is one comma-delimited ASCII file (.csv) with this data set and a list of the 39 studies used in this data set provided as a companion file in text format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780940083-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780940083-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND07_15N_Leaves_Soils_1121_1",
         "description": "This data set provides (1) delta 15N ratios and nitrogen concentrations for foliar samples and (2) delta 13C and delta 15N ratios as well as carbon and nitrogen concentrations for soil samples collected from cerrado sites within the Ecological Reserve of the Brazilian Institute of Geography and Statistic (IBGE), Brasilia, Brazil. Foliar samples, collected from 320 individuals representing 45 woody tree and shrub species, and soil samples were collected from 5 cerrado locations (2 in campo sujo, 2 in cerrado denso and 1 in cerrado). Soil samples were collected to 450 cm depth in the campo sujo and 800 cm depth elsewhere. Samples were collected during the period December 1999 to September 2000.  Eiten (1972) described campo sujo as an open savanna with scattered trees and shrubs, cerrado sensu stricto as a savanna woodland with abundant evergreen and deciduous trees and shrubs and an herbaceous understory, and cerrado denso as medium to tall woodlands with closed or semiclosed canopies (Bustamante et al., 2004).There are two comma-delimited data files with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780948560-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780948560-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND07_NO_Flux_Cerrado_1124_1",
         "description": "This data set reports the results of soil nitric oxide (NO) flux, soil moisture, and soil nitrate (NO3) and ammonium (NH4) concentration measurements on Cerrado soils receiving nitrogen fertilization. Measurements and samples were collected from control and fertillized experimental plots on Cerrado soils within the Ecological Reserve of the Brazilian Institute of Geography and Statistic (IBGE), Brasilia, Brazil. Sampling dates were from March 26, 2004 to November 25, 2004. The soils had received nitrogen and phosphorus fertilization treatments which began in 1998. The objective of this project was to determine the long-term effects of nutrient addition (N and N+P) in native Cerrado area on N oxide fluxes from soil to the atmosphere. There is one comma delimited (.csv) ASCII file with this data set.",
         "license": "proprietary"
     },
@@ -140902,7 +140863,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835087-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784835087-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND07_PLFA_Soils_Microbial_Biomass_1017_1",
         "description": "This data set reports the microbial biomass in soil samples collected from the Cerrado, a woodlands-savannah area, in Brasilia, Brazil. Microbial biomass was determined as the total concentration of phospholipid fatty acids (PLFAs). Soil samples (0-5 cm) were collected from June, 2000 to June, 2001 in two native areas of Cerrado that were subjected to a range of fire regimes. Two plots were protected from fire since 1973, another two plots were subjected to prescribed fires every two years since 1992, and a fifth plot was in a 20 year-old active pasture (Brachiaria brizantha). The analyses were conducted to determine the effects of fire regimes and changes in vegetation cover on the microbial communities of Cerrada soils. There is one comma-separated ASCII data file with this data set. ",
         "license": "proprietary"
     },
@@ -140915,7 +140876,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777842574-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777842574-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0wMiBzb2lsIHRyYWNlIGdhcyBmbHV4ZXMgaW4gZWFzdGVybiBhbWF6b25pYSwgcGFyYSwgYnJhemlsOiAxOTk5LTIwMDNcIixcIk9STkxfQ0xPVURcIixcIk5EMDJfU29pbF9HYXNfRmx1eF9BcGV1Xzk1M1wiLFwiMVwiLDI3Nzc3ODI3OTgsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTAyIHNvaWwgdHJhY2UgZ2FzIGZsdXhlcyBpbiBlYXN0ZXJuIGFtYXpvbmlhLCBwYXJhLCBicmF6aWw6IDE5OTktMjAwM1wiLFwiT1JOTF9DTE9VRFwiLFwiTkQwMl9Tb2lsX0dhc19GbHV4X0FwZXVfOTUzXCIsXCIxXCIsMjc3Nzc4Mjc5OCwyXSJ9/ND07_Stream_Chemistry_Brasilia_1018_1",
         "description": "This data set reports on dissolved nutrient concentrations, as well as dissolved oxygen, alkalinity, conductivity, turbidity, and pH measured in water samples collected from nine streams located in the state of Brasilia, Brazil, between September, 2004 and December, 2006. Streams were located in different land cover types including natural (forest), rural (agricultural), and developed landscapes. In addition, water samples from wells, lysimeters, surface runoff, and precipitation were collected from four sites, 2 natural and 2 rural, and analyzed for nutrient concentrations. Streams were sampled every 2-4 weeks; rain water was collected approximately monthly during the wet season and once during a dry season; wells and lysimeters were sampled monthly; and surface runoff collections were event based. There are three comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -140928,7 +140889,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777841094-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777841094-ORNL_CLOUD.html",
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         "description": "This data set reports on soil-atmosphere fluxes of trace carbon dioxide, carbon monoxide, nitrous oxide, and nitric oxide (CO2, CO, N2O, NO) under various natural and manipulated land use conditions. The studies were conducted near Brasilia, Brazil in pastures and agricultural areas under a variety of management regimes and in more natural areas of cerrado (20-50% canopy cover) and campo sujo (open, grass-dominated), which were either burned every 2 years or protected from fire. Results provide data and relationships needed for regional trace gas models. There are nine comma-separated ASCII data files with this data set.",
         "license": "proprietary"
     },
@@ -140941,7 +140902,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781391653-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781391653-ORNL_CLOUD.html",
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         "description": "This data set reports the concentrations of the nutrients nitrogen (N), phosphorus (P), magnesium (Mg), calcium (Ca), and potassium (K) in roots, litterfall, leaves, and twigs, biomass of fine roots and litterfall, and the decomposition of leaves and twigs in samples that were collected on the property of Jari Celulose, Monte Dourado, Para, Brazil, from 1999-2001.Samples were collected from two study sites, a eucalyptus plantation and an adjacent primary forest, during both rainy and dry seasons. Roots were sampled from three depths (0-15 cm, 35-50 cm, and 85-100 cm).There are five comma-delimited data files with this data set.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.KNOWN PROBLEMS: The data files do not identify the year in which samples were collected. The methods for nutrient, decomposition, and biomass sampling and analyses were not provided. The data file descriptions indicate that samples were collected from two soil types (sandy and clay) but there is no documentation of which data field provides that information. Also, there is no documentation for the Location or Block fields in the data files.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781620134-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781620134-ORNL_CLOUD.html",
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         "description": "This data set provides (1) carbon (C) and nitrogen (N) concentration measurements of two soil aggregate fractions (250-2000 micon, small macro-aggregates (SMAG)), and (53-250 micron (micro-aggregates (mico)) and (2) in situ soil respiration measurements (January-March 2003) on sand and clay soils from a Eucalyptus plantation and an adjacent primary forest. The soils for fractionation were sampled in July 2001 from 0-20 cm and 30-50 cm depths. The research site was on the property of Jari Celulose, Monte Dourado, Para, Brazil. There are two files with this data set in comma-delimited (.csv) format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781558603-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781558603-ORNL_CLOUD.html",
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         "description": "This data set provides the results of soil physical property and chemical measurements of samples collected from two pasture chronosequences (years since conversion from primary forest) located on two ranches south of Santarem, Para, Brazil, and east of the Tapajos River. Soil data includes soil classification, bulk density, texture, and mean concentrations of total nitrogen (N), carbon (C), phosphorus (P), and P fractions. The soils were high clay oxisols and highly sandy entisols.One chronosequence of sites was established on oxisol soils dating 2, 7, and 15 years since conversion from primary forest. A second set of sites, 1, 7, and 15 years old was established on the sandy entisols. Five of the six pasture sites were on a single ranch; the 2-year-old oxisol pasture was the exception. Ten soil samples per site were collected from 0-10 cm depth along random intervals within 100-m transects in August 1997.There are two comma-delimited (.csv) data files with this data set.",
         "license": "proprietary"
     },
@@ -140980,7 +140941,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777410780-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777410780-ORNL_CLOUD.html",
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         "description": "This data set contains stream water exports of coarse particulate organic matter (CPOM) and coarse particulate organic carbon (CPOC) during 2003-2004 from four forested headwater streams near Juruena, Mato Grosso, Brazil (Selva et al. (2007) and Johnson et al. (2006) . Data are reported in a single comma-separated ASCII  file as watershed exports in mass units, carbon content, and watershed exports per watershed area over the reported sampling intervals.Resolving the carbon balance in the Amazonian forest depends on an improved quantification of production and losses of particulate C from forested landscapes via stream export. The export of coarse organic particulate matter (>2 mm) was quantified for one year in four small watersheds (1-2 ha) under native forest in southern Amazonia near Juruena, Mato Grosso, Brazil. Stream-water exports of particulate C were positively correlated with stream flow, increasing in the rainiest months. The export of particulate C in stream flow was found to be a small (less than 1%) percentage of the amount of litterfall produced. ",
         "license": "proprietary"
     },
@@ -140993,7 +140954,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777814121-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777814121-ORNL_CLOUD.html",
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         "description": "Data were collected in the logging concession at the Fazenda Rohsamar in the municipality of Juruena in northwestern Mato Grosso.  Estimates of damage associated with logging operations were made after logging operations were complete in 2003 and 2004. Damage associated with gaps created by felling single trees was estimated in 54 individual gaps. Characteristics of the single harvested tree were recorded and included species, DBH, commercial height, total height, and canopy proportions.  Damage to all surrounding trees was recorded. Stratified transects in two logging blocks were used to estimate damage associated with road building and skid trails. Twenty-six transects were established in Block 5 and 21 transects in Block 18 to assess the frequency of damage by log skidders and tree felling. The boundaries between different types of damage were noted along the transect  and the length in meters of that damage type along the transect was recorded. From this information, the area of the logging block affected by road building and skid trails was determined.The Gap Survey and the Logging Damage Transects Survey data are provided in comma-separated ASCII files. A third file provides the coordinates of the starting points for the Survey Transects.  ",
         "license": "proprietary"
     },
@@ -141006,7 +140967,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834826-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834826-ORNL_CLOUD.html",
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         "description": "This data set contains the results of an experiment to determine litter decomposition and dynamics of carbon and nitrogen release from plant litter of differing qualities which occur in combination in agroforestry systems. Reported in five ASCII files are (1) the initial values of soil and plant litter macronutrients, nitrogen; and carbon contents; (2) descriptions of the various experimental treatments; and (3) the final nitrogen and carbon composition of the plant litter and soil and calculated releases from the litter.The study was conducted at the Empresa Brasileira de Pesquisa Agropecuaria-Centro da Pesquisa Agroflorestal (EMBRAPA-CPAA) experimental station located north of Manaus on the BR 174 highway in the central Amazon Basin. The experimental plot, located in an open grassy field, was selected based on low, homogeneous soil C and nutrient contents, minimal prior disturbance, and no previous fertilizer application. The soil was a degraded typic Hapludox with the following soil properties for the upper 0-3 cm: pH in water of 5.05, 1.3 mg N/g, 18.0 mg C/g (automatic CN Analyzer, Elementar), 2.05 mg P/kg, 55.0 mg K/kg (Mehlich-1 extractable), 11.7 mg Ca/kg, and 4.6 mg Mg/kg (KCl extractable). The experiment was conducted in the field in small plots with treatments that vary in the ratio of plant litter of two plants: gliricidia (Gliricidia sepium (Jacq.) Kunth. ex Walp.) and cupuacu (Theobroma grandiflorum). Soil and litter samples were collected prior to and during the experiment. Resin bags were used to retain mineral nitrogen released from the plant litter.",
         "license": "proprietary"
     },
@@ -141019,7 +140980,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777794683-ORNL_CLOUD.html",
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         "description": "This data set reports the results of field surveys to determine: regeneration diversity and size distribution of plants in primary undisturbed forest; and  regeneration diversity and size distribution of trees in a one hundred hectare block, six years after reduced impact logging treatment (vine removal) was applied in 1998.  In addition, wood density and carbon concentrations in commercially harvested species are reported.  All surveys were performed in 2003 and 2004 within block 5 of the logging concession at the Fazenda Rohsamar in the municipality of Jurena in northwestern Mato Grosso, Brazil. The data are reported in three comma separated files.",
         "license": "proprietary"
     },
@@ -141032,7 +140993,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777812410-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777812410-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0xMSBmb3Jlc3QgZGFtYWdlIGZvbGxvd2luZyByZWR1Y2VkIGltcGFjdCBsb2dnaW5nLCBudyBtYXRvIGdyb3NzbywgYnJhemlsXCIsXCJPUk5MX0NMT1VEXCIsXCJORDExX0xvZ2dpbmdfRGFtYWdlX01UXzk3N1wiLFwiMVwiLDI3Nzc4MTQxMjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTExIGZvcmVzdCBkYW1hZ2UgZm9sbG93aW5nIHJlZHVjZWQgaW1wYWN0IGxvZ2dpbmcsIG53IG1hdG8gZ3Jvc3NvLCBicmF6aWxcIixcIk9STkxfQ0xPVURcIixcIk5EMTFfTG9nZ2luZ19EYW1hZ2VfTVRfOTc3XCIsXCIxXCIsMjc3NzgxNDEyMSwyXSJ9/ND11_Soil_Nitrate_Moisture_MT_976_1",
         "description": "This data set reports the results of the analysis of soil samples for Nitrate (NO3) and physical properties that were collected for one year following reduced impact logging in logging concessions at the Fazenda Rohsamar in the municipality of Juruena in northwestern Mato Grosso. Sample locations were randomly selected from stratified regions of the 1,400 ha Block 5 to account for local scale soil variability. Soil samples were collected to 8-m depth in (1) nine gaps formed by single tree removal and (2) nine areas of undisturbed primary forest. Areas of undisturbed forest were confined to patches of forest within Block 5 that were protected from logging.  An additional 3 forested areas were sampled to 3-m depth that contained high sand content. These results quantified the effects of reduced impact logging, to test whether nitrogen (N) loss from leaves and coarse woody debris under reduced impact logging results in a significant accumulation of subsoil nitrate (Feldpausch et al., 2009). One comma separated data file contains the soil moisture results and a second file the soil NO3 content and soil physical properties.",
         "license": "proprietary"
     },
@@ -141045,7 +141006,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777411496-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777411496-ORNL_CLOUD.html",
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         "description": "The results of the analysis of soil chemical parameters, texture, and color are reported for 185 georeferenced soil profile sample points over four forested headwater catchments near Juruena, Mato Grosso, Brazil (Novaes Filho, et al., 2007a and Novaes Filho, et al., 2007b). Samples were collected from an approximately 20 x 20 m grid over each watershed from 2004/05/01 to 2004/08/18. By sampling each location at depths of 0-20 and 40-60 cm it was possible to distinguish and map the principle soil classes found in the study area to the 2nd category level of the Brazilian System of Soil Classification (Cooper et al., 2005) associated with the topographic relief. The data set contains one comma separated ASCII data file with spatially referenced soil nutrient and organic carbon data from 0-20 cm (A layer, topsoil) and 40-60 cm (B layer, subsoil)depths for the Juruena watersheds study area.A satisfactory relationship between the redness index of the diagnostic horizons and the soil class colors was also found. In spite of the apparent homogeneity of the visible landscape characteristics such as slope, soil color, and vegetation, the carbon and soil clay attributes were found to vary greatly. This variability over small distances demonstrates that extrapolation of soil characteristics and soil carbon stocks to larger areas could produce erroneous results if the spatial variability of the soil attributes is not taken into consideration.",
         "license": "proprietary"
     },
@@ -141058,7 +141019,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777338780-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777338780-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0xMSBmb3Jlc3QgZGFtYWdlIGZvbGxvd2luZyByZWR1Y2VkIGltcGFjdCBsb2dnaW5nLCBudyBtYXRvIGdyb3NzbywgYnJhemlsXCIsXCJPUk5MX0NMT1VEXCIsXCJORDExX0xvZ2dpbmdfRGFtYWdlX01UXzk3N1wiLFwiMVwiLDI3Nzc4MTQxMjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTExIGZvcmVzdCBkYW1hZ2UgZm9sbG93aW5nIHJlZHVjZWQgaW1wYWN0IGxvZ2dpbmcsIG53IG1hdG8gZ3Jvc3NvLCBicmF6aWxcIixcIk9STkxfQ0xPVURcIixcIk5EMTFfTG9nZ2luZ19EYW1hZ2VfTVRfOTc3XCIsXCIxXCIsMjc3NzgxNDEyMSwyXSJ9/ND11_Soil_Water_Pressure_851_1",
         "description": "This data set contains information that can be used to examine water fluxes in soils beneath tree crops in an Amazonian agroforest. The data consists of repeated measurements of soil matrix pressure and soil moisture content at several depths. The study was carried out at the Empresa Brasileira de Pesquisa Agropecuaria (Embrapa)-Amazonia Ocidental, 29 km North of Manaus, Brazil (3d 8m S, 59d 52m W, 40 - 50 m above sea level), in 1998 and 1999.Microaggregated tropical soils have shown high water conductivity even under unsaturated conditions in laboratory experiments. It is not clear, however, what depth the infiltrating soil water reaches during storm events under humid tropical conditions. Dynamics and fluxes of water were determined with high temporal resolution to a depth of 5 m in a Xanthic Hapludox of central Amazonia, Brazil. The soil water percolated to a depth of 0.9 m within 2 h of a rainfall event of 48 mm. Water fluxes were significantly slower below 0.9 m (17% of infiltration at 0 - 0.9 m) due to higher bulk densities. Percolation not only started rapidly after a rainfall event when soil water suction reached a certain threshold (ca. 20 - 30 hPa) but was also reduced to background levels less than 1 h after the rain had ended. The demonstrated extremely short-term dynamics of water fluxes have implications for measurement design of water availability and solute leaching in microaggregated tropical soil that require correct time integrals of solution concentrations and soil water dynamics. Measurement intervals of 30 min or less were necessary in our study. Rapid water flows may explain the observed high nutrient losses from the topsoil of microaggregated tropical soil and the large accumulation of nutrients in the deep soil (> 5 m).",
         "license": "proprietary"
     },
@@ -141071,7 +141032,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777741436-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777741436-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0xMSBmb3Jlc3QgZGFtYWdlIGZvbGxvd2luZyByZWR1Y2VkIGltcGFjdCBsb2dnaW5nLCBudyBtYXRvIGdyb3NzbywgYnJhemlsXCIsXCJPUk5MX0NMT1VEXCIsXCJORDExX0xvZ2dpbmdfRGFtYWdlX01UXzk3N1wiLFwiMVwiLDI3Nzc4MTQxMjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTExIGZvcmVzdCBkYW1hZ2UgZm9sbG93aW5nIHJlZHVjZWQgaW1wYWN0IGxvZ2dpbmcsIG53IG1hdG8gZ3Jvc3NvLCBicmF6aWxcIixcIk9STkxfQ0xPVURcIixcIk5EMTFfTG9nZ2luZ19EYW1hZ2VfTVRfOTc3XCIsXCIxXCIsMjc3NzgxNDEyMSwyXSJ9/ND11_Stream_Nutrients_921_1",
         "description": "This data set contains baseflow streamwater concentrations of pH, specific conductivity, base cations, carbon (dissolved organic carbon (DOC), particulate organic carbon (POC) and bicarbonate alkalinity) and silica for four headwater streams in the seasonally dry Amazon (Johnson et al. (2006a) and Johnson et al. (2006b). Data are provided in one comma-separated ASCII file.This hydrologic study of four headwater watersheds was conducted in an undisturbed forest near Juruena, Mato Grosso in the seasonally dry, southern Amazon. The small catchments range in size from 0.85 to 1.9 ha. Stream water samples were collected weekly during rainy seasons and biweekly during the dry seasons. Baseflow stream water concentrations of base cations, silica, electrical conductivity, DOC, and alkalinity varied inversely with discharge. While there was variation among the watersheds, the concentration-discharge patterns were consistent for each of the four watersheds. Baseflow discharge data are not included in this data set and will be archived separately.",
         "license": "proprietary"
     },
@@ -141084,7 +141045,7 @@
         "bbox": "-58.76, -10.42, -58.76, -10.42",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777749892-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777749892-ORNL_CLOUD.html",
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         "description": "Tree and liana (vine) measurements were collected in a logging concession at the Fazenda Rohsamar in the municipality of Jurena in northwestern Mato Grosso. Tree identification and diameter measurements were collected between July 31, 2003 and October 14, 2003 on 10-m x 1000-m transects and the liana measurements were collected between August 5, 2003 and October 14, 2003 on 10 2-m x 1000-m transects within a 1400 ha logging block ( Feldpauschh et al. 2006). Liana transects were nested within tree census transects to relate total species data to the tree inventory. The biomass of lianas was calculated using two different allometric equations derived for lianas in Amazonian forests ( Gerwing and Farias, 2000; Gerwing et al. 2004). Comma-separated data files of measurements of (1) tree species (diameter >10 cm), and forest characteristics, (2) measurements of liana diameter, forest characteristics, and calculated biomass, and (3) georeference points for the liana sampling transects are provided.Selective logging has become a dominant land-use in Brazilian Amazonia. Published data on forest biomass in southern Amazonia is sparse. As part of a larger study to evaluate the effect of reduced impact logging on carbon dynamics and nutrient stocks, forest structure, and forest regeneration potential, we conducted a pre-harvest campaign to estimate tree and liana biomass in a parcel of managed forest in northwestern Mato Grosso. Prior to logging in 2003, a scientific inventory was conducted in Block 5 of the logging concession(Figure 1). Tree characteristics for all trees and palms > 10 cm DBH was measured by stratified sampling across the block to account for differences in tree densities (trees/ha). Transects were located using a commercial timber inventory to identify tree trunks approximately 10 cm DBH, lower and upper canopy height, species, and location of all individuals to the nearest 10 cm on an x-y grid. Diameter of all liana stems were included if their ultimate rooting point before ascending into the canopy fell within the transect. Lianas that had been cut due to reduced impact logging practices were also measured. Distance along the transect was recorded for each stem.",
         "license": "proprietary"
     },
@@ -141097,7 +141058,7 @@
         "bbox": "-58.76, -10.42, -58.76, -10.42",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777792629-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777792629-ORNL_CLOUD.html",
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         "description": "This data set reports the results of a vegetation survey along transects across the transition zones between the three major forest types in the seasonally dry forest of the southwestern Amazon Basin in the municipality of Juruena, Mato Grosso in 2004. The major forest types are differentiated by tree species composition, biomass, soil type, and landscape position: (1) campinarana; high stem density and low biomass on sandstone outcrops, (2) palm forest; low-lying seasonally inundated areas dominated by palms and, (3) terra firme; low stem density and high biomass. Along these 10 x 100 m transects, all trees, palms, and lianas >= 10 cm DBH in 10 x 10 m plots and, in nested 2 x 10 m subplots, all trees, palms and lianas >=1 cm DBH were measured, identified and georeferenced. Plot locations and survey data are reported in two comma separated files.",
         "license": "proprietary"
     },
@@ -141110,7 +141071,7 @@
         "bbox": "-47.78, -15.93, -47.37, -1.27",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780955938-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780955938-ORNL_CLOUD.html",
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         "description": "This data set provides fine litterfall mass and nutrient concentrations from samples collected at chronosequences established at Sao Francisco do Para and Capitao Poco, Para, Brazil. Nitrogen (N) and phosphorus (P) concentrations were determined for litterfall samples from the Sao Francisco do Para, and N, P, potassium (K), calcium (Ca), and magnesium (Mg) concentrations are reported for samples from the Capitao Poco. In addition, carbon (C), N, delta C13, and delta N15 values were determined for leaves from the dominant species of the forests at Sao Francisco do Para; soil physical and chemical characteristics were determined for a subset of the chronosequence plots at the two study sites; and soil trace gas fluxes were determined from the Sao Francisco do Para site. All samples were collected between March 2001-February 2005. Trace gas fluxes were measured 10 times between October 2000 and June 2002 with 5 sample periods in dry season and 5 in wet season months. There are five comma-delimited data files with this data set.",
         "license": "proprietary"
     },
@@ -141123,7 +141084,7 @@
         "bbox": "-63.14, -11.04, -45.69, -1.99",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781409456-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781409456-ORNL_CLOUD.html",
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         "description": "This data set contains images of fractional cover estimates of photosynthetic vegetation (PV) canopy, nonphotosynthetic vegetation (NPV), and exposed soils (S) derived from Landsat images (30-m resolution) obtained for two ranches in the Brazilian Amazon from 1996 to 2002. The Fazenda Vitoria ranch is located in eastern Para near the city of Paragominas and is a mosaic of primary forest, logged forest, secondary forest, and pasture with moderately dissected topography. The Fazenda Nova Vida ranch is located in the state of Rondonia in western Amazonia and is a mosaic of primary forest, logged forest, and pastures. For Fazenda Vitoria, two dry-season Landsat images were obtained, subset, and analyzed. For Nova Vida three dry-season images and one end-of-wet-season image were obtained, subset, and analyzed. Spectral mixture analysis, which decomposes individual satellite pixels into constituent cover fractions of surface materials, was used with a general probabilistic modeling approach to derive subpixel cover fractions of PV, NPV, and S. There are six GeoTIFF (.tif) files with this data set.  ",
         "license": "proprietary"
     },
@@ -141136,7 +141097,7 @@
         "bbox": "-55, -2.75, -55, -2.75",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780961671-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780961671-ORNL_CLOUD.html",
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         "description": "This data set reports the results of chemical analyses of rainfall, throughfall, litter leachate, and soil water samples collected before, during, and after a rainfall exclusion experiment conducted at the km 67 Seca Floresta site, Tapajos National Forest, Brazil. Samples were collected every two weeks from May 17, 1999 through May 10, 2006. Measurements included alkalinity, conductivity, pH, and selected anions and cations analyzed by ion chromatography.The exclusion treatment, began in late January 2000 and continued through December 2004, involved diverting about 60% of throughfall (equivalent to approximately half the rainfall) from a 1-hectare plot using plastic panels installed in the understory. The comparable 1-hectare control plot was unaltered. The purpose was to observe the potential effects of severe water stress on a humid Amazonian forest (Nepstad et al., 2002 and Nepstad et al., 2007). There are five comma-delimited data files with this data set. ",
         "license": "proprietary"
     },
@@ -141149,7 +141110,7 @@
         "bbox": "-149.96, 63.82, -144.96, 65.96",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2162189202-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2162189202-ORNL_CLOUD.html",
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         "description": "This dataset provides leaf area index (LAI), tree species and canopy cover, normalized difference vegetation index (NDVI), and NDVI trends for boreal forests in interior Alaska, U.S. These data were collected to investigate NDVI trends with forest structure and composition as influenced by disturbance and succession. The data are from 102 sites surveyed in 2017 and 2018 and include locations with and without a fire since 1940. A time series of NDVI was developed from Landsat (1999-2018) to measure NDVI trends. The field data cover the period 2017-08-29 to 2018-08-20. The surveyed forest stands spanned a distance of over 425 km across interior Alaska. The sites were selected before visiting the field to include locations with and without a fire since 1940. Recently burned sites were selected to span a range of years since fire, while sites without a recent fire were selected to include a range of Landsat NDVI trends. For each year, the median NDVI during the growing season was calculated. Then, a simple linear regression trend was calculated for years 1999-2018.",
         "license": "proprietary"
     },
@@ -142150,7 +142111,7 @@
         "bbox": "145.5, -17.32, 145.72, -17.28",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947553-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947553-ORNL_CLOUD.html",
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         "description": "This data set contains eight data files (.txt format): three net primary productivity (NPP) data files and five climate data files. The NPP estimates are based on field measurements of litterfall accumulation at three tropical rainforest sub-sites near Atherton, Queensland, in northeast Australia. Additional NPP component data include standing litter biomass, leaf decomposition rates, and nutrient concentrations in litter, where available. Precipitation and temperature data are provided from measurements at two of the study sites, nearby weather stations, and from published literature sources. Annual litterfall estimates are based on weekly or bi-weekly measurements for 3-4 years (1974/5-1978) at the Wongabel (17.32 S 145.50 E) and the Gadgarra (17.30 S 145.72 E) State Forest Reserves, and weekly measurements for 5 years (1980-1985) at Tableland (17.28 S 145.57 E) near Atherton. Additional measurements were made at Wongabel and Gadgarra including branchfall (monthly); litter on the forest floor (quarterly); rainfall and throughfall (weekly); and trace element concentrations in litterfall (weekly or bi-weekly). In a related study at Gadgarra, litterfall and standing litter crop were sampled at approximately 19-day intervals from 1974 to 1976 and at approximately 3-month intervals 1976 to 1978. Total litterfall averaged 905 g/m2/year at Wongabel, 987 g/m2/year at Gadgarra, and 1,103 g/m2/year at Tableland, giving minimum estimates of above-ground NPP for this region of Australia and an indication of tropical forest productivity south of the Equator. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2001. ",
         "license": "proprietary"
     },
@@ -142163,7 +142124,7 @@
         "bbox": "-0.85, 50.92, -0.85, 50.92",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752551426-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752551426-ORNL_CLOUD.html",
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         "description": "This data set contains two ASCII text files, one providing productivity measurements for a chalk grassland on Beacon Hill, West Sussex, U.K. (50.92 N, -0.85 W) and the other containing climate data from a weather station at the former King's College London, Rogate Field Centre, 6 km distant (51.01 N, -0.85 W). Measurements of above-ground live biomass and total dead matter were made by harvesting 0.25 m2 quadrats in the 20 x 20-m study area at eight to ten week intervals from March 1972 to April 1973. Precipitation amount and minimum/maximum temperature were recorded from 1969 through 1993.Above-ground net primary production (ANPP) was estimated by several methods: 332 g/m2/year (annual increase in living biomass, sum of species); 355 g/m2/year (peak or maximum live biomass, plant dry matter weight); 773 g/m2/year (maximum live + dead biomass); 310 g/m2/year (annual increase in living biomass carbon by summing positive increments in biomass); and 691 g/m2/year (annual net production accounting for leaf turnover). The carbon content of ANPP (accounting for leaf turnover) was estimated to be 310 gC/m2/year using a conversion factor of 0.45. Below-ground production was not measured.Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1998. ",
         "license": "proprietary"
     },
@@ -142176,7 +142137,7 @@
         "bbox": "62, 35.68, 62, 35.68",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943389-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943389-ORNL_CLOUD.html",
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         "description": "This data set provides two data files in text format (.txt). One file contains estimates of above-ground live phytomass for an ephemeral desert steppe located in the Badkhyz Nature Reserve in southern Turkmenistan. Monthly measurements of plant biomass were made by harvest during the growing season (January-May) from 1948 through 1963. Afterwards, an annual measurement of peak live biomass was made in May from 1964 through 1982, with gaps for years 1973-1976. The second file contains monthly and annual climate data recorded at the study site from 1941 through 1982. Above-ground net production (ANPP) for the Badkhyz site is the lowest among the eight Eurasian grassland sites, at 100 g/m2/yr. Below-ground NPP for Badkhyz (1,745 g/m2/yr) was conservatively estimated from a similar dry, semiarid continental steppe in Northern Kazakhstan (i.e., Shortandy). Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1998. ",
         "license": "proprietary"
     },
@@ -142189,7 +142150,7 @@
         "bbox": "-148.25, -47.5, 128.27, 66.37",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948194-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948194-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibmFzbW8tdGlhbSAyNTBtIDE2LWRheSBub3J0aCBhbWVyaWNhIHN1cmZhY2Ugc29pbCBtb2lzdHVyZSBkYXRhc2V0XCIsXCJPUk5MX0NMT1VEXCIsXCJOQVNNb19UaUFNXzI1MG1fMjMyNlwiLFwiMVwiLDI5MDU0NTc3NjUsMl0iLCJ1bW0iOiJbXCJuYXNtby10aWFtIDI1MG0gMTYtZGF5IG5vcnRoIGFtZXJpY2Egc3VyZmFjZSBzb2lsIG1vaXN0dXJlIGRhdGFzZXRcIixcIk9STkxfQ0xPVURcIixcIk5BU01vX1RpQU1fMjUwbV8yMzI2XCIsXCIxXCIsMjkwNTQ1Nzc2NSwyXSJ9/NPP_BOREAL_611_2",
         "description": "This data set provides estimates of above- and below-ground biomass, above- and below-ground NPP (ANPP and BNPP), and total NPP(TNPP) for selected North American and Eurasian boreal forests located between 66.37 degrees N and 47.5 degrees N. Each stand was selected through a review of published literature and classified into one of three classes, depending upon completeness of NPP budget, ancillary site data, and stand information. Within the overall 1965-1995 temporal range, data available for individual sites varies widely.There are two ASCII files (comma-separated-value format) of NPP data.\tThe first file provides carbon distribution in above- and below-ground vegetation biomass, above- and below-ground net primary production, and mean annual biomass increment for twenty-four (24) Class I sites which have complete NPP budgets (ANPP + BNPP). Information about site characteristics and NPP measurement approaches are also provided.\tThe second file provides stand information, carbon distribution in above-ground vegetation biomass, and ANPP data for forty-five (45) Class II boreal forest stands that have incomplete NPP budgets. Revision Notes:Above- and below-ground biomass, ANPP, and TNPP values for several sites have been corrected to agree with primary published sources and related data sets. The temporal coverage for both has been corrected to agree with primary published sources. Please see the Data Set Revision section of this document for detailed information.",
         "license": "proprietary"
     },
@@ -142202,7 +142163,7 @@
         "bbox": "-110.78, 45.78, -110.78, 45.78",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752559249-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752559249-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_BRD_205_2",
         "description": "This data set contains three ASCII text files for the Bridger grassland study site in the Rocky Mountains (45.78 N, -110.78 W, Elevation 2,340 m). Two files contain above- and below-ground biomass data, one for each treatment (ungrazed and moderately grazed). The third file contains climate data from the Big Timber weather station (45.80 N, -110.00 W, Elevation 1,249 m) near Bridger. Dynamics of above- and below-ground plant biomass were monitored by harvest technique at roughly 2-week intervals during the growing season for the years 1970, 1972, and 1973. Data on above-ground live biomass, standing dead matter, and litter are provided for each sampling date. Below-ground biomass (roots and crowns) are provided for 0-30 cm and 0-50 cm depths. Data were collected as part of a coordinated study over 1-3 years at ten grassland sites of the central and western United States under the U.S. Grassland Biome Project of the International Biological Program (IBP). Above-ground net primary production (ANPP) was estimated, conservatively, by summing peak biomass of individual species. Below-ground net primary production (BNPP) was estimated as the sum of positive increments in total root biomass (including root crowns). Values varied according to treatment.Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1998. ",
         "license": "proprietary"
     },
@@ -142215,7 +142176,7 @@
         "bbox": "-79.85, 9.15, -79.85, 9.15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752547387-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752547387-ORNL_CLOUD.html",
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         "description": "This data set contains three ASCII files (.txt format). One file provides net primary productivity (NPP) data for the moist lowland tropical forest on Barro Colorado Island, Panama. NPP estimates are based on field measurements of litterfall accumulation, tree growth and mortality, and herbivory. Above-ground biomass and LAI are also reported. The other two files provide climate data recorded onsite.Annual litterfall accumulation (leaf + twig + other litterfall) averaged 1,064 g/m2/year, excluding losses to herbivory, on the central plateau of the island and in the Lutz catchment (1969-1979) and 1,246 g/m2/year at Poacher's Peninsula (1986-1990). Herbivory due to insects (about 50 g/m2/year) was estimated from leaf litterfall (1974-1977) by measuring holes and gaps in fallen leaves. An additional 30 g/m2/year may be lost to vertebrate herbivores which leave no identifiable traces in litter traps. Coarse wood litterfall due to tree damage may represent an additional 46 g/m2/year. Above-ground biomass averaged 27,425 g/m2 based on inventory data collected every 5 years from 1985 to 2000 and allometric regression equations. Tree growth of 554 g/m2/year was based on above-ground biomass changes during the three census intervals. Tree mortality of 2-3% was estimated by recording dead or missing trees (1982-1990). LAI of 7.3 was based on the average area of leaves that fell per area of ground per year. Overall, above-ground NPP for Barro Colorado Island was estimated at 1,800 g/m2/year. ",
         "license": "proprietary"
     },
@@ -142228,7 +142189,7 @@
         "bbox": "-156.67, 71.3, -156.67, 71.3",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947951-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947951-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIHRyb3BpY2FsIGZvcmVzdDogbGEgc2VsdmEsIGNvc3RhIHJpY2EsIDE5NzUtMTk5NCwgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9TTFZfMjE4XCIsXCIyXCIsMjc1MjczNDUwOSwyXSIsInVtbSI6IltcIm5wcCB0cm9waWNhbCBmb3Jlc3Q6IGxhIHNlbHZhLCBjb3N0YSByaWNhLCAxOTc1LTE5OTQsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfU0xWXzIxOFwiLFwiMlwiLDI3NTI3MzQ1MDksMl0ifQ%3D%3D/NPP_BRW_580_2",
         "description": "This data set contains three data files. One file (.csv format) provides above- and below-ground biomass and leaf area index (LAI) data for a wet arctic tundra meadow (Biome research site 2, Dupontia meadow, vegetation type V) studied from 1970 to 1971 at Point Barrow, Alaska, USA, (71.30 N -156.67 W Elevation 5 m). The second file, also in .csv format, provides net primary productivity (NPP) estimates for different plant growth forms for eight vegetation types recognized in the coastal tundra at Barrow. The third file (.txt format) provides climate data from the weather station at Barrow, Alaska (71.30 N -156.78 W Elevation 31 m). Measurements of above- and below-ground living and dead biomass were made at 10-day intervals during the growing season (mid June to end of August) by harvest methods in 6 x 6 m study plots of undisturbed vegetation. LAI was estimated at 10-day intervals with inclined point quadrats and other methods. NPP estimates are based on harvest at the period of peak above-ground vascular biomass and seasonal CO2 gas exchange estimates in 1972. The studies were conducted as part of the International Biological Program (IBP) U.S. Tundra Biome program. Average total NPP for the eight vegetation communities recognized for the coastal tundra at Barrow was 230 g/m2/year (110 g/m2/year ANPP plus 120 g/m2/year BNPP). Values varied by vegetation community type. Revision Notes: This data set has been revised to correct several values of average below-ground plant standing crop. A second NPP data file has been added to provide NPP estimates for the different vegetation types at the coastal tundra study site from measurements made in 1972. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
@@ -142241,7 +142202,7 @@
         "bbox": "-64.8, 18.33, -64.8, 18.33",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2755523295-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2755523295-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIG11bHRpLWJpb21lOiBncmlkZGVkIGVzdGltYXRlcyBmb3Igc2VsZWN0ZWQgcmVnaW9ucyB3b3JsZHdpZGUsIDE5NTQtMTk5OCwgcjNcIixcIk9STkxfQ0xPVURcIixcIk5QUF9HUklEREVEX0dQUERJXzYxNFwiLFwiNFwiLDI3NTU1NzE0MjYsMl0iLCJ1bW0iOiJbXCJucHAgbXVsdGktYmlvbWU6IGdyaWRkZWQgZXN0aW1hdGVzIGZvciBzZWxlY3RlZCByZWdpb25zIHdvcmxkd2lkZSwgMTk1NC0xOTk4LCByM1wiLFwiT1JOTF9DTE9VRFwiLFwiTlBQX0dSSURERURfR1BQRElfNjE0XCIsXCI0XCIsMjc1NTU3MTQyNiwyXSJ9/NPP_CBAY_473_2",
         "description": "This data set contains three ASCII files (.txt format). One data file contains above-ground biomass, litter, litterfall, herbivory, biomass change, and above-ground net primary productivity (ANPP) estimates for a late secondary moist subtropical forest based on measurements from 16 permanent study plots located along an elevational (60-290 m) and topological gradient within the 132-ha Cinnamon Bay watershed on St. John, U.S. Virgin Islands. The purpose of the study was to provide information on forest structure, species composition, and forest productivity along environmental gradients, including the effects of hurricanes and drought. The other two files provide climate records from nearby weather stations (1917-1981).Above-ground biomass was measured every 5 years (1983-2003). Litterfall accumulation was determined in 1992-1993. In 1983, total above-ground biomass on all plots combined averaged 13,870 g/m2; by 2003 during a post-hurricane recovery period, it had declined by nearly 7 percent. In 1983, biomass was greatest on the summit, intermediate on slopes and valleys, and least on ridges; by 2003, the quantities for all sites had converged except on the summit plot.In 1992, ANPP was estimated based on annual litterfall accumulation (897 g/m2/year) plus biomass change due to delayed mortality (142 g/m2/year) plus estimated herbivory (25 g/m2/year), giving a total ANPP of 1,064 g/m2/year. Periodic storms and drought appear to maintain the forest in a disturbed state.",
         "license": "proprietary"
     },
@@ -142254,7 +142215,7 @@
         "bbox": "-105.02, 19.5, -105.02, 19.5",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947703-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947703-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIG11bHRpLWJpb21lOiBncmlkZGVkIGVzdGltYXRlcyBmb3Igc2VsZWN0ZWQgcmVnaW9ucyB3b3JsZHdpZGUsIDE5NTQtMTk5OCwgcjNcIixcIk9STkxfQ0xPVURcIixcIk5QUF9HUklEREVEX0dQUERJXzYxNFwiLFwiNFwiLDI3NTU1NzE0MjYsMl0iLCJ1bW0iOiJbXCJucHAgbXVsdGktYmlvbWU6IGdyaWRkZWQgZXN0aW1hdGVzIGZvciBzZWxlY3RlZCByZWdpb25zIHdvcmxkd2lkZSwgMTk1NC0xOTk4LCByM1wiLFwiT1JOTF9DTE9VRFwiLFwiTlBQX0dSSURERURfR1BQRElfNjE0XCIsXCI0XCIsMjc1NTU3MTQyNiwyXSJ9/NPP_CHM_578_2",
         "description": "This data set contains five data files (.txt format). Three data files provide net primary productivity (NPP) estimates for a tropical dry deciduous forest within the 3,300-ha Chamela Biological Station, Mexico. There is one file for each of the three permanent watershed plots located along an elevational gradient from 60 to 160-m above sea level. NPP was estimated from field measurements obtained during wet and dry seasons between 1982 and 1995. A fourth NPP data file provides average nutrient fluxes into and out of five watersheds. The fifth file provides precipitation and minimum/maximum temperature data from measurements obtained onsite. Detailed data are available for above-ground NPP (ANPP) (fine litterfall, wood increment, and leaf herbivory plus an estimation of understory production), and below-ground NPP (BNPP) (fine root production and root increment). Biomass data and nutrient inputs/outputs (P, K, Ca, Mg) averaged from five watersheds are also included in the data set. Estimated ANPP ranged from 611 to 808 g/m2/year between the three sub-sites (average 682 g/m2/year), and total NPP ranged from 1,119 to 1,353 g/m2/year (average 1,206 g/m2/year). These estimates are thought to represent the lower bounds of NPP because root and stem herbivory have not been taken into account, although leaf herbivory is included. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2001. ",
         "license": "proprietary"
     },
@@ -142267,7 +142228,7 @@
         "bbox": "146.27, -26.4, 146.27, -26.4",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944333-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944333-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_CHR_468_2",
         "description": "This data set contains three ASCII files (.txt format). One file provides above- and below-ground biomass, productivity, litterfall, and bioelement data for a native C3 grassland near Charleville (-26.40 S, 146.27 E, Elevation 304 m) in southern Queensland, northeast Australia. The second file provides above- and below-ground biomass and productivity estimates for an introduced C4 grassland near Charleville. The third file contains climate data (precipitation and maximum/minimum temperature) recorded a weather station located at the Charleville Airport for the period 1942-1994. The NPP studies were carried out over a 12-month period from 1973 to 1974 using harvest techniques with a view to parameterizing a simulation model of primary production and livestock carrying capacity. Peak above-ground standing crop at the end of the summer season was 122 g/m2 and 154 g/m2 for the native and introduced grasslands, respectively. Maximum below-ground standing crop was markedly different, at 110 g/m2 and 400 g/m2, respectively, suggesting a significant difference in shoot/root allocation. Annual net primary production was estimated as the sum of above-ground peak standing crop (live + dead) and root increment. These values were 182 and 319 g/m2/yr for the native and introduced grasslands, respectively. Additional data on litter production and nutrient dynamics are available for the native grassland site. Data on soil moisture, determined gravimetrically with each biomass harvest, are available in the literature. ",
         "license": "proprietary"
     },
@@ -142280,7 +142241,7 @@
         "bbox": "-67.42, 8.93, -67.42, 8.93",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752562626-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752562626-ORNL_CLOUD.html",
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         "description": "This data set contains four ASCII text files for a 260-hectare humid Trachypogon savanna at the Estacion Biologica de Los Llanos, Calabozo, Venezuela (8.93 N, -67.42 W, Elevation 98 m). Two data files contain monthly estimates of above-ground biomass for the period January 1969 to October 1969, one file for each treatment (burned and unburned plots). These files also provide one estimate of below-ground biomass. Another NPP data file contains monthly estimates of above- and below-ground biomass, LAI, and nitrogen content of living and dead leaves and stems and below-ground biomass for an unburned area of the Calabozo savanna for March 1986 to April 1987. The fourth data file contains precipitation and maximum/minimum temperature data from a nearby weather station at Estacion Biologica de Los Llanos (8.88 N, -67.32 W, Elevation 86 m) for the period 1968-1986. Harvest methods were used to estimate above- and below-ground biomass. Total NPP (above- plus below-ground productivity) was estimated at 682 g/m2/yr for unburned and 755 g/m2/yr for burned grassland plots in 1969. Later TNPP estimates (1986/87) for the unburned grassland ranged from 823 to 1,310 g/m2/yr.Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1998. ",
         "license": "proprietary"
     },
@@ -142293,7 +142254,7 @@
         "bbox": "-115.5, 50.1, -115.25, 50.2",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943793-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943793-ORNL_CLOUD.html",
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         "description": "This data set contains two files (.txt). One file contains stand characteristics, soil characteristics, biomass distribution, and production allocation data measured during the 1984 growing season in four lodgepole pine stands (Pinus contorta var. latifolia) located near Canal Flats, British Columbia, Canada (50.2 N -115.5 W Elevation 1,300-1,380 m). The second file contains climate data from a nearby weather station at Kananaskis Boundary, Alberta (50.98 N -115.12 W Elevation 1,463 m). Two lodgepole pine stands were growing on xeric sites and two stands were growing on mesic sites. The stands were 70-78 years old, were unmanaged, and had regenerated naturally following wildfire. They were studied to determine the influence of soil water content on resource allocation to above-ground versus below-ground plant components. Above-ground NPP of the two xeric stands was 350 and 330 g/m2/yr, and below-ground NPP was 430 and 630 g/m2/yr, respectively, giving a range of total NPP from 780 to 960 g/m2/yr. ANPP of the two mesic stands was 640 and 740 g/m2/yr, and BNPP was 550 and 450 g/m2/yr, respectively, giving total NPP of 1,190 g/m2/yr in each case. Although the ANPP of the mesic stands was approximately double that of the two xeric stands, total NPP was only 36% greater for the mesic stands than for the xeric stands. Production allocation was in the following order: fine and small roots > stems > foliage > coarse roots > branches, for all but the wettest site, where stem production exceeded fine and small root production. Revision Notes: This data set has been revised to correct the sampling date (month) when above-ground biomass samples were collected. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
@@ -142306,7 +142267,7 @@
         "bbox": "-85.1, 10.4, -85.1, 10.4",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940644-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940644-ORNL_CLOUD.html",
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         "description": "This data set contains two ASCII text files; one providing above-ground biomass, productivity, and bioelement concentration data for a derived savanna at Canas (10.4 N 85.1 W Elevation 45 m) in northwestern Costa Rica, and the other providing climate data from the La Pacifica weather station near Canas and rom other sources. Monthly dynamics of above-ground plant matter were monitored from July 1969 to June 1970 using harvest procedures within an exclosure to restrict grazing. The climate data are available from three time periods: 1951-1960, 1963, and 1969-1970. The climate is characterized by a dry season from late November to April, with little seasonal differences in temperature. The Canas study site is dominated almost exclusively by Hyparrhenia rufa, a perennial grass of African origin introduced extensively throughout the tropics. The original vegetation cover was closed semideciduous forest. The study area was deforested and converted to a grass savanna around January 1947, 22.5 years before the start of the present study. Light grazing by cattle and horses is accompanied by burning of the Canas savanna annually between December and April. Above-ground net primary productivity (ANPP) was estimated by two methods: maximum standing crop of herbaceous shoot tissue (peak live + dead matter) (968 g/m2/year); and the sum of monthly estimates of shoot production (including estimated mortality) (1,387 g/m2/year). End-of-season (November, 1969) live root biomass estimates of 1,220 g/m2 at 0-20 cm depth and 2,254 g/m2 at 0-100 cm depth are available in the literature. ",
         "license": "proprietary"
     },
@@ -142319,7 +142280,7 @@
         "bbox": "-104.77, 40.82, -104.77, 40.82",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751936709-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751936709-ORNL_CLOUD.html",
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         "description": "This data set records the productivity of a semiarid shortgrass prairie steppe located in the Central Plains Experimental Reserve (CPER)/Pawnee National Grassland in north-central Colorado. There are nine data files (.txt). Four files contain measurements of monthly dynamics of harvested above-ground plant biomass, one file each for untreated, irrigated, fertilized, and irrigated + fertilized plots for the period 1970 to 1975. The fifth file contains annual above-ground NPP estimates for the untreated plot for the period 1970-1974. The sixth file contains long-term ANPP estimated from field harvest measurements made between 1970 and 1990 and by correlation with forage production measurements made between 1939 and 1990. Two additional files provide estimates of above- and below-ground NPP based on peak growing season harvests; one record covers 1970-1972 from the Pawnee site and the other covers 1985-1988 from CPER. The ninth file contains climate data for 1912-1990 from a weather station located at CPER.Revision Notes: This data set has been revised to correct the study site elevation, extend the temporal coverage, and add four data files containing estimates of NPP. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
@@ -142332,7 +142293,7 @@
         "bbox": "-102.82, 46.9, -102.82, 46.9",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752568202-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752568202-ORNL_CLOUD.html",
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         "description": "This data set contains three ASCII files (.txt format). Two files contain above- and below-ground biomass and productivity data for a northern mixed prairie grassland, one file for an ungrazed treatment and the other for a heavily grazed treatment. The study site (46.90 N, -102.82 W, Elevation 784 m) is located in the northern Great Plains, near the city of Dickinson, about 160-km west of Bismarck, North Dakota. The third file contains climate data for the period 1891-1994 obtained from a weather station near Dickinson (46.88 N, -102.80 W, Elevation 750 m). Dynamics of above-ground living and dead plant biomass were monitored by the harvest technique at roughly 2-week intervals during the growing season of 1970. Total below-ground biomass was sampled at the same intervals by manual coring within the harvested plots to a depth sufficient to include at least 90% of the root mass. Data were collected as part of a coordinated study over 1-3 years at ten grassland sites of the central and western United States, under the US Grassland Biome Project of the International Biological Program (IBP).Above-ground net primary productivity (ANPP) was estimated conservatively by summing peak biomass of individual species. These values were 351 g/m2/year for ungrazed and 302 g/m2/year for grazed grassland plots. Below-ground net primary productivity (BNPP) was estimated as the sum of positive increments in total root biomass (including root crowns); 932 g/m2/year for ungrazed and 958 g/m2/year for grazed grassland plots. Revision Notes: Only the documentation for this data set has been modified. The files have been checked for accuracy and are identical to those originally published in 1998. ",
         "license": "proprietary"
     },
@@ -142345,7 +142306,7 @@
         "bbox": "-78.12, 8.66, -78.12, 8.66",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752608647-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752608647-ORNL_CLOUD.html",
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         "description": "This NPP data set contains one ASCII file (.txt format). The data file contains above- and below-ground biomass, litterfall, LAI, vegetation/soil micro-nutrient content (P, K, Ca, Mg, etc.), and above-ground net primary productivity (ANPP) estimates for transitional moist/dry tropical forests at Rio Lara (wet season site) and Rio Sabana (dry season site) in Darien Province, Panama. Field measurements were made in 1967 and 1968. No climate data are provided.Apart from litter quantity, most of the differences between these data reflect variations between the two plots sampled, rather than seasonal changes. Both plots were considered representative of the surrounding forest. The area was thought to have been forested for the previous 400 years, following abandonment of open savanna lands maintained by the Precolumbian Indians.Total annual leaf and branch fall averaged for the two sites was 1,137 g/m2/yr, representing a minimum ANPP estimate. Litter decomposition over the 9-month wet season was around 90%. LAI at both sites was high; however, the index for the dry site (10.6 m2/m2) was only half that of the wet season site (22.4 m2/m2). ",
         "license": "proprietary"
     },
@@ -142358,7 +142319,7 @@
         "bbox": "46.78, 49.33, 46.78, 49.33",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940745-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940745-ORNL_CLOUD.html",
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         "description": "This data set provides two data files in text format (.txt). One file contains a long time series of biomass measurements made between 1955 and 1989 on a semi-desert steppe at the Dzhanybek Research Station in Kazakhstan (49.33 N 46.78 E Elevation 20 m). The second file contains monthly and annual climate data for the study site for the period 1953-1989.Peak live biomass measurements were made from 1955 to 1989 (excluding 1976) and additional measurements of above-ground live biomass and dead matter were made seasonally from 1985 to 1989. Averaged over the time series, above-ground live phytomass and standing dead were estimated to be 137 g/m2 and 32 g/m2 (dry matter weight), respectively, while below-ground phytomass dry weight was 1,750 g/m2. ANPP was estimated to be 201 g/m2/yr. BNPP and TNPP were not estimated.Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1997.",
         "license": "proprietary"
     },
@@ -142371,7 +142332,7 @@
         "bbox": "-151.92, -49.75, 179.5, 75.5",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948807-ORNL_CLOUD.html",
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         "description": "This data set represents a refined set of global net primary productivity (NPP) estimates and model driver data that are the results of the Ecosystem Model-Data Intercomparison (EMDI) workshop review and outlier analyses undertaken to assess the accuracy of global model forecasts of terrestrial carbon cycling. EMDI builds upon the accomplishments of the original worldwide synthesis of NPP measurements and associated model driver data prepared by the Global Primary Production Data Initiative (GPPDI) (Olson et al., 2001; 2013). The EMDI review and analyses produced NPP, climate, NDVI, land cover, vegetation, and soil data for a sub-set of GPPDI data: 81 Class A sites, 933 Class B sites, and 3,855 Class C 0.5-degree cell grids. Class A sites represent well-documented study sites that have complete above- and below-ground NPP measurements. Class B sites represent more numerous extensive sites with less documentation and site-specific information available. Class C cells represent estimates of NPP for 0.5-degree grid cells for which inventory, modeling, or remote-sensing tools were used to scale up the point measurements. The data files are in comma-separated-value (.csv) format:  18 data files for Class A sites which includes 12 comma-separated files (*.csv) and  six compressed files (*.zip) 11 data files for Class B sites in comma-separated format (*.csv).9 data files for Class C grid cells in comma-separated format (*.csv).This document and a companion file (Olson et al., 2001) describe the compilation of NPP estimates under the GPPDI and the EMDI review and outlier analyses that produced this refined set of NPP estimates and model driver data. Revision Notes: This data set has been revised to correct previously reported NPP estimates for three OTTER Transect sites, USA, in the Class A NPP data file. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
@@ -142384,7 +142345,7 @@
         "bbox": "19.45, 64.12, 19.45, 64.12",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943026-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943026-ORNL_CLOUD.html",
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         "description": "This data set contains three files (.txt format) for an established 8.25 ha boreal forest dominated by Norway spruce, Picea abies, at Flakaliden (64.12 N 19.45 E) in northern Sweden. Two data files contain stand characteristics, above- and below-ground biomass, and  Net Primary Productivity (NPP) allocation data (one file for plots fertilized and irrigated during the growing season and one file for control plots). The third file provides climate data for the period 1991-1995 from a weather station established at the study site. The experimental forest was established in 1963 by planting 4-year-old P. abies seedlings after clear-felling, burning, and soil scarification. A yield optimization study was started in 1986 to compare the productivity of the boreal forest under four types of treatment (only the results of fertilization/irrigation and no treatment are presented herein). Treatments began in 1987 and continued through the 1996 growing season. Field measurements were made by inventory and harvest methods. After three years of treatment, height and diameter growth in the fertilized/irrigated stands were double that of the control stand. After 10 years, volume growth of fertilized/irrigated stands were almost four times that of the control. Total net primary production (TNPP) of the 36-year-old untreated stand in 1995 was 291 g/m2/year. TNPP in the fertilized/irrigated stand (902 g/m2/year) was more than three times that of the control, confirming earlier findings that nutrient availability is a major constraint on forest production in Sweden.",
         "license": "proprietary"
     },
@@ -142397,7 +142358,7 @@
         "bbox": "114.8, 4.02, 114.88, 4.14",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945282-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945282-ORNL_CLOUD.html",
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         "description": "This data set contains seven ASCII data files (.txt format). Four files provide NPP data for contrasting lowland rainforests within Gunung Mulu National Park on the island of Borneo, Malaysia. Three files provide climate data from weather stations near Gunung Mulu.The study areas are located along an environmental gradient of varying soil types at elevations ranging from 50 to 300 m within the 544 km2 Park. The study sites are primary lowland evergreen rainforests, each about 1.0 hectare in size. They include: an alluvial forest (at 50 m elevation and often inundated during the wet season); a heath forest (on a sandy terrace at about 170 m elevation); a mixed dipterocarp forest (on ridge slopes at 200-250 m elevation); and a limestone forest (on shallow soils over limestone at the base of cliffs and ravines at 300 m elevation).The NPP files contain estimates of above-ground biomass, annual litterfall accumulation, standing litter crop, and nutrient content of different vegetation components and soils. The scientific expedition was carried out between June 1977 and September 1978. Estimates of litterfall, ranging from 886 g/m2/year to 1,203 g/m2/year, give a minimum estimate of above-ground production.The climate record for the study sites extends from 1915 through 1990. The area's climate is controlled largely by the Indo-Australian monsoon system with wet northeast monsoon from December to March and slightly drier southwest monsoon from May to October. Mean annual precipitation is around 3,000 mm and mean average temperature is about 27 C.",
         "license": "proprietary"
     },
@@ -142410,7 +142371,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949142-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949142-ORNL_CLOUD.html",
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         "description": "Net primary productivity (NPP) estimates were compiled by the Global Primary Production Data Initiative (GPPDI). The database covers 2,523 individual sites and 5,164 half-degree grid cells and underwent extensive review under the Ecosystem Model-Data Intercomparison (EMDI) process. The GPPDI database includes NPP measurements that were collected over a long time period by many investigators using a variety of methods. The measurements are categorized as either Class A, from intensively studied sites; Class B, from extensive sites; or reported as Class C, 0.5 latitude-longitude grid cells. The data set contains six comma-separated files (.csv format). There are two files for each class. One file for each class contains site locations, elevation, NPP estimates, climate data, biome and dominant species information, and references. The other file for each class contains model validation outlier flags derived from site-specific reviews. This document and a companion file (Olson et al., 2001) describe the compilation of NPP estimates under the GPPDI. The results of the EMDI review and outlier analysis produced a refined set of NPP estimates and model driver data (the EMDI database; Olson et al., 2001; 2013). Another ORNL DAAC data set (Zheng et al., 2013) contributed to the compilation of GPPDI. Revision Notes: This data set has been revised to correct previously reported ANPP, BNPP, and TNPP estimates for three OTTER Transect sites, USA, in the Class A NPP data file and BNPP, and TNPP estimates for Vindhyan, India, in the Class B NPP data file. Please see the Data Set Revisions section of this document for detailed information.",
         "license": "proprietary"
     },
@@ -142423,7 +142384,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2755571426-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2755571426-ORNL_CLOUD.html",
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         "description": "This data set provides two data files (.csv format) containing gridded (0.5-degree) estimates of net primary productivity (NPP), elevation, temperature, precipitation, NDVI, and biome type for selected terrestrial regions of the world. The field data used to develop NPP estimates came from 15 worldwide data sources in several different biomes covering the period 1954-1998. NPP values were developed from natural resource field inventories (e.g., forest, rangeland, crop) at different scales, from plot to county; from data compiled from published literature and high resolution maps; from simulation models using key independent variables; from regression analyses with environmental variables; and by using relationships between remotely-sensed spectral vegetation indices and field observations. The first file, NPP_Gridded_3654_cells_R3.csv with 3,654 0.5-degree grid cells, is suitable for biome level and overall analyses because of a larger sample size. In this file, 36 cells have above-ground net primary production (ANPP) only, 320 cells have total net promary production (TNPP) only, and 3,298 cells have both TNPP and ANPP. The second file, NPP_Gridded_2335_unique_cell_R3s.csv, was derived from the larger file and contains 2,335 0.5-degree grid cells after outliers were excluded, replicate measurements were averaged out for each unique geographic location, and cells classified as water, bare ground, and urban were excluded. This smaller data file is more appropriate for model/data inter-comparisons. Overall, gridded ANPP values ranged from 3 to 890 gC/m2/yr, and gridded TNPP values ranged from 3 to 1,235 gC/m2/yr. The lowest values are for sparsely vegetated ground (e.g., open shrublands) and the highest values are for forests. Revision Notes: This data set has been revised to correct the previously reported temporal coverage of field data measurements that were used to develop NPP estimates and the data set title was also corrected to reflect the date change. Missing value codes were added. Please see the Data Set Revisions section of this document for detailed information.",
         "license": "proprietary"
     },
@@ -142436,7 +142397,7 @@
         "bbox": "-83.46, 35.67, -83.28, 35.74",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751950039-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751950039-ORNL_CLOUD.html",
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         "description": "This data set contains two data files (.csv format). One file contains site characteristics, stand descriptors, and above-ground biomass and ANPP data for seven old-growth temperate forest stands and one young cove forest stand in the Great Smoky Mountains of Tennessee. The old-growth stands (> 200 years old) span several watersheds on the north slope of the mountains at elevations ranging from 720 to 1,140 m. The younger stand (48-63 years old, elevation 910 m) developed after agricultural abandonment. The second file contains monthly mean climate data averaged over four years (1947-1950) from four climate stations located along an elevational gradient (445-1,920 m) in Great Smoky Mountains National Park. DBH measurements were made at the beginning of the study and biomass increment was measured from a subset of trees. ANPP was estimated using regional species-specific allometric relationships for tree mass. Biomass, volume, and annual input of coarse woody detritus are also reported. Live biomass in the old-growth stands (32,600-47,100 g/m2) is among the highest reported for temperate forests of eastern North America while ANPP is moderate (630-1,010 g/m2/yr). ANPP in the younger stand was higher (1,180-1,310 g/m2/yr). In comparison with forests worldwide, inputs of coarse woody debris is moderate. Revision Notes: Previously reported field collection dates have been corrected in the NPP file. Biomass and ANPP values were converted from Mg/ha and Mg/ha/yr to g/m2 and g/m2/yr, respectively, consistent with units in other files in the NPP collection. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
@@ -142449,7 +142410,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949814-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949814-ORNL_CLOUD.html",
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         "description": "This data set includes monthly grassland biomass data, net primary productivity (NPP) estimates, and climate (rainfall amounts and temperature) data for multiple study sites in major grassland types worldwide.  Field measurements of biomass and associated environmental data were compiled for the multiple grassland study sites. When sufficient biomass data were available, NPP was estimated by six different algorithms for 31 grassland sites to examine potential bias associated with the algorithms (Scurlock et al. 2002).The data consisted of monthly measurements of biomass components including aboveground live material, standing dead, litter, belowground biomass, and belowground dead material. However, many of the sites did not collect all of the components. There are 1,477 field measurements of some component of NPP, all sites having at least aboveground biomass measurements. Of the 31 sites, 20 also measured standing dead and litter or total live plus dead material. In addition, 17 sites measured total belowground biomass, and six of these sites provided separate measurements of live and dead root components. The study sites had from 1 to 29 years of biomass data with an average of three years per site. Five ecoregions were represented, including cold desert steppe, temperate dry steppe, humid savanna, humid temperate, and savanna. The selection of study sites was based on the availability of complete and consistent information on NPP or at least partial NPP, together with the dynamics of live biomass and dead matter for at least the growing season (Scurlock et al. 2002). Site-description metadata, such as latitude, longitude, elevation, and information on vegetation type (biome), soil type, and land-use history were also desirable for inclusion for study sites in the compilation. Study sites were included that had at least one reference from the peer-reviewed literature.There are two data files in comma-separated (.csv) format with this data set.Revision Notes: Only the documentation for this data set has been modified from the original data set publication. ",
         "license": "proprietary"
     },
@@ -142462,7 +142423,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948597-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948597-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_Grassland_613_2",
         "description": "In many grasslands, aboveground net primary productivity (ANPP) is commonly estimated by measuring peak aboveground biomass. Estimates of belowground net primary productivity (BNPP), and consequently, total net primary productivity (NPP), are more difficult. We addressed one of the three main objectives of the Global Primary Productivity Data Initiative for grassland systems - to develop simple models or algorithms to estimate missing components of total system NPP.",
         "license": "proprietary"
     },
@@ -142475,7 +142436,7 @@
         "bbox": "-99.38, 38.87, -99.38, 38.87",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752578763-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752578763-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_HYS_208_2",
         "description": "This data set contains three ASCII files (.txt format). Two files contain above- and below-ground biomass and productivity data for a mixed prairie grassland, one file for an ungrazed treatment and the other for a moderately grazed treatment. The study site (38.87 N, - 99.38 W, Elevation 714 m) is located in the central Great Plains near the city of Hays, Kansas, about 400-km west of Kansas City. The third file contains monthly and annual climate data for the period 1891-1994 obtained from a weather station (38.87 N, -99.38 W, Elevation 613 m) located at the Hays grassland study site. Dynamics of above-ground living and dead plant biomass were monitored by the harvest technique at roughly 2-week intervals during the growing season of 1970. Total below-ground biomass was sampled at the same intervals by manual coring within the harvested plots to a depth sufficient to include at least 90% of the root mass. Data were collected as part of a coordinated study over 1-3 years at ten grassland sites of the central and western United States, under the US Grassland Biome Project of the International Biological Program (IBP).Annual above-ground net primary production (ANPP) was estimated conservatively by summing peak biomass of individual species. These values were 363 g/m2/year for ungrazed and 372 g/m2/year for grazed grassland plots. Annual below-ground net primary production (BNPP) was estimated as the sum of positive increments in total root biomass (including root crowns); 1,062 g/m2/year for ungrazed and 855 g/m2/year for grazed grassland plots.",
         "license": "proprietary"
     },
@@ -142488,7 +142449,7 @@
         "bbox": "-148, -37.42, 145.17, 66.37",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751942730-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751942730-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogbmFpcm9iaSwga2VueWEsIDE5ODQtMTk5NCwgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9OUkJfMTUxXCIsXCIyXCIsMjc1MTkzOTE4NCwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IG5haXJvYmksIGtlbnlhLCAxOTg0LTE5OTQsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfTlJCXzE1MVwiLFwiMlwiLDI3NTE5MzkxODQsMl0ifQ%3D%3D/NPP_IBP_198_2",
         "description": "This data set provides four data files containing net primary productivity (NPP) data, edaphic characteristics, average climatic conditions, and basic descriptive and quantitative information on vegetation for 117 globally-distributed terrestrial forest sites. The data set was derived from the IBP (International Biological Programme) Woodlands Data Set of DeAngelis et al. (1981). The data were collected from the mid 1950s to the early 1970s and were compiled into an electronic data set at the Oak Ridge National Laboratory to facilitate comparisons involving the diverse woodland ecosystems. One data file provides a complete synthesis of NPP, vegetation, edaphic, and climate data and data-source references for each of the 117 sites as published in DeAngelis et al. (1981) for a total of 5,887 records. The second file provides site location, biome, and selected forest productivity and soils data for the 117 sites. The third file provides summary climate data (temperature, precipitation, radiation, growing season length) for each site, and the fourth file provides forest type, investigator(s), and years of the study for each site. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally archived in 1997 (DeAngelis, et al, 1997.) ",
         "license": "proprietary"
     },
@@ -142501,7 +142462,7 @@
         "bbox": "16.5, 60.82, 16.5, 60.82",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943280-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943280-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibmFzbW8tdGlhbSAyNTBtIDE2LWRheSBub3J0aCBhbWVyaWNhIHN1cmZhY2Ugc29pbCBtb2lzdHVyZSBkYXRhc2V0XCIsXCJPUk5MX0NMT1VEXCIsXCJOQVNNb19UaUFNXzI1MG1fMjMyNlwiLFwiMVwiLDI5MDU0NTc3NjUsMl0iLCJ1bW0iOiJbXCJuYXNtby10aWFtIDI1MG0gMTYtZGF5IG5vcnRoIGFtZXJpY2Egc3VyZmFjZSBzb2lsIG1vaXN0dXJlIGRhdGFzZXRcIixcIk9STkxfQ0xPVURcIixcIk5BU01vX1RpQU1fMjUwbV8yMzI2XCIsXCIxXCIsMjkwNTQ1Nzc2NSwyXSJ9/NPP_JDR_202_2",
         "description": "This data set contains three files (.txt format). Two of the files contain stand characteristics, above- and below-ground biomass, and above- and below-ground production allocation data for Scots pine (Pinus sylvestris) forests near Jadraas, Sweden. One file is for a young regenerating forest (14-20 years old) and the other is for an old-growth forest (120-125 years old). The field measurements were made by destructive and non-destructive methods between 1973 and 1983. The third file contains climate data recorded at the Jadraas site from 1974 through 1990.The research was conducted under the auspices of SWECON (Swedish Coniferous Forest Biome) Project to enhance understanding of plant biomass dynamics and factors regulating plant growth. Most of the research concerned plant and vegetation processes, but particular interest was also given to soil processes, consumption processes, and energy and water exchange in the canopy and the soil.Total net primary production (NPP) in the young forest was estimated at 860 g/m2/year (above-ground = 372 g/m2/year; below-ground = 488 g/m2/year). NPP for the old-growth forest was not calculated; however, the data set contains estimates of branch and trunk growth (43 g/m2/year and 106 g/m2/year, respectively), annual litterfall (135-162 g/m2/year), needle grazing loss (1.55 g/m2/year), fine tree root production (188 g/m2/year), and understory root production (30 g/m2/year).Revision Notes: The NPP data file has been split into two files, one for the young regenerating forest and one for old-growth forest. The data files have been revised to correct previously reported data and information and to add new data from published sources. Please see the ORNL DAAC Data Set Change Information file for more information. ",
         "license": "proprietary"
     },
@@ -142514,7 +142475,7 @@
         "bbox": "-76.65, 18.08, -76.65, 18.08",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945511-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945511-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIG11bHRpLWJpb21lOiBncmlkZGVkIGVzdGltYXRlcyBmb3Igc2VsZWN0ZWQgcmVnaW9ucyB3b3JsZHdpZGUsIDE5NTQtMTk5OCwgcjNcIixcIk9STkxfQ0xPVURcIixcIk5QUF9HUklEREVEX0dQUERJXzYxNFwiLFwiNFwiLDI3NTU1NzE0MjYsMl0iLCJ1bW0iOiJbXCJucHAgbXVsdGktYmlvbWU6IGdyaWRkZWQgZXN0aW1hdGVzIGZvciBzZWxlY3RlZCByZWdpb25zIHdvcmxkd2lkZSwgMTk1NC0xOTk4LCByM1wiLFwiT1JOTF9DTE9VRFwiLFwiTlBQX0dSSURERURfR1BQRElfNjE0XCIsXCI0XCIsMjc1NTU3MTQyNiwyXSJ9/NPP_JHN_475_2",
         "description": "This data set contains five NPP data files and three climate data files (ASCII .txt format). There is one NPP file for each of the five sub-types of upper montane tropical forest located along John Crow Ridge in the Blue Mountains of Jamaica. Biomass, productivity, tree mortality, standing crop of litter, LAI, and nutrient content of leaf fall were measured from 1974 to 1978. Long-term climate data are available from Cinchona Botanic Gardens, approximately 3 km south of the John Crow Ridge study area and at similar elevation.The John Crow Ridge study areas (18.08 N 76.65 W) consist of 8 to 10 contiguous 10 m x 10 m permanent plots. The forests are of low stature and appear to be completely undisturbed. The forest floor at one sub-site (Mor Ridge) was overlain by a 30-50 cm layer of mor humus with a high C/N ratio.ANPP was estimated to be between 654-997 g/m2/year (sum of litterfall and trunk/branch increment), or 854-1,057 g/m2/year (including tree mortality). These figures are lower than for lowland tropical forests with greater leaf turnover and reflect the relatively low stature of the upper montane forest plots. Above-ground biomass was estimated by both destructive methods and nondestructive regression analysis. Values ranged from 23,000 to 34,000 g/m2. Below-ground biomass (5,370 g/m2) was determined for one site by harvesting roots to a depth of 50 cm. LAI for trees plus understory, where measured, was 5.5-5.7 m2/m2.",
         "license": "proprietary"
     },
@@ -142527,7 +142488,7 @@
         "bbox": "-106.85, 32.6, -106.85, 32.6",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752582478-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752582478-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_JRN_209_2",
         "description": "This data set contains three ASCII files (.txt format). Two files contain above- and below-ground biomass and productivity data for a desert grassland in the Jornada Experimental Range, New Mexico, one file for an ungrazed treatment and the other for a light to moderately grazed treatment. The study site (32.60 N, -106.85 W, Elevation 1,350 m) is located in the Basin and Range geomorphic province at the northernmost extent of the Chihuahuan Desert, near the city of Las Cruces, New Mexico, about 60-km northwest of El Paso, Texas. The third file contains climate data for the period 1954-1992 obtained from a weather station located near the study site (32.62 N, -106.73 W, Elevation 1,300 m).Dynamics of above-and below-ground plant biomass were monitored at roughly 2-week intervals during the growing season from 1970 to 1972. Data on above-ground live biomass, recent and old dead matter, and root-crown biomass are available for one to two replications of grazed and \"ungrazed\" (relatively undisturbed) treatments. Total below-ground biomass was also sampled. Data were collected as part of a coordinated study over 1-3 years at ten grassland sites of the central and western United States, under the US GrasslandBiome Project of the International Biological Program (IBP).Annual above-ground net primary production (ANPP) was estimated, conservatively, by summing peak biomass of individual species, and annual below-ground net primary production (BNPP) estimated as the sum of positive increments in total root biomass. ",
         "license": "proprietary"
     },
@@ -142540,7 +142501,7 @@
         "bbox": "-0.92, 6.15, -0.92, 6.15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752610968-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752610968-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIG11bHRpLWJpb21lOiBncmlkZGVkIGVzdGltYXRlcyBmb3Igc2VsZWN0ZWQgcmVnaW9ucyB3b3JsZHdpZGUsIDE5NTQtMTk5OCwgcjNcIixcIk9STkxfQ0xPVURcIixcIk5QUF9HUklEREVEX0dQUERJXzYxNFwiLFwiNFwiLDI3NTU1NzE0MjYsMl0iLCJ1bW0iOiJbXCJucHAgbXVsdGktYmlvbWU6IGdyaWRkZWQgZXN0aW1hdGVzIGZvciBzZWxlY3RlZCByZWdpb25zIHdvcmxkd2lkZSwgMTk1NC0xOTk4LCByM1wiLFwiT1JOTF9DTE9VRFwiLFwiTlBQX0dSSURERURfR1BQRElfNjE0XCIsXCI0XCIsMjc1NTU3MTQyNiwyXSJ9/NPP_KDE_216_2",
         "description": "This data set contains one NPP data file and two climate data files (ASCII .txt format). The NPP file contains above- and below- ground biomass, litterfall, standing litter crop, and nutrient content data for a moist semi-deciduous secondary tropical forest at the Kade Agricultural Research Station (6.15 N 0.92 W), Ghana, spanning several collections periods between 1957 and 1972. Climate data come from weather stations at Kade near the study site (1958-1997) and at Kumasi near Kade (1945-1990).The Kade study site is typical of an old secondary forest which has probably not been cultivated or harvested since around 1915-1925. Tree basal area measured in 1957 was quite high at 33.7 m2/ha; measurements in 1968 of a plot a few hundred meters away gave 30.6 m2/ha.Detailed above- and below-ground biomass data are provided from a single clear-felling made in 1957. Nutrient content for lianas, leaves and twigs, branches, large wood, standing dead wood, stumps, litter, and roots is also provided. Total live + dead biomass was 36,102 g/m2, of which 5,414 g/m2 (15%) was below-ground live biomass and 23,568 g/m2 was above-ground live biomass. Monthly litterfall is available for 26 months (1970-72).Total annual NPP was estimated in the late 1950s at about 2,400 g/m2/year based on litterfall of 1,054 g/m2/year plus rough estimates of timber fall (1,070-1,121 g/m2/year) and root production (258 g/m2/year). In the 1970s, NPP was recalculated at 2,200-2,500 g/m2/year based on additional measurements of litter, wood fall, and decomposition. ",
         "license": "proprietary"
     },
@@ -142553,7 +142514,7 @@
         "bbox": "99.8, 7.58, 99.8, 7.58",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752614515-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752614515-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIG11bHRpLWJpb21lOiBncmlkZGVkIGVzdGltYXRlcyBmb3Igc2VsZWN0ZWQgcmVnaW9ucyB3b3JsZHdpZGUsIDE5NTQtMTk5OCwgcjNcIixcIk9STkxfQ0xPVURcIixcIk5QUF9HUklEREVEX0dQUERJXzYxNFwiLFwiNFwiLDI3NTU1NzE0MjYsMl0iLCJ1bW0iOiJbXCJucHAgbXVsdGktYmlvbWU6IGdyaWRkZWQgZXN0aW1hdGVzIGZvciBzZWxlY3RlZCByZWdpb25zIHdvcmxkd2lkZSwgMTk1NC0xOTk4LCByM1wiLFwiT1JOTF9DTE9VRFwiLFwiTlBQX0dSSURERURfR1BQRElfNjE0XCIsXCI0XCIsMjc1NTU3MTQyNiwyXSJ9/NPP_KHC_217_2",
         "description": "This data set contains one net primary productivity (NPP) data file and three climate data files (.txt format) for a fully closed tropical rainforest in the Khao Chong Reserve (7.58 N 99.8 E) in southern Thailand. The Reserve comprises 500 ha of well-preserved rainforest considered typical of the region, although maximum tree height (36 m) and biodiversity were less than in Malaysian forests. Net primary productivity (NPP) was estimated as the sum of annual net above-and below-ground biomass increase plus extrapolated annual litterfall and tree mortality. Biomass increment for trees > 4.5 cm diameter at breast height (DBH) was monitored between 1962 to 1965, and daily litterfall was measured for one month in 1962. Total NPP was estimated at 2,860 g/m2/year. This value includes a possible over-estimate of litterfall (2,330 g/m2/year) plus above-ground woody biomass increment and turnover as mortality combined (489 g/m2/year) plus below-ground woody biomass increment (41 g/m2/year). Fine root turnover and herbivory were not included in these estimates. Allometric relationships for estimating above-ground biomass were checked by destructive harvest. Leaf area index was relatively high at 11.4-12.3 m2/m2. Long-term climate data for Khao Chong are available from weather stations at Songkhla, Thailand (7.2 N 100.6 E) and Trang, Thailand (7.52 N 99.62 E). Depending on station location and temporal coverage, mean annual temperature is 27.2-27.4 C and mean annual precipitation is between 1,928 and 2,696 mm. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1998.",
         "license": "proprietary"
     },
@@ -142566,7 +142527,7 @@
         "bbox": "38, 47.17, 38, 47.17",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751936985-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751936985-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_KHM_146_2",
         "description": "This data set provides two data files in text format (.txt). One file contains biomass measurements made in 1948 and between 1967 and 1970 for a humid temperate steppe in the Khomutovskaya Steppe Nature Reserve in the Donezk Region of Ukraine. The second file contains monthly and annual climate data for the study site for the period 1955-1972.Biomass measurements were made once in July of 1948 and biweekly to monthly during the growing season (April-August/September) from 1967 to 1970 at the permanent Khomutovskaya research station. ANPP was calculated for each sampling date and cumulatively over the four years, 1967-1970. Averaged over the time series, above-ground live phytomass, standing dead, and litter biomass were estimated to be 340, 90, and 240 g/m2 (dry matter weight), respectively, while below-ground phytomass and mortmass were estimated to be 1,675 and 792 g/m2 (dry matter weight), respectively. ANPP was estimated to be 460 g/m2/yr. BNPP was estimated to be 1,340 g/m2/yr.",
         "license": "proprietary"
     },
@@ -142579,7 +142540,7 @@
         "bbox": "100.9, 6.3, 100.9, 6.3",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751937461-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751937461-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_KLN_147_2",
         "description": "This data set provides three data files in text format (.txt). One file contains monthly biomass measurements and Net Primary Productivity (NPP) estimates made between April 1984 and July 1990 on a semi-natural tropical monsoon grassland in southern Thailand. The second file contains a year-long record of monthly biomass measurements and NPP estimates made on a portion of the same grassland that was accidentally burned in January 1985. The third file contains monthly and annual climate data for the study site for the period 1973-1989.Two accidental fires occurred during the course of the study; the one in January 1985 burnt 40% of the study area and the other in February 1986 burnt most of the site. During 1985, sampling occurred simultaneously on unburned primary and burned secondary portions of the grassland; afterwards sampling continued on the primary site. Measurements of above- and below-ground live and dead biomass were made on the 15th day of each month. NPP estimates were calculated from changes in biomass and decomposition rates in unburned areas from 1984 through 1986. From April 1984 to April 1985, NPP was 2,036 g/m2/yr, with below-ground organs contributing 23% of this total. Production in the unburned area in 1985 was substantially lower (1,677 g/m2/yr) which coincided with a 35% decrease in mean leaf area index. NPP in the 1985 burned area was only slightly lower (1,524 g/m2/yr); however, NPP was substantially lower after the second fire in 1986 (134 g/m2/yr).Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996.",
         "license": "proprietary"
     },
@@ -142592,7 +142553,7 @@
         "bbox": "-96.61, 39.1, -96.61, 39.1",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751937858-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751937858-ORNL_CLOUD.html",
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         "description": "This data set contains three ASCII files (.txt format). Two files contain above-ground biomass and productivity data for a humid temperate tall-grass prairie grassland located in the Konza Prairie Natural Research Area, Kansas. One file provides data for an unburned treatment and the other for a burned treatment for 1975 to 1990. The third file contains climate data for the period 1891-1988 obtained from a weather station at Konza. The above-ground net primary productivity measurement presented here (394 g/m2/year) is a 10-year average (1975-1984) based on peak seasonal live biomass values averaged for burned and unburned lowland and upland grasslands. The Konza study site (39.10 N, - 96.61 W, Elevation 400 m) is situated near the town of Manhattan in north-eastern Kansas, about 170-km west of Kansas City. The Konza research program is built upon a long-term database on ecological pattern and process data derived from a fully replicated watershed-level experimental design, in place at the Konza Prairie Biological Station since 1977. This design includes replicate watersheds subject to different fire and grazing treatments. Within the watersheds, permanent sampling transects are replicated at various topographic positions, where plant species composition, plant and consumer populations, above-ground net primary production (ANPP), soil properties, and other key above- and below-ground processes are measured. In addition to these watershed-level studies, the Konza Long Term Ecological Research (LTER) program includes a number of long-term plot-level experiments. ",
         "license": "proprietary"
     },
@@ -142605,7 +142566,7 @@
         "bbox": "76.85, 29.97, 76.85, 29.97",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751941068-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751941068-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_KRK_193_2",
         "description": "This data set contains two ASCII files (.txt format). One file contains above- and below-ground biomass (including standing dead material and litter) and productivity data for a tropical grassland at Kurukshetra University (29.97 N, 76.85 E, Elevation 247 m) in northern India, about 150-km north-northwest of Delhi. The second file contains climate data from a weather station located at the study site. Biomass measurements were made monthly by harvest methods from mid-May 1970 to mid-May 1971. Annual net primary productivity (NPP) was calculated for the grassland according to several methods, with preference shown for the estimate given by summing positive increases in biomass and accounting for mortality. Total NPP was estimated at 3,538 g/m2/yr, with above-ground net primary productivity (ANPP) of 2,407 g/m2/yr and below-ground net primary productivity (BNPP) of 1,131 g/m2/yr. Seasonal changes in the vegetation were studied through tiller analysis. Examination of vertical distribution of above-ground biomass showed that different layers of vegetation were dominated by different species in different months. ANPP was maximum during the rainy season (1,706 g/m2) and BNPP was maximum during the dry winter season (785 g/m2). Production was more directed above ground during the rainy season and below ground during the dry season. Apparent efficiency of energy conversion was calculated at 1.66% on the basis of 50% total solar radiation. ",
         "license": "proprietary"
     },
@@ -142618,7 +142579,7 @@
         "bbox": "36.5, 51.67, 36.5, 51.67",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751938395-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751938395-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIGdyYXNzbGFuZDogYmVhY29uIGhpbGwsIHUuay4sIDE5NzItMTk5MywgcjFcIixcIk9STkxfQ0xPVURcIixcIk5QUF9CQ05fMjA0XCIsXCIyXCIsMjc1MjU1MTQyNiwyXSIsInVtbSI6IltcIm5wcCBncmFzc2xhbmQ6IGJlYWNvbiBoaWxsLCB1LmsuLCAxOTcyLTE5OTMsIHIxXCIsXCJPUk5MX0NMT1VEXCIsXCJOUFBfQkNOXzIwNFwiLFwiMlwiLDI3NTI1NTE0MjYsMl0ifQ%3D%3D/NPP_KRS_149_2",
         "description": "This data set provides two data files in text format (.txt). One file contains a long time series of biomass measurements made between 1954 and 1983 on a virgin meadow steppe in the Central-Chernozem V.V. Alyekhin Natural Reserve, Kursk Region, Russia. The second file contains monthly and annual climate data for the study site for the period 1947-1983.Above-ground live biomass measurements were made at biweekly to monthly intervals over the entire 30-year time series. Discontinuous measurements of above-ground standing dead matter and litter biomass (1956-1983) and below-ground live and dead biomass (1972-1973 and 1981-1983) were also made. Cumulative ANPP was estimated at the end of the growing season (1956-1963 and 1972-1973) and monthly (1982-1983). Averaged over the time series, above-ground live phytomass, standing dead, and litter biomass were estimated to be 362, 344,  and 424 g/m2 (dry matter weight), respectively, while below-ground phytomass and mortmass were 910 and 1,370 g/m2  (dry matter weight), respectively. ANPP was estimated to be 774 g/m2/yr and BNPP was estimated to be 1,700 g/m2/yr for a TNPP estimate of 2,474 g/m2/yr. The study site is one of eight major grassland types of Eurasia which encompass an extremely wide climatic gradient in the direction of increasing maximum summer temperatures and continentality and decreasing precipitation in a north-west to the south-east band of steppes in the European and Asian parts of the former USSR (Commonwealth of Independent States). Kurst, on rich loamy chernozem soil, is one of the most productive upland grassland ecosystems of Russia with annual mean maximum/minimum temperatures of 24.8/-14.4 C and annual mean precipitation of 582.7 mm for the period 1947-1983. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996. ",
         "license": "proprietary"
     },
@@ -142631,7 +142592,7 @@
         "bbox": "29.32, 66.37, 29.32, 66.37",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944012-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944012-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibmFzbW8tdGlhbSAyNTBtIDE2LWRheSBub3J0aCBhbWVyaWNhIHN1cmZhY2Ugc29pbCBtb2lzdHVyZSBkYXRhc2V0XCIsXCJPUk5MX0NMT1VEXCIsXCJOQVNNb19UaUFNXzI1MG1fMjMyNlwiLFwiMVwiLDI5MDU0NTc3NjUsMl0iLCJ1bW0iOiJbXCJuYXNtby10aWFtIDI1MG0gMTYtZGF5IG5vcnRoIGFtZXJpY2Egc3VyZmFjZSBzb2lsIG1vaXN0dXJlIGRhdGFzZXRcIixcIk9STkxfQ0xPVURcIixcIk5BU01vX1RpQU1fMjUwbV8yMzI2XCIsXCIxXCIsMjkwNTQ1Nzc2NSwyXSJ9/NPP_KSM_466_2",
         "description": "This data set contains three files (.txt format). One file provides stand characteristics, biomass, and production allocation data for an old-growth boreal forest near Kuusamo, Finland. The research was conducted during the 1967-1972 growing seasons. The other two files provide climate data from a weather station about 60 km south of the forest. One record contains precipitation and mean average temperature data for the 1961-1994 period (excluding 1971-1980) and the other contains precipitation data for 1908-1994. The Kuusamo research site is located just south of the Arctic Circle (66.37 N 29.32 E) and belongs to the northern boreal zone of taiga forests. The forest is an old Hylocomium-Myrtillus type spruce forest which has remained in a natural state and reached climatic climax long ago. The average age of the dominant spruces (Picea abies) is about 260 years. There is a well-developed ground layer of vegetation, chiefly dwarf scrub and mosses (dominant species: Vaccinium myrtillus, V. vitis-idaea, Hylocomium splendens, and Pleurozium schreberi). The northerly location of the forest and the age of its trees are the main factors responsible for low biomass and net production figures in comparison with spruce forests further south. Total above-ground biomass (including tree, understory, and moss layers) was determined by harvest methods and estimated to be 10,194 g/m2. Below-ground tree biomass estimates, also determined by harvest methods, are less reliable, at 3,753 g/m2. Total net primary productivity (NPP) for this site was estimated to be 441 g/m2/yr (421 g/m2/yr above-ground, 20 g/m2/yr below-ground).",
         "license": "proprietary"
     },
@@ -142644,7 +142605,7 @@
         "bbox": "-5.03, 6.22, -5.03, 6.22",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751938861-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751938861-ORNL_CLOUD.html",
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         "description": "This data set provides three data files in text format (.txt). One file contains monthly above-ground biomass measurements made in 1965 in a humid grass savanna at the Lamto Research Station, Cote Ivoire, Africa. The second file contains monthly above- and below-ground biomass measurements and calculations of carbon/nitrogen ratio of above-ground live and dead biomass and below-ground biomass from the same site for 1969-1987. The third file contains monthly and annual climate data for the study site for the period 1969-1990.Total net primary production (NPP) of the Loudetia simplex grass savanna was estimated at 2,150 g/m2/yr, of which 1,320 g/m2/yr (61%) was below-ground production. Normally 50-90% of above-ground grass biomass is burned annually,Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996. ",
         "license": "proprietary"
     },
@@ -142657,7 +142618,7 @@
         "bbox": "-65.82, 18.27, -65.73, 18.33",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945793-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945793-ORNL_CLOUD.html",
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         "description": "This data set contains ten ASCII files (.txt format), one NPP file for each of the nine different montane tropical rainforest sites within the Luquillo Experimental Forest (LEF) of Puerto Rico and one file containing climate data. The NPP study sites are located along an environmental gradient of different soils, elevation (100-1,000 m), develop stage, and mean annual rainfall. Field measurements were carried out from 1946 through 1994.",
         "license": "proprietary"
     },
@@ -142670,7 +142631,7 @@
         "bbox": "-71.42, -45.6, -71.42, -45.6",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752586142-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752586142-ORNL_CLOUD.html",
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         "description": "This data set contains two ASCII files (.txt format). One file provides monthly above-ground live biomass, dead matter, and litter data and daily above-ground net primary productivity (ANPP) data for a temperate grassland steppe at the Media Luna Ranch in Patagonia, Argentina (45.60 S, 71.42 W, Elevation 630 m) for the period May 1981 to March 1983. The second file contains climate data recorded at Media Luna Ranch from 1981 through 1985. Productivity of the steppe was monitored at monthly or bi-monthly intervals during two growing seasons. The ANPP measurement presented here is the sum of the increase in above-ground live biomass, dead matter, and litter. ANPP was estimated to be 0.00-0.15 g/m2/day in winter months (May-September) and 0.22-0.94 g/m2/day in the warmer months. Annual ANNP was estimated to be 35 g/m2/year. The study site is a 2.5-hectare exclosure situated on the Rio Mayo terraces. The steepe represents one of the most important grassland areas of Patagonia which occupy a narrow belt in the foothills of the Andes. The region has been over-grazed by introduced livestock since the early 1900s, and is currently used for sheep production. ",
         "license": "proprietary"
     },
@@ -142683,7 +142644,7 @@
         "bbox": "-73.56, 6.39, -73.56, 6.39",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946032-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946032-ORNL_CLOUD.html",
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         "description": "This data set contains two NPP data files and one climate data file (ASCI .txt format). The NPP files contain data for above-ground biomass, litterfall, and nutrient content of above-ground vegetation, organic surface layer, and soils measured during an 18-month period in 1970 and 1971 at two contrasting tropical seasonal evergreen forests in Magdalena Valley, Colombia. The climate record provides mean monthly and annual precipitation (1951-1992) and mean monthly and annual average temperature (1970-1997) from Barranca Bermeja (7.00 N 73.80 W) near the Magdalena Valley sites. ",
         "license": "proprietary"
     },
@@ -142696,7 +142657,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2755668037-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2755668037-ORNL_CLOUD.html",
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         "description": "This data set contains one data file (.csv format) that quantifies net primary productivity (NPP) as a function of rainfall in mesic to wet montane rainforests on the island of Maui, Hawaii, U.S.A. The NPP data were collected at six mature forests stands that comprise the Maui Moisture Gradient, a sequence of sites located on Maui where mean annual precipitation ranges from 2,200 mm to 5,050 mm while temperature and all other state factors (parent material, substrate age, organisms, and topography) that control NPP remain relatively constant. ",
         "license": "proprietary"
     },
@@ -142709,7 +142670,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947828-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947828-ORNL_CLOUD.html",
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         "description": "This data set includes six ASCII files (.txt format). Five files contain productivity values for several types of tropical Amazon rainforest near Manaus, Brazil studied between 1963 and 1990, and one file contains monthly and annual climate data for the period 1910-1993.",
         "license": "proprietary"
     },
@@ -142722,7 +142683,7 @@
         "bbox": "-98.91, 19.46, -98.91, 19.46",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943588-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751943588-ORNL_CLOUD.html",
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         "description": "This data set provides three data files in text format (.txt). One file contains monthly biomass measurements and net primary productivity (NPP) estimates made between June 1984 and December 1994 on an ungrazed saline grassland (MNT1) that was accidently burned in February 1986 at the Colegio de Postgraduados field station site, Montecillo, Mexico. The second file contains a shorter time series of monthly biomass measurements and NPP estimates on an adjacent saline grassland (MNT2) that was burned in May 1989, probably by local farmers following normal burning practices. Both files also contain above-and below-ground dead matter decomposition rates. There are data gaps in both files. The third file contains monthly and annual climate data for the period 1963-1989 from the Chapingo meteorological station located 5 km northeast for the study area.Annual NPP at MNT1 was calculated for 1985-1987 to determine impacts of the unexpected fire. Above-ground NPP (NPP) averaged 669.2 g/m2/yr despite post-fire decline and recovery and variable rainfall over the period. Below-ground NPP (BNPP) was higher, averaging 1,007 g/m2/yr, but with a similar post-fire decline and recovery pattern. Total NPP reflected the yearly variation in ANPP and BNPP, averaging 1,676 g/m2/yr over the 3 year period. Monthly ANPP and BNPP values for MNT2 were lower overall but were not analyzed to determine annual trends.Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996. ",
         "license": "proprietary"
     },
@@ -142735,7 +142696,7 @@
         "bbox": "145.18, -6, 145.18, -6",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946089-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946089-ORNL_CLOUD.html",
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         "description": "This data set contains two ASCII files (.txt format), one providing net primary production (NPP) component data for a lower montane rainforest and the other providing climate data. The NPP studies were conducted at Marafunga (6.00 S 145.18 E) in the highlands of Papua New Guinea to the east of Mount Kerigomna, about 25 km west of the town of Goroka. LAI, litterfall, litter standing crop and decomposition, and nutrient content of different vegetation components were measured from November 1970 through December 1971 at four representative forest stands: Ridge Top; Ridge Gap; Valley; and Slope. Forest inventories and field measurements of above- and below-ground biomass were made by destructive harvest at a fifth stand (Ridge Top) during October-December 1970 and April-August 1971. The results of these studies are given for the forest at large. The only component of NPP determined at Marafunga was litterfall (755 g/m2/year). ",
         "license": "proprietary"
     },
@@ -142748,7 +142709,7 @@
         "bbox": "-83.38, 46.35, -83.38, 46.35",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946671-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946671-ORNL_CLOUD.html",
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         "description": "This data set contains two files (.txt format) for study sites in the Mississagi River area of Ontario, Canada (46.35 N -83.38 W elevation 860 m). One file summarizes the results of a series of investigations on the nutrition of jack pine ecosystems, including stand characteristics, above-ground biomass, and where available, litterfall amount and nutrient content of vegetation, litterfall, and soil horizons. Field data were collected in three jack pine (Pinus banksiana) study plots between 1969 and 1973. The stands were 20, 30, and 65 years of age. The second file contains climate data recorded at two weather stations near the Mississagi sites. Precipitation data were obtained from Saulte Sainte Marie, Michigan, USA (46.5 N -84.4 W elevation 218 m) and temperature data were obtained from Saulte Sainte Marie, Ontario, Canada (46.5 N -84.5 W elevation 188 m). Net primary productivity (NPP) was not directly measured, but is estimated based on above-ground tree growth and litterfall. For the different aged stands, above-ground tree growth was estimated at 262 g/m2/yr (0-20 years), 289 g/m2/yr (20-30 years), and 93 g/m2/yr (30-65 years). Annual tree litter production for the 30-year-old stand averaged 372.9 g/m2/yr over the course of 3 years. Understory litterfall production for the 30-year-old stand in one year was 33.1 g/m2/yr. Revision Notes: The NPP and climate data files for Mississagi have been revised to correct previously reported temporal coverage and litterfall data. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
@@ -142761,7 +142722,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944500-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944500-ORNL_CLOUD.html",
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         "description": "This data set contains five ASCII files (.txt format). Three files contain productivity data for a mixed prairie at the Matador Field Station, Canada, and two files contain climate data. The 8-km2 Matador Field Station (50.70 N, -107.72 W, Elevation 676 m) is located approximately 47-km north of the city of Swift Current in southern Saskatchewan Province at the northern limit of the \"mixed prairie\" portion of the North American Great Plains. The study area is located on the bed of a former glacial lake. One NPP file contains monthly measurements of above-ground standing live and dead biomass and litter made in \"Section 16\" by harvest methods during the growing season from March or April 1968 to October or November 1972. The second NPP file contains monthly measurements of root biomass made at different depths in \"Section 16\" during the growing season from April 1968 to July 1971. The third NPP file contains monthly above-ground biomass estimates for a secondary study area during the growing season from May 1970 to August 1972. The climate data are reported from two locations, one file from a weather station at Swift Current (1938-1990) and the other from a weather station at the Field Station during the study period (1968-1972). The above- and below-ground net primary productivity (ANPP and BNPP, respectively) were calculated for \"Section 16\" only. ANPP (363 g/m2/yr) was sum of the increase in green biomass over the growing season, plus increase in dead biomass and litter. BNPP (600 g/m2/yr) was the increase in root biomass over the growing season.",
         "license": "proprietary"
     },
@@ -142774,7 +142735,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949500-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949500-ORNL_CLOUD.html",
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         "description": "This data set contains one data file (.csv format) that provides net primary productivity (NPP) estimates for 34 grasslands, 14 tropical forests, and 5 boreal forest sites distributed worldwide. The NPP data were compiled from published literature. In addition to above- and below-ground NPP, and total NPP estimates, the file includes site name and location, biome type, mean annual precipitation, and mean annual temperature, where available. Aboveground net primary production (ANPP),  ranged from 35 to 2,320 g/m2/year, belowground net primary production (BNPP) ranged from 20 to 1,832 g/m2/year, and total net primary production (TNPP) ranged from 182 to 3,538 g/m2/year. Revision Notes: This data file has been revised to add a negative sign to south latitude and west longitude decimal degree coordinates,  and the compass direction (N, S, E, W) for coordinates has been removed. NPP data for Vindhyan, India; Atherton, Australia; John Crow Ridge, Jamaica; and La Selva, Costa Rica, have been revised to correct previously reported values. Additional data references for Kuusamo, Finland, and La Selva, Costa Rica, have been added. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751950299-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751950299-ORNL_CLOUD.html",
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         "description": "This data set, NPP Multi-Biome: Summary Data from Intensive Studies at 125 Sites, 1936-2006, contains a single shapefile that provides site-level summary statistics from 125 sites in five biomes: boreal forest, grassland, temperate forest, tropical forest, and tundra. The spatial coverage is global and spans the time period from 1936 through 2006. Study periods, and both spatial and temporal resolution vary by site. Data include georeferenced location, elevation, mean annual precipitation, mean annual minimum and maximum air temperature, dominant soil type, ecoregion type, dominant plant species, general vegetation types, annual mean or peak living above- and below-ground biomass, average annual above- and below-ground Net Primary Productivity (NPP), and reference information. Additionally study sampling period and intervals, plot management, and long-term site management history are also provided.",
         "license": "proprietary"
     },
@@ -142800,7 +142761,7 @@
         "bbox": "28.7, -24.65, 28.7, -24.65",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751941513-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751941513-ORNL_CLOUD.html",
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         "description": "This data set contains five data files in text format (.txt). Three files contain biomass dynamics data for a broad-leaved savanna located in the 800-hectare Nylsvley study site 200 km north of Johannesburg, South Africa. One net primary productivity (NPP) file contains monthly above-ground biomass data from harvests made between mid-October 1974 and mid-September 1977. A second NPP file contains three-year mean monthly values for above-ground, standing dead, and litter biomass. The third NPP file contains monthly below-ground living and dead biomass data from excavations made from August 1988 to November 1989. Climate data are provided in the other two files. One file contains air temperature data measured at the study site (1975-1983). The other file contains rainfall data measured at a nearby farmhouse (1917-1995).Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published.",
         "license": "proprietary"
     },
@@ -142813,7 +142774,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939184-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939184-ORNL_CLOUD.html",
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         "description": "This data set provides three data files in text format (.txt). One file contains a long time series of monthly biomass measurements and net primary productivity (NPP) estimates made between July 1984 and November 1994 on an ungrazed tropical dry savanna grassland in the Nairobi National Park, Kenya. The second file contains a shorter time series (October 1989-June 1991) of monthly biomass measurements made on an adjacent savanna that had been clipped in September 1989. The third file contains monthly and annual climate data for the study site for the period 1969-1989.Measurements of above-ground live phytomass, standing dead, and litter biomass were made on the 15th day of each month on the ungrazed grassland over the time series (except during 1987 and at a few other times). The time series for below-ground biomass (BNPP) measurements (live and dead) is more discontinuous with large gaps in 1987-1989. NPP estimates are only available for part of 1984 through 1986 on the ungrazed savanna. The above-ground NPP (ANPP) values averaged 1,004 g/m2/yr and BNPP averaged 875 g/m2/yr. The record of above- and below-ground biomass measurements for the clipped savanna is complete except for a few months in 1990. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published.",
         "license": "proprietary"
     },
@@ -142826,7 +142787,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752605983-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752605983-ORNL_CLOUD.html",
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         "description": "This data set contains three files. The first file provides net primary productivity (NPP) estimates, vegetation characteristics, and summary climate data for 720 globally-distributed terrestrial sites. Each site is geographically referenced (latitude/longitude) and classified according to biome (i.e., cropland, desert, forest, grassland, Mediterranean, pasture, plantation, savanna, tundra, and wetlands), where known. The data were extracted and synthesized from scientific literature dating from 1869 to 1982. The majority of references were published in the 1960s and 1970s. The second file provides a summary of climate, vegetation type, species, and type for the 720 records. The third file provides the bibliography of 858 original-source references of data on NPP from Esser et al. (1997). Literature that is not directly cross-referenced to the NPP data set records is marked with an asterisk (*). Of the 720 unique NPP records, about two-thirds have above-ground net primary production (ANPP) estimates that range between 1 and 8,530 g/m2/year dry matter, one-fourth of the sites have estimates for below-ground NPP that range between 0 and 5,828 g/m2/year, and more than half of the sites have total NPP estimates that range from 3 to 9,320 g/m2/year dry matter. The high-range estimates are lower when doubtful values, wetlands estimates, and estimates for crops/pastures and other managed systems are excluded from calculations. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1998. ",
         "license": "proprietary"
     },
@@ -142839,7 +142800,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751941950-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751941950-ORNL_CLOUD.html",
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         "description": "This data set contains two ASCII files (.txt format). One file contains monthly above-ground biomass data (total live biomass plus dead matter) for May 1956 to February 1958 for an annually burned, humid derived savanna in the Olokemeji Forest Reserve, Nigeria (7.42 N, 3.55 E) . This file also contains single measurements of above-ground biomass for years 1963 and 1964, single measurements of above-ground biomass at a nearby area for years 1960 and 1964, a single measurement of peak herbaceous leaf area index (LAI) for 1963, and a single measurement of peak tree/shrub LAI for 1964. Harvest procedures were used to measure biomass. LAI was determined by direct measurements. The second file contains climate data (precipitation amount and maximum/minimum temperature) from a weather station at the study site for the period 1956/01/01 through 1964/12/31.Annual above-ground net primary production (ANPP) estimates presented here are the sum of the increase in above-ground plant matter accumulation (total live biomass plus dead matter). ANPP of the herbaceous layer was estimated in 1957 to be around 680 g/m2/yr based on peak total clipped matter.",
         "license": "proprietary"
     },
@@ -142852,7 +142813,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752588786-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752588786-ORNL_CLOUD.html",
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         "description": "This data set contains three ASCII files (.txt format). Two files contain above- and below-ground biomass and productivity data for the Osage tallgrass prairie study site (36.95 N, -96.55 W, Elevation 392 m) in the U.S. Central Lowlands. There is one file for each treatment area (ungrazed and lightly grazed). The third file contains climate data from weather station at Pawhuska, Oklahoma (36.67 N, -96.35 W, Elevation of 255 m) near Osage.Dynamics of above- and below-ground plant biomass were monitored by harvest technique at roughly 2-week intervals during the growing season for the years 1970-1972. Data on above-ground live biomass, standing dead matter, and litter are available for two replications each at recently grazed and an \"ungrazed\" (relatively undisturbed) grassland sites at Osage. Below-ground biomass was sampled at 0-30 cm and 0-90 cm depths. The data were collected as part of a coordinated study over 1-3 years at ten grassland sites of the central and western United States, under the US Grassland Biome Project of the International Biological Program (IBP). Annual above-ground net primary production (ANPP) was estimated conservatively by summing peak biomass of individual species (346 g/m2/yr), and annual below-ground net primary production (BNPP) was estimated as the sum of positive increments in root biomass (including crown biomass) (542 g/m2/yr). Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1998. ",
         "license": "proprietary"
     },
@@ -142865,7 +142826,7 @@
         "bbox": "30.25, 60.83, 30.25, 60.83",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939511-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939511-ORNL_CLOUD.html",
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         "description": "This data set provides three data files in text format (.txt). Two files contain biomass and above-ground net primary production (ANPP) estimates for two upland meadows with contrasting soil types at the Otradnoe research station of the V.L. Komarov Botanical Institute of the Russian Academy of Sciences located on the Karelian peninsula 100-km to the north of St. Petersburg, Russia. The third file contains monthly and annual climate data recorded at the study site for the period 1968-1973. Measurements of above- and below-ground live and dead biomass were made at a sandy meadow (OTRS) from 1969 to 1972 and at a loamy meadow (OTRL) from 1969 to 1973. Additional biomass measurements were made at OTRS in June 1972 and at OTRL in May 1973. Monthly N, P, and S content of above-ground live biomass were measured 1969-1971 at OTRS.Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996. ",
         "license": "proprietary"
     },
@@ -142878,7 +142839,7 @@
         "bbox": "-124.02, 44.27, -121.17, 44.95",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945080-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751945080-ORNL_CLOUD.html",
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         "description": "This data set provides net primary productivity (NPP) estimates and associated field measurements for six sites located along the 250-km, west-east transect of the Oregon Transect Ecosystem Research Project (OTTER) in the Pacific Northwest. Leaf area indices, biomass, and NPP vary about 10-fold across the OTTER transect. Leaf area index (LAI) ranges from 0.4 m2/m2 at the Juniper/Sisters site to 8.6 m2/m2 at the Scio western Cascade site. Total NPP follows a similar trend with the Juniper/Sisters site having the lowest NPP value (300 g/m2/yr) and the Scio site having the highest (2,250-2,570 g/m2/yr). Total tree biomass across the transect ranges from to 1,080 g/m2 at Juniper/Sisters to 71,080 g/m2 at Cascade Head. Vegetation intercepts 22% to 99.5% of incident photosynthetically active radiation along the transect.There is one data file (.csv format) with this data set. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1999. ",
         "license": "proprietary"
     },
@@ -142891,7 +142852,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2755541560-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2755541560-ORNL_CLOUD.html",
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         "description": "There is one comma-separated (.csv) data file and one text (.txt) file (bibliographic information) with this data set. This data set provides above-ground net primary production (ANPP) and total net primary producitivity (NPP) [expressed in grams of carbon per square meter per year (gC/m2/year)], and the C fraction used to convert dry biomass weight to carbon content, for 127 unique study sites in northern Eurasia. The sites are classified by ecozone (i.e., tundra, forest-tundra, taiga, mixed forest, broadleaf forest, small-leaved secondary forests, forest bogs, meadows, steppe, semi-desert, and polar desert) and plant community (phytocoenosis). Each study location is georeferenced (latitude/longitude) with elevation and zonal/interzonal information. References to original author, year of publication, and table/record in Bazilevich (1993) are also included. The data set also provides a bibliography of 274 original-source references (in Russian) to accompany the 127 data records on NPP from Bazilevich (1993). The data are a subset of data adapted from Bazilevich, N.I. 1993. Biological Productivity of Ecosystems of Northern Eurasia. Nauka Publishers, Moscow. 293 pp. (in Russian). The data set originated from field measurements of primary productivity collected between 1940 and 1988 for most of the terrestrial vegetation types in northern Eurasia.  The NPP data collection contains field measurements of biomass, estimated NPP, and climate data for terrestrial grassland, tropical forest, temperate forest, boreal forest, and tundra sites worldwide. Data were compiled from the published literature for intensively studied and well-documented individual field sites and from a number of previously compiled multi-site, multi-biome data sets of georeferenced NPP estimates. The principal compilation effort (Olson et al., 2001) was sponsored by the NASA Terrestrial Ecology Program. For more information, please visit the NPP web site at http://daac.ornl.gov/NPP/npp_home.html.",
         "license": "proprietary"
     },
@@ -142904,7 +142865,7 @@
         "bbox": "-69.83, -45.43, -69.83, -45.43",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752591369-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752591369-ORNL_CLOUD.html",
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         "description": "This data set contains two ASCII files (.txt format). One file contains monthly productivity data measured on an arid dwarf-shrub steppe in northern Patagonia, Argentina from August 1980 to March 1982. The second file contains climate data recorded at a weather station set up onsite for the duration of the NPP study.Dynamics of above-ground biomass, dead matter, and litter were monitored at Pampa de Leman (-45.43 S, -69.83 W, Elevation 400 m) at monthly or bi-monthly intervals in a 1.5-hectare exclosure area protected from sheep grazing. The vegetative community is dominated by the dwarf shrub Nassauvia glomerulosa, with two grasses (Poa dusenii and Hordeum comosum).Annual above-ground net primary productivity (ANPP) of 78 g/m2/yr was estimated from the sum of the increase in above-ground biomass, dead matter, and litter.",
         "license": "proprietary"
     },
@@ -142917,7 +142878,7 @@
         "bbox": "102.31, 2.98, 102.31, 2.98",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752738171-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752738171-ORNL_CLOUD.html",
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         "description": "This data set contains four ASCII data files (.txt format), one providing net primary production (NPP) component data and three providing climate data. The NPP studies were conducted in a lowland tropical rainforest in the Pasoh Forest Reserve, Malaysia (2.98 N 102.31 E) from 1971 through 1973. Precipitation and temperature data are available from weather stations located about 25 km from the study sites.",
         "license": "proprietary"
     },
@@ -142930,7 +142891,7 @@
         "bbox": "-123, 40.35, -123, 40.35",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2755668336-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2755668336-ORNL_CLOUD.html",
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         "description": "This data set contains site characteristics, stand descriptors, and measured and calculated above-ground biomass, above-ground net primary production (ANPP), and woody detritus input data for an old Sequoia sempervirens stand at Bull Creek in Humboldt Redwoods State Park, California. There is one data file (.csv format) with this data set. Productivity of the Sequoia stand was studied via tree re-measurement (1972 and 2001) and allometric relationships. Measurements of tree circumference at 1.7 m above ground were made at the beginning and the end of the study. A 1972 stem map of the stand allowed the investigators to identify and re-measure trees >10 cm in diameter. ANPP was estimated using a range of specific gravities and several allometric relationships for tree volume. Estimation procedures were outlined by Busing and Fujimori (2005). Tree loss to mortality over the study interval was included in the analysis. Estimates of total tree ANPP ranged from 600 to 1,400 g/m2/yr. However, ANPP values in the range of 700-1,000 g/m2/yr were considered to be the most reasonable estimate because of the accuracy of the particular equations, specific gravities, and assumptions used to obtain them (Busing and Fujimori, 2005). Above-ground total tree biomass was extremely high (> 300,000 g/m2). Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2005. ",
         "license": "proprietary"
     },
@@ -142943,7 +142904,7 @@
         "bbox": "-70.27, -45.68, -70.27, -45.68",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947073-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947073-ORNL_CLOUD.html",
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         "description": "This data set contains three data files in text format (.txt) for a temperate dry steppe at Rio Mayo, Argentia. One file contains quarterly above-ground biomass data for grasses on the steepe (May 1984-May 1985). The second file contains average annual above-ground primary production (ANPP) data for grasses and shrubs for years 1972-1997 based upon peak above-ground biomass estimates. The third file contains precipitation and maximum/minimum temperature data for the Rio Mayo site for the period 1968 through 1990.Rio Mayo is located in the Patagonia region of Argentina. The vegetation is chiefly composed of grasses and shrubs. Harvest methods were used to estimate grass and shrub production. Between 1972 and 1997, peak annual ANPP of grasses plus shrubs ranged from 21 to 75 g/m2/yr, with an average of about 60 g/m2/yr. Grasses accounted for about two-thirds of the productivity. ANPP was reduced in a drought year, but did not increase in relatively wet years, suggesting that it may not be linearly related to precipitation. ANPP for 1984-1985 was slightly higher (79 g/m2/yr) when a different algorithm was used for estimation. Revision Notes: The original npp data file (rmy_npp.txt) has been split into two files, one file containing seasonal biomass and the other containing annual ANPP estimates. The data file containing annual ANPP estimates has been revised to extend temporage coverage and add additional annual ANPP data. See the Revisions section in this document for details.",
         "license": "proprietary"
     },
@@ -142956,7 +142917,7 @@
         "bbox": "-67.7, 54.72, -67.7, 54.72",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946862-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946862-ORNL_CLOUD.html",
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         "description": "This data set contains two files (.txt format). One file provides above- and below-ground biomass, soil, and nutrient data for a mature boreal ecosystem (subarctic Picea mariana/lichen woodland) near Schefferville, Canada (54.72 N, -67.70) for the 1974 growing season. The second data file contains climate data (precipitation amount and maximum/minimum temperature) from a weather station located 22 km northeast of the study site for the 1948-1990 period. The black spruce/lichen woodland is a vegetation type found in the transitional zone between boreal forest and tundra on well-drained, nutrient-poor podzolic soils. These spruce/lichen woodlands are generally not subject to attack by herbivory, but natural fires are common. The study forest was estimated to be 110 years old, based on annual tree ring data which showed the number of years since it was last burned. Biomass estimates were determined by harvesting trees, shrubs, and ground cover in the 0.2 ha study plot. To confirm the \"typical\" nature of the site, species composition and density were evaluated for the principal plot and compared to that of fifteen other plots. Organic and mineral soils were also extracted. The plant and soil samples were evaluated for nutrient and mineral content. Living tree, shrub, and lichen components contributed a total biomass of 2,636, 833, and 939 g/m2, respectively. NPP was estimated by the Terrestrial Ecosystem Model (TEM) to be about 340 g/m2/yr. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2001. ",
         "license": "proprietary"
     },
@@ -142969,7 +142930,7 @@
         "bbox": "-67.05, 1.93, -67.05, 1.93",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946380-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946380-ORNL_CLOUD.html",
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         "description": "This data set includes five ASCII files (.txt format). Three files contain above- and below-ground biomass and net primary productivity (NPP) data, one file for each tropical forest study site near San Carlos de Rio Negro, Venezuela. The study sites are located along an ecosystem gradient from riverine to lateritic hill: Tall Amazon Caatinga forest on coarse sandy spodosols close to river level; Bana vegetation on sandy soils less prone to flooding; and Tierra Firme mixed forest on clay oxisols of higher ground. Bioelement concentrations are also provided. The other two files contain climate data from a weather station in San Carlos village.",
         "license": "proprietary"
     },
@@ -142982,7 +142943,7 @@
         "bbox": "-71.35, 8.62, -71.35, 8.62",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946587-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751946587-ORNL_CLOUD.html",
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         "description": "This data set contains three ASCII data files (.txt format), one for net primary production (NPP) component data and two for climate data. The NPP studies were conducted in a tropical montane forest in the Sierra de Merida at San Eusebio (8.62 N 71.35 W) in northwestern Venezuela. The forest is mostly primary in character, with some selective logging having taken place in the past. Biomass, litterfall, and nutrient content of above- and below-ground vegetation and soil were determined in 1973-1974.",
         "license": "proprietary"
     },
@@ -142995,7 +142956,7 @@
         "bbox": "71, 51.67, 71, 51.67",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939588-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939588-ORNL_CLOUD.html",
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         "description": "This data set provides two data files in text format (.txt). One file contains biomass measurements and cumulative ANPP calculations made between 1977 and 1980 on a dry continental steppe at Shortandy Biological Station in Kazakhstan. The second file contains monthly and annual climate data for the study site for the period 1976-1980.Measurements of above- and below-ground live and dead matter were made at biweekly to monthly intervals during the growing season at Shortandy from 1977 to 1980. Cumulative ANPP estimates are calculated from these measurements. The study site is one of eight major grassland types of Eurasia which encompass an extremely wide climatic gradient in the direction of increasing maximum summer temperatures and continentality and decreasing precipitation in a north-west to the south-east band of steppes in the European and Asian parts of the former USSR (Commonwealth of Independent States). Shortandy represents the semiarid continental grass-forb steppe found on the southern chernozem soils of northern Kazakhstan. The site had annual mean maximum/minimum temperatures of 27.7/-24.6 degrees C and annual mean precipitation of 349.8 mm for the period 1976-1980. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996. ",
         "license": "proprietary"
     },
@@ -143008,7 +142969,7 @@
         "bbox": "-83.98, 10.43, -83.98, 10.43",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752734509-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752734509-ORNL_CLOUD.html",
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         "description": "There are two data files with this data set in (.txt) format. The files contain net primary productivity (NPP) data and climate data for a mature tropical lowland rainforest at the La Selva Biological Station, Costa Rica. The La Selva forest reserve (10.43 N, 83.98 W) covers over 1,500 ha, of which 53% is primary forest and the rest is in various types of secondary forest and abandoned land.Above- and below-ground biomass, litterfall, root production, and nutrient content of different vegetation components and soils were determined in different areas of the biological station on different occasions between 1975 and 1994. Work has continued to the present day. Precipitation (1984-1997) and maximum/minimum temperature (1992-1997) were measured at the forest study site.NPP has not been completely estimated although detailed data on forest dynamics are available from a variety of published and unpublished sources. A crude minimum estimate of NPP for La Selva was obtained by summing the estimates of litterfall [850 g/m2/year predicted for average annual temperature and precipitation conditions at La Selva by the equation of Brown and Lugo (1982)] and unpublished data on root production (550-1,250 g/m2/year), giving a NPP range of about 1,400-2,100 g/m2/year.Revision Notes: The NPP data file has been revised to add additional root biomass estimates, correct temporal coverage of data series, correct parameter label for potassium concentration in leaf litterfall, and add additional References/Comments. Please see the Data Set Revisions section of this document for detailed information.",
         "license": "proprietary"
     },
@@ -143021,7 +142982,7 @@
         "bbox": "-92.51, 47.97, -91.77, 48.17",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940441-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940441-ORNL_CLOUD.html",
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         "description": "This data set contains two files (.txt format). One file provides ground-based biophysical measurements and above-ground net primary productivity (ANPP) estimates for 31 black spruce (Picea mariana) and 30 quaking aspen (Populus tremuloides) stands in Superior National Forest (SNF) in northeastern Minnesota, U.S.A. (-92 W 48 N). The measurements were obtained during a 1983-1984 intensive field campaign. Non-destructive measurements were made in over 100 forest plots covering a 50 x 50 km area. Trees sacrificed for biomass and annual increment measurements were taken outside the plots. The second file provides climate data from nearby weather stations for the period 1976-1986. The data set provides stand structural measurements (diameter at breast height, tree height, crown depth, and stem density), above-ground biomass, leaf area index, bark area index, and ANPP estimates. ANPP data are based on a combination of allometric relationships and annual tree-ring (radial) increments for the 5-year period 1979-1983. In the spruce stands, above-ground biomass ranged from 700-15,100 g/m2, LAI varied between 0.5-4.3, and ANPP ranged from 39-572 g/m2/yr. In comparison, above-ground biomass among aspen stands ranged from 600-22,000 g/m2, LAI varied between 1.3-4.0, and ANPP ranged from 213-1,199 g/m2/yr. The purpose of the SNF campaign was to investigate the ability of remote sensing to provide estimates of ecosystem biophysical properties. In addition to the results presented herein, satellite, aircraft, and helicopter observations and other ground measurements for the study sites are available from the ORNL DAAC Superior National Forest (SNF) Project web site [http://daac.ornl.gov/SNF/snf.shtml]. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1997. ",
         "license": "proprietary"
     },
@@ -143034,7 +142995,7 @@
         "bbox": "83, 53, 103, 58",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944268-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944268-ORNL_CLOUD.html",
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         "description": "This data set contains two files (comma-separated-value format). One file provides components of net primary productivity, standing biomass, age and stand structure, and litterfall data for 11 stands of Scots pine (Pinus sylvestris) in the Tomsk Region of Russia (approx. 58 N 83 E). The second file contains data for the same types of variables for three stands of Scots pine in the Irkutsk Region of Siberia (approx. 53 N 103 E). Field measurements were made in 0.3-0.4 ha forest plots between 1968 and 1974. The forest plots range in age from 25 to 122 years old. Tree biomass was determined from volume and density measurements and selective harvest. Understory and ground cover was harvested in 0.25m2 plots. Root mass has determined from harvested trees and soil monoliths. Wood increment was measured from annual rings. Root production was based on species-specific turnover rates. Leaf litterfall was measured in 0.5-1.0 m2 traps, and branch litterfall was estimated from 4.0 m2 plots. Revision Notes: The NPP data file has been split into two files, one for the Tomask forests and one for the Irkutsk forests. The data files have been revised to rearrange columns, add a total ANPP column, and correct previously reported data, where needed. Please see the Data Set Revisions section of this document for detailed information. The Net Primary Productivity (NPP) data collection contains field measurements of biomass, estimated NPP, and climate data for terrestrial grassland, tropical forest, temperate forest, boreal forest, and tundra sites worldwide. Data were compiled from the published literature for intensively studied and well-documented individual field sites and from a number of previously compiled multi-site, multi-biome data sets of georeferenced NPP estimates. The principal compilation effort (Olson et al., 2001) was sponsored by the NASA Terrestrial Ecology Program. For more information, please visit the NPP web site at http://daac.ornl.gov/NPP/npp_home.html.",
         "license": "proprietary"
     },
@@ -143047,7 +143008,7 @@
         "bbox": "-148.25, -41.18, 174.97, 65.43",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944964-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944964-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibnBwIG11bHRpLWJpb21lOiBncmlkZGVkIGVzdGltYXRlcyBmb3Igc2VsZWN0ZWQgcmVnaW9ucyB3b3JsZHdpZGUsIDE5NTQtMTk5OCwgcjNcIixcIk9STkxfQ0xPVURcIixcIk5QUF9HUklEREVEX0dQUERJXzYxNFwiLFwiNFwiLDI3NTU1NzE0MjYsMl0iLCJ1bW0iOiJbXCJucHAgbXVsdGktYmlvbWU6IGdyaWRkZWQgZXN0aW1hdGVzIGZvciBzZWxlY3RlZCByZWdpb25zIHdvcmxkd2lkZSwgMTk1NC0xOTk4LCByM1wiLFwiT1JOTF9DTE9VRFwiLFwiTlBQX0dSSURERURfR1BQRElfNjE0XCIsXCI0XCIsMjc1NTU3MTQyNiwyXSJ9/NPP_TEM_471_2",
         "description": "This data set contains one data file (.csv format) that is known as the Terrestrial Ecosystem Model (TEM) data set. The data provide pool sizes and fluxes of carbon (C) and nitrogen (N) for 16 globally distributed field sites that represent a wide range of terrestrial biomes, tundra to tropical forest, but exclude wetlands. The net primary productivity (NPP) data were extracted from the literature. They were not previously widely available to the ecosystem modeling community in electronic form until this data set and additional NPP data sets were published by the ORNL DAAC. The data were used to calibrate the ecosystem process-based TEM. The TEM was developed by staff at the Ecosystem Center, Marine Biological Laboratory, Woods Hole, Massachusetts, USA, to estimate the spatial and temporal distribution of major carbon (C) and nitrogen (N) fluxes and pool sizes at continental to global scales (resolution: 0.5 degrees latitude x 0.5 degrees longitude). Eight of the TEM calibration sites are also included in the ORNL DAAC NPP data collection as individual site NPP data sets. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1999. ",
         "license": "proprietary"
     },
@@ -143060,7 +143021,7 @@
         "bbox": "-149.72, 68.45, -149.37, 68.63",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948015-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948015-ORNL_CLOUD.html",
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         "description": "This data set contains one text file (.csv format) that provides productivity data for four contrasting tundra vegetation types studied during 1982 near Toolik Lake in the northern foothills of the Brooks Range on the North Slope of Alaska (68.63 N 149.72 W). The vegetation types include a \"tussock\" tundra containing graminoids, deciduous shrubs, and evergreen shrubs; a \"shrub\" tundra dominated by deciduous willow shrubs; a \"heath\" tundra of evergreen shrubs; and a \"wet\" tundra site containing rhizomatous graminoids. The study sites were selected to represent extreme examples of the wide range of local plant growth forms in the region.Living above- and below-ground biomass were sampled on three occasions during the growing season using randomly located quadrats ranging in size from 10 cm x 20 cm to 50 cm x 50 cm. Production and biomass of most tissues were determined by harvest methods, with additional separate determinations of stem secondary growth and below-ground rhizome growth as components of net primary production (NPP). Elemental content of above-ground samples was analyzed. Production, biomass, and elemental content of roots were not determined. Leaf area index (LAI) was measured using a LI-COR leaf area meter.NPP, excluding fine roots, was estimated at 37, 99, 278, and 475 g/m2/year, at the heath, wet, tussock, and shrub sites, respectively. Inclusion of estimated production by roots increased these NPP figures to 140, 200, 430, and 780 g/m2/year, respectively. Leaf area index was similarly ranked.",
         "license": "proprietary"
     },
@@ -143073,7 +143034,7 @@
         "bbox": "17.5, 59.2, 17.5, 59.2",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751942244-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751942244-ORNL_CLOUD.html",
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         "description": "This data set contains three ACSII files (.txt format). Two files contain above-ground biomass data for two ungrazed seashore meadow plots dominated by the saltmeadow rush Juncus gerardii at Tullgarnsnaset, near Stockholm, Sweden (approximately 59.20 N, 17.50 E). There is one file for each plot. The third data file contains monthly and annual climate data from weather station near Stockholm (59.4 N, 18.0 E) for the period 1951-1990. Measurements of above-ground live biomass and total dead matter were made approximately monthly from April 1968 to April 1969. Below-ground biomass was also measured, but the data are not reported in this data set. Annual above-ground net primary production (ANPP) was estimated by several calculation methods, including peak total live plus current dead matter; sum of species maxima (biomass + dead material); single square clippings; and variations of these equations. The rate of disappearance of dead material and mortality were also determined. Mean ANPP estimates ranged from 324 g/m2/yr (max live + dead) to 430 g/m2/yr (taken as the mean of the two sites accounting for disappearance of dead matter). ",
         "license": "proprietary"
     },
@@ -143086,7 +143047,7 @@
         "bbox": "123, 46.1, 123, 46.1",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944800-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751944800-ORNL_CLOUD.html",
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         "description": "This data set contains four ASCII files (.txt format). Three files contain monthly above- and below-ground biomass data, one data file for each cold meadow steppe studied from 1981 to 1990 at Tumugi, Xingan League, in eastern Inner Mongolia, China (approximately 46.10 N 123.00 E Elevation 191 m). The fourth file contains climate data recorded at a weather station located in the study area for the length of the study.The Tumugi study sites consist of three different natural steppes dominated by Filifolium sibiricum, Stipa baicalensis, and Leymus chinense, respectively. Measurements of above- and below-ground live biomass were made monthly throughout the growing season (March to November) by clipping 1.0 m2 quadrats and sampling 1.0 m2 soil pits to a depth of 1.0 m, respectively. The study areas had been protected from grazing since 1976.Above-ground net primary productivity (ANPP) was estimated at 155 g/m2/year (average for the three steppes, based on peak above-ground living biomass). Peak live below-ground biomass was used to estimate below-ground net primary productivity (BNPP): 968 g/m2/year for the F. sibiricum steppe; 983 g/m2/year the Stipa baicalensis steppe; and 1,022 g/m2/year for the L. chinense steppe. Above- and below-ground biomass data were compared with simulation results from the CENTURY model. Simulated data agreed reasonably well with the observed data (within +25%). ",
         "license": "proprietary"
     },
@@ -143099,7 +143060,7 @@
         "bbox": "112.5, 47.4, 112.5, 47.4",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939819-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751939819-ORNL_CLOUD.html",
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         "description": "This data set provides two data files in text format (.txt). One file contains tri-monthly measurements of above-ground biomass made during the growing season between July 1982 and August 1990 on a dry, cold Eurasian steppe dominated by Stipa grandis at the Tumentsogt Research Station in Mongolia. The second file contains monthly and annual climate data recorded at the study site from 1963 through 1983. Mongolian steppes occupy a major part of eastern Mongolia and northern China and are characterized climatically by low mean annual rainfall and temperature, with a highly seasonal pattern in both. The beginning of spring rainfall and warming are strongly correlated, and the onset of the growing season rainfall triggers the green-up in the region. Land use is dominated by grazing, historically by nomadic pastoralists and more recently for cooperative livestock production. Privatization of grazing land and cropland conversions have been increasing since 1990. Ecosystem degradation such as deterioration of vegetation (e.g., vegetation removal and replacement) and soil (e.g., erosion) is becoming widespread. Peak above-ground biomass at Tumentsogt occurs during a short rainy season (June-August). The amount of biomass fluctuates from year-to-year coherently with rainfall variation. Above-ground net primaryp roductivity (ANPP) estimates are relatively low in comparison to other temperate grasslands, ranging from 72 to 160 g/m2/yr. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996.",
         "license": "proprietary"
     },
@@ -143112,7 +143073,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949039-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751949039-ORNL_CLOUD.html",
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         "description": "This data set contains documented field measurements of NPP components for 39 old-growth tropical forests distributed worldwide between latitudes 23.58 N and 23.58 S. The data were compiled from published literature and other extant sources. The data are georeferenced to each intensive study site and include above- and below-ground biomass, fine root biomass, litterfall, branchfall, above-ground biomass increment, and herbivory estimates, where available. Other site characteristics are included, such as elevation, forest type and age, soil type, and climate summaries. Key references are provided. Estimates of above-ground net primary productivity (ANPP) for the 39 sites were made based on the sum of (1) measured or estimated above-ground biomass increment, (2) measured or estimated fine litterfall accumulation, (3) estimated losses to consumers, and (4) estimated biogenic volatile organic compound emissions. Estimates of below-ground NPP were made based on professional judgment that below-ground production is 0.2 x ANPP (lower bounds) or 1.2 x ANPP (upper bounds). TNPP was calculated as the range between the low and high values of ANPP + BNPP. Average BNPP and TNPP estimates were also calculated. Across the broad spectrum of the tropical forests studied (dry to wet, lowland to montane, nutrient-rich to nutrient-poor soils), the estimates of total NPP range from 3.4 to 34.4 Mg/ha/yr (lower bounds) and from 6.2 to 63.0 Mg/ha/yr (upper bounds). There is one comma-separated data file (.csv) with this data set. The ORNL DAAC [http://daac.ornl.gov] NPP Collection for tropical forests contains additional biomass and NPP component estimates and climate data for 28 of the intensive study sites in this data set. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2001. ",
         "license": "proprietary"
     },
@@ -143125,7 +143086,7 @@
         "bbox": "94.42, 51.83, 94.42, 51.83",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940066-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751940066-ORNL_CLOUD.html",
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         "description": "This data set provides two data files in text format (.txt). One file contains biomass measurements and cumulative ANPP estimates made between 1978 and 1985 at an ultracontinental steppe at the Tuva Research Station in Russia. The second file contains monthly and annual climate data for the study site for 1976-1985.Monthly measurements of above-ground live phytomass, standing dead, and litter biomass were made during each growing season (May-August) of the eight-year study period. Harvests of below-ground biomass were made at the end of the growing season in some years. A year-end measurement of above-ground biomass (particularly standing dead and litter) was also made in 1980. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996. ",
         "license": "proprietary"
     },
@@ -143138,7 +143099,7 @@
         "bbox": "28.35, 24.9, 28.35, 24.9",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2752598982-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2752598982-ORNL_CLOUD.html",
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         "description": "This data set provides seven data files in text format (.txt). The files provide biomass estimates, soil carbon (C), nitrogen (N), and phosphorus (P) measurements made at an artificially-established grassland savanna study site in Towoomba, South Africa. The study site was part of a long-term experiment to test the effect of fertilizer application. Biomass data are available for the years 1950-1981 (data are not available for 1976 or 1977); soil C, N, and P data are available for the years 1949, 1962, 1980, and 1990. The 1949 estimates were inferred in 1990 from undisturbed savanna adjacent to the experiment. The savanna-fertilizer experiment was several hectares in extent, with five levels of nitrogen and three levels of phosphorus laid out in a randomized block design on an area from which all trees were removed. The ammonium sulphate and superphosphate fertilizers were added during November (50% of total), January (25%) and February (25%). The response to N fertilizer saturated at higher levels, so data from only six (3 x 2) of the 15 possible treatment combinations are provided.Above-ground biomass was sampled by mowing to 5-cm height. It was assumed that 50 g/m2 was left in the field, plus an additional 5% of the mowed dry weight. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published. ",
         "license": "proprietary"
     },
@@ -143151,7 +143112,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947305-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751947305-ORNL_CLOUD.html",
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         "description": "This data set contains one data file in comma-delimited (.csv format) that provides observations from Australia for use in parameterizing the Vegetation and Soil-carbon Transfer (VAST) Model (version 1.1). The observations include net primary productivity (NPP), biomass, litter mass, surface horizon soil carbon concentration (i.e., mass fraction) and bulk density, and soil carbon and bulk density measurements at various depths. The data consist of 33 estimates of above-ground NPP based on cut grass swards and visual assessment of growth, 150 measurements of litterfall (leaf and fine twig), 76 measurements of above-ground biomass (phytomass), 91 determinations of fine litter mass, 341 measurements of soil carbon concentration in surface layers (to 15 cm depth), and 50 determinations of soil bulk density (to 15 cm depth). All these data were derived from 174 original literature references describing study sites throughout Australia. VAST is a conceptual carbon (C) cycle model that depicts large scale dynamics of terrestrial C pools and the net exchange of C between the land surface and the atmosphere at a resolution of 0.05 degrees. The model consists of 10 C pools comprising two above-ground biomass pools, two litter pools, and three pools each of below-ground biomass and soil C. Below-ground pools are distributed among three soil layers (0-20, 20-50, and 50-100 cm). Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2001. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751942556-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751942556-ORNL_CLOUD.html",
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         "description": "This data set contains four data files in text format (.txt). Three files provide above- and below-ground productivity data for three derived savannas on the Vindhyan plateau in northern India from 1986 to 1989, one file for each of three treatments. Each study site (Ranitali, Hathinala, Telburva) contains three treatment areas: ungrazed; grazed annually for 30-40 years; and grazed but temporarily fenced for 2-6 years prior to the study. The fourth file provides climate data from a weather station at Daltonganj, India, for the period 1893-1990. Monthly dynamics of above- and below-ground biomass were measured by harvest methods in each treatment area at each site for two annual cycles (1986/1987 and 1987/1988). Additional above-ground peak biomass data (live shoot + dead shoot) for October 1988 from ungrazed and grazed plots represent the 1988/1989 annual cycle.Annual above-ground net primary production (ANPP) was estimated using trough-peak analysis of increments in live biomass, standing dead matter, and litter. Annual below-ground production (BNPP) was estimated from biomass increments combined with root in-growth studies. Mean ANPP for the ungrazed treatment areas on the three sites ranged from 377 to 664 g/m2/yr over the 1986 to 1989 period. Mean BNPP in the same areas was estimated at 510 and 727 g/m2/yr for 1986/1987 and 1987/1988, respectively. Mean total ungrazed NPP (ANPP + BNPP) was estimated at 1,082 and 1,391 g/m2/yr for 1986/1987 and 1987/1988, respectively.Revision Notes: The NPP data for the temporarily fenced grassland sites for the 1987/1988 annual cycle have been revised to correct previously reported BNPP estimates. Please see the Data Set Revisions section of this document for detailed information. ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2755668925-ORNL_CLOUD.html",
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         "description": "This data set contains five data files, in comma-separated format (.csv), derived from the Walker Branch Watershed (WBW) vegetation inventory in eastern Tennessee. Field studies of permanent vegetation plots were conducted using one sampling design over a 40-year period (1967 to 2006). The data set contains long-term measurements of diameter at breast height (DBH) determined on stratified randomly-located inventory plots within the 4 different vegetation types (oak-hickory, pine-oak-hickory, pine, and mesophytic hardwoods) located in the WBW in 1967. The WBW plot-level vegetation DBH data are provided in four files. One file contains the complete set of inventory records (139,806 observations). To accommodate spreadsheet use, the complete inventory is split into three files, one containing 52,110 observations and the other two containing 48,231 and 39,465 observations, respectively. The fifth file contains the WBW vegetation species inventory with species names, the numeric species code for each species, a species group designation, the scientific name for each species, and the literature-derived ratio of g lignin/g N for leaves of each species. NPP values have been reported for various forest stands at different locations within the WBW by Olson et al. (2012a, b; DeAngelis et al. (1997); and Esser (1998). Total NPP values range from 380 gC/m2/yr for forest stands dominated by yellow poplar to 790 gC/m2/yr for forest stands dominated by oaks. Revision Notes: This updated vegetation inventory data set includes results of the 2006 survey and updates to previous results based on the latest survey. The 1967-2006 data set completely supersedes the 1967-1997 data set. If you downloaded the 1967-1997 data set before September 3, 2013, you should download the 1967-2006 version at your earliest convenience.",
         "license": "proprietary"
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         "description": "There are two data files (tab-delimited .txt format) with this data set that provide estimates of above-ground biomass per county; county-level annual above-ground biomass growth, removals (harvest), and mortality of woody biomass per hectare; county-level total annual above-ground woody biomass production per hectare; forest area per county; mortality (%) in forests within each county; and total annual production and mortality per county. The data provide annual mean above-ground wood increments for temperate forests in 1,956 counties of the 28 eastern US states. The data are derived from forest inventory data from 1960s to 1990s that were collected from an extensive network of permanent inventory plots as part of the US Department of Agriculture Forest Service Forest Inventory and Analysis (FIA). Based on the analysis of the above-ground production data (Brown and Schroeder, 1999), above-ground production of woody biomass (APWB) for hardwood forests ranged from 0.6 to 28 Mg/ha/yr and averaged 5.2 Mg/ha/yr. For softwood forests, APWB ranged from 0.2 to 31 Mg/ha/yr and averaged 4.9 Mg/ha/yr. APWB was generally highest in southeastern and southern counties, mostly along an arc from southern Virginia to Louisiana and eastern Texas. No clear spatial pattern of mortality of woody biomass (MWB) existed, except for a distinct area of high mortality in South Carolina as a result of Hurricane Hugo in 1989. For hardwood forests, MWB ranged from 0 to 15 Mg/ha/yr and averaged 1.1 Mg/ha/yr. The average MWB for softwood forests was 0.6 Mg/ha/yr with a range of 0 to 10 Mg/ha/yr. The rate of above-ground MWB averaged <1%/yr for both hardwood and softwood forests. Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 2003. ",
         "license": "proprietary"
     },
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         "description": "This data set provides two data files in text format (.txt). One file contains bi-weekly measurements of above-ground live biomass recorded during the growing season (early May to early October) from 1980 through 1989 on a cold desert steppe at the Inner Mongolia Grassland Research Station of the Chinese Academy of Sciences within the Xilingol Biosphere Reserve. The second file contains monthly and annual climate data recorded at the study site from 1978 through 1989. The study site contains grassland steppes of Leymus chinense and Stipa grandis which are the dominant vegetation types, respectively, in the Eastern Eurasian steppe zone (semi-arid and sub-humid) and the middle Eurasian steppe zone (semi-arid). Both steppes provide good livestock forage and are used mainly as natural grazing lands. Above-ground net primary production (ANPP) was estimated by summing peak live biomass of each of 5 species categories. Peak live biomass of L. chinense steppe occurred between late July and late August and averaged 182.68 g/m2 between 1980 and 1988 while that of S. grandis steppe occurred in mid August to early September and averaged 144.43 g/m2 over the same time period. Mean ANPP for L. chinense steppe during 1980-1989 was 248.63 g/m2/yr. ANPP for S. grandis steppe was not calculated. Data are only provided for the  Leymus chinense steppe in this data set.Revision Notes: Only the documentation for this data set has been modified. The data files have been checked for accuracy and are identical to those originally published in 1996. ",
         "license": "proprietary"
     },
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         "description": "This data set contains an inventory of natural and anthropogenic methane emissions for all counties in the six New England states of Connecticut, Rhode Island, Massachusetts, Vermont, New Hampshire, and Maine. The inventory represents a snapshot in time (circa 1990-1994) and provides emission estimates for multiple sources including wetlands, landfills, ruminant animals, residential wood combustion, fossil fuel combustion and use, animal manure, wastewater treatment, and natural gas transmission pipelines. Also included is the uptake or sink of methane in relatively well-drained upland soils.",
         "license": "proprietary"
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         "description": "The New Hampshire Geographically Referenced Analysis and Information Transfer System (GRANIT) land cover data set provides a land cover and land use product at 30-m resolution with 23 individual classes across the state. The classification is based largely on the analysis of 12 Landsat Thematic Mapper (TM and ETM+) images. Over 1,400 new classification training site data points were collected to supplement 1,200 archived sites from previous projects. The classification represents a snapshot in time from 1996 to 2001.  This time range spans the dates of the most recent acquisitions of a TM scene for each region of the state and the dates of the most recent field data collection.",
         "license": "proprietary"
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@@ -147012,7 +146973,7 @@
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         "description": "This dataset provides chlorophyll fluorescence measurements made on pine and spruce needle tissues at the Niwot Ridge AmeriFlux Core site (US-NR1) near Nederland, Colorado, USA, during the summers of 2017 and 2018. Two types of measurements were made using pulse-amplitude-modulation (PAM) fluorometry: the photosystem II (PSII) operating efficiency in the light (Fq'/Fm' at variable light levels), and the maximum quantum efficiency of PSII photochemistry (Fv/Fm) on dark-acclimated tissues. Chlorophyll fluorescence measurements were made to determine seasonality of photosynthetic performance at the needle level.",
         "license": "proprietary"
     },
@@ -147025,7 +146986,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389021615-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389021615-ORNL_CLOUD.html",
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         "description": "This dataset provides concentrations of pigments in pine and spruce needle tissues collected at the Niwot Ridge AmeriFlux Core site (US-NR1) near Nederland, Colorado, USA, during the summers of 2017 and 2018. Pigments measured included Chlorophyll A and B, Violaxanthin, Antheraxanthin, Zeaxanthin, Neoxanthin, Lutein, and beta-Carotene. Measurements were made on sun foliage from two canopy-access towers near the main flux tower, and in the laboratory on branches collected from those towers, every 4-8 weeks over the annual cycle. Due to canopy structure, a limited number of trees were accessible from the towers, preventing extensive replication. Pigments were extracted in acetone and analyzed by HPLC. The measurements were made to evaluate seasonal changes associated with the down-regulation of photosynthesis.",
         "license": "proprietary"
     },
@@ -147324,7 +147285,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2143403370-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2143403370-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic3BhdGlvLXRlbXBvcmFsIGNoYXJhY3RlcmlzdGljcyBvZiByYWluZmFsbCBpbiBhZnJpY2EsIDAuMjUgZGVncmVlcywgZnJvbSAxOTk4LTIwMTJcIixcIk9STkxfQ0xPVURcIixcIkFmcmljYW5fUmFpbmZhbGxfUGF0dGVybnNfMTI2M1wiLFwiMVwiLDI3NzY4NzQ4NzMsMl0iLCJ1bW0iOiJbXCJzcGF0aW8tdGVtcG9yYWwgY2hhcmFjdGVyaXN0aWNzIG9mIHJhaW5mYWxsIGluIGFmcmljYSwgMC4yNSBkZWdyZWVzLCBmcm9tIDE5OTgtMjAxMlwiLFwiT1JOTF9DTE9VRFwiLFwiQWZyaWNhbl9SYWluZmFsbF9QYXR0ZXJuc18xMjYzXCIsXCIxXCIsMjc3Njg3NDg3MywyXSJ9/Nongrowing_Season_CO2_Flux_1692_1",
         "description": "This dataset provides a synthesis of winter ( September-April) in situ soil CO2 flux measurement data from locations across pan-Arctic and Boreal permafrost regions. The in situ data were compiled from 66 published and 21 unpublished studies conducted from 1989-2017. The data sources (publication references) are provided. Sampling sites spanned pan-Arctic Boreal and tundra regions (>53 Deg N) in continuous, discontinuous, and isolated/sporadic permafrost zones. The CO2 flux measurements were aggregated at the monthly level, or seasonally when monthly data were not available, and are reported as the daily average (g C m-2 day-1) over the interval. Soil moisture and temperature data plus environmental and ecological model driver data (e.g., vegetation type and productivity, soil substrate availability) are also included based on gridded satellite remote sensing and reanalysis sources.",
         "license": "proprietary"
     },
@@ -147389,7 +147350,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2162118968-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2162118968-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibHVoMi1nY2IyMDE5OiBsYW5kLXVzZSBoYXJtb25pemF0aW9uIDIgdXBkYXRlIGZvciB0aGUgZ2xvYmFsIGNhcmJvbiBidWRnZXQsIDg1MC0yMDE5XCIsXCJPUk5MX0NMT1VEXCIsXCJMVUgyX0dDQjIwMTlfMTg1MVwiLFwiMVwiLDI3NTY4NDc3NDMsMl0iLCJ1bW0iOiJbXCJsdWgyLWdjYjIwMTk6IGxhbmQtdXNlIGhhcm1vbml6YXRpb24gMiB1cGRhdGUgZm9yIHRoZSBnbG9iYWwgY2FyYm9uIGJ1ZGdldCwgODUwLTIwMTlcIixcIk9STkxfQ0xPVURcIixcIkxVSDJfR0NCMjAxOV8xODUxXCIsXCIxXCIsMjc1Njg0Nzc0MywyXSJ9/North_Slope_Transect_Veg_Maps_1386_1",
         "description": "This dataset includes vegetation cover maps, Normalized Difference Vegetation Index (NDVI) maps, snow depth and thaw depth data that were obtained as part of a biocomplexity project on the North Slope of Alaska, USA, and the Northwest Territories (NWT), Canada. In Alaska, seven sites are located along the Dalton Highway and in the Prudhoe Bay Oilfield area, forming a transect across the climate gradient of the North Slope. From South to North, the sites are Happy Valley, Sagwon (an acidic and nonacidic site), Franklin Bluffs, Deadhorse, West Dock and Howe Island. Four sites are in the NWT, forming a latitudinal gradient from South to North; the sites include Inuvik, Green Cabin, Mould Bay, and Isachsen.",
         "license": "proprietary"
     },
@@ -147415,7 +147376,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170969582-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiaXNsc2NwIGlpIHJpdmVyIHJvdXRpbmcgZGF0YSAoc3RuLTMwcClcIixcIk9STkxfQ0xPVURcIixcInJpdmVyX3JvdXRpbmdfc3RuX3hkZWdfMTAwNVwiLFwiMVwiLDI3ODUyNzQ2ODQsMl0iLCJ1bW0iOiJbXCJpc2xzY3AgaWkgcml2ZXIgcm91dGluZyBkYXRhIChzdG4tMzBwKVwiLFwiT1JOTF9DTE9VRFwiLFwicml2ZXJfcm91dGluZ19zdG5feGRlZ18xMDA1XCIsXCIxXCIsMjc4NTI3NDY4NCwyXSJ9/Northern_Alaska_Veg_Maps_1359_1",
         "description": "This data set provides four land cover and ecosystem classification maps for northern Alaska. The maps were produced for several projects and from different data sources including Landsat imagery and existing maps and models, and cover a range of ecosystem and vegetation classes. The data used to derive the maps covered the period 1976-08-04 to 2014-09-01.",
         "license": "proprietary"
     },
@@ -147705,6 +147666,19 @@
         "description": "Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA missiondesigned to collect space-based measurements of atmospheric carbon dioxidewith the precision, resolution, and coverage needed to characterize theprocesses controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and inmolecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time tothe Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO2_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.",
         "license": "proprietary"
     },
+    {
+        "id": "OCO2_L1B_Calibration_11.2r",
+        "title": "OCO-2 Level 1B calibrated, geolocated calibration spectra Retrospective Processing V11.2r (OCO2_L1B_Calibration) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
+        "state_date": "2019-11-30",
+        "end_date": "",
+        "bbox": "-180, -90, 180, 90",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMWEgY29sbGF0ZWQsIHBhcnNlZCwgY2FsaWJyYXRpb24gZGF0YSB2MTAgKG9jbzJfbDFhaW5fcGl4ZWwpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT0NPMl9MMWFJbl9QaXhlbFwiLFwiMTBcIiwxNjg1NzgzOTc0LDIzXSIsInVtbSI6IltcIm9jby0yIGxldmVsIDFhIGNvbGxhdGVkLCBwYXJzZWQsIGNhbGlicmF0aW9uIGRhdGEgdjEwIChvY28yX2wxYWluX3BpeGVsKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDFhSW5fUGl4ZWxcIixcIjEwXCIsMTY4NTc4Mzk3NCwyM10ifQ%3D%3D/OCO2_L1B_Calibration_11.2r",
+        "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA missiondesigned to collect space-based measurements of atmospheric carbon dioxidewith the precision, resolution, and coverage needed to characterize theprocesses controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and inmolecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time tothe Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO2_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.",
+        "license": "proprietary"
+    },
     {
         "id": "OCO2_L1B_Calibration_11r",
         "title": "OCO-2 Level 1B calibrated, geolocated calibration spectra, Retrospective Processing V11r (OCO2_L1B_Calibration) at GES DISC",
@@ -147744,6 +147718,19 @@
         "description": "Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the output from the Level 1B process. It converts the raw instrument data numbers into calibrated radiances. This conversion is based upon files of instrument characteristics and algorithm parameters that may vary over time. In addition to calibrated radiances, the Level 1B output products have geolocation information recorded for each measurement for use in higher-level processes.",
         "license": "proprietary"
     },
+    {
+        "id": "OCO2_L1B_Science_11.2r",
+        "title": "OCO-2 Level 1B calibrated, geolocated science spectra Retrospective Processing V11.2r (OCO2_L1B_Science) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
+        "state_date": "2019-11-30",
+        "end_date": "",
+        "bbox": "-180, -90, 180, 90",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib2NvLTIgbGV2ZWwgMWEgY29sbGF0ZWQsIHBhcnNlZCwgY2FsaWJyYXRpb24gZGF0YSB2MTAgKG9jbzJfbDFhaW5fcGl4ZWwpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT0NPMl9MMWFJbl9QaXhlbFwiLFwiMTBcIiwxNjg1NzgzOTc0LDIzXSIsInVtbSI6IltcIm9jby0yIGxldmVsIDFhIGNvbGxhdGVkLCBwYXJzZWQsIGNhbGlicmF0aW9uIGRhdGEgdjEwIChvY28yX2wxYWluX3BpeGVsKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9DTzJfTDFhSW5fUGl4ZWxcIixcIjEwXCIsMTY4NTc4Mzk3NCwyM10ifQ%3D%3D/OCO2_L1B_Science_11.2r",
+        "description": "Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the output from the Level 1B process. It converts the raw instrument data numbers into calibrated radiances. This conversion is based upon files of instrument characteristics and algorithm parameters that may vary over time. In addition to calibrated radiances, the Level 1B output products have geolocation information recorded for each measurement for use in higher-level processes.",
+        "license": "proprietary"
+    },
     {
         "id": "OCO2_L1B_Science_11r",
         "title": "OCO-2 Level 1B calibrated, geolocated science spectra, Retrospective Processing V11r (OCO2_L1B_Science) at GES DISC",
@@ -147896,7 +147883,7 @@
         "bbox": "-180, -90, 180, 90",
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         "license": "proprietary"
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+    {
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+        "catalog": "GES_DISC STAC Catalog",
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+        "license": "proprietary"
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         "title": "OCO-2 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air, Retrospective Processing V11r (OCO2_L2_CO2Prior) at GES DISC",
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         "license": "proprietary"
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+    {
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+        "license": "proprietary"
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         "title": "OCO-2 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information, Retrospective Processing V11r (OCO2_L2_Diagnostic) at GES DISC",
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         "title": "OCO-2 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V11r (OCO2_L2_IMAPDOAS) at GES DISC",
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         "license": "proprietary"
     },
+    {
+        "id": "OCO2_L2_Lite_FP_11.2r",
+        "title": "OCO-2 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V11.2r (OCO2_L2_Lite_FP) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
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+        "end_date": "",
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         "license": "proprietary"
     },
+    {
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         "license": "proprietary"
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         "license": "proprietary"
     },
+    {
+        "id": "OCO2_L2_Met_11.2r",
+        "title": "OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding Retrospective Processing V11.2r (OCO2_L2_Met) at GES DISC",
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+        "license": "proprietary"
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         "title": "OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO2_L2_Met) at GES DISC",
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         "description": "Version 9r is the current version of the data set. Previous versions have been superseded by Version 9r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.  ",
         "license": "proprietary"
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         "description": "Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.",
         "license": "proprietary"
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         "description": "Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).",
         "license": "proprietary"
     },
+    {
+        "id": "OCO2_L2_Standard_11.2r",
+        "title": "OCO-2 Level 2 geolocated XCO2 retrievals results, physical model Retrospective Processing V11.2r (OCO2_L2_Standard) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
+        "state_date": "2019-11-30",
+        "end_date": "",
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+        "license": "proprietary"
+    },
     {
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         "title": "OCO-2 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V11r (OCO2_L2_Standard) at GES DISC",
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         "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.",
         "license": "proprietary"
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         "description": "Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.   The OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.  This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO3_L1B_Science (L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the direction of the boresight vector.   ",
         "license": "proprietary"
     },
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+        "license": "proprietary"
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         "title": "OCO-3 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Forward Processing V10 (OCO3_L2_ABand) at GES DISC",
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+        "title": "OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO3_L2_Met) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
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         "description": "Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   ",
         "license": "proprietary"
     },
+    {
+        "id": "OCO3_L2_Standard_11r",
+        "title": "OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V11r (OCO3_L2_Standard) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
+        "state_date": "2019-08-06",
+        "end_date": "",
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+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.html",
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+        "description": "Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 \u00b5m. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   ",
+        "license": "proprietary"
+    },
     {
         "id": "OCTS_L1_1",
         "title": "ADEOS-I Ocean Color and Temperature Scanner (OCTS) Data Regional Data",
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         "description": "This Level-2G daily global gridded product OMAEROG is based on the pixel level OMI Level-2 Aerosol product OMAERO, based on the multi-wavelength algorithm that uses up to 20 wavelength bands between 331 nm and 500 nm. OMAEROG is a special Level-2 gridded product where pixel level products are binned into 0.25 x 0.25 degree global grids. It contains the data for all scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products.  The OMAEROG data product contains almost all parameters that are in OMAERO. For example, in addition to the extinction optical depth and single scattering albedo, it also contains aerosol indices, cloud fraction, cloud pressure, terrain height, geolocation, solar and satellite viewing angles, and extensive quality flags.  The OMAEROG files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMAEROG data product is about 78 Mbytes.",
         "license": "proprietary"
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         "description": "The reprocessed OMI/Aura Level-2 Zoomed Aerosol data product OMAEROZ at 13x12 km resolution have been made available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access in March 2012. There are two Level-2 Aura OMI aerosol products OMAERO and OMAERUV. The OMAERUV product uses the near-UV algorithm. The OMAERO (13x24 km resolution) and OMAEROZ (13x12 km resolution) is based on the multi-wavelength algorithm that uses up to 20 wavelength bands between 331 nm and 500 nm. The multi-wavelength retrieval algorithm is developed by the KNMI OMI Team Scientists. Drs. Deborah Stein-Zweers, Martin Sneep and Pepijn Veefkind are now the key investigators of this product. The OMAEROZ products contain Aerosol Optical Depths, Single Scattering Albedo, Aerosol Type, Aerosol Layer Height, and other intermediate and ancillary parameters and geolocation information.  The OMAEROZ files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). OMAEROZ data files are based on Zoomed Level 1B radiance observations which are made once a month. Thus there is one day of zoomed data (approximately 14 orbits) per month. The maximum file size for the OMAEROZ data is about 11 Mbytes.  A Readme document containing brief algorithm description and known data quality related issues and file specifications are provided by the OMAERO Algorithm lead.",
         "license": "proprietary"
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         "description": "The Level-2 Aura Ozone Monitoring Instrument (OMI) Aerosol Product (OMAERO) is now available from NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access. This is the second public release of version 003. The data was re-processed in late 2011 using an improved algorithm (processing version 1.2.3.1). After some quick validation the reprocessed data was released to the public in March 2012. The shortname for this Level-2 Aerosol Product is OMAERO_V003. There are two Level-2 Aura OMI aerosol products OMAERUV and OMAERO. The OMAERUV product uses the near-UV algorithm. The OMAERO product is based on the multi-wavelength algorithm and that uses up to 20 wavelength bands between 331 nm and 500 nm. OMAERO retrieval algorithm is developed by the KNMI OMI Team Scientists. Drs. Deborah Stein-Zweers, Martin Sneep and Pepijn Veefkind are now the key investigators of this product. The OMAERO product contains Aerosol Optical Depths, Single Scattering Albedo, and other ancillary and geolocation information.  The OMAERO files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERO data product is about 6 Mbytes.",
         "license": "proprietary"
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         "description": "The OMI science team produces this Level-3 Aura/OMI Global Aerosol Data Products OMAEROe (0.25deg Lat/Lon grids). The OMAEROe product selects best aerosol value from the Level2G good quality data that are reported in each grid, based on the multi-wavelength algorithm that uses up to 20 wavelength bands between 331 nm and 500 nm.  The selection criteria is based on the shortest optical path length (secant of solar zenith angle + secant of viewing zenith angle).  The OMAEROe files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMAEROe data product is about 7 Mbytes. (The shortname for this Level-3 Global Gridded Aerosol Product is OMAEROe)",
         "license": "proprietary"
     },
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         "description": "This Level-2G daily global gridded product OMAERUVG is based on the pixel level OMI Level-2 AERUV product OMAERUV. This Level-2G daily global gridded product OMAERUVG is based on the pixel level OMI Level-2 Aerosol product OMAERUV. OMAERUVG data product is a special Level-2 gridded product where pixel level products are binned into 0.25x0.25 degree global grids. It contains the data for all scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products.  The OMAERUVG files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits mapped on the Global 0.25x0.25 deg Grids. The maximum file size for the OMAERUVG data product is about 50 Mbytes.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966768-GES_DISC.html",
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         "description": "The Aura Ozone Monitoring Instrument level-2 near UV Aerosol data product 'OMAERUV', recently re-processed using an enhanced algorithm, is now released (April 2012) to the public. The data are available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The shortname for this Level-2 near-UV Aerosol Product is OMAERUV_V003. The OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Absorption and Aerosol Extinction Optical Depths, and Single Scattering Albedo at three different wavelengths (354, 388 and 500 nm), Aerosol Index, and other ancillary and geolocation parameters, in the OMI field of view (13x24 km).  The OMAERUV files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 6 Mbytes.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3185856256-GES_DISC.html",
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         "description": "The Aura Ozone Monitoring Instrument level-2 near UV Aerosol data product OMAERUV (Version 004) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. The OMAERUV retrieval algorithm is developed by the US OMI Team Scientists. Dr. Omar Torres (GSFC/NASA) is the principal investigator of this product. The OMAERUV product contains Aerosol Optical Depth, Aerosol Single Scattering Albedo, Absorption Optical Depth, UV Aerosol Index, and Aerosol Optical Depth over clouds at three wavelengths (354, 388, and 500 nm), and other ancillary and geolocation parameters, in the OMI field of view (13x24 km).  The OMAERUV files are stored in the  version 4.0 Network Common Data Form (NetCDF). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMAERUV data product is about 17 Mbytes.",
         "license": "proprietary"
     },
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         "description": "This is a CloudSat-collocated subset of the original OMI product OMAERUV, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications.              (The shortname for this CloudSat-collocated OMI Level 2 near-UV aerosol subset is OMAERUV_CPR_003)",
         "license": "proprietary"
     },
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         "description": "The OMI science team produces this Level-3 daily global gridded product OMAERUVd (1 deg Lat/Lon grids). The OMAERUVd product is produced with all data pixels that fall in a grid box with quality filtered and then averaged, based on the pixel level OMI Level-2 Aerosol data product OMAERUV. The OMAERUV data product is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data. The OMAERUVd data product contains extinction and absorption optical depths at three wavelenghts (355 nm, 388 nm and 500 nm).   The OMAERUVd files are stored in version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMAERUVd data product is about 0.2 Mbytes.",
         "license": "proprietary"
     },
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         "description": "The Aura Ozone Monitoring Instrument (OMI) collection-3 Bromine Monoxide Product OMBRO from the Aura-OMI, is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. The shortname for this Level-2 OMI total column BrO product is OMBRO. The algorithm leads for this product are the US OMI scientists Dr. Kelly Chance and Dr. Thomas Kurosu from the Harvard-Smithsonian Center, Cambridge, MA. The OMBRO product contains total vertical column BrO, standard errors (rms and sigma), quality flags, geolocation and other ancillary information.  The OMBRO files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The average file size for the OMBRO data product is about 5 Mbytes.",
         "license": "proprietary"
     },
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         "description": "This Level-2G daily global gridded product OMCLDO2G is based on the pixel level OMI Level-2 CLDO2 product OMCLDO2. This level-2G global cloud product (OMCLDO2G) is based on the spectral fitting of O2-O2 absorption band at 477 nm using DOAS technique. This product contains cloud pressure, cloud fraction, slant column O2-O2 and Ozone, Ring coefficients, uncertainties in derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The short name for this Level-2 OMI cloud product is OMCLDO2G and the lead scientist for this product and for OMCLDO2 (the data source of OMCLDO2G) is KNMI scientist Dr. Pepijn Veefkind. OMCLDO2G data product is a special Level-2 Global Gridded Product where pixel level data (OMCLDO2) are binned into 0.25x0.25 degree global grids. It contains the OMCLDO2 data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid are saved 'Without Averaging'. Scientists can apply a data filtering scheme of their choice and create new gridded products.  The OMCLDO2G product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each daily data file contains data from the day lit portion of the orbits (~14 orbits) and is roughly 85 MB in size.",
         "license": "proprietary"
     },
@@ -149911,7 +150119,7 @@
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         "description": "The reprocessed Aura Ozone Monitoring Instrument (OMI) Level-2 zoomed cloud data product OMCLDO2Z at 13x12 km resolution is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. It is the second release of Version 003 and was reprocessed late 2011. OMI provides two cloud products based on two different algorithms, the Rotational Raman Scattering method and O2-O2 absorption method using the DOAS technique. This level-2 zoomed cloud product at the pixel resolution (13x12 km2 at nadir) is based on the spectral fitting of O2-O2 absorption band at 477 nm using DOAS technique. This product contains effective cloud pressure, effective cloud fraction, slant column O2-O2; uncertainties in derived, parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Zoomed cloud product is OMCLDO2Z. The lead scientist for this product is Dr. Pepijn Veefkind.  The OMCLDO2Z files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes) and is roughly 20 MB in size. OMCLDO2Z data files are based on Zoomed Level 1B radiance observations which are made once a month. Thus there is one zoomed cloud product per month.",
         "license": "proprietary"
     },
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         "description": "The reprocessed OMI/Aura Level-2 cloud data product OMCLDO2 is now available from the NASA GoddardEarth Sciences Data and Information Services Center (GES DISC) for the public access. It is the second release of Version 003 and was reprocessed in late 2011. OMI provides two cloud products based on two different algorithms, the Rotational Raman Scattering method, and O2-O2 absorption method using the DOAS technique. This level-2 global cloud product, with a pixel resolution of 13x24 km2at nadir, is based on the spectral fitting of O2-O2 absorption band at 477 nm using DOAS technique. This product contains cloud pressure, cloud fraction, slant column O2-O2, ozone, ring coefficients, uncertainties in derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The lead scientist for this product is Dr. Pepijn Veefkind.  The OMCLDO2 product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes) and is roughly 15.096 MB in size. There are approximately 14 orbits per day thus the total data volume is approximately 200 GB/day.",
         "license": "proprietary"
     },
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         "description": "This the OMI/Aura Cloud Pressure and Fraction (O2-O2 Absorption) subset along CloudSat track, for the purposes of the A-Train mission. The original product uses the DOAS technique method. This level-2 global cloud product at the pixel resolution (13x24 km2 at nadir) is based on the spectral fitting of O2-O2 absorption band at 477 nm using DOAS technique. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track. This product contains cloud pressure, cloud fraction, slant column O2-O2 and O3, ring coefficients, uncertainties in derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications.        (The shortname for this Level-2 OMI cloud pressure and fraction (O2-O2 absorption) subset along CloudSat track product is OMCLDO2_CPR)",
         "license": "proprietary"
     },
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         "description": "This Level-2G daily global gridded product OMCLDRRG is based on the pixel level OMI Level-2 CLDRR product OMCLDRR. This level-2G global cloud product (OMCLDRRG) provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The algorithm lead for the products OMCLDRR and OMCLDRRG is NASA OMI scientist Dr. Joanna Joinner. OMCLDRRG data product is a special Level-2G Gridded Global Product where pixel level data (OMCLDRR)are binned into 0.25x0.25 degree global grids. It contains the OMCLDRR data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products.  The OMCLDRRG data products are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each daily file contains data from the day lit portion of the orbits (~14 orbits). The average file size for the OMCLDRRG data product is about 75 Mbytes.",
         "license": "proprietary"
     },
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         "description": "The reprocessed Aura Ozone Monitoring Instrument (OMI) Version 003 Level 2 Cloud Data Product OMCLDRR is available to the public from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Aura OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product, OMCLDRR, provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering).  This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner.  The OMCLDRR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes.",
         "license": "proprietary"
     },
@@ -149989,7 +150197,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3159637081-GES_DISC.umm_json",
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         "description": "This is the Aura Ozone Monitoring Instrument (OMI) Version 004 Level 2 Cloud Data Product OMCLDRR. OMI provides two Level-2 Cloud products (OMCLDRR and OMCLDO2) at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms, the Rotational Raman Scattering method and the O2-O2 absorption method. This level-2 global cloud product, OMCLDRR, provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI Cloud Pressure and Fraction product is OMCLDRR and the algorithm lead for this product is NASA OMI scientist Dr. Joanna Joinner.  The OMCLDRR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMCLDRR data product is about 9 Mbytes.",
         "license": "proprietary"
     },
@@ -150002,7 +150210,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236350980-GES_DISC.html",
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         "description": "This is the OMI/Aura Cloud Pressure and Fraction (Raman Scattering) subset along CloudSat tracks, for the purposes of the A-Train mission. The original data product uses the Rotational Raman Scattering method. This level-2 global cloud product provides effective cloud pressure and effective cloud fraction that is based on the least square fitting of the Ring spectrum (filling-in of Fraunhofer lines in the range 392 to 398 nm due to rotational Raman scattering). The goal of this subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications.  (The shortname for this Level-2 OMI cloud pressure and fraction subset along CloudSat tracks product is OMCLDRR_CPR)",
         "license": "proprietary"
     },
@@ -150015,7 +150223,7 @@
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         "description": "This Level-2G daily global gridded product OMDOAO3G is based on the pixel level OMI Level-2 DOAO3 product OMDOAO3.  This Level-2G global total column ozone product is derived from OMDOAO3 which is based on the Differential Absorption Spectroscopy (DOAS) fitting technique that essentially uses the OMI visible radiance values between 331.1 and 336.1 nm. In addition to the total ozone column this product also contains some auxiliary derived and ancillary input parameters, e.g. ozone slant column density, ozone ghost column density, etc. The short name for this Level-2 OMI ozone product is OMDOAO3G and the lead algorithm scientist for this product and for OMDOAO3 (the data source of OMDOAO3G) is Dr. Pepijn Veefkind from KNMI.  The OMDOAO3G product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each daily file contains data from the day lit portion of the orbits (approximately 14 orbits) and is roughly 80 MB in size.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966798-GES_DISC.html",
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         "description": "The reprocessed Aura Ozone Monitoring Instrument (OMI) Level-2 Zoomed Ozone data product OMDOAO3Z at 13x12 km resolution is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. It is the second release of Version 003 and was reprocessed late 2011. OMI provides two sets of total column ozone products OMTO3 and OMDOAO3 which are based on two different algorithms.  OMTO3 product is based on TOMS like ozone retrieval algorithm whereas OMDOAO3 total column ozone product  is based on the Differential Absorption Spectroscopy (DOAS) fitting technique that essentially uses the OMI visible radiance values between 331.1 and 336.1 nm.  The DOAS retrieval algorithm is developed by the KNMI OMI Scientist, Dr  Pepijn Veefkind. Based on spatial resolutions, there are two DOAS algorithm based ozone products, OMDOAO3 (at 13x24 km resolution) and OMDOAO3Z (13x12 km resolution). In addition to the total ozone column values these DOAS based ozone products also contain some auxiliary derived and ancillary input parameters e.g. ozone slant column density, ozone ghost column density, air mass factor, scene reflectivity, radiance over the DOAS fit window, root mean square of DAOS fit, cloud fraction, cloud radiance, cloud pressure, terrain height,  geolocation, viewing angles and quality flags. The shortname for this Level-2 OMI Zoomed Ozone product is OMDOAO3Z.  The OMDOAO3Z files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). OMDOAO3Z data files are based on Zoomed Level 1B radiance observations which are made once a month. Thus there is one day of zoomed data (approximately 14 orbits) per month. The maximum file size for the OMDOAO3Z data is approximately 30 MB.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966794-GES_DISC.html",
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         "description": "The second release of Aura Ozone Monitoring Instrument (OMI) Version 003 OMI/Aura Level-2 Total Column Ozone Data Product OMDOAO3 is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. The data were processed in late 2011 using Algorithm or PGE version 1.2.3 and released in March 2012. OMI provides two total column ozone products based on two different algorithms. This level-2 global total column ozone product at the pixel resolution (13x24 km at nadir), is based on the Differential Absorption Spectroscopy (DOAS) fitting technique that essentially uses the OMI UV radiance values between 331.1 and 336.1 nm. In addition to the total ozone column this product also contains auxiliary , derived and ancillary input parameters e.g. ozone slant column density, ozone ghost column density, air mass factor, scene reflectivity, radiance over the DOAS fit window, root mean square of DAOS fit, cloud fraction, cloud radiance, cloud pressure, terrain height, geolocation, viewing angles and quality flags. The shortname for this Level-2 OMI total column ozone product is OMDOAO3. The lead scientist for this product is Dr. J. Pepijn Veefkind.  The OMDOAO3 product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (approximately 53 minutes) and is approximately 11 MB in size. There are approximately 14 orbits per day.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136037-GES_DISC.html",
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         "description": "The OMI science team produces this Level-3 Aura/OMI Global OMDOAO3e Data Products (0.25deg Lat/Lon grids). This Level-3 global total column ozone product is derived from OMDOAO3 which is based on the Differential Absorption Spectroscopy (DOAS) fitting technique that essentially uses the OMI visible radiance values between 331.1 and 336.1 nm. In addition to the total ozone column (best quality data, satisfying the shortest path length) and its precision this product also contains some ancillary parameters such as cloud fraction, cloud height, etc. The short name for this Level-3 OMI ozone product is OMDOAO3e and the lead Algorithm scientist for this product and for OMDOAO3 (the data source of OMDOAO3e) is Dr. Pepijn Veefkind from KNMI.  The OMDOAO3e product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5). Each daily file contains data from the day lit portion of the orbits (approximately 14 orbits) and is roughly 8 MB in size.",
         "license": "proprietary"
     },
@@ -150080,7 +150288,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1611899353-GES_DISC.html",
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         "description": "The OMI/Aura Global Geometry-Dependent Surface LER 1-Orbit L2 Swath 13x24km product, or OMGLER, provides GLER, and the computed top-of-atmosphere (TOA) radiance from which GLER is derived, for the OMI field of view. The OMGLER data also contain a number of ancillary/input parameters for each OMI pixel used to compute TOA radiance. The primary intended use of the product is to provide surface reflectance information for OMI cloud, aerosol and trace gas algorithms. GLER is designed to easily replace commonly used LER climatologies within existing OMI algorithms. The product lead is Joanna J. Joiner (OMI US science team leader). The algorithm developer is Wenhan Qin.  The OMGLER product file is produced in the version 5 Hierarchical Data Format (HDF-EOS5). Each file contains GLER data for the daylit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. Files are roughly 9 MB in size.",
         "license": "proprietary"
     },
@@ -150236,7 +150444,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136038-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136038-GES_DISC.html",
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         "description": "This Level-2G daily global gridded product OMHCHOG is based on the pixel level OMI Level-2 HCHO product OMHCHO.  OMHCHOG data product is a special Level-2 Global Gridded Product where pixel level data are binned into 0.25x0.25 degree grids. It contains data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved without Averaging (third dimension provides indexing for the data points in each small grid). Scientists can apply a data filtering scheme of their choice and create Level-3 global gridded products. The OMHCHOG data product contains almost all parameters (e.g. total vertical column HCHO, standard errors, quality flags, geolocation and ancillary information) that are contained in the OMHCHO product.  The OMHCHOG data are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portions of 14 to 15 orbits that cover the globe in a day. The average file size for the OMGCHOG data product is about 55 Mbytes.",
         "license": "proprietary"
     },
@@ -150249,7 +150457,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966779-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966779-GES_DISC.html",
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         "description": "The Aura Ozone Monitoring Instrument (OMI) Version-3 Formaldehyde Product OMHCHO is now  available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the  public access. The shortname for this Level-2 OMI total column Formaldehyde product is OMHCHO. The algorithm leads for this product are the US OMI scientists Dr. Kelly Chance and Dr. Thomas Kurosu from the Harvard-Smithsonian Center, Cambridge, MA. The OMHCHO product contains total vertical column HCHO, standard errors (rms and sigma), quality flags, geolocation and other ancillary information.  The OMHCHO files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The average file size for the OMHCHO data product is about 5 MB.",
         "license": "proprietary"
     },
@@ -150262,7 +150470,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1626121562-GES_DISC.html",
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         "description": "The OMI/Aura Formaldehyde (HCHO) Total Column Daily L3 Weighted Mean Global 0.1deg Lat/Lon Grid (OMHCHOd). The formaldehyde values in each file are the average for 0.1 x 0.1 degree grid cell of cloud-screened total HCHO columns for a single day.  Other variables included in the files are the weight of each grid cell, the standard error of column averages, mean albedo, mean cloud fraction, mean cloud pressure, and surface height. The weight information is useful for combining data from several files and reducing the noise of the retrievals by co-adding in the temporal or spatial dimensions.  The OMHCHOd files are in the netCDF4 format which is compatible with most HDF5 readers and tools. Each file contains daily data from approximately 15 orbits. The maximum file size for the OMHCHOd data product is about 80 Mbytes.",
         "license": "proprietary"
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         "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this projects describes a multi-decadal Fundamental Climate Data Record (FCDR) of calibrated radiances as well as an Earth System Data Record (ESDR) of aerosol properties over the continents derived from a 32-year record of satellite near-UV observations by three sensors.    The OMI/Aura Near UV (version 1) Aerosol Index, Optical Depth and Single Scattering Albedo data product consists of aerosol absorption optical depth, aerosol optical depth, aerosol single scattering albedo, cloud fraction, cloud optical depth, refractive index, radiance, reflectivity and residue at approximately 13x24km. This product also contains ancillary data for ocean corrected surface albedo and terrain pressure.  These Level-2 data are stored in the Hierarchical Data Format 5 (HDF5) and are available from the Goddard Earth Sciences (GES) Data and Information Services Center (DISC).",
         "license": "proprietary"
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         "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2011), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.",
         "license": "proprietary"
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         "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2011), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.",
         "license": "proprietary"
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         "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this project entitled \u201cMulti-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS)\u201d will develop consistent long-term global trend-quality data records spanning the last two decades, over which remarkable changes in nitrogen oxides (NOx) emissions have occurred. The objective of the project Is to adapt Ozone Monitoring Instrument (OMI) operational algorithms to other satellite instruments and create consistent multi-satellite L2 and L3 nitrogen dioxide (NO2) columns and value-added L4 surface NO2 concentrations and NOx emissions data products, systematically accounting for instrumental differences. The instruments include Global Ozone Monitoring Experiment (GOME, 1996-2011), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY, 2002-2012), OMI (2004-present), GOME-2 (2007-present), and TROPOspheric Monitoring Instrument (TROPOMI, 2018-present). The quality assured L2-L4 products will be made available to the scientific community via the NASA GES DISC website in Climate and Forecast (CF)-compliant Hierarchical Data Format (HDF5) and netCDF formats.",
         "license": "proprietary"
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         "description": "The OMI Level 1B solar irradiance product is the radiometrically calibrated and geolocated measurements of the UV and Visible channels of the spectral solar irradiance. It is the averaged measurements of the solar irradiances over a single solar observation in the wavelength ranges of UV1 (264-311 nm, 159 channels), UV2 (307-383 nm, 557 channels) and VIS (349-504 nm, 751 channels). The data contain solar measurement products for both the global and the spatial zoom-in mode. This product only contains measurements obtained with the quartz volume diffuser and provides average of the individual measurements made along track to average out the solar elevation dependent bidirectional reflectance distribution function (BRDF) features of the diffuser. The shortname for this OMI Level-1B Product is OML1BIRR. The lead algorithm scientists for this product is Dr. Marcel Dobber from the Roayl Netherlands Meteorological Institude (KNMI).  OMI calibrated and geolocated radiances for the UV and Visible channels, spectral irradiances, calibration measurements, and all derived geophysical atmospheric products are archived at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). OML1BIRR files are stored in the HDF4 based EOS Hierarchical Data Format. The radiances for the earth measurements (also referred as signal) and its precision are stored as a 16 bit mantissa and an 8-bit exponent. The signal can be computed using the equation: signal = mantissa x 10^exponent. For the precision, the same exponent is used as for the signal.",
         "license": "proprietary"
     },
@@ -150353,7 +150561,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2045794731-GES_DISC.html",
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         "description": "The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) UV Averaged Solar Irradiances product (shortname OML1BIRR) contains the averaged radiometrically calibrated irradiance measurements from the UV and VIS detectors. The OMI UV Band 1 (264-311 nm) has 159 wavelength bins, the UV Band 2 (307-383 nm) has 559 wavelength bins, and the VIS Band 3 (349-504 nm) has 751 wavelength bins. The data files are written in netCDF version 4 format and are usually made once per day when the Sun is within the solar port field-of-view just before the spacecraft moves into the night shadow at the north end of an orbit. The lead algorithm scientist for this product is Quintus Kleipool from the Royal Netherlands Meteorological Institude (KNMI).",
         "license": "proprietary"
     },
@@ -150366,7 +150574,7 @@
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         "description": "The Aura Ozone Monitoring Instrument (OMI) Level-1B (L1B) Geo-located Earth View VIS Radiance, Zoom-in-Mode (OML1BRVZ) Version-3 product contains geo-located Earth view spectral radiances from the VIS detectors in the wavelength range of 349 to 504 nm using spectral and spatial zoom-in measurement modes. In zoom-in measurement mode, OMI observes 60 ground pixels (13 km x 24 km at nadir) across the swath. Each file contains data from the day lit portion of an orbit (~60 minutes) and is roughly 190 MB in size. There are approximately 14 orbits per day. OMI performs spatial zoom-in measurements one day per month. For that day, this product also contains VIS measurements that are rebinned from the spatial zoom-in measurements. The lead algorithm scientist for this product is Dr. Marcel Dobber from the Royal Netherlands Meteorological Institude (KNMI).  The OML1BRVZ files are stored in the HDF4 based EOS Hierarchical Data Format (HDF-EOS). The radiances for the earth measurements (also referred as signal) and its precision are stored as a 16 bit mantissa and an 8-bit exponent. The signal can be computed using the equation: signal = mantissa x 10^exponent. For the precision, the same exponent is used as for the signal.",
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         "description": "The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) Zoom-in Earthshine UV Radiance, Zoom-mode (shortname OML1BRVZ) Version 4 product contains geolocated Earth view spectral radiances from the VIS detectors in the wavelength range of 349 to 504 nm taken in the zoom-in measurement mode. In the zoom-in mode, OMI observes 60 ground pixels (13 km x 12 km at nadir) across the swath (~750 km width) for each of the 751 channels of Band 3 (349-504 nm). There are approximately 14 files of orbital data per day. Each file contains data from the daylit portion of an orbit and is roughly 240 MB in size. This OML1BRVZ zoom-in mode product is only available about once a month. The data in the OML1BRVZ files are stored in the Network Common Data Form (netCDF) format. The lead algorithm scientist for the OMI Level 1 products is Dr. Quintus Kleipool of the Royal Netherlands Meteorological Institude (KNMI).",
         "license": "proprietary"
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         "description": "The OMI Earth Surface Reflectance Climatology product, OMLER (Global 0.5 degrees Lat/Lon grid) which is based on Version 003 Level-1B top of atmosphere upwelling radiance and incoming irradiance. OMI calibrated and geolocated radiances from 159 channels in UV1(264-311 nm), 557 channels in UV2 (307-383 nm) and 751 channels in VIS (349-504) spectral regions, spectral irradiances, calibration measurements, and all derived geophysical atmospheric products (Level-2 and 3) are archived at the NASA Goddard DAAC.  OMLER spectral surface reflectance product contains monthly and yearly climatology of the Earth's surface Lambert Equivalent Reflectance (LER) for 23 wavelengths in the spectral range 309 to 500 nm, at a spatial resolution of 0.5 by 0.5 degrees. This LER is defined as the required reflectance of an isotropic surface needed to match the observed top of the atmosphere (TOA) reflectance in a pure Rayleigh scattering atmosphere under cloud free conditions and no aerosols. The climatology is based on statistical analysis of the three years of OMI version 03 radiance data (Oct 2004-Oct 2007). This product also provides minimum spectral surface reflectivity observed during the three year period.  The OMLER product file is produced in the version 5 Hierarchical Data Format (HDF-EOS5). It is roughly 300 MB in size.",
         "license": "proprietary"
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         "description": "The OMI/Aura and MODIS/Aqua Aerosol Geo-colocation Product 1-Orbit L2 Swath 13x24 km (OMMYDAGEO) is a Level-2 orbital data product that links the MODIS/Aqua aerosol geo-coordinates at 3 and 10 km with the OMI indices along the OMI orbital track. This product allows users to match up MODIS granules with the OMI orbit for analysis and validation. It co-locates MODIS and OMI cloud and radiance information onto the OMI pixel.  The OMMYDAGEO data files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5) using the swath model, and follows the same conventions used by the other OMI Level-2 data products. Each file contains data for 5 minutes, corresponding to the MODIS granule from the daylit side of the orbit. There are on the order of about 140 swath files per day. The file size for the OMMYDAGEO data product is about 12 Megabytes.",
         "license": "proprietary"
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         "description": "The OMI/Aura and MODIS/Aqua Merged Cloud Product 1-Orbit L2 Swath 13x24 km (OMMYDCLD) is a Level-2 orbital product that combines cloud parameters retrieved by the Ozone Mapping Instrument (OMI) on the Aura satellite with collocated statistical information for cloud parameters retrieved by the Moderate Resolution Imaging Spectrometer (MODIS) on the Aqua spacecraft. This product is designed to take advantage of the synergy between OMI and MODIS, which both fly on satellites in the NASA A-Train constellation of Earth-observing satellites that follow similar orbital tracks and collect near-simultaneous observations. This product can be used for cloud-clearing, detection of multi-layered clouds, and other applications that may exploit these multi-spectral measurements.  The algorithm for the OMMYDCLD product co-locates daytime cloud parameters from MODIS onto the OMI visible (VIS) pixel for a given OMI orbit and generates statistical information from the collocated MODIS pixels. For each OMI granule, the orbit start and end times are used to select the corresponding 5-minute MODIS granules for processing. A contiguous list of MODIS granules spanning the full duration of the OMI orbit are selected based on the relative time lag between Aqua and Aura. The algorithm lead for this product is NASA OMI scientist Dr. Joanna Joiner.  The OMMYDCLD data files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5) using the swath model, and follows the same conventions used by the other OMI Level-2 data products. Each file contains data from the day lit portion of an orbit (about 53 minutes). There are approximately 14 orbits per day. The file size for the OMMYDCLD data product is about 8 Mbytes.",
         "license": "proprietary"
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         "description": "This Level-2G daily global gridded product OMNO2G is based on the pixel level OMI Level-2 NO2 product OMNO2.  OMNO2G data product is a special Level-2 Gridded Product where pixel level data are binned into 0.25x0.25 degree global grids. It contains the data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a rid box are saved Without Averaging. Nitrogen dioxide is an important chemical species in both the stratosphere, where it plays a key role in ozone chemistry, and in the troposphere, where it is a precursor to ozone production. In the troposphere, it is produced in various combustion processes and in lightning and is an indicator of poor air quality. The OMNO2G data product contains almost all parameters that are contained in OMNO2 product.  The OMNO2G data are stored in version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of the orbit (~14 orbits). The average file size for the OMNO2G data product is about 115 Mbytes.",
         "license": "proprietary"
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         "description": "The Version 4.0 Aura Ozone Monitoring Instrument (OMI) Nitrogen Dioxide (NO2) Standard Product (OMNO2) is now available from the NASA Goddard Earth Sciences Data and Information Services Center. The major V4.0 updates include: (1) use of a new daily and OMI \ufb01eld of view speci\ufb01c geometry dependent surface Lambertian Equivalent Re\ufb02ectivity (GLER) product in both NO2 and cloud retrievals; (2) use of improved cloud parameters (e\ufb00ective cloud fraction and cloud optical centroid pressure) from a new cloud algorithm (OMCDO2N) that are retrieved consistently with NO2 using a new algorithm for O2-O2 slant column data and the GLER product for terrain re\ufb02ectivity; (3) use of a more accurate terrain pressure calculated using OMI ground pixel-averaged terrain height and monthly mean GMI terrain pressure; and (4) improved treatment over snow/ice surfaces by using the concept of scene LER and scene pressure. The details can be found in the updated OMNO2 readme document (see Documentation). The OMNO2 product contains slant column NO2 (total amount along the average optical path from the sun into the atmosphere, and then toward the satellite), the total NO2 vertical column density (VCD), the stratospheric and tropospheric VCDs, air mass factors (AMFs), scattering weights for calculation of AMFs, and other ancillary data. The short name for the Level-2 swath type column NO2 products is OMNO2. Other OMNO2-associated NO2 products include the Level-2 gridded column product, OMNO2G, and the Level-3 gridded column product, OMNO2d.  The OMNO2 files are stored in version 5 EOS Hierarchical Data Format (HDF-EOS5). Each Level-2 file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMNO2 is ~24 MB.",
         "license": "proprietary"
     },
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         "description": "This is a CloudSat-collocated subset of the original product OMNO2, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain  and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications.  (The shortname for this CloudSat-collocated OMI Level 2 NO2 subset is OMNO2_CPR_V003)",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136111-GES_DISC.html",
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         "description": "This is Level-3 daily global gridded (0.25x0.25 degree) Nitrogen Dioxide Product (OMNO2d). OMNO2d data product is a Level-3 Gridded Product where pixel level data of good quality are binned and \"averaged\" into 0.25x0.25 degree global grids. This product contains Total column NO2 and Total Tropospheric Column NO2, for all atmospheric conditions, and for sky conditions where cloud fraction is less than 30 percent.  Nitrogen dioxide is an important chemical species in both, the stratosphere where it plays a key role in ozone chemistry, and in the troposphere where it is a precursor to ozone production. In the troposphere, it is produced in various combustion processes and in lightning and is an indicator of poor air quality.  The OMNO2d data are stored in version 5 EOS Hierarchical Data Format (HDF-EOS). Each file contains data from the day lit portion of the orbit (~14 orbits). The average file size for the OMNO2d data product is about 12 Mbytes.",
         "license": "proprietary"
     },
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         "description": "The Aura Ozone Monitoring Instrument Level-2 Ozone Profile data product OMO3PR (Version 003) is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI Level-2 ozone profile product, OMO3PR at the pixel resolution 13x 48 km (at nadir), is based on the optimal estimation algorithm (Rodgers, 2000) with climatological ozone profiles as a-priori information. The OMO3PR retrieval algorithm uses spectral radiance values from the UV1 channel (270 nm to 308.5 nm) and from the first part of the UV2 channel (311.5 nm to 33 0 nm). OMO3PR product provides ozone values (in Dobson unit) for 18 atmospheric layers. It also provides a-priori ozone profile values, error covariance matrix, averaging kernel and some ancillary information such as time, latitude, longitude, solar zenith and viewing zenith angles and quality flags. The short name for this Level-2 OMI ozone profile product is OMO3PR. The lead scientist for this product is Dr. Johan de Haan.  The OMO3PR product files are stored in the version 5 Hierarchical Data Format (HDF-EOS5).  Each file contains data from the day lit portion of an orbit (approximately 53 minutes). There are approximately 14 orbits per day thus the total data volume is approximately 150 GB/day.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966829-GES_DISC.html",
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         "description": "The Aura Ozone Monitoring Instrument (OMI) collection-3 Chlorine Dioxide Product OMOCLO is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access. The shortname for this Level-2 OMI total column OClO product is OMOCLO. The algorithm leads for this product are the US OMI scientists Dr. Kelly Chance and Dr. Thomas Kurosu from the Harvard-Smithsonian Center, Cambridge, MA. The OMOCLO product contains slant column OClO, standard errors (rms  and sigma), quality flags, geolocation and other ancillary information.  The OMOCLO files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an  orbit (~53 minutes). There are approximately 14 orbits per day. The  maximum file size for the OMOCLO data product is about 20 MB.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966812-GES_DISC.html",
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         "description": "The Version-3 Aura Ozone Monitoring Instrument (OMI) Pixel Corner Product in zoom-in mode, OMPIXCORZ, is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access. The shortname for this Level-2 OMI product is OMPIXCORZ. The algorithm lead for this product is the US OMI scientists Dr. Thomas Kurosu from the Harvard-Smithsonian Center, Cambridge, MA.  The OMPIXCORZ product contains ground locations of the OMI pixel corners in the zoom-in scanning mode. The motivation for the development of the OMI ground pixel corner products was the common need for: the visualization of derived OMI data products, the provision of ground pixel area for computations of trace gas emissions per area, the facilitation of the development of cross-platform pixel mapping applications (e.g., between OMI and MODIS), and to generally aid validation studies, to name just a few.  The OMPIXCORZ files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes) . There are approximately 14 orbits approximately one day per month. The average file size for the OMPIXCORZ data product is about 8 Mbytes.",
         "license": "proprietary"
     },
@@ -150600,7 +150808,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966810-GES_DISC.html",
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         "description": "The Version-3 Aura Ozone Monitoring Instrument (OMI) Pixel Corner Product, OMPIXCOR, is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for public access. The shortname for this Level-2 OMI product is OMPIXCOR. The algorithm lead for this product is the US OMI scientists Dr. Thomas Kurosu from the Harvard-Smithsonian Center, Cambridge, MA.  The OMPIXCOR product contains ground locations of the OMI pixel corners in the global scanning mode. The motivation for the development of the OMI ground pixel corner products was the common need for: the visualization of derived OMI data products, the provision of ground pixel area for computations of trace gas emissions per area, the facilitation of the development of cross-platform pixel mapping applications (e.g., between OMI and MODIS), and to generally aid validation studies, to name just a few.  The OMPIXCOR files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes) . There are approximately 14 orbits per day. The average file size for the OMPIXCOR data product is about 5 Mbytes.",
         "license": "proprietary"
     },
@@ -150613,7 +150821,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2477751536-GES_DISC.html",
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         "description": "The OMPS-N20 L2 NM Formaldehyde (HCHO) Total Column swath orbital product provides formaldehyde measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the NOAA-20 (JPSS-1) satellite. The total column HCHO amount is derived from radiances at wavelengths between 328.5 and 356.5 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day. Each has typically 1201 swaths. The swath width of the NM is about 2800 km. Prior to orbit 6419 on 13 February 2019, each swath has 104 scenes, or pixels, with a footprint size of 17 km x 17 km at nadir. Orbits 6419 and later have 140 scenes across the swath, with a footprint size of 12 km x 17 km. The files are written in the new netCDF version 4 format.",
         "license": "proprietary"
     },
@@ -150626,7 +150834,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808692512-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808692512-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbm8yIHRvdGFsIGFuZCB0cm9wb3NwaGVyaWMgY29sdW1uIGRhaWx5IGwyIGdsb2JhbCBncmlkZGVkIDAuMjUgZGVncmVlIHggMC4yNSBkZWdyZWUgdjMgKG9tbm8yZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTU5PMkdcIixcIjNcIiwxMjY2MTM2MTIxLDQzXSIsInVtbSI6IltcIm9taS9hdXJhIG5vMiB0b3RhbCBhbmQgdHJvcG9zcGhlcmljIGNvbHVtbiBkYWlseSBsMiBnbG9iYWwgZ3JpZGRlZCAwLjI1IGRlZ3JlZSB4IDAuMjUgZGVncmVlIHYzIChvbW5vMmcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01OTzJHXCIsXCIzXCIsMTI2NjEzNjEyMSw0M10ifQ%3D%3D/OMPS_N20_NMSO2_PCA_L2_Step1_1",
         "description": "The OMPS-N20 NM PCA SO2 Step1 Total Column 1-Orbit L2 Swath 17x13km collection 1 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the NOAA-20 (JPSS-1) satellite. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017) used to retrieve the SO2 total column amounts assuming different SO2 plume heights, including the boundary layer (lowest 1 km of the atmosphere), the lower (centered at 3 km), middle (centered at 8 km) and upper (centered at 13 km) troposphere, as well as the lower stratosphere (centered at 18 km).  Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 104 pixels in the cross-track direction before February 13, 2019 with a pixel resolution of about 17 km x 17 km at nadir. Since then, the pixel resolution has been enhanced to 17 km x 13 km at nadir, with 140 pixels in the cross-track direction. The files are written using netCDF version 4.",
         "license": "proprietary"
     },
@@ -150643,6 +150851,32 @@
         "description": "The OMPS-N20 NM PCA SO2 Step1 Total Column 1-Orbit L2 Swath 17x13km collection 1 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the NOAA-20 (JPSS-1) satellite. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017) used to retrieve the SO2 total column amounts assuming different SO2 plume heights, including the boundary layer (lowest 1 km of the atmosphere), the lower (centered at 3 km), middle (centered at 8 km) and upper (centered at 13 km) troposphere, as well as the lower stratosphere (centered at 18 km).  Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 104 pixels in the cross-track direction before February 13, 2019 with a pixel resolution of about 17 km x 17 km at nadir. Since then, the pixel resolution has been enhanced to 17 km x 13 km at nadir, with 140 pixels in the cross-track direction. The files are written using netCDF version 4.  ",
         "license": "proprietary"
     },
+    {
+        "id": "OMPS_N21_LP_L1G_EV_1.0",
+        "title": "OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V1.0 (OMPS_N21_LP_L1G_EV) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
+        "state_date": "2022-11-10",
+        "end_date": "",
+        "bbox": "-180, -84, 180, 84",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_N21_LP_L1G_EV_1.0",
+        "description": "The OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA 21 (JPSS-2) satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
+        "license": "proprietary"
+    },
+    {
+        "id": "OMPS_N21_LP_L2_O3_DAILY_1.0",
+        "title": "OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit V1.0 (OMPS_N21_LP_L2_O3_DAILY) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
+        "state_date": "2022-11-10",
+        "end_date": "",
+        "bbox": "-180, -90, 180, 90",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_N21_LP_L2_O3_DAILY_1.0",
+        "description": "The OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit collection contains ozone measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA-21 satellite. The LP ozone product measures the vertical distribution of ozone in the stratosphere and lower mesosphere. The algorithm derives ozone profile values along with errors in the UV from 29.5 km and 52.5 km, and in the visible from cloud top to 37.5 km (when there are no clouds the lower limit is 12.5 km).   Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, the data from the center of the LP three slits are used to make a vertical profile. The profile is measured from the ground up to about 60 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
+        "license": "proprietary"
+    },
     {
         "id": "OMPS_NPP_LP_L1G_EV_2",
         "title": "OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V2 (OMPS_NPP_LP_L1G_EV) at GES DISC",
@@ -150652,7 +150886,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1412974463-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1412974463-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L1G_EV_2",
         "description": "The OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150665,7 +150899,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2469227759-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L1G_EV_2.6",
         "description": "The OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150678,7 +150912,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1898401389-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1898401389-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L2_AER_DAILY_2",
         "description": "The OMPS-NPP L2 LP Aerosol Extinction Vertical Profile swath daily 3slit (AER) product contains the retrieved aerosol extinction coefficients measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The AER product measures stratospheric aerosol abundance and evolution at 6 wavelengths (510, 600, 675, 745, 869 and 997 nm) to complement the OMPS LP measurements of stratospheric and mesospheric profile ozone. This product replaces the previous single wavelength 675 nm (AER675) product.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150691,7 +150925,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1410181089-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1410181089-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L2_O3_DAILY_2",
         "description": "The OMPS-NPP L2 LP Ozone (O3) Vertical Profile swath daily 3slit collection contains ozone measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP ozone product measures the vertical distribution of ozone in the stratosphere and lower mesosphere. The algorithm derives ozone profile values along with errors in the UV from 29.5 km and 52.5 km, and in the visible from cloud top to 37.5 km (when there are no clouds the lower limit is 12.5 km).   Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, the data from the center of the LP three slits are used to make a vertical profile. The profile is measured from the ground up to about 60 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150704,7 +150938,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2567918494-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2567918494-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L2_O3_DAILY_2.6",
         "description": "Version 2.6 is the current version of this data product, and supersedes all previous versions.  The OMPS-NPP L2 LP Ozone (O3) Vertical Profile swath daily Center slit collection contains ozone measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP ozone product measures the vertical distribution of ozone in the stratosphere and lower mesosphere. The algorithm derives ozone profile values along with errors in the UV from 29.5 km and 52.5 km, and in the visible from cloud top to 37.5 km (when there are no clouds the lower limit is 12.5 km). See the README for full description of the product and updated retrieval algorithm.   Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, the data from the center of the LP three slits are used to make a vertical profile. The profile is measured from the ground up to about 60 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150730,7 +150964,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2849507277-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2849507277-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L2_Temp_DAILY_1.0",
         "description": "The OMPS-NPP LP L2 Temperature Vertical Profile swath daily 3-slit collection contains the temperature profile measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The product measures the temperature in the stratosphere and lower mesosphere.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, the data from the center of the LP three slits are used to make a vertical profile. The profile is measured from the ground up to about 60 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150743,7 +150977,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2567921544-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2567921544-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_LP_L3_AER_MONTHLY_1",
         "description": "The OMPS-NPP L3 LP Aerosol Extinction Vertical Profile 5 x 15 deg lat-lon grid multi-wavelength monthly (AER) product contains the retrieved aerosol extinction coefficients measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The AER product measures stratospheric aerosol abundance and evolution at 6 wavelengths (510, 600, 675, 745, 869 and 997 nm) to complement the OMPS LP measurements of stratospheric and mesospheric profile ozone.  Each granule contains data from the daylight portion of each orbit averaged over an entire month in 5 x 15 deg lat-lon grids. Spatial coverage is global (-90 to  90 degrees latitude). The profiles are gridded from the ground up to about 41 km with a vertical resolution of the 1.0 km. The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150769,7 +151003,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1701674727-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1701674727-GES_DISC.html",
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         "description": "The OMPS-NPP L2 NM Cloud Pressure and Fraction swath orbital product provides effective cloud fraction and effective cloud pressure retrievals from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite. The cloud pressure algorithm retrieves effective cloud pressus, a.k.a optical centroid pressure (OCP) and effective cloud fraction (ECF) using a concept of Mixed Lambert Equivalent Reflectivity (MLER) at 354.1 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150782,7 +151016,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1279850629-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1279850629-GES_DISC.html",
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         "description": "The OMPS-NPP L1B NM Radiance EV Calibrated Geolocated Swath Orbital collection contains calibrated and geolocated radiances from 300 to 380 nm measured by the OMPS Nadir-Mapper sensor on the Suomi-NPP satellite.  Each granule contains data from the daylight portion of a single orbit (about 50 minutes). Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each with a swath width of 2600 km.",
         "license": "proprietary"
     },
@@ -150795,7 +151029,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2477579430-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2477579430-GES_DISC.html",
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         "description": "The OMPS-NPP L2 NM Formaldehyde (HCHO) Total Column swath orbital product provides formaldehyde measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite. The total column HCHO amount is derived from radiances at wavelengths between 328.5 and 356.5 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day. Each has typically 400 swaths. The swath width of the NM is about 2800 km with 36 scenes, or pixels, with a footprint size of 50 km x 50 km at nadir. The files are written in the new netCDF version 4 format.",
         "license": "proprietary"
     },
@@ -150808,7 +151042,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1564538427-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1564538427-GES_DISC.html",
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         "description": "The OMPS-NPP L2 NM Aerosol Index swath orbital product provides aerosol index values from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite. This is now the official NASA aerosol index product, replacing the aerosol index found in the OMPS-NPP L2 NM Total Ozone product. The aerosol index is derived from normalized radiances using 2 wavelength pairs at 340 and 378.5 nm. Additionally, this data product contains measurements of normalized radiances, reflectivity, cloud fraction, reflectivity, and other ancillary variables.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, each has typically 400 swaths. The swath width of the NM is about 2800 km with 36 scenes, or pixels, with a footprint size of 50 km x 50 km at nadir.  The data are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150821,7 +151055,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1396070100-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1396070100-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIiwidW1tIjoiW1wib21wcy1uMjAgbm0gcGNhIHNvMiBzdGVwIDEgdG90YWwgY29sdW1uIDEtb3JiaXQgbDIgc3dhdGggMTd4MTNrbVwiLFwiR0VTX0RJU0NcIixcIk9NUFNfTjIwX05NU08yX1BDQV9MMl9TdGVwMVwiLFwiMVwiLDI4MDg2OTI1MTIsMTFdIn0%3D/OMPS_NPP_NMNO2_L2_2",
         "description": "The OMPS-NPP L2 NM Nitrogen Dioxide (NO2) Total and Tropospheric Column swath orbital collection 2 version 2.0 product contains the retrieved nitrogen dioxide (NO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the Suomi-NPP satellite. A direct vertical column fitting (DVCF) algorithm is used to retrieve the NO2 total column amount and a new spatial technique is applied to separate the stratospheric and tropospheric amounts.  Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 35 pixels in the cross-track direction, with a pixel resolution of about 50 km x 50 km at nadir. The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150834,7 +151068,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1396070103-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1396070103-GES_DISC.html",
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         "description": "The OMPS-NPP L2 NM Sulfur Dioxide (SO2) Total and Tropospheric Column swath orbital collection 2 version 2.0 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the Suomi-NPP satellite. A direct vertical column fitting (DVCF) algorithm is used to retrieve the SO2 total column amount and column amounts in the lower (centered at 2.5 km), middle (centered at 7.5 km) and upper (centered at 11 km) troposphere, as well as the lower stratosphere (centered at 16 km).  Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 35 pixels in the cross-track direction, with a pixel resolution of about 50 km x 50 km at nadir. The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
     },
@@ -150847,7 +151081,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1917909223-GES_DISC.html",
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         "description": "The OMPS_NPP_NMSO2_PCA_L2 product is part of the MEaSUREs (Making Earth Science Data Records for Use in Research Environments) suite of products.  It is retrieved from the NASA/NOAA Suomi National Polar-orbiting Partnership (SNPP) Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) spectrometer and provides contiguous daily global monitoring of anthropogenic and volcanic sulfur dioxide (SO2), an important pollutant and aerosol precursor that affects both air quality and the climate. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017), and continues (Zhang et al., 2017) NASA's Earth Observing System (EOS) standard Aura/Ozone Monitoring Instrument SO2 product (OMSO2).   The latest OMPS_NPP_NMSO2_PCA_L2 V2 product uses new Jacobian lookup tables and more realistic model based a priori profiles in anthropogenic SO2 retrievals. This helps to more accurately account for the pixel-to-pixel variation in SO2 sensitivity due to different factors such as the vertical distribution of SO2, solar and viewing angles, surface reflectivity, and cloudiness. As compared with the previous OMPS_NPP_NMSO2_PCA_L2 V1.2 product that assumes the same SO2 sensitivity for all OMPS pixels, the new V2 anthropogenic SO2 retrievals have reduced retrieval biases especially over background regions (see Figure 1 for an example). The same updated PCA SO2 retrieval algorithm (Li et al., 2020) is also used to produce the recently released OMSO2 V2 product (doi:10.5067/Aura/OMI/DATA2022). The new OMPS_NPP_NMSO2_PCA_L2 V2 product thus offers enhanced consistency between the NASA EOS standard (OMI) and continuity (OMPS) SO2 data records  Sulfur Dioxide (SO2) is a short-lived gas primarily produced by volcanoes, power plants, refineries, metal smelting and burning of fossil fuels. Where SO2 remains near the Earth's surface, it is toxic, causes acid rain, and degrades air quality. Where SO2 is lofted into the free troposphere, it forms aerosols that can alter cloud reflectivity and precipitation. In the stratosphere, volcanic SO2 forms sulfate aerosols that can result in climate change.",
         "license": "proprietary"
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         "description": "The OMPS-NPP L3 NM PCA Sulfur Dioxide (SO2) Total Column Daily Best Pixel Global Gridded 0.25 x 0.25 degree product contains sulfur dioxide amounts gridded at 0.25 x 0.25 degree resolution using the 'best' pixel method. Data are measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the Suomi-NPP satellite. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017).  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and the spatial resolution is 0.25 x 0.25 degrees.  The files are written using netCDF version 4.",
         "license": "proprietary"
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         "description": "The OMPS-NPP L2 NM Ozone (O3) Total Column swath orbital product provides total ozone measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite. The total column ozone amount is derived from normalized radiances using 2 wavelength pairs 317.5 and 331.2 nm under most conditions, and 331.2 and 360 nm for high ozone and high solar zenith angle conditions. Additionally, this data product contains measurements of UV aerosol index and reflectivity at 331 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, each has typically 400 swaths. The swath width of the NM is about 2800 km with 36 scenes, or pixels, with a footprint size of 50 km x 50 km at nadir. The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
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         "description": "The OMPS-NPP L3 NM Ozone (O3) Total Column 1.0 deg grid daily product provides total ozone measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite. The level-3 gridding algorithm is used to combine the orbital OMPS cross track measurements into a daily map product with a fixed global grid. Grid cells are computed as weighted averages of a given parameter derived for the field-of-views that overlay the given cell. The current version of this product includes UV aerosol index and reflectivity at 331 nm retrievals as well.   Each granule contains data for a full day. Spatial coverage is global (-90 to  90 degrees latitude), with a resolution of 1.0 degree in longitude and 1.0 degree in latitude, and array size of 360 by 180. The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
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         "description": "The OMPS-NPP L2 NP Ozone (O3) Total Column swath orbital product provides ozone profile retrievals from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Profiler (NP) instrument on the Suomi-NPP satellite. The V8 ozone profile algorithm relies on nadir profiler measurements made in the 250 to 310 nm range, as well as from measurements from the nadir mapper in the 300 to 380 nm range. Ozone mixing ratios are reported at 15 pressure levels between 50 and 0.5 hPa. Additionally, this data product contains measurements of total ozone, UV aerosol index and reflectivities at 331 and 380 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-82 to +82 degrees latitude), and there are about 14.5 orbits per day, each has typically 80 profiles. The NP footprint size is 250 km x 250 km. The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
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         "description": "The OMPS-NPP L2 NP Ozone (O3) Total Column swath orbital product provides ozone profile retrievals from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Profiler (NP) instrument on the Suomi-NPP satellite. The V8 ozone profile algorithm relies on nadir profiler measurements made in the 250 to 310 nm range, as well as from measurements from the nadir mapper in the 300 to 380 nm range. Ozone mixing ratios are reported at 15 pressure levels between 50 and 0.5 hPa. Additionally, this data product contains measurements of total ozone, UV aerosol index and reflectivities at 331 and 380 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-82 to +82 degrees latitude), and there are about 14.5 orbits per day, each has typically 80 profiles. The NP footprint size is 250 km x 250 km. The files are written using the Hierarchical Data Format Version 5 or HDF5.",
         "license": "proprietary"
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         "description": "The OMPS-NPP L1B NP Radiance EV Calibrated Geolocated Swath Orbital collection contains calibrated and geolocated radiances from 300 to 380 nm measured by the OMPS Nadir-Profiler sensor on the Suomi-NPP satellite.  Each granule typically contains data from the daylight portion of a single orbit (about 50 minutes). Spatial coverage is nearly global (-82 to 82 degrees latitude), and there are about 14.5 orbits per day each with a single nadir measurement along the satellite track.",
         "license": "proprietary"
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@@ -150938,7 +151172,7 @@
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         "description": "This Level-2G daily global gridded product OMSO2G is based on the pixel level OMI Level-2 SO2 product OMSO2.  OMSO2G data product is a special Level-2 gridded product where pixel level products are binned into 0.125x0.125 degree global grids. It contains the data for all scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999 . All data pixels that fall in a grid box are saved without averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products.  The OMSO2G data product contains almost all parameters that are contained in OMSO2 files. For example, in addition to three values of SO2 Vertical column corresponding to three a-priori vertical profiles used in the  retrieval algorithm, and ancillary parameters, e.g., UV aerosol index, cloud fraction, cloud pressure, geolocation, solar and satellite viewing angles, and quality flags.  The OMSO2G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 146 Mbytes.",
         "license": "proprietary"
     },
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         "description": "The Aura Ozone Monitoring Instrument (OMI) level 2 sulphur dioxide (SO2) total column product (OMSO2) has been updated with a principal component analysis (PCA)-based algorithm (v2) with new SO2 Jacobian lookup tables and a priori profiles that significantly improve retrievals for anthropogenic SO2. The data files (or granules) contain different estimates of the vertical column density (VCD) of SO2 depending on the users investigating anthropogenic or volcanic sources.  Files also contain quality flags, geolocation and other ancillary information. The lead scientist for the OMSO2 product is Can Li.  The OMSO2 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the daylit half of an orbit (~53 minutes). There are approximately 14 orbits per day. The resolution of the data is 13x24 km2 at nadir, with a swath width of 2600 km and 60 pixels per scan line every 2 seconds.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236350970-GES_DISC.html",
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         "description": "This is a CloudSat-collocated subset of the original product OMSO2, for the purposes of the A-Train mission.  The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. Even though collocated with CloudSat, this subset can serve many other A-Train applications.  (The shortname for this CloudSat-collocated subset of the original product OMSO2 Product is OMSO2_CPR_V003)              This document describes the original OMI SO2 product (OMSO2) produced from global mode UV measurements of the Ozone Monitoring Instrument (OMI). OMI was launched on July 15, 2004 on the EOS Aura satellite, which is in a sun-synchronous ascending polar orbit with 1:45pm local equator crossing time. The data collection started on August 17, 2004 (orbit 482) and continues to this day with only minor data gaps. The minimum SO2 mass detectable by OMI is about two orders of magnitude smaller than the detection threshold of the legacy Total Ozone Mapping Spectrometer (TOMS) SO2 data (1978-2005) [Krueger et al 1995]. This is due to smaller OMI footprint and the use of wavelengths better optimized for separating O3 from SO2.  The product file, called a data granule, covers the sunlit portion of the orbit with an approximately 2600 km wide swath containing 60 pixels per viewing line. During normal operations, 14 or 15 granules are produced daily, providing fully contiguous coverage of the globe. Currently, OMSO2 products are not produced when OMI goes into the \"zoom mode\" for one day every 452 orbits (~32 days). For each OMI pixel we provide 4 different estimates of the column density of SO2 in Dobson Units (1DU=2.69x10^16 molecules/cm2) obtained by making different assumptions about the vertical distribution of the SO2. However, it is important to note that in most cases the precise vertical distribution of SO2 is unimportant. The users can use either the SO2 plume height, or the center of mass altitude (CMA) derived from SO2 vertical distribution, to interpolate between the 4 values:   1)Planetary Boundary Layer (PBL) SO2 column (ColumnAmountSO2_PBL), corresponding to CMA of 0.9 km. 2)Lower tropospheric SO2 column (ColumnAmountSO2_TRL), corresponding to CMA of 2.5 km. 3)Middle tropospheric SO2 column, (ColumnAmountSO2_TRM), usually produced by volcanic degassing, corresponding to CMA of 7.5 km,   4)Upper tropospheric and Stratospheric SO2 column (ColumnAmountSO2_STL), usually produced by explosive volcanic eruption, corresponding to CMA of 17 km.   The accuracy and precision of the derived SO2 columns vary significantly with the SO2 CMA and column amount, observational geometry, and slant column ozone. OMI becomes more sensitive to SO2 above clouds and snow/ice, and less sensitive to SO2 below clouds. Preliminary error estimates are discussed below (see Data Quality Assessment).   OMSO2 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMSO2 data product is about 9 Mbytes.",
         "license": "proprietary"
     },
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         "description": "The OMI science team produces this Level-3 Aura/OMI Global OMSO2e Data Products (0.25 degree Latitude/Longitude grids). In this Level-3 daily global SO2 data product, each grid contains only one observation of Total Column Density of SO2 in the Planetary Boundary Layer (PBL), based on an improved Principal Component Analysis (PCA) Algorithm. This single observation is the \"best pixel\", selected from all \"good\" L2 pixels of OMSO2 that overlap this grid and have UTC time between UTC times of 00:00:00 and 23:59:59.999. In addition to the SO2 Vertical column value some ancillary parameters, e.g., cloud fraction, terrain height, scene number, solar and satellite viewing angles, row anomaly flags, and quality flags have been also made available corresponding to the best selected SO2 data pixel in each grid.  The OMSO2e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5) using the grid model.",
         "license": "proprietary"
     },
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         "description": "This Level-2G daily global gridded product OMTO3G is based on the pixel level OMI Level-2 Total Ozone Product OMTO3. The OMTO3 product is from the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. The OMTO3G data product is a special Level-2 Global Gridded Product where pixel level data are binned into 0.25x0.25 degree global grids. It contains the data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All data pixels that fall in a grid box are saved Without Averaging. Scientists can apply a data filtering scheme of their choice and create new gridded products.  The OMTO3G data product contains almost all parameters that are contained in the OMTO3. For example, in addition to the total column ozone it also contains  UV aerosol index, cloud fraction, cloud pressure, terrain height, geolocation, solar and satellite viewing angles, and quality flags.  The OMTO3G files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3G data product is about 150 Mbytes.",
         "license": "proprietary"
     },
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         "description": "The Aura Ozone Monitoring Instrument (OMI) Level-2 Total Column Ozone Data Product OMTO3 (Version 003) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI provides two Level-2 (OMTO3 and OMDOAO3) total column ozone products at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms. This level-2 global total column ozone product (OMTO3) is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrievals (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3. The algorithm lead for this product is NASA OMI scientist  Dr. Pawan K. Bhartia.  The OMTO3 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is approximately 35 MB.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236350982-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbGV2ZWwgMWIgdXYgem9vbS1pbiBnZW9sb2NhdGVkIGVhcnRoc2hpbmUgcmFkaWFuY2VzIDEtb3JiaXQgbDIgc3dhdGggMTN4MTIga20gdjAwMyAob21sMWJydXopIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01MMUJSVVpcIixcIjNcIiwxMjM5OTY2NzgwLDM4XSIsInVtbSI6IltcIm9taS9hdXJhIGxldmVsIDFiIHV2IHpvb20taW4gZ2VvbG9jYXRlZCBlYXJ0aHNoaW5lIHJhZGlhbmNlcyAxLW9yYml0IGwyIHN3YXRoIDEzeDEyIGttIHYwMDMgKG9tbDFicnV6KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIk9NTDFCUlVaXCIsXCIzXCIsMTIzOTk2Njc4MCwzOF0ifQ%3D%3D/OMTO3_CPR_003",
         "description": "This is a CloudSat-collocated subset of the original product OMTO3, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications.             (The shortname for this CloudSat-collocated OMI Level 2 Total Ozone Column subset is OMTO3_CPR_V003)",
         "license": "proprietary"
     },
@@ -151055,10 +151289,23 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136070-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136070-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbm8yIHRvdGFsIGFuZCB0cm9wb3NwaGVyaWMgY29sdW1uIGRhaWx5IGwyIGdsb2JhbCBncmlkZGVkIDAuMjUgZGVncmVlIHggMC4yNSBkZWdyZWUgdjMgKG9tbm8yZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTU5PMkdcIixcIjNcIiwxMjY2MTM2MTIxLDQzXSIsInVtbSI6IltcIm9taS9hdXJhIG5vMiB0b3RhbCBhbmQgdHJvcG9zcGhlcmljIGNvbHVtbiBkYWlseSBsMiBnbG9iYWwgZ3JpZGRlZCAwLjI1IGRlZ3JlZSB4IDAuMjUgZGVncmVlIHYzIChvbW5vMmcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01OTzJHXCIsXCIzXCIsMTI2NjEzNjEyMSw0M10ifQ%3D%3D/OMTO3d_003",
         "description": "The OMI science team produces this Level-3 daily global TOMS-Like Total Column Ozone gridded product OMTO3d (1 deg Lat/Lon grids). The OMTO3d product is produced by gridding and averaging only good quality level-2 total column ozone orbital swath data (OMTO3, based on the enhanced TOMS version-8 algorithm) on the 1x1 degree global grids.  The OMTO3d files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3d data product is about 0.65 Mbytes.",
         "license": "proprietary"
     },
+    {
+        "id": "OMTO3e_003",
+        "title": "OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC",
+        "catalog": "GES_DISC STAC Catalog",
+        "state_date": "2004-10-01",
+        "end_date": "",
+        "bbox": "-180, -90, 180, 90",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbm8yIHRvdGFsIGFuZCB0cm9wb3NwaGVyaWMgY29sdW1uIGRhaWx5IGwyIGdsb2JhbCBncmlkZGVkIDAuMjUgZGVncmVlIHggMC4yNSBkZWdyZWUgdjMgKG9tbm8yZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTU5PMkdcIixcIjNcIiwxMjY2MTM2MTIxLDQzXSIsInVtbSI6IltcIm9taS9hdXJhIG5vMiB0b3RhbCBhbmQgdHJvcG9zcGhlcmljIGNvbHVtbiBkYWlseSBsMiBnbG9iYWwgZ3JpZGRlZCAwLjI1IGRlZ3JlZSB4IDAuMjUgZGVncmVlIHYzIChvbW5vMmcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01OTzJHXCIsXCIzXCIsMTI2NjEzNjEyMSw0M10ifQ%3D%3D/OMTO3e_003",
+        "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles.  The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes.",
+        "license": "proprietary"
+    },
     {
         "id": "OMTO3e_003",
         "title": "OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT",
@@ -151072,19 +151319,6 @@
         "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) .",
         "license": "proprietary"
     },
-    {
-        "id": "OMTO3e_003",
-        "title": "OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC",
-        "catalog": "GES_DISC STAC Catalog",
-        "state_date": "2004-10-01",
-        "end_date": "",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbm8yIGNsb3VkLXNjcmVlbmVkIHRvdGFsIGFuZCB0cm9wb3NwaGVyaWMgY29sdW1uIGwzIGdsb2JhbCBncmlkZGVkIDAuMjUgZGVncmVlIHggMC4yNSBkZWdyZWUgdjMgKG9tbm8yZCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTU5PMmRcIixcIjNcIiwxMjY2MTM2MTExLDQ1XSIsInVtbSI6IltcIm9taS9hdXJhIG5vMiBjbG91ZC1zY3JlZW5lZCB0b3RhbCBhbmQgdHJvcG9zcGhlcmljIGNvbHVtbiBsMyBnbG9iYWwgZ3JpZGRlZCAwLjI1IGRlZ3JlZSB4IDAuMjUgZGVncmVlIHYzIChvbW5vMmQpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01OTzJkXCIsXCIzXCIsMTI2NjEzNjExMSw0NV0ifQ%3D%3D/OMTO3e_003",
-        "description": "The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles.  The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes.",
-        "license": "proprietary"
-    },
     {
         "id": "OMUANC_004",
         "title": "Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUANC) at GES DISC",
@@ -151094,7 +151328,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2556143653-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2556143653-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21wcy9ucHAgbDFiIG5wIHJhZGlhbmNlIGV2IGNhbGlicmF0ZWQgZ2VvbG9jYXRlZCBzd2F0aCBvcmJpdGFsIHYyIChvbXBzX25wcF9ucGV2X2wxYikgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTVBTX05QUF9OUEVWX0wxQlwiLFwiMlwiLDEyNzk4NTA2MTEsMjRdIiwidW1tIjoiW1wib21wcy9ucHAgbDFiIG5wIHJhZGlhbmNlIGV2IGNhbGlicmF0ZWQgZ2VvbG9jYXRlZCBzd2F0aCBvcmJpdGFsIHYyIChvbXBzX25wcF9ucGV2X2wxYikgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTVBTX05QUF9OUEVWX0wxQlwiLFwiMlwiLDEyNzk4NTA2MTEsMjRdIn0%3D/OMUANC_004",
         "description": "The Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km (OMUANC) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath.  The fields in this product include snow cover, sea ice cover, land cover, terrain height, row anomaly flag, and pixel area. The OMI team also provides a corresponding product for the OMI VIS swath, OMVANC. This product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir.  The OMUANC files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools.  Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official.",
         "license": "proprietary"
     },
@@ -151146,7 +151380,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136073-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136073-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbm8yIHRvdGFsIGFuZCB0cm9wb3NwaGVyaWMgY29sdW1uIGRhaWx5IGwyIGdsb2JhbCBncmlkZGVkIDAuMjUgZGVncmVlIHggMC4yNSBkZWdyZWUgdjMgKG9tbm8yZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTU5PMkdcIixcIjNcIiwxMjY2MTM2MTIxLDQzXSIsInVtbSI6IltcIm9taS9hdXJhIG5vMiB0b3RhbCBhbmQgdHJvcG9zcGhlcmljIGNvbHVtbiBkYWlseSBsMiBnbG9iYWwgZ3JpZGRlZCAwLjI1IGRlZ3JlZSB4IDAuMjUgZGVncmVlIHYzIChvbW5vMmcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01OTzJHXCIsXCIzXCIsMTI2NjEzNjEyMSw0M10ifQ%3D%3D/OMUVBG_003",
         "description": "This is Level-2G daily global gridded Aura-OMI Spectral Surface UVB Irradiance and Erythemal Dose product (OMUVBG). The OMUVBG is a special Level-2 Global Gridded type data Product (referred as Level 2G or L2G) where Level-2 or swath pixel data are binned (but not averaged)into 0.25x0.25 degree global grids. It contains the data for all L2 scenes that have observation time between UTC times of 00:00:00 and 23:59:59.9999. All ancillary parameters such as latitude, longitude, time, solar and viewing angles are also saved for each pixel. First two dimensions of each parameter correspond to spatial (Lat/Lon based) Grid ID and third dimension identifies the pixel or observed scene (referred as 'candidates' ID). Scientists can apply a data filtering scheme of their choice, average good quality pixels data in each grid and create their Level-3 products.  The OMUVBG files are available in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from the day lit portion of the globe. The maximum file size for the OMUVBG data product is about 128 MBytes.",
         "license": "proprietary"
     },
@@ -151159,7 +151393,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966859-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239966859-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1wib21pL2F1cmEgbm8yIHRvdGFsIGFuZCB0cm9wb3NwaGVyaWMgY29sdW1uIGRhaWx5IGwyIGdsb2JhbCBncmlkZGVkIDAuMjUgZGVncmVlIHggMC4yNSBkZWdyZWUgdjMgKG9tbm8yZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJPTU5PMkdcIixcIjNcIiwxMjY2MTM2MTIxLDQzXSIsInVtbSI6IltcIm9taS9hdXJhIG5vMiB0b3RhbCBhbmQgdHJvcG9zcGhlcmljIGNvbHVtbiBkYWlseSBsMiBnbG9iYWwgZ3JpZGRlZCAwLjI1IGRlZ3JlZSB4IDAuMjUgZGVncmVlIHYzIChvbW5vMmcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiT01OTzJHXCIsXCIzXCIsMTI2NjEzNjEyMSw0M10ifQ%3D%3D/OMUVB_003",
         "description": "The Aura Ozone Monitoring Instrument (OMI) Version 003 Surface UV Irradiance Product (OMUVB) is now available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. The shortname for this Level-2 OMI Surface UVB product is OMUVB. The algorithm scientists for this product are: Dr. Jari Hovila, Dr. Antii Arola and Dr. Johanna Taminnen. The OMUVB product contains erythemally weighted daily dose and dose rate, and spectral irradiances at 305, 310, 324, and 380 nm. It also contains quality flags, cloud optical depth, Lambertian Equivalent Reflectivity, Total Column Ozone amount, and other ancillary information.  The OMUVB files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an  orbit (~53 minutes). There are approximately 14 orbits per day. The  maximum file size for the OMUVB data product is about 10 Mbytes.",
         "license": "proprietary"
     },
@@ -151172,7 +151406,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136072-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1266136072-GES_DISC.html",
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         "description": "This is Level-3 daily global gridded Aura-OMI Spectral Surface UVB Irradiance and Erythemal Dose product (OMUVBd). The OMUVBd product contains global erythemally weighted daily dose and erythemal dose rate at local solar noon at 1.0x1.0 deg grids.  The OMUVBd files are available in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from the day lit portion of the globe. The maximum file size for the OMUVBd data product is about 5 MBytes.",
         "license": "proprietary"
     },
@@ -151185,7 +151419,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2556149060-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2556149060-GES_DISC.html",
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         "description": "The Primary Ancillary Data Geo-Colocated to OMI/Aura VIS 1-Orbit L2 Swath 13x24km (OMVANC) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath.  The fields in this product include snow cover, sea ice cover, land cover, terrain height, row anomaly flag, and pixel area. The OMI team also provides a corresponding product for the OMI UV2 swath, OMUANC. This product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir.  The OMVANC files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools.  Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official.",
         "license": "proprietary"
     },
@@ -151293,19 +151527,6 @@
         "description": "The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Coregistered Single-Look Complex (CSLC) from Sentinel-1 (S1) Static Layers (CSLC-S1-STATIC) validated product contains static radar geometry layers associated with the OPERA Coregistered Single-Look Complex (CSLC) from Sentinel-1 (S1) validated product. Due to the S1 mission\u2019s narrow orbital tube, radar-geometry layers vary slightly over time for each position on the ground, and therefore are considered static. These static layers are provided separately from the OPERA CSLC-S1 product, as they are produced only once or a limited number of times, to account for changes in the DEM, in the S1 orbit, or in the static layers generation algorithm. Each OPERA CSLC-S1-STATIC product is distributed as a Hierarchical Data Format version 5 (HDF5) file following the CF-1.8 convention containing both data raster layers and product metadata and corresponds to matching CSLC-S1 products with the same burst ID. OPERA CSLC-S1 products are available over North America which includes the USA and U.S. Territories, Canada within 200 km of the U.S. border, and all mainland countries from the southern U.S. border down to and including Panama. The CSLC-S1 products are available in the associated OPERA Coregistered Single-Look Complex from Sentinel-1 validated product (Version 1) dataset.",
         "license": "proprietary"
     },
-    {
-        "id": "OPERA_L2_CSLC-S1_CALVAL_V1_1",
-        "title": "OPERA Coregistered Single-Look Complex from Sentinel-1 product for Calibration & Validation (Version 1)",
-        "catalog": "ASF STAC Catalog",
-        "state_date": "2014-10-14",
-        "end_date": "2023-07-29",
-        "bbox": "-180, 4.9744342, -64.4225561, 71.2183663",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2803501758-ASF.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2803501758-ASF.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ASF/collections?cursor=eyJqc29uIjoiW1wiZXJzLTFfbGV2ZWwwXCIsXCJBU0ZcIixcIkVSUy0xX0wwXCIsXCIxXCIsMTIxMDE5Nzc2OCwxOTk4XSIsInVtbSI6IltcImVycy0xX2xldmVsMFwiLFwiQVNGXCIsXCJFUlMtMV9MMFwiLFwiMVwiLDEyMTAxOTc3NjgsMTk5OF0ifQ%3D%3D/OPERA_L2_CSLC-S1_CALVAL_V1_1",
-        "description": "This dataset contains the products used for calibration and validation of the Observational Products for End-Users from Remote Sensing Analysis (OPERA) Coregistered Single-Look Complex (CSLC) from Sentinel-1 validated product. The CSLC-S1 product is derived from Copernicus Sentinel-1A and Sentinel-1B Interferometric Wide (IW) SLC data, provided by the European Space Agency.  OPERA CSLC-S1 products are available over North America which includes USA and US Territories within 200 km from the US border, Canada, and all mainland countries from the southern US border down to and including Panama. ",
-        "license": "proprietary"
-    },
     {
         "id": "OPERA_L2_CSLC-S1_V1_1",
         "title": "OPERA Coregistered Single-Look Complex from Sentinel-1 validated product (Version 1)",
@@ -151332,19 +151553,6 @@
         "description": "The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) Static Layers (RTC-S1-STATIC) validated product contains static radar geometry layers associated with the OPERA Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) (RTC-S1) validated product.  Due to the S1 mission\u2019s narrow orbital tube, radar-geometry layers such as incidence angle, local incidence angle, number of looks, and RTC Area Normalization Factor (ANF) vary slightly over time for each position on the ground, and therefore are considered static. These static layers are provided separately from the OPERA RTC-S1 product, as they are produced only once or a limited number of times, to account for changes in the DEM, in the S1 orbit, or in the static-layers generation algorithm.  Static layers are provided as single-band cloud-optimized GeoTIFF (COG) files, with map grid matching RTC-S1 products with the same burst ID.  The standard OPERA RTC-S1 product is derived from the original Copernicus Sentinel-1 (S1) interferometric wide (IW) single-look complex (SLC) data, provided by the European Space Agency, with a temporal sampling coincident with the availability of Sentinel-1A and Sentinel-1B SLC data. The OPERA RTC-S1-STATIC and RTC-S1 products are provided at a near global scope (land masses excluding Antarctica).  The RTC-S1 products are available in the associated OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 validated product (Version 1) dataset.",
         "license": "proprietary"
     },
-    {
-        "id": "OPERA_L2_RTC-S1_CALVAL_V1_1",
-        "title": "OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 product for Calibration & Validation (Version 1)",
-        "catalog": "ASF STAC Catalog",
-        "state_date": "2014-10-28",
-        "end_date": "2023-07-13",
-        "bbox": "-180, -90, 180, 90",
-        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2803501097-ASF.umm_json",
-        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2803501097-ASF.html",
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-        "description": "This dataset contains the products used for calibration and validation of the Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) validated product.  The OPERA RTC-S1 product is derived from the original Copernicus Sentinel-1 Interferometric Wide (IW) Single Look Complex (SLC) data, provided by the European Space Agency, with a near global scope and temporal sampling coincident with the availability of S1 SLC data.      ",
-        "license": "proprietary"
-    },
     {
         "id": "OPERA_L2_RTC-S1_V1_1",
         "title": "OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 validated product (Version 1)",
@@ -151367,7 +151575,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2746980408-LPCLOUD.html",
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         "description": "The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Land Surface Disturbance Alert from Harmonized Landsat Sentinel-2 (HLS) product Version 1 maps vegetation disturbance alerts that are derived from data collected by Landsat 8 and Landsat 9 Operational Land Imager (OLI) and Sentinel-2A and Sentinel-2B Multi-Spectral Instrument (MSI). A vegetation disturbance alert is detected at 30 meter (m) spatial resolution when there is an indicated decrease in vegetation cover within an HLS pixel. The Level-3 data product also provides additional information about more general disturbance trends and auxiliary generic disturbance information as determined from the variations of the reflectance through the HLS scenes. HLS data represent the highest temporal frequency data available at medium spatial resolution. The combined observations will provide greater sensitivity to land changes, whether of large magnitude/short duration or small magnitude/long duration.  The OPERA_L3_DIST-ALERT-HLS (or DIST-ALERT) data product is provided in Cloud Optimized GeoTIFF (COG) format, and each layer is distributed as a separate file. There are 19 layers contained within the DIST-ALERT product. The layers for both vegetation and generic disturbance include disturbance status, loss or anomaly, maximum loss anomaly, disturbance confidence layer, date of disturbance, count of observations with loss anomalies, days of ongoing anomalies, and day of last disturbance detection. Additional layers are vegetation cover percent, historical percent vegetation cover, and data mask. See the Product Specification Document  for a more detailed description of the individual layers provided in the DIST-ALERT product.  ",
         "license": "proprietary"
     },
@@ -151380,7 +151588,7 @@
         "bbox": "-180, -90, 180, 90",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2519119034-LPCLOUD.html",
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         "description": "The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Land Surface Disturbance Annual from Harmonized Landsat Sentinel-2 (HLS)  product Version 1 summarizes the DIST-ALERT data product into an annual vegetation disturbance data product. Vegetation disturbance is mapped when there is an indicated decrease in vegetation cover within an HLS Version 2 pixel. The product also provides auxiliary generic disturbance information as determined from the variations of the reflectance through the DIST-ALERT scenes to provide information about more general disturbance trends. The DIST-ANN product tracks changes at the annual scale, aggregating changes identified in the DIST-ALERT product. Only confirmed disturbances from the associated year are reported together with the date of initial disturbance. As confirmed disturbances are determined using subsequent cloud-free observations to determine if the loss detections persist, the required number of HLS scenes depends on visibility of the target. Due to this dependency, summarizing the DIST-ALERT in the DIST-ANN product will have some latency contingent on the algorithmic calibration and is detailed in the Algorithm Theoretical Basis Document (ATBD).  The OPERA_L3_DIST-ANN-HLS (or DIST-ANN) data product is provided in Cloud Optimized GeoTIFF (COG) format, and each layer is distributed as a separate COG. There are 21 layers contained within the DIST-ANN product: vegetation disturbance status, historical vegetation cover indicator, maximum vegetation cover indicator, maximum vegetation anomaly value, vegetation disturbance confidence layer, date of initial vegetation disturbance, number of detected vegetation loss anomalies, vegetation disturbance duration, date of last observation assessed for vegetation disturbance, and several generic disturbance layers. Each product layer is gridded to the same resolution and tiling system as HLS V2: 30 meter (m) and Military Grid Reference System (MGRS).  See the Product Specification Document (PSD) for a more detailed description of the individual layers provided in the DIST-ANN product.   ",
         "license": "proprietary"
     },
@@ -153928,7 +154136,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2756238692-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756238692-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1widmVtYXAgMTogc2VsZWN0ZWQgbW9kZWwgcmVzdWx0c1wiLFwiT1JOTF9DTE9VRFwiLFwidmVtYXAtMV9yZXN1bHRzXzczMVwiLFwiMVwiLDI3NjIyNTM3OTYsN10iLCJ1bW0iOiJbXCJ2ZW1hcCAxOiBzZWxlY3RlZCBtb2RlbCByZXN1bHRzXCIsXCJPUk5MX0NMT1VEXCIsXCJ2ZW1hcC0xX3Jlc3VsdHNfNzMxXCIsXCIxXCIsMjc2MjI1Mzc5Niw3XSJ9/PAD_2011_1133_2",
         "description": "The Peace-Athabasca Delta (PAD) is a hydrologically complex and ecologically diverse freshwater delta formed by the confluence of the Peace, Athabasca, and Birch Rivers near the western end of Lake Athabasca, Alberta, Canada. This data set includes 3 comma-delimited ASCII files: one containing water quality data and site characteristics from June and July 2010, a second containing water quality data and site characteristics for June and July 2011, and a third containing spectral reflectance of the water surface for 2011. The 2010 data file has measurements from 62 unique sites, the majority of which were revisited in 2011. Both of the 2011 data files have measurements from 99 unique sites visited 1-4 times. ",
         "license": "proprietary"
     },
@@ -153941,7 +154149,7 @@
         "bbox": "-111.71, 58.35, -111.11, 58.65",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2756235671-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756235671-ORNL_CLOUD.html",
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         "description": "The Peace-Athabasca Delta (PAD) is a large boreal wetland located in northeastern Alberta, Canada at the confluence of the Peace and Athabasca Rivers with Lake Athabasca (Figures 1 and 2). A Ramsar Convention wetland and UNESCO World Heritage Site, it is among the world's most ecologically significant wetlands.  This data set contains four comma-delimited ASCII files, two of which contain water surface elevation site and measurement information and two contain water quality and ancillary parameter location and measurement data for 120 sites within the PAD.Data archived include water surface elevation and water quality parameters measured at points throughout the Delta during summers 2006 and 2007. These data sets were originally collected to improve understanding of hydrologic recharge processes in low-relief environments and to provide ground-based measurements to validate satellite observations of inundation and sediment transport. All work was supported by the NASA Terrestrial Hydrology Program under grant NNG06GE05G to the Department of Geography, University of California-Los Angeles, Los Angeles, California. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236350976-GES_DISC.html",
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         "description": "This is the POLDER/Parasol Level-2 Radiation Budget Subset, collocated with the CloudSat track. The subset is processed at the A-Train Data Depot of the GES DISC, NASA. The algorithm first converts the original POLDER binary data, which is Level-2 but nevertheless in a sinusoidal grid, into HDF4 format, and thus stores the full-sized data in HDF4. Then, it calculates the CloudSat ground track coordinates, and proceeds to extract the closest POLDER grid cells. Along with the extraction, the algorithm re-orders the subset grid cells in a line-by-line fashion, so that the output subset is in array format and resembles a swath. This array has a cross-track dimension of 11 columns.  That makes about 200-km-wide coverage.              All original parameters are preserved in the subset. As it is collocated with CloudSat, the subset is automatically collocated with CALIPSO as well.",
         "license": "proprietary"
     },
@@ -154136,7 +154344,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768943309-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768943309-ORNL_CLOUD.html",
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         "description": "This data set provides the mean diurnal cycle of precipitation, near-surface thermodynamics, and surface fluxes generated from short-term forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) model.The model outputs were 12- to 36-hour short-range forecasts, run at a triangular truncation of T319 and a vertical resolution of 60 levels, from each daily 1200 (UTC) analysis. The version of the forecast model used to prepare this data product was the operational ECMWF model in fall 2000, which included the tiled land-surface scheme (TESSEL) (Van den Hurk et al., 2000) and recent revisions to the convection, radiation, and cloud schemes described by Gregory et al., (2000). The ECMWF model was run for two Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) campaigns conducted in Rondonia, Brazil, during January and February of 1999: the Wet Season Atmospheric Mesoscale Campaign (WETAMC) and the Tropical Rainfall Measuring Mission (TRMM). See Silva Dias et al.,(2002) for additional information regarding the WETAMAC and TRMM campaigns. There are two comma-delimited data files with this data set: the ECMWF model output data and a file containing the mean hourly precipitation observations used to check the model output for biases.",
         "license": "proprietary"
     },
@@ -154188,7 +154396,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1575363595-GES_DISC.html",
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         "description": "The Princeton University MEaSUREs Potential Evapotranspiration (PET) dataset provides a set of estimates of PET based on near surface meteorology and surface radiation data derived from a combination of reanalysis, satellite and gridded gauge data. The rationale of the project is to reduce the error from the input meteorological forcing and provide a variety of widely-used PET methods for different research and application purposes.  PET is estimated using three methods: Penman open-water method (Penman), Priestley-Taylor method (PT), Reference crop evapotranspiration using the UN Food and Agricultural Organization approach (FAO). The Penman equation assumes PET occurs from an open water surface and calculates PET based on observations of surface net radiation, near-surface air temperature, wind speed, and specific humidity (Shuttleworth, 1993). The PT equation calculates PET based on surface net radiation and near-surface air temperature and does not account for the aerodynamic component (Priestley and Taylor, 1972). The FAO equation is a specific application of the Penman-Monteith equation for crop and short-grass reference surfaces and is based on surface net radiation, near-surface air temperature, wind speed, and specific humidity (Allen, 1998).   This first version of dataset is estimated at a 3 hourly temporal resolution and 0.25x0.25 degrees spatial resolution globally, spanning the 23-year period 1984-2006. Datasets are stored as a 3-dimensional array with dimension 720 x 1440 x 8 for each day, in NetCDF-4 format.",
         "license": "proprietary"
     },
@@ -154201,7 +154409,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2028928738-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2028928738-GES_DISC.html",
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         "description": "This is version 2 of  Princeton University MEaSUREs Potential Evapotranspiration (PET) dataset, which provides a set of estimates of PET based on near surface meteorology and surface radiation data derived from a combination of reanalysis, satellite and gridded gauge data. The rationale of the project is to reduce the error from the input meteorological forcing and provide a variety of widely-used PET methods for different research and application purposes.  PET is estimated using three methods: Penman open-water method (Penman), Priestley-Taylor method (PT), Reference crop evapotranspiration using the UN Food and Agricultural Organization approach (FAO). The Penman equation assumes PET occurs from an open water surface and calculates PET based on observations of surface net radiation, near-surface air temperature, wind speed, and specific humidity (Shuttleworth, 1993). The PT equation calculates PET based on surface net radiation and near-surface air temperature and does not account for the aerodynamic component (Priestley and Taylor, 1972). The FAO equation is a specific application of the Penman-Monteith equation for crop and short-grass reference surfaces and is based on surface net radiation, near-surface air temperature, wind speed, and specific humidity (Allen, 1998).  As a follow-on to PET_PU_3H025 Version 1, PET_PU_3H025 Version 2 seeks to continue to reduce the error from the input meteorological forcing and provide a variety of widely-used PET methods for different research and application purposes. The modifications include the addition of the FAO tall reference crop equation, an extension of the radiation data and temporal coverage, the usage of the GLASS satellite albedo to estimate upward short-wave radiation and the estimation of ground heat flux based on diurnal phase shift of net radiation.  This second version of the dataset is estimated at a 3 hourly temporal resolution and 0.25x0.25 degrees spatial resolution globally, spanning the 33-year period 1984-2016. Datasets are stored as a 3-dimensional array with dimension 720 x 1440 x 8 for each day, in NetCDF-4 format.  The DOI for version 1 of the data is: 10.5067/GPZDZYELYG1A.",
         "license": "proprietary"
     },
@@ -154331,7 +154539,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1432636971-GES_DISC.html",
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         "description": "PMRN6L1RAD_CDROM is the gridded Nimbus-6 Pressure Modulated Radiometer (PMR) Level 1 Radiance Data Product. The radiances are measured at CO2 lines in the 15 micron band. The purpose of the PMR experiment is to measure the temperature of the upper stratosphere and mesosphere from 40 to 90 km with a vertical resolution of about 10 km, and 500 km horizontal resolution. This product contains radiances in a daily 4 degree latitude x 10 degree longitude grid format, as well as copies of the original tapes. The data for this product are available from 16 June 1975 to 24 June 1978. The principal investigator for the PMR experiment was Dr. John T. Houghton from Oxford University.  This product was created by the Oxford University's Atmospheric, Oceanic and Planetary Physics (AOPP) group. The data are stored on two CD-ROMs in ASCII files of hexadecimal characters, and are available in gzipped Unix tar archive files. The first CD-ROM contains the gridded radiance data and a few original tape data files, the second CD-ROM contains the remaining compressed copies of the original data tapes. The byte-ordering in the data files follows the DEC convention for 16-bit integers of less significant byte first. Normal 2's complement integer storage is assumed.",
         "license": "proprietary"
     },
@@ -154764,6 +154972,45 @@
         "description": "The data presented in this level 2 orbital product are rain rate estimates expressed as mm/hour determined from brightness temperatures (Tbs) obtained from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) flown on the TRMM satellite. Most of the products generated in this data set are based upon the algorithms developed for the 3rd Algorithm Intercomparison Project (AIP-3) of the Global Precipitation Climatology Project (GPCP).  Details of these 15 algorithms and development of a quality score which is a measure of confidence in the estimate, along with processing and algorithmic flags, can be found in the Algorithm Theoretical Basis Document  (ATBD).  The data in this product cover the period from 1997 to 2015 with one file per orbit.",
         "license": "proprietary"
     },
+    {
+        "id": "PREFIRE_SAT2_0-BUS-TLM_R01",
+        "title": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 telemetry R01",
+        "catalog": "LARC_CLOUD STAC Catalog",
+        "state_date": "2024-05-01",
+        "end_date": "",
+        "bbox": "-180, -84, 180, 84",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/PREFIRE_SAT2_0-BUS-TLM_R01",
+        "description": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Telemetry (PREFIRE_SAT2_0-BUS-TLM) contains positioning and pointing information for one of two PREFIRE polar orbiting CubeSats. Both CubeSats carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 \u00b5m. Most polar emissions are in the FIR but have not been measured on a large scale.  PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions.  This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.    This collection contains the time, beta angle, orbit position and velocity, and the quaternion of PREFIRE Satellite 2 (PREFIRE-SAT2).  Combined with a Digital Elevation Map, these telemeters geolocate PREFIRE data on the Earth\u2019s surface.      Data retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions.  This data is retrieved at a frequency of 1Hz and is available in CSV format.    Positioning and pointing information for the sister satellite, PREFIRE-SAT1, can be found in the PREFIRE_SAT1_0-BUS-TLM collection.    ",
+        "license": "proprietary"
+    },
+    {
+        "id": "PREFIRE_SAT2_0-PAYLOAD-TLM_R01",
+        "title": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Curated Radiance R01",
+        "catalog": "LARC_CLOUD STAC Catalog",
+        "state_date": "2024-05-01",
+        "end_date": "",
+        "bbox": "-180, -84, 180, 84",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712936-LARC_CLOUD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712936-LARC_CLOUD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/PREFIRE_SAT2_0-PAYLOAD-TLM_R01",
+        "description": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Curated Radiance (PREFIRE_SAT2_0-PAYLOAD-TLM) contains the curated raw measurements from one of two PREFIRE Thermal Infrared Spectrometers (TIRS-PREFIRE), which is a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 \u00b5m. Most polar emissions are in the FIR but have not been measured on a large scale. PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions. This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.    This collection contains the raw, curated digital number counts for TIRS-PREFIRE aboard PREFIRE Satellite 2 (PREFIRE-SAT2). Data retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. This data has a temporal resolution of 0.707 seconds and is available in binary format.    Raw, curated digital number counts for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_0-PAYLOAD-TLM collection.  ",
+        "license": "proprietary"
+    },
+    {
+        "id": "PREFIRE_SAT2_0-PAYLOAD_R01",
+        "title": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Payload R01",
+        "catalog": "LARC_CLOUD STAC Catalog",
+        "state_date": "2024-05-01",
+        "end_date": "",
+        "bbox": "-180, -84, 180, 84",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/PREFIRE_SAT2_0-PAYLOAD_R01",
+        "description": "Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Payload (PREFIRE_SAT2_0-PAYLOAD) contains the uncurated raw measurements from one of two PREFIRE Thermal Infrared Spectrometers (TIRS-PREFIRE), which is a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 \u00b5m. Most polar emissions are in the FIR but have not been measured on a large scale.  PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions.  This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.    This collection contains the raw and uncurated digital number counts for TIRS-PREFIRE aboard PREFIRE Satellite 2 (PREFIRE-SAT2).  Data retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions.  This data has a temporal resolution of 0.707 seconds and is available in binary format.    Raw, uncurated digital number counts for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_0-PAYLOAD collection.",
+        "license": "proprietary"
+    },
     {
         "id": "PREPP_0",
         "title": "Pearl River Estuary Pollution Project (PREPP)",
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864221-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864221-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZ2xvYmFsIGZvcmVzdCBlY29zeXN0ZW0gc3RydWN0dXJlIGFuZCBmdW5jdGlvbiBkYXRhIGZvciBjYXJib24gYmFsYW5jZSByZXNlYXJjaFwiLFwiT1JOTF9DTE9VRFwiLFwiZm9yZXN0X2NhcmJvbl9mbHV4Xzk0OVwiLFwiMVwiLDI3ODQ4OTA5MjcsMl0iLCJ1bW0iOiJbXCJnbG9iYWwgZm9yZXN0IGVjb3N5c3RlbSBzdHJ1Y3R1cmUgYW5kIGZ1bmN0aW9uIGRhdGEgZm9yIGNhcmJvbiBiYWxhbmNlIHJlc2VhcmNoXCIsXCJPUk5MX0NMT1VEXCIsXCJmb3Jlc3RfY2FyYm9uX2ZsdXhfOTQ5XCIsXCIxXCIsMjc4NDg5MDkyNywyXSJ9/Peatland_carbon_balance_1382_1",
         "description": "This data set provides a time series of global peatland carbon balance and carbon dioxide emissions from land use change throughout the Holocene (the past 11,000 yrs). Global peatland carbon balance was quantified using a) a continuous net carbon balance history throughout the Holocene derived from a data set of 64 dated peat cores, and b) global model simulations with the LPX-Bern model hindcasting the dynamics of past peatland distribution and carbon balance. CO2 emissions from land-use change are based on published scenarios for anthropogenic land use change (HYDE 3.1, HYDE 3.2, KK10) covering the last 10,000 years. This combination of model estimates with CO2 budget constraints narrows the range of past anthropogenic land use change emissions and their contribution to past carbon cycle changes.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2254686682-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2254686682-ORNL_CLOUD.html",
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         "description": "This dataset consists of an ensemble of model projections from 1901 to 2299 for the northern hemisphere permafrost domain. The model projections include monthly average values for a common set of diagnostic outputs at a spatial resolution of 0.5 x 0.5 degrees latitude and longitude. The model simulations resulted from a synthesis effort organized by the Permafrost Carbon Network to evaluate the impacts of climate change on the carbon cycle in permafrost regions in the high northern latitudes.  The model teams used different historical input weather data, but most used driver data developed by the Climate Research Unit - National Centers for Environmental Prediction (CRUNCEP) as modified for the Multiscale Terrestrial Model Intercomparison Project (MsTMIP).  The teams scaled the driver data for the projections using output from global climate models from the fifth Coupled Model Intercomparison Project (CMIP5). The synthesis evaluated the terrestrial carbon cycle in the modern era and projected future emissions of carbon under two climate warming scenarios: Representative Concentration Pathways 4.5 and 8.5 (RCP45 and RCP85) from CMIP5. RCP45 represents emissions resulting in a global climate close to the target climate in the Paris Accord. RCP85 represents unconstrained greenhouse gas emissions.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764826583-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764826583-ORNL_CLOUD.html",
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         "description": "This data set provides a time series of vegetation phenological observations for 393 sites across diverse ecosystems of the world (mostly North America) from 2000-2018. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and means and other statistics calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764728896-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764728896-ORNL_CLOUD.html",
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         "description": "This dataset provides a time series of visible-wavelength digital camera imagery collected through the PhenoCam Network at each of 393 sites predominantly in North America from 2000-2018. The raw imagery was used to derive information on phenology, including time series of vegetation color, canopy greenness, and phenology transition dates for the PhenoCam Dataset v2.0. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764693210-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764693210-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGFuZCBzdXJmYWNlIG1vZGVsIChsc20gMS4wKSBmb3IgZWNvbG9naWNhbCwgaHlkcm9sb2dpY2FsLCBhdG1vc3BoZXJpYyBzdHVkaWVzXCIsXCJPUk5MX0NMT1VEXCIsXCJMU01fODA3XCIsXCIxXCIsMjk1NjUzOTI0NCwyXSIsInVtbSI6IltcImxhbmQgc3VyZmFjZSBtb2RlbCAobHNtIDEuMCkgZm9yIGVjb2xvZ2ljYWwsIGh5ZHJvbG9naWNhbCwgYXRtb3NwaGVyaWMgc3R1ZGllc1wiLFwiT1JOTF9DTE9VRFwiLFwiTFNNXzgwN1wiLFwiMVwiLDI5NTY1MzkyNDQsMl0ifQ%3D%3D/Phenology_AmeriFlux_Neon_Sites_2033_1",
         "description": "This land surface phenology (LSP) dataset provides spatially explicit data related to the timing of phenological changes such as the start, peak, and end of vegetation activity, vegetation index metrics and associated quality assurance flags. The data are for the growing seasons of 2017-2021 for 10-km x 10-km windows centered over 104 eddy covariance towers at AmeriFlux and National Ecological Observatory Network (NEON) sites. The dataset is derived at 3-m spatial resolution from PlanetScope imagery across a range of plant functional types and climates in North America. These LSP data can be used to assess satellite-based LSP products, to evaluate predictions from land surface models, and to analyze processes controlling the seasonality of ecosystem-scale carbon, water, and energy fluxes. The data are provided in NetCDF format along with geospatial area-of-interest information and visualizations of the analysis window for each site in GeoJSON and HTML formats.",
         "license": "proprietary"
     },
@@ -155215,7 +155462,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764880255-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764880255-ORNL_CLOUD.html",
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         "description": "This dataset provides Landsat phenology algorithm (LPA) derived start and end of growing seasons (SOS and EOS) at 500-m resolution for deciduous and mixed forest areas of 75 selected Landsat sidelap regions across the Eastern United States and Canada. The data are a 30-year time series (1984-2013) of derived spring and autumn phenology for forested areas of the Eastern Temperate Forest, Northern Forest, and Taiga ecoregions.",
         "license": "proprietary"
     },
@@ -155332,7 +155579,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2240727642-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2240727642-ORNL_CLOUD.html",
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         "description": "This dataset includes field measurements from unburned and burned 10 m x 10 m and 1 m x 1 m plots in the Noatak, Seward, and North Slope regions of the Alaskan tundra during July through August in the years 2016-2018. The data include vegetation coverage, soil moisture, soil temperature, soil thickness, thaw depth, and weather measurements. Measurements were recorded using ocular assessments and standard equipment. Plot photographs are included.",
         "license": "proprietary"
     },
@@ -155371,7 +155618,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2236236883-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2236236883-ORNL_CLOUD.html",
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         "description": "This data set provides 3-hourly estimates of gross ecosystem CO2 exchange (GEE) and respiration (autotrophic and heterotrophic) for the state of Alaska from 2012 to 2014. The data were generated using the Polar Vegetation Photosynthesis and Respiration Model (PolarVPRM) and are provided at ~ 1 km2 [1/4-degree (longitude) by 1/6-degree (latitude)] pixel resolution. The PolarVPRM produces high-frequency estimates of GEE of CO2 for North American biomes from remotely-sensed data sets. For Alaska, the model used meteorological inputs from the North American regional re-analysis (NARR) and inputs of fractional snow cover and land surface water index (LSWI) from the Moderate Resolution Imaging Spectroradiometer (MODIS). Land surface greenness was factored into the model from three sources: 1) Enhanced Vegetation Index (EVI) from MODIS; 2) Solar Induced Florescence (SIF) from the Orbiting Carbon Observatory 2 (OCO-2); and 3) SIF from the Global Ozone Monitoring Experiment 2 (GOME-2). Three independent estimates of GEE are included in the data set, one for each source of greenness observations.",
         "license": "proprietary"
     },
@@ -155475,7 +155722,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2854211353-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2854211353-ORNL_CLOUD.html",
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         "description": "This dataset provides site moisture, soil organic layer thickness, soil organic carbon, nonvascular plant functional group, stand dominance, ecozone, time-after-fire, jack pine proportion, and deciduous proportion for 511 forested plots spanning  ~140,000 km2 across two ecozones of the Northwest Territories, Canada (NWT). The plots were established during 2015-2018 across 41 wildfire scars and unburned areas (no burn history prior to 1965), with 317 plots in the Plains and 194 plots in the Shield regions. At each plot, two adjacent 30-m transects were established 2 m apart, running north from the plot origin. Soil organic layer (SOL) depth (cm) was measured every 3 m and the mean was taken from the 10 measurements to calculate a plot-level SOL thickness. Three soil organic layer profiles were destructively sampled at 0, 12, and 24 m using a corer that was custom designed for NWT soils. Within the transects, all stems taller than 1.37 m were identified to species to calculate tree density (stems / m2). Nonvascular plant percent cover was identified to functional group at five, 1-m2 quadrats spaced 6 m apart along the belt transect. A subset of 2,067 of 5,137 total increments from 1,803 profiles from 421 plots were analyzed for total percent C using a CHN analyzer. Time-after-fire was established using fire history records. For older plots where no known fire history is recorded, tree age was used. Data are for the period 2015-06-11 to 2018-08-24 and are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2143402734-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2143402734-ORNL_CLOUD.html",
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         "description": "This data set provides level 1 (L1) polarimetric radar backscattering coefficient (sigma-0), multi-look complex, polarimetrically calibrated, and georeferenced data products from the Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS) radar instrument collected over 10 study sites across Northern Alaska, USA. Flight campaigns took place in August 2014, October 2014, April 2015, August 2015, September 2015, and October 2015. The acquired L1 P-band radar backscatter data will be used to derive estimates of soil water content and permafrost state at the study sites.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025124066-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025124066-ORNL_CLOUD.html",
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         "description": "This dataset provides river discharge measurements collected at selected locations across the Atchafalaya River Basin, within the Mississippi River Delta (MRD) floodplain in coastal Louisiana, USA. The measurements were made during the Pre-Delta-X campaign on October 15 to 20, 2016. Seventy-five channel surveys were conducted with a SonTek RiverSurveyor M9 acoustic doppler current profiler (ADCP) on selected wide channels (~100 m) and a few selected (~10 m) narrow channels. ADCP data provide near-instantaneous estimates of river discharge across the sampled channels. Sites coincided with AirSWOT swaths in the Atchafalaya River Basin and water level measurement locations. This in situ dataset was used to calibrate and validate Delta-X hydrodynamic models.",
         "license": "proprietary"
     },
@@ -155514,7 +155761,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126590-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126590-ORNL_CLOUD.html",
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         "description": "This dataset contains lidar-derived water surface elevation profiles for river channels between Wax Lake, in the Atchafalaya River Basin of the Mississippi River Delta, and the Gulf of Mexico. The provided elevation profiles (i.e., water levels) were estimated using remotely sensed lidar data in combination with in situ field measurements of water levels for elevation calibration and to quantify uncertainty in estimates. The lidar data were collected during the Fall 2016 Pre-Delta-X Campaign using an Airborne Snow Observatory (ASO) lidar instrument. The results are time-specific water levels measured as elevation in meters with respect to the North American Vertical Datum 1988 (NAVD 88) geoid (or orthometric height) and the World Geodetic System 1984 (WGS 84) ellipsoidal surface (or ellipsoidal/GPS height) along the water channels in this drainage system.",
         "license": "proprietary"
     },
@@ -155527,7 +155774,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123576-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123576-ORNL_CLOUD.html",
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         "description": "This dataset provides measurements of in situ remote-sensing reflectance (Rrs; per steradian) of surface water across Atchafalaya Basin, southern coastal Louisiana, USA within Mississippi River Delta (MRD) floodplain. The in situ spectral reflectance measurements were made during the Pre-Delta-X campaign in Fall 2016 (October 14 to 2). Hand-held spectrometer measurements were collected from a boat at 35 locations selected to represent a range of suspended sediment concentrations and properties from a variety of hydrodynamic and physical settings typically encountered across the Atchafalaya basin. These 35 spectral reflectance measurements were collected at 24 unique sites that coincide with measurements of total suspended solids (TSS). The data serves two main purposes, to ground-truth the remote-sensing reflectance derived from NASA's Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) instrument, and to calibrate and validate algorithms for the retrieval of TSS from AVIRIS-NG.",
         "license": "proprietary"
     },
@@ -155540,7 +155787,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126944-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126944-ORNL_CLOUD.html",
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         "description": "This Level 2 (L2) dataset provides surface spectral reflectance data acquired over the Atchafalaya and Terrebonne basins of the Mississippi River Delta (MRD) of coastal Louisiana, USA, in 2015-2016. The data include georectified images with Lambertian-equivalent surface reflectance and composite mosaics with adjustments for Bidirectional Reflectance Distribution Function (BRDF) effects. The imagery was acquired by the Airborne Visible/Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG), as part of the Pre-Delta-X campaign.",
         "license": "proprietary"
     },
@@ -155553,7 +155800,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025125582-ORNL_CLOUD.html",
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         "description": "This dataset provides water surface elevations over the Wax Lake Delta in the Atchafalaya Basin in coastal Louisiana, USA, in May 2015. These Level 2 (L2) data were collected by AirSWOT, an airborne instrument employing near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and produce continuous gridded elevation data at 3.6 m resolution. Along with elevation estimates, the dataset includes measures of estimation errors, sensitivity, incidence angle, backscatter, and interferometric correlation. For this application, in situ water level data were added into the AirSWOT phase calibration procedure. These L2 data consist of a set of rasters in Universal Transverse Mercator (UTM) map coordinates for each of the 39 AirSWOT flight lines. These elevation data were later used for calculating elevation and slopes along the main channels in this wetland system, as well as tying observations to ocean tidal conditions.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126705-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126705-ORNL_CLOUD.html",
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         "description": "This dataset includes aboveground biomass (AGB) and vegetation of herbaceous and forest wetland at 5.4 m resolution across the Wax Lake Delta (WLD) in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Vegetation classes were derived from Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquired over the Atchafalaya Basin and the Terrebonne Basin in October 2016 in combination with a digital elevation model. The AVIRIS-NG surface reflectance data were also combined with L-band Uninhabited Airborne Vehicle Synthetic Aperture Radar (UAVSAR) HV backscatter and scattering component values from coincident vegetation sample sites to develop and test AGB models for emergent herbaceous and forested wetland vegetation. This study used the integrated airborne data from AVIRIS-NG and UAVSAR to assess the instruments' unique capabilities in combination for estimating AGB in coastal deltaic wetlands. The 5.4 m resolution vegetation classification map for the WLD study area was then used to apply the best models to estimate AGB across the WLD.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126777-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126777-ORNL_CLOUD.html",
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         "description": "This dataset includes total suspended solids (TSS) at the water surface across the Atchafalaya and Terrebonne Basins in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. AVIRIS-NG, the Next Generation Airborne Visible to Infrared Imaging Spectrometer, acquired data over the study area in 2015 and 2016. The remote imageries were combined with coincident field measurements to develop and validate spatially explicit estimates at 3.7-5.4 m resolution of the concentration (mg/L) of TSS.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126456-ORNL_CLOUD.html",
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         "description": "This dataset contains water level profiles generated from the AirSWOT data collected in the Atchafalaya Basin in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Part of the Pre-Delta-X Campaign, AirSWOT used near-nadir wide-swath Ka-band radar interferometry to measure water-surface elevation and uncertainty in May 2015. This Level 3 (L3) AirSWOT dataset is in the form of numerous profiles of water level along the Wax Lake Outlet.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025124955-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025124955-ORNL_CLOUD.html",
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         "description": "This dataset provides water depths and water surface elevations collected during bathymetric surveys of the main channel of the Wax Lake Delta within the Mississippi River Delta (MRD) floodplain of coastal Louisiana, USA. The measurements were made during the Pre-Delta-X Campaign in Fall 2016. The in situ continuous (1 Hz) surveys of channel bathymetry were conducted using a SonarMite Hydrolite Single Beam Echo Sounder mounted on the side of the research boat. The sounder was located directly beneath the Septentrio global navigation satellite system (GNSS) antenna, about 30 cm below the water surface. The sounder depth observations were integrated with the GNSS location and elevation data into one data file per day for October 16-20. These bathymetry measurements were used to generate a merged digital elevation model (DEM) through interpolation with ancillary DEMs to expand the existing wetland DEM to include channels. The merged DEM product is distributed in GeoTIFF format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123470-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123470-ORNL_CLOUD.html",
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         "description": "This dataset contains the total suspended solids (TSS) concentration of in situ water samples collected at selected sites across the Atchafalaya and Terrebonne Basins within the Mississippi River Delta (MRD) floodplain of coastal Louisiana, USA. The measurements were made during the Pre-Delta-X campaign in Spring 2015 and Fall 2016. The sampling sites spanned large and small channels at locations chosen to cover a representative range of suspended sediment concentrations from a variety of hydrodynamic and physical settings typically encountered across the basins. Water samples were collected by bottle just beneath the surface and stored on ice until filtering. The TSS concentration was calculated as the difference of the filter weight (before and after filtration) divided by the volume of sample filtered. Both TSS and in situ spectral reflectance measurements were collected at some sampling sites. Pre-Delta-X sampling focused on surface waters, where the TSS data are used as inputs for hydrodynamic models for sediment transport and to calibrate the model to convert AVIRIS-NG spectral reflectance measurements into TSS.",
         "license": "proprietary"
     },
@@ -155631,7 +155878,7 @@
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         "description": "This dataset provides spatial data on water channels in the estuary of the Atchafalaya Basin of the Mississippi River Delta of coastal Louisiana. These Level-3 (L3) channel maps were developed from interferograms derived from Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data collected on 2016-10-16 and 2016-10-17 during low and high tides. The channel maps define open water paths in hydrodynamic models and are used to evaluate model performance.",
         "license": "proprietary"
     },
@@ -155644,7 +155891,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025125085-ORNL_CLOUD.html",
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         "description": "This Level 1 (L1) dataset includes single look complex (SLC) stack products and co-registered interferograms in the HH (horizontal transmit and horizontal receive) polarization for the Atchafalaya Basin, in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. The data were collected in October 2016 by Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), a polarimetric L-band synthetic aperture radar flown on the NASA Gulfstream-III aircraft as part of the Pre-Delta-X campaign. A single study region, flight line \"gulfco_12011\", was sampled six times at approximately 30-minute intervals to monitor changing water levels. The SLC stack product is a standard UAVSAR product delivered by the UAVSAR processing team. The L1 interferograms were generated from the SLC stacks.",
         "license": "proprietary"
     },
@@ -155657,7 +155904,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126876-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025126876-ORNL_CLOUD.html",
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         "description": "This dataset contains five maps of cumulative changes in water levels at 30-minute intervals over a 150-minute period on 2016-10-16 in the Atchafalaya Basin in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Water surface elevations were measured on six flights at 30-minute intervals, with the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), a polarimetric L-band synthetic aperture radar (SAR) flown on the NASA Gulfstream-III aircraft. The five georeferenced maps at 6 m resolution show the cumulative change of water levels (cm) every 30 minutes relative to the first sampling flight. These Level 3 maps were generated using the InSAR time series Small Baseline Subsets (SBAS) algorithm implemented in the Generic InSAR Analysis Toolbox (GIAnT) toolbox and served to evaluate and compare hydrodynamic models.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123672-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123672-ORNL_CLOUD.html",
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         "description": "This dataset provides vegetation species, height, stem density and diameter, and species aboveground biomass (AGB) measurements collected at herbaceous and forested wetland sites across the Atchafalaya and Terrebonne basins within the Mississippi River Delta (MRD) floodplain in coastal Louisiana, USA. The measurements were made during the Pre-Delta-X campaign in Spring 2015 and Fall 2015. Vegetation height and density and diameter data are only provided for forested Atchafalaya sites during the spring collections. At the nine herbaceous wetland sites, a transect was established perpendicular to the wetland edge with replicate sample plots (0.25 m2, 5 m apart) located at 50, 100, and 150 m from the wetland edge to capture the range of vegetation structure, zonation, and composition.  AGB was harvested inside the duplicate plots at each sampling location. At the six forested wetland sites, duplicate circular plots (10 m radius, 50 m apart) were established inside the forest approximately 30 m from the wetland edge. All trees with a diameter at breast height (DBH at 1.3 m) > 2.5 cm were measured within each plot and identified to species. The height of trees was measured with a laser range finder. AGB was estimated using species-specific allometric equations. Measurements were used to generate marsh and forested wetland coverage and biomass in response to seasonality within both basins. The data will be used to calibrate remote sensing data (e.g., UAVSAR, AVIRIS-NG) and hydrodynamics and sediment transport models.",
         "license": "proprietary"
     },
@@ -155683,7 +155930,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123345-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2025123345-ORNL_CLOUD.html",
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         "description": "This dataset provides absolute water level elevations derived for 10 locations across the Wax Lake Delta, Atchafalaya Basin, in Southern Louisiana, USA, within the Mississippi River Delta (MRD) floodplain. Field measurements were made during the Pre-Delta-X campaign on October 13-20, 2016. Relative water level measurements were recorded every five minutes during a one-week period using in situ pressure transducers (Solinst) to measure water surface elevation change with millimeter accuracy. The Solinst system combines a total pressure transducer (TPT) and a temperature detector. Once underwater, the TPT measures the sum of the atmosphere and water pressure above the sensor. Atmospheric pressure fluctuations must be accounted for to obtain the height of the water column above the TPT. An absolute elevation correction was applied to the water level data using an iterative approach with the USGS Calumet Station water level height and Airborne Snow Observatory (ASO) lidar water level profiles. These Pre-Delta-X water level measurements served to calibrate and validate the campaign's remote sensing observations and hydrodynamic models.",
         "license": "proprietary"
     },
@@ -155696,7 +155943,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2762262185-ORNL_CLOUD.html",
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         "description": "The data set presents the principal data from the Anglo-BRazilian Amazonian Climate Observation Study (ABRACOS) (Gash et al, 1996) and provides quality controlled information from five of the study topics considered by the project in five zipped files containing ASCII text data. The five study topics include Micrometeorology, Climate, Carbon Dioxide and Water Vapor, Plant Physiology, and Soil Moisture. The objectives of the ABRACOS were to monitor Amazonian climate and improve the understanding of the consequences of deforestation and to provide data for the calibration and validation of GCMs and GCM sub-models of Amazonian forest and post-deforestation pasture (Shuttleworth et al, 1991). Three areas were instrumented, each with different soils, dry season intensities and deforestation densities (Gash et al, 1996). In each area, an automatic weather station and soil moisture measurement equipment were installed: in a primary forest site and in nearby cattle pasture, for monitoring climate and soil status throughout the year. Additional intensive periods of study (or Missions), of varying duration, were operated at these sites: for calibration purposes, to understand the physical processes relevant to each site, and for detailed comparisons between sites. These data were collected under the ABRACOS project and made available by the UK Institute of Hydrology and the Instituto Nacional de Pesquisas Espaciais (Brazil). ABRACOS is a collaboration between the Agencia Brasileira de Cooperacao and the UK Overseas Development Administration. The processed, quality controlled and integrated data in the documented Pre-LBA data sets were originally published as a set of three CD_ROMs (Marengo and Victoria, 1998) but are now archived individually.",
         "license": "proprietary"
     },
@@ -155748,7 +155995,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2162616071-ORNL_CLOUD.html",
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         "description": "This data set provides a collection of maps of geoecological characteristics of areas within the Beechey Point quadrangle near Prudhoe Bay on the North slope of Alaska: a geobotanical atlas of the Prudhoe Bay region, a land cover map of the Beechey Point quadrangle, and cumulative impact maps in the Prudhoe Bay Oilfield for ten dates from 1968 to 2010. The geobotanical atlas is based on aerial photographs and covers 145 square kilometers of the Prudhoe Bay Oilfield. The land cover map of the Beechey Point quadrangle was derived from the Landsat multispectral scanner, aerial photography, and other  field and cartographic methods. The cumulative impact maps of the Prudhoe Bay Oilfield show historical infrastructure and natural changes digitized from aerial photos taken in each successive analysis year (1968, 1970, 1972, 1973, 1977, 1979, 1983, 1990, 2001, and 2010). Nine geoecological attributes are included: dominant vegetation, secondary vegetation, tertiary vegetation, percentage open water, landform, dominant surface form, secondary surface form, dominant soil, and secondary soil. These data document environmental changes in an Arctic region that is affected by both climate change and rapid industrial development.",
         "license": "proprietary"
     },
@@ -155995,7 +156242,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777751525-ORNL_CLOUD.html",
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         "description": "The RADAMBRASIL project extensively mapped the Amazon soils using a combination of soil pit information, aerial photography, and geologic maps.  During the project, 1,153 soil pits, distributed basin-wide, were described and sampled by horizon and analyzed for texture and chemical composition.This data set, which consists of one file in ASCII comma separated format, contains soil profile descriptions for locations throughout Brazilian Amazonia. These data are based on RADAMBRASIL surveys from the Soil Profiles of Amazonia (Source: IPAM, Brazil/WHRC, USA). See the companion file Soil Profiles of Amazonia.pdf",
         "license": "proprietary"
     },
@@ -156086,7 +156333,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777741028-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wicHJlLWxiYSBmbHVhbWF6b24gZXhwZXJpbWVudCBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJGTFVBTUFaT05fODk2XCIsXCIxXCIsMjgwNDgyMDgwNiwyXSIsInVtbSI6IltcInByZS1sYmEgZmx1YW1hem9uIGV4cGVyaW1lbnQgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwiRkxVQU1BWk9OXzg5NlwiLFwiMVwiLDI4MDQ4MjA4MDYsMl0ifQ%3D%3D/RBLE_917_1",
         "description": "The atmospheric boundary layer (ABL) is the layer of air closest to the ground which is directly influenced on a daily basis by the heating and cooling of the earth's surface. The exact depth of the ABL varies according synoptic weather conditions and the time of day. During the daytime it is usually between 1 and 3 km; during the night it is much shallower. The ABL is important because it links the fluxes of heat and water vapor observed at the surface to the general circulation of the atmosphere. To model climate correctly, it is necessary for the ABL to be well understood and represented in the model. Because the air in the ABL is turbulent, small scale variations (about 1 km or less) in evaporation and heat flux at the surface are smoothed, with the temperature, humidity and depth of the ABL being uniform over the entire area. Larger scale variations (on the scale of 10 km or more) may lead to differences in ABL properties between the different surface types. Such differences may cause local atmospheric circulations to develop which may be important for the local climate of an area. During ABRACOS, three ABL measurement campaigns were carried out. These campaigns were called the Rondonia Boundary Layer Experiment (RBLE) 1, 2 and 3 and were held at Ji-Parana where the scale of the forested and deforested areas is large enough for each surface type to develop its own ABL. Refer to the related data set, Pre-LBA Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) Data, for additional information.The processed, quality controlled and integrated data in the documented Pre-LBA Data sets were originally published as a set of three CD_ROMs (Marengo and Victoria, 1998) but are now archived individually.  The campaigns were held during the dry season when the difference in evaporation between the two surfaces types, forest and pasture, is at its greatest. Measurements were made with both free-flying radiosondes which measure temperature, humidity, and wind up to about 12 km and with a tethered balloon which makes more detailed measurements in the lowest 1 km of the atmosphere. Measurements were made at both the forest and clearing sites. Profiles of potential temperature measured during RBLE2 show that the daytime ABL was deeper over the clearing than the forest. The data have been used to test several models of ABL development. It appears that the ABL over pastures or over clearings grows more rapidly than predicted by the models, possibly because of the increased turbulence generated by the strips of forest typical of this area. The data have also been used to initialize one-dimensional climate models used in experiments to investigate the sensitivity of climate to land surface parameters, and to initialize a mesoscale model which can predict local effects on climate caused by the pattern of deforestation in this area.",
         "license": "proprietary"
     },
@@ -156675,6 +156922,19 @@
         "description": "Hydrometeorological data on the conditions of the environment are held       by the Russian State Fund of data. This dataset was created by West       Subiria Computer Centre in 1977 and containes data from 1078 stations       of the USSR. Data is currently stored on magnetic tape (800 bit/inch).",
         "license": "proprietary"
     },
+    {
+        "id": "RSS18_AVIRIS_L1B_449_1",
+        "title": "BOREAS RSS-18 Level 1B AVIRIS At-Sensor Radiance Imagery",
+        "catalog": "ORNL_CLOUD STAC Catalog",
+        "state_date": "1996-08-14",
+        "end_date": "1996-08-14",
+        "bbox": "-106.49, 53.45, -105.03, 54.32",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHJzcy0xNCBnb2VzLTcgbGV2ZWwtMiBzaG9ydHdhdmUgYW5kIGxvbmd3YXZlIHJhZGlhdGlvbiBpbWFnZXNcIixcIk9STkxfQ0xPVURcIixcImdvZXM3Ml81NTRcIixcIjFcIiwyOTI5MTYzODk2LDJdIiwidW1tIjoiW1wiYm9yZWFzIHJzcy0xNCBnb2VzLTcgbGV2ZWwtMiBzaG9ydHdhdmUgYW5kIGxvbmd3YXZlIHJhZGlhdGlvbiBpbWFnZXNcIixcIk9STkxfQ0xPVURcIixcImdvZXM3Ml81NTRcIixcIjFcIiwyOTI5MTYzODk2LDJdIn0%3D/RSS18_AVIRIS_L1B_449_1",
+        "description": "This dataset holds Level 1B (L1B) radiance data collected by the AVIRIS-Classic instrument near Prince Albert, Saskatchewan, Canada, on August 14, 1996.  This imagery was acquired for the Boreal Ecosystem-Atmosphere Study (BOREAS) project in the boreal forests of central Canada. BOREAS focused on improving the understanding of exchanges of radiative energy, sensible heat, water, CO2 and trace gases between the boreal forest and the lower atmosphere. NASA's AVIRIS-Classic is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-Classic measures reflected radiance in 224 contiguous bands at approximately 10-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 400-2500 nm. The AVIRIS-Classic sensor has a 1 milliradian instantaneous field of view, providing altitude dependent ground sampling distances from 20 m to sub meter range. For these data, AVIRIS-Classic was deployed on NASA's ER-2 high altitude aircraft.  These spectra are acquired as images with 20-meter spatial resolution, 11 km swath width, and flight lines up to 800 km in length. The measurements are spectrally, radiometrically, and geometrically calibrated. There are seven flight lines subdivided into 66 scenes. The dataset includes the radiance imagery cube for each scene along with calibration and navigation information. The radiance data are in instrument coordinates, georeferenced by center of each scan line, and provided in a binary file. Metadata are included in a mixture of binary and text file formats.",
+        "license": "proprietary"
+    },
     {
         "id": "RSS_WindSat_L1C_TB_V08.0_8.0",
         "title": "RSS WindSat L1C Calibrated TB Version 8",
@@ -156814,7 +157074,7 @@
         "bbox": "-149.5, 68.4, -148.7, 69.15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2170968277-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170968277-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIiwidW1tIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIn0%3D/ReSALT_ALT_GPR_1265_1",
         "description": "This data set includes estimates of permafrost Active Layer Thickness (ALT; cm), and calculated uncertainties, derived using a ground-penetrating radar (GPR) system in the field in August 2014 near Toolik Lake and Happy Valley on the North Slope of Alaska. GPR measurements were taken along 10 transects of varying length (approx. 1 to 7 km). Traditional ALT estimates from mechanical probing every 100 to 500 m along each transect are also included. These data are suitable for future studies of how ALT varies over relatively large geological features, such as hills and valleys, wetland areas, and drained lake basins.",
         "license": "proprietary"
     },
@@ -156827,7 +157087,7 @@
         "bbox": "-156.89, 71.2, -156.39, 71.35",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2170968517-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170968517-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIiwidW1tIjoiW1wib3B0aWNhbCB0aGlja25lc3MgZGF0YTogc3RhZmYgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX29wdGljYWxfb3Rfc3RhZmZfNjZcIixcIjFcIiwyOTgwNTAxMTcxLDJdIn0%3D/ReSALT_InSAR_Barrow_1266_1",
         "description": "Active layer thickness (ALT) is a critical parameter for monitoring the status of permafrost that is typically measured at specific locations using probing, in situ temperature sensors, or other ground-based observations. The thickness of the active layer is the average annual thaw depth, in permafrost areas, due to solar heating of the surface. This data set includes the mean Remotely Sensed Active Layer Thickness (ReSALT) over years 2006 to 2011 for the region near Barrow, Alaska. The data were produced by an Interferometric Synthetic Aperture Radar (InSAR) technique that measures seasonal surface subsidence and infers ALT. ReSALT estimates were validated by comparison with ground-based ALT obtained using probing and Ground Penetrating Radar at multiple sites. These results indicate remote sensing techniques based on InSAR could be an effective way to measure and monitor ALT over large areas on the Arctic coastal plain.These data provide gridded (30-m) estimates of active layer thickness (cm; ALT) and seasonal subsidence (cm), as well as calculated uncertainty in each of these parameters. This data set was developed in support  of NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) field campaign.The data are presented in one netCDF (*.nc) file. ",
         "license": "proprietary"
     },
@@ -156892,7 +157152,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863171-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863171-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZ2VvYm90YW5pY2FsIGFuZCBpbXBhY3QgbWFwIGNvbGxlY3Rpb24gZm9yIHBydWRob2UgYmF5IG9pbGZpZWxkLCBhbGFza2EsIDE5NzItMjAxMFwiLFwiT1JOTF9DTE9VRFwiLFwiUHJ1ZGhvZV9CYXlfVmVnX01hcHNfMTM4N1wiLFwiMVwiLDIxNjI2MTYwNzEsNl0iLCJ1bW0iOiJbXCJnZW9ib3RhbmljYWwgYW5kIGltcGFjdCBtYXAgY29sbGVjdGlvbiBmb3IgcHJ1ZGhvZSBiYXkgb2lsZmllbGQsIGFsYXNrYSwgMTk3Mi0yMDEwXCIsXCJPUk5MX0NMT1VEXCIsXCJQcnVkaG9lX0JheV9WZWdfTWFwc18xMzg3XCIsXCIxXCIsMjE2MjYxNjA3MSw2XSJ9/Respiration_622_1",
         "description": "This data set is a compilation of soil respiration rates (g C m-2 yr-1) from terrestrial and wetland ecosystems reported in the literature prior to 1992. These rates were measured in a variety of ecosystems to examine rates of microbial activity, nutrient turnover, carbon cycling, root dynamics, and a variety of other soil processes. Also included in the data set are biome type, vegetation type, locality, and geographic coordinates.",
         "license": "proprietary"
     },
@@ -156970,7 +157230,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773247983-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773247983-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wicmVtb3RlIHNlbnNpbmcgZGVyaXZlZCB0b3Bzb2lsIGFuZCBhZ3JpY3VsdHVyYWwgZWNvbm9taWMgbG9zc2VzLCBtaWR3ZXN0ZXJuIHVzYVwiLFwiT1JOTF9DTE9VRFwiLFwiVG9wU29pbF9Fcm9zaW9uX01pZFdlc3RfVVNfMTc3NFwiLFwiMVwiLDIyMTY4NjQzNTMsNl0iLCJ1bW0iOiJbXCJyZW1vdGUgc2Vuc2luZyBkZXJpdmVkIHRvcHNvaWwgYW5kIGFncmljdWx0dXJhbCBlY29ub21pYyBsb3NzZXMsIG1pZHdlc3Rlcm4gdXNhXCIsXCJPUk5MX0NMT1VEXCIsXCJUb3BTb2lsX0Vyb3Npb25fTWlkV2VzdF9VU18xNzc0XCIsXCIxXCIsMjIxNjg2NDM1Myw2XSJ9/Russian_Forest_Disturbance_1294_1",
         "description": "This data set provides Boreal forest disturbance maps at 30-m resolution for 55 selected sites across Northern Eurasia within the Russian Federation. Disturbance events were derived from selected high-quality multi-year time series of Landsat Thematic Mapper and Enhanced Thematic Mapper Plus images (stacks) over the 1984 to 2000 time period. Forest pixels were classified by year of latest disturbance or as undisturbed.",
         "license": "proprietary"
     },
@@ -157009,7 +157269,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2796825238-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2796825238-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic2FmYXJpIDIwMDAgbW9kaXMgbDMgYWxiZWRvIGFuZCBsYW5kIGNvdmVyIGRhdGEsIHNvdXRoZXJuIGFmcmljYSwgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJtb2Rpc19sM19hbGJlZG9fODQwXCIsXCIxXCIsMjc4OTEwMzUxNiwyXSIsInVtbSI6IltcInNhZmFyaSAyMDAwIG1vZGlzIGwzIGFsYmVkbyBhbmQgbGFuZCBjb3ZlciBkYXRhLCBzb3V0aGVybiBhZnJpY2EsIGRyeSBzZWFzb24gMjAwMFwiLFwiT1JOTF9DTE9VRFwiLFwibW9kaXNfbDNfYWxiZWRvXzg0MFwiLFwiMVwiLDI3ODkxMDM1MTYsMl0ifQ%3D%3D/S2K_EACM_Subset_623_1",
         "description": "This is a data set of mean monthly surface climate data over Southern Africa for nearly all of the twentieth century. The data set is gridded at 0.5-degree latitude/longitude resolution and includes seven variables: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapour pressure, cloud cover, and ground-frost frequency.",
         "license": "proprietary"
     },
@@ -157217,7 +157477,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1442068494-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1442068494-GES_DISC.html",
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         "description": "The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). TROPOMI Level-1B (L1B) product is generated by the Koninklijk Nederlands Meteoroligisch Instituut (KNMI) TROPOMI L01B processor from Level-0 input data and auxiliary data products with the netCDF-4 enhanced model. It provides users with radiance, irradiance, calibration and engineering products.",
         "license": "proprietary"
     },
@@ -157230,7 +157490,7 @@
         "bbox": "-180, -90, 180, 90",
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. Starting from July 13th in 2020, five Sentinel-5P TROPOMI level-2 products including total and tropospheric column ozone, sulfur dioxide, CLOUD, and formaldehyde have been generated in processor version 2. For data before August 6th of 2019, please check S5P_L2__HCHO___1 data collection. For data between August 6th of 2019 and July 13th of 2020, please check S5P_L2__HCHO___HiR_1 data collection. For data after July 13th of 2020, please check S5P_L2__HCHO___HiR_2 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  The retrieval algorithm for Sentinel-5P TROPOMI HCHO from ultraviolet spectral measurements is the Differential Optical Absorption Spectroscopy (DOAS) method. The relevant information of absorption cross section, instrument characteristics, cloud cover as well as aerosol index are utilized to derive HCHO slant column density (SCD). The air mass factor (AMF) Look-up table has been created with the VLIDORT 2.6 radiative transfer model at the wavelength of 340 nm, and the AMF is used to compute the total column averaging kernels (AK). The background normalization of the slant columns is essential for weak absorbent like formaldehyde to compensate for possible systematic offsets. The main outputs of the DOAS algorithm are the vertical column density (VCD), SCD, AMF, uncertainty, AK, and quality flags.",
         "license": "proprietary"
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. For data before August 6th of 2019, please check S5P_L2__NO2____1 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  The TROPOMI retrieval of total and tropospheric NO2, is based on the DOMINO approach, a DOAS retrieval, a pre-calculated air-mass factor (AMF) look-up table, and a data assimilation/chemistry transport model for the separation of the stratospheric and tropospheric contributions to the NO2 column. It also include many retrieval developments of the European Quality Assurance for Essential Climate Variables (QA4ECV) project.",
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. For data after August 6th of 2019, please check S5P_L2__NP_BD3 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  Copernicus Sentinel-5P is flying in a loose formation with U.S. Suomi National Polar-orbiting Partnership (SNPP) so that S5P is able to utilize the high spatial resolution capability of the Visible Infrared Imager Radiometer Suite (VIIRS) instrument. S5P_L2_NP_BDx product contains VIIRS cloud information for each S5P across-track observation in a given band (i.e. band 3, band 6 and band 7). In addition to the nominal filed-of-view (FOV), the S5P_NPPC products are also generated for three scaled FOVs both in along and across-track directions to account for the presence of cloud covering a more extended area than the nominal FOV. The main output of S5P_L2_NP_BDx are the number of VIIRS pixels classified as confidently cloudy, probably cloudy, probably clear, and confidently clear; and the VIIRS sun-normalized radiance information in band M7, M9, and M11 such as mean, standard deviation, as well as number of valid radiance contributions.",
         "license": "proprietary"
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. Starting from July 13th in 2020, five Sentinel-5P TROPOMI level-2 products including total and tropospheric column ozone, sulfur dioxide, CLOUD, and formaldehyde have been generated in processor version 2. For data before August 6th of 2019, please check S5P_L2__O3_TOT_1 data collection. For data between August 6th of 2019 and July 13th of 2020, please check S5P_L2__O3_TOT_HiR_1 data collection. For data after July 13th of 2020, please check S5P_L2__O3_TOT_HiR_2 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  This total column ozone product (S5P_L2__O3_TOT, aka ESA's S5P_L2__O3____) applies the the Direct-fitting algorithm (S5P_TO3_GODFIT), comprising a non-linear least squares inversion by comparing the simulated and measured backscattered radiances. The main products include total vertical column ozone, ozone effective temperature, and the error information in NetCDF-4 format.",
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. Starting from July 13th in 2020, five Sentinel-5P TROPOMI level-2 products including total and tropospheric column ozone, sulfur dioxide, CLOUD, and formaldehyde have been generated in processor version 2. For data before August 6th of 2019, please check S5P_L2__O3_TOT_1 data collection. For data between August 6th of 2019 and July 13th of 2020, please check S5P_L2__O3_TOT_HiR_1 data collection. For data after July 13th of 2020, please check S5P_L2__O3_TOT_HiR_2 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  This total column ozone product (S5P_L2__O3_TOT, aka ESA's S5P_L2__O3____) applies the the Direct-fitting algorithm (S5P_TO3_GODFIT), comprising a non-linear least squares inversion by comparing the simulated and measured backscattered radiances. The main products include total vertical column ozone, ozone effective temperature, and the error information in NetCDF-4 format.",
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. Starting from July 13th in 2020, five Sentinel-5P TROPOMI level-2 products including total and tropospheric column ozone, sulfur dioxide, CLOUD, and formaldehyde have been generated in processor version 2. For data before August 6th of 2019, please check S5P_L2__O3_TOT_1 data collection. For data between August 6th of 2019 and July 13th of 2020, please check S5P_L2__O3_TOT_HiR_1 data collection. For data after July 13th of 2020, please check S5P_L2__O3_TOT_HiR_2 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  This total column ozone product (S5P_L2__O3_TOT, aka ESA's S5P_L2__O3____) applies the the Direct-fitting algorithm (S5P_TO3_GODFIT), comprising a non-linear least squares inversion by comparing the simulated and measured backscattered radiances. The main products include total vertical column ozone, ozone effective temperature, and the error information in NetCDF-4 format.",
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         "license": "proprietary"
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. Starting from July 13th in 2020, five Sentinel-5P TROPOMI level-2 products including total and tropospheric column ozone, sulfur dioxide, CLOUD, and formaldehyde have been generated in processor version 2. For data before August 6th of 2019, please check S5P_L2__SO2____1 data collection. For data between August 6th of 2019 and July 13th of 2020, please check S5P_L2__SO2____HiR_1 data collection. For data after July 13th of 2020, please check S5P_L2__SO2____HiR_2 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  The retrieval algorithm for Sentinel-5P TROPOMI SO2 from ultraviolet spectral measurements is the Differential Optical Absorption Spectroscopy (DOAS) method. The relevant information of absorption cross section, instrument characteristics, cloud cover, and geolocation are utilized to derive SO2 slant column density (SCD). A sensitive spectral window of 312 to 326 nm is set as the baseline for the slant column fit with another two spectral windows (325 to 335 nm, 360 to 390 nm) to account for the non-linear effects in those high column amount cases. The SCD is then corrected with the empirical offsets to the systematic biases. The air mass factor (AMF) Look-up table has been created with the LIDORT radiative transfer model. The outputs of the DOAS algorithm are SO2 vertical column density (VCD), SCD, AMF, the DOAS-type averaging kernels (AK), and error estimates.",
         "license": "proprietary"
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. Starting from July 13th in 2020, five Sentinel-5P TROPOMI level-2 products including total and tropospheric column ozone, sulfur dioxide, CLOUD, and formaldehyde have been generated in processor version 2. For data before August 6th of 2019, please check S5P_L2__SO2____1 data collection. For data between August 6th of 2019 and July 13th of 2020, please check S5P_L2__SO2____HiR_1 data collection. For data after July 13th of 2020, please check S5P_L2__SO2____HiR_2 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  The retrieval algorithm for Sentinel-5P TROPOMI SO2 from ultraviolet spectral measurements is the Differential Optical Absorption Spectroscopy (DOAS) method. The relevant information of absorption cross section, instrument characteristics, cloud cover, and geolocation are utilized to derive SO2 slant column density (SCD). A sensitive spectral window of 312 to 326 nm is set as the baseline for the slant column fit with another two spectral windows (325 to 335 nm, 360 to 390 nm) to account for the non-linear effects in those high column amount cases. The SCD is then corrected with the empirical offsets to the systematic biases. The air mass factor (AMF) Look-up table has been created with the LIDORT radiative transfer model. The outputs of the DOAS algorithm are SO2 vertical column density (VCD), SCD, AMF, the DOAS-type averaging kernels (AK), and error estimates.",
         "license": "proprietary"
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         "description": "Starting from August 6th in 2019, Sentinel-5P TROPOMI along-track high spatial resolution (~5.5km at nadir) has been implemented. Starting from July 13th in 2020, five Sentinel-5P TROPOMI level-2 products including total and tropospheric column ozone, sulfur dioxide, CLOUD, and formaldehyde have been generated in processor version 2. For data before August 6th of 2019, please check S5P_L2__SO2____1 data collection. For data between August 6th of 2019 and July 13th of 2020, please check S5P_L2__SO2____HiR_1 data collection. For data after July 13th of 2020, please check S5P_L2__SO2____HiR_2 data collection.  The Copernicus Sentinel-5 Precursor (Sentinel-5P or S5P) satellite mission is one of the European Space Agency's (ESA) new mission family - Sentinels, and it is a joint initiative between the Kingdom of the Netherlands and the ESA. The sole payload on Sentinel-5P is the TROPOspheric Monitoring Instrument (TROPOMI), which is a nadir-viewing 108 degree Field-of-View push-broom grating hyperspectral spectrometer, covering the wavelength of ultraviolet-visible (UV-VIS, 270nm to 495nm), near infrared (NIR, 675nm to 775nm), and shortwave infrared (SWIR, 2305nm-2385nm). Sentinel-5P is the first of the Atmospheric Composition Sentinels and is expected to provide measurements of ozone, NO2, SO2, CH4, CO, formaldehyde, aerosols and cloud at high spatial, temporal and spectral resolutions.  The retrieval algorithm for Sentinel-5P TROPOMI SO2 from ultraviolet spectral measurements is the Differential Optical Absorption Spectroscopy (DOAS) method. The relevant information of absorption cross section, instrument characteristics, cloud cover, and geolocation are utilized to derive SO2 slant column density (SCD). A sensitive spectral window of 312 to 326 nm is set as the baseline for the slant column fit with another two spectral windows (325 to 335 nm, 360 to 390 nm) to account for the non-linear effects in those high column amount cases. The SCD is then corrected with the empirical offsets to the systematic biases. The air mass factor (AMF) Look-up table has been created with the LIDORT radiative transfer model. The outputs of the DOAS algorithm are SO2 vertical column density (VCD), SCD, AMF, the DOAS-type averaging kernels (AK), and error estimates.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1432636975-GES_DISC.html",
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         "description": "SAMSN7L1RAD_CDROM is the gridded Nimbus-7 Stratospheric and Mesospheric Sounder (SAMS) Level 1 Radiance Data Product. The radiances were selected to derive gas concentrations at the wavelength bands 15 (CO2), 25-100 (H2O) 4-5 (CO and NO), and 7.7 (N2O and CH4) microns in the stratosphere and mesosphere, with a resolution of 100 km in the horizontal by 10 km in the vertical at the limb. This product contains radiances in a daily 2.5 degree latitude x 10 degree longitude grid format, gridded temperature profiles at 100, 30, 10, 3, 1, 0.3, 0.1, 0.03, 0.01 and 0.003 hPa, as well as the calibration, apriori and reformatted copies of the original tapes. The data for this product are available from 22 October 1978 through June 9 1983, with a few additional raw radiances to 16 April 1984. The principal investigators for the SAMS experiment were Prof. John T. Houghton and Dr. Fredric W. Taylor from Oxford University.  This product was created by the Oxford University's Atmospheric, Oceanic and Planetary Physics (AOPP) group. The data are stored on a set of 53 CD-ROMs in ASCII files of hexadecimal characters, and are available in gzipped Unix tar archive files. The first CD-ROM contains the a-priori temperature profile, monthly mean retrieved temperature profile, pre-launch calibration, housekeeping and instrument subsystem status files. CD-ROMs 2-5 contain the gridded temperature data. CD-ROMs 6-22 contain the radiances from the C-series and G-series tapes, and CD-ROMs 34-53 contain the raw radiance values from the R-series tape. The byte-ordering in the data files follows the DEC convention for 16-bit integers of less significant byte first. Normal 2's complement integer storage is assumed.",
         "license": "proprietary"
     },
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         "description": "SAMSN7L1RAT is the gridded Nimbus-7 Stratospheric and Mesospheric Sounder (SAMS) Level 1 Radiance Data Product. The radiances were selected to derive gas concentrations at the wavelength bands 15 (CO2), 25-100 (H2O) 4-5 (CO and NO), and 7.7 (N2O and CH4) microns in the stratosphere and mesosphere, with a vertical resolution of 10 km. The instrument scanned the vertical from about 15 km to 140 km. The data were recovered from the original magnetic tapes, and are now stored online as orbit files in their original proprietary binary format each with about 14 orbits per day.  The data for this product are available from 26 October 1978 through June 9 1983. The principal investigators for the SAMS experiment were Prof. John T. Houghton and Dr. Fredric W. Taylor from Oxford University. This product was subsequently used to create the SAMS/Nimbus-7 Level 1 Radiance Data from CD-ROM product (SAMSN7L1RAD_CDROM), a set of 53 CD-ROMs.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1959158936-GES_DISC.html",
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         "description": "SAMSN7L3GRIDT is the Nimbus-7 Stratospheric and Mesospheric Sounder (SAMS) Level 3 Gridded Retrieval Temperature Data Product. The Earth's surface is divided into 2.5 deg latitude by 10 deg longitude grids that extend from 50 deg South to 67.5 deg North. The data are stored in two different record types. The first contains temperatures at all 62 retrieved pressure levels between 246 and 0.0012 mbar, and the second contains temperature and error values at 10 standard pressure levels: 100, 30, 10, 3, 1, 0.3, 0.1, 0.03, 0.01 and 0.003 mbar. The data were recovered from the original magnetic tapes, and are now stored online as daily files in their original proprietary binary format.  The data for this product are available from 24 December 1978 through 9 June 1983. The principal investigators for the SAMS experiment were Prof. John T. Houghton and Dr. Fredric W. Taylor from Oxford University.  This product was previously available from the NSSDC with the identifier ESAD-00016 (old ID 78-098A-02B).",
         "license": "proprietary"
     },
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         "description": "SAMSN7L3ZMTG is the Nimbus-7 Stratospheric and Mesospheric Sounder (SAMS) Level 3 Zonal Means Composition Data Product. The Earth's surface is divided into 2.5-deg latitudinal zones that extend from 50 deg South to 67.5 deg North. Retrieved mixing ratios of nitrous oxide (N2O) and methane (CH4) are averaged over day and night, along with errors, at 31 pressure levels between 50 and 0.125 mbar. Because the N2O and CH4 channels cannot function simultaneously, only one type of measurement is made for any nominal day. The data were recovered from the original magnetic tapes, and are now stored online as one file in its original proprietary binary format.  The data for this product are available from 1 January 1979 through 30 December 1981. The principal investigators for the SAMS experiment were Prof. John T. Houghton and Dr. Fredric W. Taylor from Oxford University.  This product was previously available from the NSSDC with the identifier ESAD-00180 (old ID 78-098A-02C).",
         "license": "proprietary"
     },
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         "description": "As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRA, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRA worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.",
         "license": "proprietary"
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         "description": "As part of the 3rd Intensive Campaign of SAFARI 2000, the South African Weather Bureau Aerocommander, JRB, flew 19 missions, for a total of 28 separate flights conducted between August 15th and September 7th, 2000.  JRB worked closely with the other Aerocommander, JRA, and was dedicated to the measurement of trace gas and aerosol properties.  A suite of trace analyzers (for O3, SO2, CO and NO), laser aerosol probes and atmospheric probes were present for all flights.  Other instruments and sampling units present for some of the flights included, a nephelometer (Elias), CO flasks (Novelli) for MOPITT validation purposes, and VOC canisters for the collection and characterization of volatile organic compounds present over various land surface types.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051468-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-9 Level-2 daily product (SBUV2N09L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUV2N09L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from February 1985 through January 1998. The SBUV2N09L2 data product was used as input in creating the SBUV2N09L3zm monthly zonal mean data product.",
         "license": "proprietary"
     },
@@ -158764,7 +159024,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051471-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-9 Level-3 monthly zonal mean (MZM) product (SBUV2N17L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 156 months of data from February 1985 through January 1998. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
@@ -158777,7 +159037,7 @@
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         "description": "The version 8 SBUV/2 NOAA-9 ozone data were first released at the 2004 Quadrennial Ozone Symposium on DVD. The DVD contained all of the SBUV/2 data from NOAA-9, NOAA-11 and NOAA-16 satellites as well as SBUV data from the Nimbus-7 satellite. The DVD is no longer available, however all the data are available on-line from the NASA GES DISC. The NOAA-9 SBUV/2 v8 data are available in two time periods from 1985-02-02 to 1989-12-31 (ascending orbits) and again from 1992-01-01 to 1998-02-19 (descending orbits) due to the drift of the NOAA-9 satellite. The instrument spatial resolution is 180 km x 180 km footprint at nadir. The ozone profiles are made at 21 pressure levels between 1000 and 0.1 hPa. Each data file contains a days worth of ozone measurements, and is written in an ASCII text format.  The SBUV/2 is a scanning double monochromator and a cloud cover radiometer (CCR) designed to measure ultraviolet (UV) spectral intensities. In its primary mode of operation, the monochromator measures solar radiation backscattered by the atmosphere in 12 discrete wavelength bands in the near-UV, ranging from 252.0 to 339.8 nanometers, each with a bandpass of 1.1 nm. The total-ozone algorithm uses the four longest wavelength bands (312.5, 317.5, 331.2 and 339.8 nm), whereas the profiling algorithm uses the shorter wavelengths. The cloud cover radiometer operates at 379 nm (i.e., outside the ozone absorption band) with a 3.0 nm bandpass and was designed to measure the reflectivity of the surface in the IFOV. The SBUV/2 also makes periodic measurements of the solar flux by deploying a diffuser plate into the FOV to reflect sunlight into the measurement.",
         "license": "proprietary"
     },
@@ -158790,7 +159050,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051523-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-11 Level-2 daily product (SBUV2N11L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUV2N11L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from January 1989 through March 2001. The SBUV2N11L2 data product was used as input in creating the SBUV2N11L3zm monthly zonal mean data product.",
         "license": "proprietary"
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-11 Level-3 monthly zonal mean (MZM) product (SBUV2N11L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 147 months of data from January 1989 through March 2001. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
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         "description": "The version 8 SBUV/2 NOAA-11 ozone data were first released at the 2004 Quadrennial Ozone Symposium on DVD. The DVD contained all of the SBUV/2 data from NOAA-9, NOAA-11 and NOAA-16 satellites as well as SBUV data from the Nimbus-7 satellite. The DVD is no longer available, however all the data are available on-line from the NASA GES DISC. The NOAA-11 SBUV/2 v8 data are available from 1988-12-01 to 2001-03-27. The instrument spatial resolution is 180 km x 180 km footprint at nadir. The ozone profiles are made at 21 pressure levels between 1000 and 0.1 hPa. Each data file contains a days worth of ozone measurements, and is written in an ASCII text format.  The SBUV/2 is a scanning double monochromator and a cloud cover radiometer (CCR) designed to measure ultraviolet (UV) spectral intensities. In its primary mode of operation, the monochromator measures solar radiation backscattered by the atmosphere in 12 discrete wavelength bands in the near-UV, ranging from 252.0 to 339.8 nanometers, each with a bandpass of 1.1 nm. The total-ozone algorithm uses the four longest wavelength bands (312.5, 317.5, 331.2 and 339.8 nm), whereas the profiling algorithm uses the shorter wavelengths. The cloud cover radiometer operates at 379 nm (i.e., outside the ozone absorption band) with a 3.0 nm bandpass and was designed to measure the reflectivity of the surface in the IFOV. The SBUV/2 also makes periodic measurements of the solar flux by deploying a diffuser plate into the FOV to reflect sunlight into the measurement.",
         "license": "proprietary"
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-14 Level-2 daily product (SBUV2N14L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUV2N14L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from March 1995 through September 2006. The SBUV2N14L2 data product was used as input in creating the SBUV2N14L3zm monthly zonal mean data product.",
         "license": "proprietary"
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-14 Level-3 monthly zonal mean (MZM) product (SBUV2N14L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 139 months of data from March 1995 through September 2006. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-16 Level-2 daily product (SBUV2N16L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUV2N16L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from October 2000 through July 2013. The SBUV2N16L2 data product was used as input in creating the SBUV2N16L3zm monthly zonal mean data product.",
         "license": "proprietary"
     },
@@ -158868,7 +159128,7 @@
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-16 Level-3 monthly zonal mean (MZM) product (SBUV2N16L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 154 months of data from October 2000 through July 2013. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652224-GES_DISC.html",
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         "description": "The version 8 SBUV/2 NOAA-16 ozone data were first released at the 2004 Quadrennial Ozone Symposium on DVD. The DVD contained all of the SBUV/2 data from NOAA-9, NOAA-11 and NOAA-16 satellites as well as SBUV data from the Nimbus-7 satellite. The DVD is no longer available, however all the data are available on-line from the NASA GES DISC. The NOAA-16 SBUV/2 v8 data are available from 2000-10-03 to 2003-12-31. The instrument spatial resolution is 180 km x 180 km footprint at nadir. The ozone profiles are made at 21 pressure levels between 1000 and 0.1 hPa. Each data file contains a days worth of ozone measurements, and is written in an ASCII text format.  The SBUV/2 is a scanning double monochromator and a cloud cover radiometer (CCR) designed to measure ultraviolet (UV) spectral intensities. In its primary mode of operation, the monochromator measures solar radiation backscattered by the atmosphere in 12 discrete wavelength bands in the near-UV, ranging from 252.0 to 339.8 nanometers, each with a bandpass of 1.1 nm. The total-ozone algorithm uses the four longest wavelength bands (312.5, 317.5, 331.2 and 339.8 nm), whereas the profiling algorithm uses the shorter wavelengths. The cloud cover radiometer operates at 379 nm (i.e., outside the ozone absorption band) with a 3.0 nm bandpass and was designed to measure the reflectivity of the surface in the IFOV. The SBUV/2 also makes periodic measurements of the solar flux by deploying a diffuser plate into the FOV to reflect sunlight into the measurement.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051640-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-17 Level-2 daily product (SBUV2N17L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUV2N17L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from July 2002 through April 2013. The SBUV2N17L2 data product was used as input in creating the SBUV2N17L3zm monthly zonal mean data product.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051604-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-17 Level-3 monthly zonal mean (MZM) product (SBUV2N17L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 126 months of data from August 2002 through January 2013. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
@@ -158920,7 +159180,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051650-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-18 Level-2 daily product (SBUV2N18L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUV2N18L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from June 2005 through December 2012. The SBUV2N18L2 data product was used as input in creating the SBUV2N18L3zm monthly zonal mean data product.",
         "license": "proprietary"
     },
@@ -158933,7 +159193,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051612-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-18 Level-3 monthly zonal mean (MZM) product (SBUV2N18L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 90 months of data from July 2005 through December 2012. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
@@ -158946,7 +159206,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051657-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-19 Level-2 daily product (SBUV2N19L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUV2N19L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from February 2009 through July 2013. The SBUV2N19L2 data product was used as input in creating the SBUV2N19L3zm monthly zonal mean data product.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1251051721-GES_DISC.html",
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from NOAA-19 Level-3 monthly zonal mean (MZM) product (SBUV2N19L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 53 months of data from March 2009 through July 2013. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from Nimbus-7 Level-2 daily product (SBUVN07L2) contains ozone nadir profile and total column data from retrievals generated from the v8.6 SBUV algorithm. The v8.6 SBUV algorithm estimates the ozone nadir profile and total column from SBUV measurements using 1) the Brion-Daumont-Malicet ozone cross sections, 2) an OMI-derived cloud-height climatology, 3) a revised a priori ozone climatology, and 4) inter-instrument calibration based on comparisons with no local time difference.  The SBUVN07L2 product is written as daily files using the HDF5 format, with file sizes ranging from about 1 to 5 Mbytes. Data are available from November 1978 through May 1990. The SBUVN07L2 data product was used as input in creating the SBUVN07L3zm monthly zonal mean data product.",
         "license": "proprietary"
     },
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         "description": "The Solar Backscattered Ultraviolet (SBUV) from Nimbus-7 Level-3 monthly zonal mean (MZM) product (SBUVN07L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 139 months of data from November 1978 through May 1990. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer).   The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions:   1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees).  2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone).  NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm.  The zonal means computed for each month are screened according to the following statistical criteria:   1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month.  2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band.  3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).",
         "license": "proprietary"
     },
@@ -158998,7 +159258,7 @@
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         "description": "The version 8 SBUV Nimbus-7 ozone data were first released at the 2004 Quadrennial Ozone Symposium on DVD. The DVD contained all of the SBUV/2 data from NOAA-9, NOAA-11 and NOAA-16 satellites as well as SBUV data from the Nimbus-7 satellite. The DVD is no longer available, however all the data are available on-line from the NASA GES DISC. The Nimbus-7 SBUV v8 data are available from 1978-10-31 to 1990-06-21. The instrument spatial resolution is 180 km x 180 km footprint at nadir. The ozone profiles are made at 21 pressure levels between 1000 and 0.1 hPa. Each data file contains a days worth of ozone measurements, and is written in an ASCII text format.  The SBUV measures incoming solar irradiance and radiance backscattered by the atmosphere at 12 wavelengths in the UV range [0.25-0.34 micrometer] with a spectral band pass of 0.001 micrometer. The wavelength channels used for ozone retrievals for SBUV were: 256, 273, 283, 288, 292, 298, 302, 306, 312, 318, 331, and 340 nm. Radiation at these wavelengths are absorbed by ozone, such that the difference between the incoming and outgoing radiation can be related to the amount of ozone in the atmosphere.  The SBUV consists of a double Ebert-Fastie spectrometer and a filter photometer similar to the BUV on Nimbus 4. The bandwidth of the photometer is about 3 nm and the spectral resolution for SBUV monochromator is 1.1 nm.",
         "license": "proprietary"
     },
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         "description": "The SCAMSN6IM data product consists of images of brightness temperatures, water vapor and temperature on 70 mm film strips from the Nimbus-6 Scanning Microwave Spectrometer. Each display contains eight vertical strips of data from one orbit. All strips have the same geographic coverage, but each represents a different parameter. The first three are brightness temperatures for channels 2 (31.65 GHz) and 3 (52.85 GHz) and their differences. The next two represent retrieved water vapor and liquid water from clouds or precipitation over the oceans, respectively. The remaining three strips on the right represent inverted mean temperatures for atmospheric layers 1000-500 mbar, 500-250 mbar, and 250-100 mbar, respectively. The first five parameters are displayed in 18-step gray levels, the values of which can be found in a table in each of the first five volumes of \"The Nimbus 6 Data Catalog.\" The last three parameters are displayed by contour bands (labeled on the side) that are spaced 4 K apart. Spatial resolution on the ground for the parameters varies from 145 km at nadir to 330 km at the scan extremes. The images are saved as TIFF digital files. About 3-5 months of images are archived into a ZIP file. Additional information can be found in section 2.4.1 of \"The Nimbus 6 User's Guide.\"  The SCAMS experiment on Nimbus-6 is a follow on to the successful Nimbus-5 NEMS experiment. SCAMS continuously monitored emitted microwave radiation at frequencies of 22.235, 31.65, 52.85, 53.85 and 55.45 GHz. The three channels near the 5.0-mm oxygen absorption band were used primarily to deduce atmospheric temperature profiles. The two channels near 10 mm permitted water vapor and cloud water content over calm oceans to be estimated separately. The instrument, a Dicke-superheterodyne type, scanned +/- 45 degrees normal to the orbital plane with a 10 degree field of view. The three oxygen channels shared common signal and reference antennas. Both water vapor channels had their own signals and reference antennas. The absolute rms accuracy of the oxygen channels was better than 2 Kelvin and that of the water vapor channels better than 1 Kelvin.  The SCAMS Principal Investigator was Prof. David H. Staelin from MIT. The Nimbus-6 SCAMS images are available from June 15, 1975 (day of year 166) through May 31, 1976 (day of year 152).  This product was previously available from the NSSDC with the identifier ESAD-00200 (old ID 75-052A-10B).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652168-GES_DISC.html",
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         "description": "The Nimbus-6 Scanning Microwave Spectrometer (SCAMS) Level 2 data product contains water vapor and temperature profiles, as well as antenna and brightness temperatures. SCAMS was designed to map tropospheric temperature profiles, water vapor abundance, and cloud water content to be used for weather prediction even in the presence of clouds, which block conventional satellite infrared sensors. The data, originally written on IBM 360 machines, were recovered from 9-track magnetic tapes. The data are archived in their original IBM 32-bit word binary record format, also referred to as a binary TAP file, and contain one orbit of measurements.           The SCAMS experiment on Nimbus-6 is a follow on to the successful Nimbus-5 NEMS experiment.  SCAMS continuously monitored emitted microwave radiation at frequencies of 22.235, 31.65, 52.85, 53.85 and 55.45 GHz. The three channels near the 5.0-mm oxygen absorption band were used primarily to deduce atmospheric temperature profiles. The two channels near 10 mm permitted water vapor and cloud water content over calm oceans to be estimated separately. The instrument, a Dicke-superheterodyne type, scanned +/- 45 degrees normal to the orbital plane with a 10 degree field of view. The three oxygen channels shared common signal and reference antennas. Both water vapor channels had their own signals and reference antennas. The absolute rms accuracy of the oxygen channels was better than 2 Kelvin and that of the water vapor channels better than 1 Kelvin.                The SCAMS Principal Investigator was Prof. David H. Staelin from MIT. The Nimbus-6 SCAMS data are available from June 15, 1975 (day of year 166) through May 31, 1976 (day of year 152).  This product was previously available from the NSSDC with the identifier ESAD-00093 (old ID 75-052A-10A).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804821183-ORNL_CLOUD.html",
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         "description": "This data set contains meteorological data, reanalysis data, remote sensing images, and data on atmospheric composition collected during the Smoke, Clouds, and Radiation - Brazil (SCAR-B) experiment. The SCAR-B examined the effects of biomass burning on atmospheric processes with four primary goals: (1) improving techniques for remote sensing of these process from space, (2) obtain measurements of the rates of emissions of trace gases and particles from biomass burning, (3) observe the influence of atmospheric processes on the emission products was to obtain measurements of the rates of emissions of trace gases and particles from biomass burning, and to observe the influence of atmospheric processes on these emission products, and (4) characterize the physical and radiative properties of smoke particles from biomass burning. SCAR-B was conducted during biomass burning in the cerrado ( dry savannah) and Amazonia rainforest to understand the influence of land cover type on smoke, clouds, and radiation.Selected archived data and images from SCAR-B are described in the Data Description section table. Extensive background information on SCAR-B is provided following the Data Description.The processed, quality controlled and integrated data in the documented Pre-LBA Data sets were originally published as a set of three CD_ROMs (Marengo and Victoria, 1998) but are now archived individually.  ",
         "license": "proprietary"
     },
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         "description": "SCMRN5L1RAD is the Nimbus-5 Surface Composition Mapping Radiometer (SCMR) Level 1 Calibrated and Geolocated Radiances data product. SCMR measured (1) terrestrial radiation in the 8.3 to 9.3 micron and 10.2 to 11.2 micron intervals and (2) reflected solar radiation in the 0.8 to 1.1 micron range. Surface composition and sea surface temperatures could be obtained from these measurements. The SCMR had an instantaneous field of view (FOV) of 0.6 mrad, equivalent to a ground resolution of 660 m at nadir. The scan mirror rotated at 10 rps to provide scan lines 800 km wide across the spacecraft track.  Data are available from December 11, 1972 through December 30, 1972. A modified version of this instrument, the Heat Capacity Mapping Radiometer, was flown on the Heat Capacity Mapping Mission (HCMM) in 1978.",
         "license": "proprietary"
     },
@@ -159245,7 +159505,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1459756630-GES_DISC.html",
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         "description": "SCRN4L1RAD is the Nimbus-4 Selective Chopper Radiometer (SCR) Level 1 Calibrated Radiances data product. The calibrated radiances are measured at 6 channels from 2.3 to 15 micrometers with a ground resolution of 25 km, and are \"declouded\" (interpolated and smoothed across regions of cloud). The radiances were used to obtain the temperatures of six successive 10-km layers of the atmosphere from earth or cloudtop level to 60-km height. The data were recovered from the original 9-track tapes, and are now stored online as daily files in their original proprietary binary format with about 14 orbits per day.  Spatial coverage is near global from latitude -80 to +80 degrees. The data are available from 27 July 1970 (day of year 208) to 20 February 1973 (day of year 51). The channel 1 temperature monitoring system failed on June 15, 1970, thereby reducing the accuracy of the SCR data. Channels 3 and 4 became noisy and unusable on April 18, 1972. The principal investigator for the SCR experiment was Dr. John T. Houghton from Oxford University.           This product was previously available from the NSSDC with the identifier ESAD-00096 (old ID 78-098A-10E).",
         "license": "proprietary"
     },
@@ -159258,7 +159518,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1432636960-GES_DISC.html",
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         "description": "SCRN4L1RAD_CDROM is the gridded Nimbus-4 Selective Chopper Radiometer (SCR) Level 1 Radiance Data Product. The radiances are measured by 16 channels at 2.3 to 15 micrometers with a ground resolution of 25 km. The CD-ROM contains corrected radiances in a daily 4 degree latitude x 10 degree longitude grid format, as well as the original orbit format. The data for this product are available from 27 July 1970 to 2 November 1972. The principal investigator for the SCR experiment was Dr. John T. Houghton from Oxford University.  This product was created by the Oxford University's Atmospheric, Oceanic and Planetary Physics (AOPP) group. The data are stored on a single CD-ROM in ASCII files of hexadecimal characters, and are available in a single gzipped Unix tar archive file. The byte-ordering in the data files follows the DEC convention for 16-bit integers of less significant byte first. Normal 2's complement integer storage is assumed.",
         "license": "proprietary"
     },
@@ -159271,7 +159531,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1529927432-GES_DISC.html",
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         "license": "proprietary"
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         "description": "SCRN5L1RAD_CDROM is the gridded Nimbus-5 Selective Chopper Radiometer (SCR) Level 1 Radiance Data Product. The radiances are measured by 16 channels at 2.3 to 15 micrometers with a ground resolution of 25 km. This product contains corrected and uncorrected radiances in a daily 4 degree latitude x 10 degree longitude grid format, as well as the original orbit format and reformatted copies of the original tapes. This was the follow-on to the SCR experiment flown on Nimbus-4. The data for this product are available from 13 December 1972 to 20 April 1978. The principal investigator for the SCR experiment was Dr. John T. Houghton from Oxford University.  This product was created by the Oxford University's Atmospheric, Oceanic and Planetary Physics (AOPP) group. The data are stored on a set of 28 CD-ROMs in ASCII files of hexadecimal characters, and are available in gzipped Unix tar archive files. The first CD-ROM contains the gridded radiance data and a few original tape data files, the subsequent CD-ROMs contain the remaining compressed copies of the original data tapes. The byte-ordering in the data files follows the DEC convention for 16-bit integers of less significant byte first. Normal 2's complement integer storage is assumed.",
         "license": "proprietary"
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         "description": "Metadata for Sentinel-1A level zero product",
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         "license": "proprietary"
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         "license": "proprietary"
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         "description": "This dataset contains Level 2A (L2A) unrectified surface reflectance images from NASA's Airborne Visible / Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) instrument. This imagery was collected as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign which occurred during February to May, 2022, with a follow up activity for one week in September. The SHIFT campaign leveraged NASA's AVIRIS-NG facility instrument to collect VSWIR data at approximately a weekly cadence across a broad study area, enabling traceability analyses related to the science value of VSWIR revisits. This campaign will generate precise, high-frequency data on plant communities collected over nearly 1,656 square kilometers across Santa Barbara County, California, US, and nearby coastal Pacific waters. AVIRIS-NG is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-NG measures reflected radiance at 5-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 380-2510 nm. The AVIRIS-NG sensor has a 1 milliradian instantaneous field of view, providing altitude dependent ground sampling distances from 20 m to sub-meter range.  The AVIRIS-NG L2A data are provided in ENVI binary format, which includes a flat binary file accompanied by a header (.hdr) file holding metadata in text format.",
         "license": "proprietary"
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         "description": "This dataset provides per-pixel vegetation canopy water content (CWC) derived from surface reflectance measured by the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) instrument from 2022-02-24 to 2022-05-17. This imagery was acquired as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign. AVIRIS-NG measures reflected radiance in 425 bands at 5-nanometer (nm) intervals in the visible to shortwave infrared spectral range between 380 and 2510 nm. Measurements were radiometrically and geometrically calibrated as well as atmospherically corrected, and are provided at approximately 5-meter spatial resolution. These data include mosaics of several flight lines that were flown on a weekly basis covering a 640-square-mile (1,656-square-kilometer) study area, which stretches from Los Padres National Forest in the east to the Central California coast and into the coastal ocean in the west, including Dangermond Preserve and UCSB's Sedgwick Reserve. These data will help track changes in vegetation characteristics from late winter through early summer by providing insights into health and resilience of ecosystems as California's climate grows drier. In particular, temporal and spatial patterns of CWC will indicate drought stress and increased wildfire risk. The CWC files in this publication were processed by applying a simple fitting of spectral absorption features of liquid water and are distributed in cloud-optimized GeoTIFF (COG) format.",
         "license": "proprietary"
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         "description": "This dataset holds full-resolution 3-band (true color) imagery acquired by NASA's Airborne Visible / Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) instrument. This imagery was collected as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign which occurred during February to May, 2022, with a follow up activity for one week in September. The SHIFT campaign leveraged NASA's AVIRIS-NG facility instrument to collect VSWIR data at approximately a weekly cadence across a broad study area, enabling traceability analyses related to the science value of VSWIR revisits. AVIRIS-NG is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-NG measures radiance at approximately 5-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 380-2510 nm. The images in this dataset are true color (RGB) images from the wavelengths centered at approximately 808, 658, and 563 nm, subset from the full spectrum collected by AVIRIS-NG. The spatial resolution matches the native observed resolution (variable depending on the flightline, generally finer than 5 m and down to 2 m). There are two files for each flight line, one in PNG and one in georeferenced cloud-optimized GeoTIFF format; the GeoTIFF contains radiance floating point values while the PNG has been scaled and converted to integers.",
         "license": "proprietary"
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         "description": "This dataset contains Level 1A (L1A) unrectified surface radiance image files as well as files of observational geometry and illumination parameters and supporting sensor band information from NASA's Airborne Visible / Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) instrument. This imagery was collected as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign. The SHIFT campaign leveraged NASA's AVIRIS-NG facility instrument to collect VSWIR data at approximately a weekly cadence across a broad study area, enabling traceability analyses related to the science value of VSWIR revisits. This campaign will generate precise, high-frequency data on plant communities collected over nearly 1,656 square kilometers across Santa Barbara County, California, US, and nearby coastal Pacific waters. AVIRIS-NG is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-NG measures reflected radiance at 5-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 380-2510 nm. The AVIRIS-NG sensor has a 1 milliradian instantaneous field of view, providing altitude dependent ground sampling distances from 20 m to sub-meter range. In this dataset, for each flight line, four file types are included: unrectified measured surface radiance image (rdn) files, geometric lookup table (glt), gridded files of input geometry (igm), and parameters relating to the geometry of observation and illumination rendered using the geometric lookup table (obs). The AVIRIS-NG L1B data are provided in ENVI binary format, which includes a flat binary file (bin) accompanied by a header (hdr) file holding metadata in text format.",
         "license": "proprietary"
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         "description": "This dataset provides full-spectrum (350-2500 nm) reflectance measurements of dried ground leaf samples from meadow, shrub, and tree sites. Samples were collected during the period of February 23, 2022 to September 27th, 2022 for the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign in Santa Barbara County, California, USA. The primary goal of the SHIFT campaign was to collect a repeated dense time series of airborne Visible to ShortWave Infrared (VSWIR) airborne imaging spectroscopy data with coincident field measurements in both inland terrestrial and coastal aquatic areas.  Reflectance measurements were collected using a ASD FieldSpec 3 spectrometer following Serbin et al. (2014) and Wang et al. (2020). After sample collection, each leaf sample was divided into two portions: one portion with ~10 g fresh weight was oven dried and another portion with ~5 g fresh weight was flash frozen. Both samples were ground and homogenized (20-mesh, 833 micrometers). The oven dried samples were then re-dried in oven at 70 degrees C for 24 h and the flash frozen samples were dried using a Virtis Model 24DX48 specimen freeze dryer before the reflectance measurement. Data are in a comma-separated values (.csv) format.",
         "license": "proprietary"
     },
@@ -160324,7 +160584,7 @@
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         "description": "This dataset contains vegetation plot locations, descriptions, fractional cover, and sample identifier information from surveys conducted as part of the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign. Surveys took place from 2022-02-23 to 2022-09-27 at the Jack and Laura Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt Marsh Reserve, which are located in Santa Barbara County, California, USA. This project collected field data contemporaneously with weekly flights of the NASA Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) facility instrument over the study areas. Plot information includes: plot tree subform, species lists, plot description, plot samples characterization, and plot location and contextual information. Related data packages contain additional biogeochemical, reflectance, and foliar data. Survey data and metadata are presented in comma-separated values (*.csv) format along with survey plot polygons in GeoJSON (*.geojson) format.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2953889427-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2953889427-ORNL_CLOUD.html",
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         "description": "This dataset holds laboratory foliar chemical analyses results for field samples collected during the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign in Santa Barbara County, California, USA. Leaf samples were collected from plots within the Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt Marsh Reserve during the period of 2022-02-23 to 2022-09-27 and dried for later analysis. This project collected field data contemporaneously with weekly flights of the NASA's Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) facility instrument over the study areas. Sixteen chemical traits from two different lab analyses are provided. (a) Elemental analysis: foliar nitrogen (%), phosphorus (%), magnesium (%), potassium (%), calcium (%), sulfur (%), boron (ppm), iron (ppm), manganese (ppm), copper (ppm), zinc (ppm), aluminum (ppm), and sodium (ppm). (b) AnkomFiber analysis: foliar hemicellulose and bound protein (%), cellulose (%), and lignin (%). Related data packages contain additional plot-level characterization, biogeochemical, reflectance, and foliar data. These data are provided in comma separated values (CSV) format.",
         "license": "proprietary"
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         "description": "This dataset holds Level 1 (L1) brightness temperature data collected by the Hyperspectral Thermal Emission Spectrometer (HyTES) instrument. This imagery was acquired as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign on March 23, 2022. The SHIFT campaign generated precise, high-frequency data on plant communities for nearly 1,656 square kilometers across Santa Barbara County, California, US, and the nearby ocean. HyTES is a compact image spectrometer that acquires data in 256 spectral bands between 7.5 and 12 micrometers; it was deployed on a Twin Otter aircraft.  The SHIFT campaign sought to demonstrate the joint use of both VSWIR and thermal infrared (TIR) data. TIR data are used to measure land surface temperature (LST), which informs models of water flux from land surface through processes such as evapotranspiration. LST is sensitive to solar heat gains and local cooling effects due to evaporative cooling. The HyTES instrument measures TIR radiances that can be used to derive LST, emissivity and Level 3 products such as latent heat flux and detection of air pollution sources.  The HyTES data are provided in HDF5 format and include 91 flight scenes. The data are not projected, but georeferencing information for each pixel are provided in the HDF5 and a separate ENVI file for each flight scene. In addition, the flight scene boundaries and an overlay image are provided in Keyhole Markup Language (KML) along with a quicklook image and spectral response data.",
         "license": "proprietary"
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         "description": "This dataset holds Level 2 (L2) data for surface emissivity and land surface temperature (LST) collected by the Hyperspectral Thermal Emission Spectrometer (HyTES) instrument. This imagery was acquired as part of the Surface Biology and Geology High-Frequency Time Series (SHIFT) campaign on March 23, 2022. The SHIFT campaign generated precise, high-frequency data on plant communities for nearly 1,656 square kilometers across Santa Barbara County, California, US, and the nearby ocean. HyTES is a compact image spectrometer that acquires data in 256 spectral bands between 7.5 and 12 micrometers; it was deployed on a Twin Otter aircraft. The SHIFT campaign sought to demonstrate the joint use of both VSWIR and thermal infrared (TIR) data. TIR data are used to measure land surface temperature (LST), which informs models of water flux from land surface through processes such as evapotranspiration. LST is sensitive to solar heat gains and local cooling effects due to evaporative cooling. The HyTES instrument measures TIR radiances that can be used to derive LST, emissivity and Level 3 products such as latent heat flux and detection of air pollution sources. The HyTES data are provided in HDF5 format and include 91 flight scenes. In addition, overlay images for emissivity and LST are provided in compressed Keyhole Markup Language (KMZ) along with a quicklook image.",
         "license": "proprietary"
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         "description": "This dataset provides leaf images and measurements of leaf traits (area, wet weight, dry weight, leaf mass per area, leaf water content) and leaf pigments (chlorophyll) and species information as sampled from meadow, shrub, and tree from Santa Barbara California, USA. Samples were collected from plots within the Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt March Reserve during the period of February 23, 2022 to September 27, 2022 for the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign.  The associated data package contains image scans used for the leaf area calculations as well as python processing code used to calculate the area. A comma-separated value (CSV) formatted file includes plot-level leaf area (cm2), wet weight (g), leaf mass area (LMA, g leaf dry mass per meter square), leaf water content (LWC, (wet weight - dry weight/wet weight, %)), chlorophyll fluorescence ratio (CFR), and chlorophyll content (CHL).",
         "license": "proprietary"
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         "description": "This dataset contains photographs of the plots where field vegetation sampling was conducted during the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign. Sampling occurred at the Jack and Laura Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt Marsh Reserve, which are located in Santa Barbara County, California, USA. Photographs were taken from 2022-02-23 to 2022-09-18. This project collected field data contemporaneously with weekly flights of Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over the study areas. Related SHIFT data packages contain additional biogeochemical, reflectance, and foliar data.",
         "license": "proprietary"
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         "description": "This dataset provides calculated remote sensing reflectance (Rrs) from measurements collected with a Ramses TriOS radiometer deployed on the Santa Barbara Museum of Natural History Sea Center at Stearns Wharf, Santa Barbara, California, U.S. All measurements were taken over a fixed position at (34.41037665, -119.68557147). Three sensors are used to collect solar downwelling irradiance (Ed), sky radiance (Ls) and water-leaving radiance (Lw). These data have been processed to Rrs at 10 second intervals and are either concurrent or taken within 2.5 hours of SHIFT campaign flights. The data collected by the three Ramses TriOS sensors for eight days during the period 2022-04-05 to 2022-05-29 are also included. The data were translated from the proprietary format output by the Ramses TriOS instrument and saved in comma-separated values (CSV) format.",
         "license": "proprietary"
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         "description": "This dataset provides estimated solar-induced chlorophyll fluorescence (SIF) of specific vegetation types and total SIF under clear-sky and real/cloudy conditions at a resolution of 4 km for the Midwest USA. The estimates are 8-day averaged daily means over the 2018 crop growing season for the time period 2018-05-01 to 2018-09-29. SIF of a specific vegetation type (i.e., corn, soybean, grass/pasture, forest) was expressed as the product of photosynthetically active radiation (PAR), the fraction of photosynthetically active radiation absorbed by the canopy (fPAR), and canopy SIF yield (SIFyield) for each vegetation type. Uncertainty of each variable was also calculated and is provided. These components of the SIF model were derived using a TROPOspheric Monitoring Instrument (TROPOMI) dataset, the USDA National Agricultural Statistics Service Cropland Data Layer, and the MODIS MCD15A2H 8-day 500 m fPAR product. These data could be used to improve estimates of vegetation productivity and vegetation stress.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2847119443-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2847119443-ORNL_CLOUD.html",
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         "description": "This dataset provides global solar-induced chlorophyll fluorescence (SIF) estimates at a 0.05-degree resolution (approximately 5 km at the equator) for each month from January 2003 through December 2017. SIF data (740 nm) was retrieved from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) and Global Ozone Monitoring Experiment 2 (GOME-2) instruments onboard the MetOp-A satellite. The data were downscaled to 0.05 degrees using the Random Forest algorithm and predictors from Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis, and then harmonized with the cumulative distribution function (CDF) matching technique. The uncertainty of the harmonized SIF estimates was also quantified and provided. Validation of the harmonized product showed that it retained high spatial and temporal consistency with the original SCIAMACHY and GOME-2 SIF retrievals and had good correlations with independent airborne and ground-based SIF measurements. The dataset can inform on the synergy between satellite SIF and photosynthesis and research on drought, yield estimation, and land degradation evaluation. The data are provided in netCDF format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1622768257-GES_DISC.html",
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         "description": "SIRSN3L1 is the Nimbus-3 Satellite Infrared Spectrometer (SIRS) Level 1 Radiance Data product. SIRS measured infrared radiation (11 to 36 micrometers) emitted from the earth and its atmosphere in 13 selected spectral intervals in the carbon dioxide and water vapor bands plus one channel in the 11-micrometer atmospheric window. The radiances were used to determine the vertical temperature and water vapor profiles of the atmosphere. The data were recovered from the original 6250 tapes, and are now stored online as daily files in their original proprietary binary format each with about 14 orbits per day.  The Nimbus-3 SIRS only viewed the nadir of the subsatellite track. Spatial coverage is near global from about latitude -80 to +80 degrees. The data are available from 08 April 1970 (day of year 98) to 08 April 1971. The principal investigator for the SIRS experiment was Dr. David Q. Wark from the NOAA National Environmental Satellite Data and Information Service.  This product was previously available from the NSSDC with the identifier ESAD-00130 (old ID 70-025A-04A).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1622768259-GES_DISC.html",
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         "description": "SIRSN4L1 is the Nimbus-4 Satellite Infrared Spectrometer (SIRS) Level 1 Radiance Data product. SIRS measured infrared radiation (11 to 36 micrometers) emitted from the earth and its atmosphere in 13 selected spectral intervals in the carbon dioxide and water vapor bands plus one channel in the 11-micrometer atmospheric window. The radiances were used to determine the vertical temperature and water vapor profiles of the atmosphere. The data were recovered from the original 6250 tapes, and are now stored online as daily files in their original proprietary binary format each with about 14 orbits per day.  The Nimbus-4 SIRS used a scan mirror to observe 12.5 deg to either side of the subsatellite track. Spatial coverage is near global from latitude -85 to +85 degrees. The data are available from 08 April 1970 (day of year 98) to 08 April 1971. The principal investigator for the SIRS experiment was Dr. David Q. Wark from the NOAA National Environmental Satellite Data and Information Service.  This product was previously available from the NSSDC with the identifier ESAD-00130 (old ID 70-025A-04A).",
         "license": "proprietary"
     },
@@ -161065,7 +161325,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3114843226-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3114843226-ORNL_CLOUD.html",
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         "description": "The Space-based Imaging Spectroscopy and Thermal pathfindER (SISTER) activity originated in support of the NASA Earth System Observatory's Surface Biology and Geology (SBG) mission to develop prototype workflows with community algorithms and generate prototype data products envisioned for SBG. SISTER focused on developing a data system that is open, portable, scalable, standards-compliant, and reproducible. This collection contains EXPERIMENTAL workflows and sample data products, including (a) the Common Workflow Language (CWL) process file and a Jupyter Notebook that run the entire SISTER workflow capable of generating experimental sample data products spanning terrestrial ecosystems, inland and coastal aquatic ecosystems, and snow, (b) the archived algorithm steps (as OGC Application Packages) used to generate products at each step of the workflow, (c) a small number of experimental sample data products produced by the workflow which are based on the Airborne Visible/Infrared Imaging Spectrometer-Classic (AVIRIS or AVIRIS-CL) instrument, and (d) instructions for reproducing the sample products included in this dataset. DISCLAIMER: This collection contains experimental workflows, experimental community algorithms, and experimental sample data products to demonstrate the capabilities of an end-to-end processing system. The experimental sample data products provided have not been fully validated and are not intended for scientific use. The community algorithms provided are placeholders which can be replaced by any user's algorithms for their own science and application interests. These algorithms should not in any capacity be considered the algorithms that will be implemented in the upcoming Surface Biology and Geology mission.",
         "license": "proprietary"
     },
@@ -161104,7 +161364,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2266194621-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2266194621-ORNL_CLOUD.html",
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         "description": "This dataset contains estimated gross primary productivity (GPP), photosynthetically active radiation (PAR), soil adjusted near infrared reflectance of vegetation (SANIRv), the fraction of C4 crops in vegetation  (fC4), and their uncertainties for the conterminous United States (CONUS) from 2000 to 2019. The daily estimates are SatelLite Only Photosynthesis Estimation (SLOPE) products at 250-m resolution. There are three distinct features of the GPP estimation algorithm: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR, (2) SLOPE couples gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRv (SANIRv) dataset, and (3) SLOPE couples a temporal pattern recognition approach with a long-term Crop Data Layer (CDL) product to predict dynamic C4 crop fraction. PAR, SANIRv and C4 fraction are used to drive a parsimonious model with only two parameters to estimate GPP, along with a quantitative uncertainty, on a per-pixel and daily basis. The slope GPP product has an R2 = 0.84 and a root-mean-square error (RMSE) of 1.65 gC m-2 d-1.",
         "license": "proprietary"
     },
@@ -161182,7 +161442,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1539078443-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1539078443-NSIDC_ECS.html",
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         "description": "This ancillary SMAP product contains three dynamic GMAO GEOS-5 modeled data sets. Each data set contains surface and atmospheric parameters pertinent to SMAP provided in 1) hourly, 2) 3-hour, and 3) averaged over 3-hour intervals.",
         "license": "proprietary"
     },
@@ -161195,7 +161455,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1539129339-NSIDC_ECS.html",
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         "license": "proprietary"
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         "license": "proprietary"
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         "license": "proprietary"
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         "license": "proprietary"
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         "description": "This ancillary SMAP product contains daily meteorological model log files, including model outputs. The meteorological model is derived from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data set and used as an input in the SMAP L4 Carbon algorithm.",
         "license": "proprietary"
     },
@@ -161312,7 +161572,7 @@
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         "description": "This ancillary SMAP product contains three dynamic Land Data Assimilation Systems (LDAS) data sets. These data sets include Brightness Temperature (TB) scaling parameters; catchment model parameters such as topographic statistics, soil texture, and soil hydraulic parameters; and LDAS L-band microwave radiative transfer model parameters.",
         "license": "proprietary"
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         "description": "This ancillary SMAP product contains Land Data Assimilation Systems (LDAS) model configurations, including model inputs.",
         "license": "proprietary"
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         "description": "This ancillary SMAP product contains static restart files for the Land Data Assimilation Systems (LDAS) Catchment model. This product includes prognostic variables for both the catchment model and perturbations model.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1569839798-GES_DISC.html",
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         "description": "Smerge-Noah-CCI root zone soil moisture 0-40 cm L4 daily 0.125 x 0.125 degree V2.0 is a multi-decadal root-zone soil moisture product. Smerge is developed by merging the North American Land Data Assimilation System (NLDAS) land surface model output with surface satellite retrievals from the European Space Agency Climate Change Initiative. The data have a 0.125 degree resolution at a daily time-step, covering the entire continental United States and spanning nearly four decades (January 1979 to May 2019).  This data product contains root-zone soil moisture of 0 - 40 cm layer, Climate Change Initiative (CCI) derived soil moisture anomalies of 0-40 cm layer, and a soil moisture data estimation flag.  This data product is the recommended replacement for the AMSR-E/Aqua root zone soil moisture L3 1 day 25 km x 25 km descending and 2-Layer Palmer Water Balance Model V001 product (LPRM_AMSRE_D_RZSM3), which will be removed from archive on June 27, 2022. Smerge provides a better root zone soil moisture estimation because it has higher data quality and longer temporal coverage.   ",
         "license": "proprietary"
     },
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         "description": "SMMRN7IM is the Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) Color Image data product scanned from 17\" x 15\" color prints and saved as JPEG-2000 files. Sea surface temperature, sea surface winds, total atmospheric water vapor over oceans, total atmospheric liquid water over oceans, including brightness temperature parameters are available as both 6-day composites and 1-month averages between 64 south and north latitudes in Mercator projection. Sea ice fraction, sea ice and ocean surface temperature, sea ice concentration, including brightness temperature parameters are available as both 3-day and 1-month averages in north and south polar stereographic projections. Images may contain between one and three measured parameters. These SMMR images are available from 30 October 1978 through 2 November 1983. The principal investigator for the SMMR experiment was Dr. Per Gloersen from NASA GSFC.   These products were previously available from the NSSDC under the ids ESAD-00007, ESAD-00056, ESAD-00123, ESAD-00124, ESAD-00162, ESAD-00172, ESAD-00173, ESAD-00176 ESAD-00177, ESAD-00178, and ESAD-00241 (old ids 78-098A-08I-S).",
         "license": "proprietary"
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         "description": "The Climate Hyperspectral Infrared Radiance Product (CHIRP) is a Level 1 radiance product derived from Atmospheric Infrared Sounder (AIRS) on EOS-AQUA and the Cross-Track Infrared Sounders (CrIS) on the SNPP and JPSS-1+ platforms.  (JPSS-1 is also called NOAA-20). CHIRP provides a consistent spectral response function (SRF) across all instruments. Inter-instrument radiometric offsets are removed with SNPP-CrIS chosen as the \"standard\".  CHIRP follows the original instrument storage, i.e., granule in, granule out, and contains all information needed for retrievals (including cross-track, along-track, fov id, etc.). This version of CHIRP, SNDR13CHRP1AQCal, only contains CHIRP data derived from the AIRS instrument on EOS-AQUA that is not present in the main CHIRP product, SNDR13CHRP1, and therefore starts on Sept. 1, 2016 and will continue until the AIRS end of mission.",
         "license": "proprietary"
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         "description": "The Climate Hyperspectral Infrared Radiance Product (CHIRP) is a Level 1 radiance product derived from Atmospheric Infrared Sounder (AIRS) on EOS-AQUA and the Cross-Track Infrared Sounders (CrIS) on the SNPP and JPSS-1+ platforms.  (JPSS-1 is also called NOAA-20). CHIRP provides a consistent spectral response function (SRF) across all instruments. Inter-instrument radiometric offsets are removed with SNPP-CrIS chosen as the \"standard\".  CHIRP follows the original instrument storage, i.e., granule in, granule out, and contains all information needed for retrievals (including cross-track, along-track, fov id, etc.). This version of CHIRP, SNDR13CHRP1J1Cal, contains CHIRP data derived from the JPSS-1 (NOAA-20) CrIS instrument that is not present in the main CHIRP product, SNDR13CHRP1, which include JPSS-1 data from February 17, 2018 through August 31, 2018.",
         "license": "proprietary"
     },
@@ -162248,7 +162508,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2011289954-GES_DISC.html",
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         "description": "The Climate Hyperspectral Infrared Radiance Product (CHIRP) is a Level 1 radiance product derived from Atmospheric Infrared Sounder (AIRS) on EOS-AQUA and the Cross-Track Infrared Sounders (CrIS) on the SNPP and JPSS-1+ platforms.  (JPSS-1 is also called NOAA-20). CHIRP provides a consistent spectral response function (SRF) across all instruments. Inter-instrument radiometric offsets are removed with SNPP-CrIS chosen as the \"standard\".  CHIRP follows the original instrument storage, i.e., granule in, granule out, and contains all information needed for retrievals (including cross-track, along-track, fov id, etc.). This version of CHIRP, SNDR13CHRP1SNCal, contains CHIRP data derived from the CrIS instrument on the SNPP platform that is not present in the main CHIRP product, SNDR13CHRP1, and therefore covers the date ranges of November 2, 2015 (when CrIS started producing high-spectral resolution data which is required for CHIRP) through August 31, 2016 when the main CHIRP product, SNDR13CHRP1, switches to using CrIS on JPSS-1. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2011289787-GES_DISC.html",
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         "description": "The Climate Hyperspectral Infrared Radiance Product (CHIRP) is a Level 1 radiance product derived from Atmospheric Infrared Sounder (AIRS) on EOS-AQUA and the Cross-Track Infrared Sounders (CrIS) on the SNPP and JPSS-1+ platforms.  (JPSS-1 is also called NOAA-20). CHIRP provides a consistent spectral response function (SRF) across all instruments. Inter-instrument radiometric offsets are removed with SNPP-CrIS chosen as the \"standard\".  CHIRP follows the original instrument storage, i.e., granule in, granule out, and contains all information needed for retrievals (including cross-track, along-track, fov id, etc.). This version of CHIRP, SNDR13CHRP1, is the primary CHIRP product which provides a full radiance record from 2002 onwards starting with AIRS from September 1, 2002 to August 30, 2016, switching to the SNPP CrIS instrument on September 1, 2016.  The SNDR13CHRP1 product then switches to using JPSS-1 CrIS radiances starting September 1, 2018.  This selection of time periods provides the best match to times when the microwave sounders on each of these platforms exhibited good performance and avoids long outages (such as SNPP CrIS in early Spring 2019).  CHIRP is available for AIRS, CrIS-SNPP, and CrIS-JPSS-1 for time periods not used in the product distributed here, and are named SNDR13CHRP1AQCal, SNDR13CHRP1SNCal, and SNDR13CHRP1J1Cal respectively.  ",
         "license": "proprietary"
     },
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         "description": "This data set provides an estimate of the surface air temperature.  It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight.    The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft.  The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. These are all daily products on a \u00bc x \u00bc degree latitude/longitude grid covering the continental United States (CONUS).    The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2284971212-GES_DISC.html",
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         "description": "The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft.  The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. This data set provides an estimate of the vapor pressure deficit.  It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. These are all daily products on a \u00bc x \u00bc degree latitude/longitude grid covering the continental United States (CONUS).    The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1693440794-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS CLIMCAPS Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.     Cloud-Cleared Radiances contain calibrated, geolocated channel-by-channel AIRS infrared radiances (milliWatts/m2/cm-1/steradian) that would have been observed if there were no clouds in the FOV.  An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track for each of the approximate 2378 channels. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1693440795-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files.  For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov   The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS CLIMCAPS Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.    The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  An AIRS level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  ",
         "license": "proprietary"
     },
@@ -162326,7 +162586,7 @@
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         "description": "The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS CLIMCAPS Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.  The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  An AIRS level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day. ",
         "license": "proprietary"
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the comprehensive quality control (QC) methodology. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.  ",
         "license": "proprietary"
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the comprehensive quality control (QC) methodology. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.   ",
         "license": "proprietary"
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         "description": "WARNING: Users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.  The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the specific quality control (QC) methodology. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  ",
         "license": "proprietary"
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         "description": "WARNING: Users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the specific quality control (QC) methodology. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.   ",
         "license": "proprietary"
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         "description": "This data set provides an estimate of the surface air temperature.  It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight.  The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft.  The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder.  It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. These are all daily products on a \u00bc x \u00bc degree latitude/longitude grid covering the continental United States (CONUS).    The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from. ",
         "license": "proprietary"
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         "description": "This data set provides an estimate of the vapor pressure deficit.  It infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight.  The Spatial Statistical Data Fusion (SSDF) surface continental United States (CONUS) products, fuse data from the Atmospheric InfraRed Sounder (AIRS) instrument on the EOS-Aqua spacecraft with data from the Cross-track Infrared and Microwave Sounding Suite (CrIMSS) instruments on the Suomi-NPP spacecraft.  The CrIMSS instrument suite consists of the Cross-track Infrared Sounder (CrIS) infrared sounder and the Advanced Technology Microwave Sounder (ATMS) microwave sounder. These are all daily products on a \u00bc x \u00bc degree latitude/longitude grid covering the continental United States (CONUS).  The SSDF algorithm infers a value for each grid point based on nearby and distant values of the input Level-2 datasets and estimates of the variance of those values, with lower variances given higher weight. Performing the data fusion of two (or more) remote sensing datasets that estimate the same physical state involves four major steps: (1) Filtering input data; (2) Matching the remote sensing datasets to an in situ dataset, taken as a truth estimate; (3) Using these matchups to characterize the input datasets via estimation of their bias and variance relative to the truth estimate; (4) Performing the spatial statistical data fusion. We note that SSDF can also be performed on a single remote sensing input dataset. The SSDF algorithm only ingests the bias-corrected estimates, their latitudes and longitudes, and their estimated variances; the algorithm is agnostic as to which dataset or datasets those estimates, latitudes, longitudes, and variances originated from. ",
         "license": "proprietary"
     },
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         "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. AIRS/Aqua Level-1C calibration subset including clear cases, special calibration sites, random nadir spots, and high clouds. Infrared temperature sounders generate a large amount of Level-1B spectral data.  For example, the AIRS instrument with 2378 channels, its visible light component and AMSU with 15 channels create 3x240 files each day, for a total of over 500 MB of data.   The purpose of the Calibration Data Subsets is extract key information from these data into a few daily files to:     1. Facilitate a quick evaluation of the absolute calibration of the instruments.     2. Facilitate an assessment of the instrument performance under clear, cloudy, and extreme hot and cold conditions.     3. Facilitate the evaluation of instrument trends and their significance relative to climate trends.     4. Facilitate the comparison of AIRS with CrIS using their equivalent data subsets.  The output files are constructed from Level-1B or Level-1C IR and MW brightness or antenna temperatures.  Each file contains selected observations taken from a nominal 24-hour period. The \u201csummary\u201d product includes a large set of cases of interest, including all identified spectra that match selection criteria detailed below for clear, special cloud classes, etc.  These amount to about 10% of all spectra.  But for each selected case only brightness temperatures (BTs) for selected key channels are saved.",
         "license": "proprietary"
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         "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. AIRS/Aqua Level-1C calibration subset including clear cases, special calibration sites, random nadir spots, and high clouds. Infrared temperature sounders generate a large amount of Level-1B spectral data.  For example, the AIRS instrument with 2378 channels, its visible light component and AMSU with 15 channels create 3x240 files each day, for a total of over 500 MB of data.   The purpose of the Calibration Data Subsets is extract key information from these data into a few daily files to:     1. Facilitate a quick evaluation of the absolute calibration of the instruments.     2. Facilitate an assessment of the instrument performance under clear, cloudy, and extreme hot and cold conditions.     3. Facilitate the evaluation of instrument trends and their significance relative to climate trends.     4. Facilitate the comparison of AIRS with CrIS using their equivalent data subsets. The output files are constructed from Level-1B or Level-1C IR and MW brightness or antenna temperatures.  Each file contains selected observations taken from a nominal 24-hour period. ",
         "license": "proprietary"
     },
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         "description": "The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.     Cloud-Cleared Radiances contain calibrated, geolocated channel-by-channel AIRS infrared radiances (milliWatts/m2/cm-1/steradian) that would have been observed within each AMSU footprint if there were no clouds in the FOV.  An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track for each of the approximate 2378 channels. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.",
         "license": "proprietary"
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.    The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track for each of the approximate 2378 channels. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.   ",
         "license": "proprietary"
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         "description": "The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.  The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track for each of the approximate 2378 channels. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day",
         "license": "proprietary"
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.  The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the comprehensive quality control (QC) methodology. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.  ",
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         "description": "The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.   This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the comprehensive quality control (QC) methodology. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.  WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 48.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/48.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov",
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         "description": "WARNING: Users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the specific quality control (QC) methodology. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  ",
         "license": "proprietary"
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the AIRS (Atmospheric Infrared Sounder) and AMSU (Advanced Microwave Sounding Unit). The AIRS instrument is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. The AIRS in combination with the AMSU constitutes an innovative atmospheric sounding group of infrared and microwave sensors. The AIRS Standard Retrieval Product consists of retrieved estimates of cloud and surface properties, plus profiles of retrieved temperature, water vapor, ozone, carbon monoxide and methane. The temperature profile vertical resolution is 100 levels total between 1100 mb and 0.1 mb, while moisture profile is reported at atmospheric layers between 1100 mb and 300 mb. The horizontal resolution is 50 km.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.   This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the specific quality control (QC) methodology. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  ",
         "license": "proprietary"
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         "description": "The Advanced Technology Microwave Sounder (ATMS) Level 1B data files contain brightness temperature measurements along with ancillary spacecraft, instrument, and geolocation data of the ATMS instrument on the Joint Polar Satellite System-1 (JPSS-1) platform. This platform is also known as NOAA-20 (National Oceanic and Atmospheric Administration).   The ATMS is a 22-channel mm-wave radiometer. The ATMS will measure upwelling radiances in six frequency bands centered at 23 GHz, 31 GHz, 50-58 GHz, 89 GHz, 66 GHz, and 183 GHz. The ATMS is a total power radiometer, with \"through-the-antenna\" radiometric calibration. Radiometric data is collected by a pair of antenna apertures, scanned by rotating flat plate reflectors. Scanning is performed cross-track to the satellite motion from sun to anti-sun, using the \"integrate-while-scan\" type data collection. The scan period is 8/3 second, synchronized to the Cross-track Infrared Sounder (CrIS) using a spacecraft provided scan synchronization pulse.  Since the JPSS-1 satellite is orbiting at an altitude of about 830 km, the instantaneous spatial resolution on the ground at nadir is about 16 km, 32 km, or 75 km depending upon the channel. The brightness temperature data are contained in an array with 135 rows in the along-track direction, 96 columns in the cross-track direction, and a 3rd dimension for each of the 22 channels. The ATMS cross-track scan interval is 0.018 seconds and the along-track scan period is 8/3 seconds.. Data products are constructed on six minute boundaries. The Granule Map Product consists of daily images of granule coverage in PDF format. ",
         "license": "proprietary"
     },
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the NOAA-20 platform, also known as JPSS-1. The CrIS instrument is a Fourier transform spectrometer with a total of 2211 FSR (Full Spectral Resolution) infrared sounding channels covering the longwave (645-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2100-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.   This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable.  Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  ",
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         "license": "proprietary"
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         "description": "This level 2 product is generated by the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the NOAA-20 (National Oceanic and Atmospheric Administration) also know as Joint Polar Satellite System (JPSS-1) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II Level-2 retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties for six minutes of instrument observation at a time. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval  A level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  ",
         "license": "proprietary"
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         "description": "This level 3 daily product is generated from the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the NOAA-20 (National Oceanic and Atmospheric Administration) also know as Joint Polar Satellite System (JPSS-1) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable.  ",
         "license": "proprietary"
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         "description": "This level 3 monthly product is generated from the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the  NOAA-20 (National Oceanic and Atmospheric Administration) also know as Joint Polar Satellite System (JPSS-1) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval  This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable.  ",
         "license": "proprietary"
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         "description": "The Advanced Technology Microwave Sounder (ATMS) Level 1B data files contain brightness temperature measurements along with ancillary spacecraft, instrument, and geolocation data of the ATMS instrument on the Suomi National Polar-orbiting Partnership Project (S-NPP).  The ATMS instrument is a cross-track scanner with 22 microwave channels in the range 23.8-183.31 Gigahertz (GHz). The beam width is 1.1 degrees for the channels in the 160-183 GHz range, 2.2 degrees for the 80 GHz and 50-60 GHz channels, and 5.2 degrees for the 23.8 and 31.4 GHz channels. Since the SNPP satellite is orbiting at an altitude of about 830 km, the instantaneous spatial resolution on the ground at nadir is about 16 km, 32 km, or 75 km depending upon the channel. The brightness temperature data are contained in an array with 135 rows in the along-track direction, 96 columns in the cross-track direction, and a 3rd dimension for each of the 22 channels. The ATMS cross-track scan interval is 0.018 seconds and the along-track scan period is 8.3 seconds.   Data products are constructed on six minute boundaries. The Granule Map Product consists of daily images of granule coverage in PDF format. ",
         "license": "proprietary"
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         "description": "The Cross-track Infrared Sounder (CrIS) Level 1B Normal Spectral Resolution (NSR) data files contain radiance measurements along with ancillary spacecraft, instrument, and geolocation data of the CrIS instrument on the Suomi National Polar-orbiting Partnership Project (SNPP). In December 2014, the CrIS instrument on the SNPP satellite doubled the spectral resolution of shortwave infrared data being transmitted to the ground.  In November 2015, additional points were included at the ends of the longwave and shortwave interferograms to improve the quality of the calibration.  Prior to November 2, 2015 the data are only available in Normal Spectral Resolution, after November 2, 2015 at 16:06 UTC, the data are available in both NSR and Full Spectral Resolution (FSR).   The NSR files have 1,317 channels: 163 shortwave channels from 3.9 to 4.7 microns (2555 to 2150 cm-1), 437 midwave channels from 5.7 to 8.05 microns (1752.5 to 1242.5 cm-1), and 717 longwave channels from 9.1 to 15.41 microns (1096.25 to 648.75 cm-1). Each CrIS field-of-regard (FOR) contains 9 field-of-views (FOVs) arranged in a 3X3 array. The Level 1B files contain 30 FORs in the cross track direction and 45 in the along track direction. Data products are constructed on six minute boundaries.  The Visible Infrared Imaging Radiometer Suite (VIIRS) has 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns. It provides the sensor data records for clouds, sea surface temperature, ocean color, and others. This IMG_COL product contains the colocation indices of the VIIRS pixels within each CrIS footprint.",
         "license": "proprietary"
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         "description": "The Cross-track Infrared Sounder (CrIS) Level 1B Normal Spectral Resolution (NSR) data files contain radiance measurements along with ancillary spacecraft, instrument, and geolocation data of the CrIS instrument on the Suomi National Polar-orbiting Partnership Project (SNPP). In December 2014, the CrIS instrument on the SNPP satellite doubled the spectral resolution of shortwave infrared data being transmitted to the ground.  In November 2015, additional points were included at the ends of the longwave and shortwave interferograms to improve the quality of the calibration.  Prior to November 2, 2015 the data are only available in Normal Spectral Resolution, after November 2, 2015 at 16:06 UTC, the data are available in both NSR and Full Spectral Resolution (FSR).   The NSR files have 1,317 channels: 163 shortwave channels from 3.9 to 4.7 microns (2555 to 2150 cm-1), 437 midwave channels from 5.7 to 8.05 microns (1752.5 to 1242.5 cm-1), and 717 longwave channels from 9.1 to 15.41 microns (1096.25 to 648.75 cm-1). Each CrIS field-of-regard (FOR) contains 9 field-of-views (FOVs) arranged in a 3X3 array. The Level 1B files contain 30 FORs in the cross track direction and 45 in the along track direction. Data products are constructed on six minute boundaries.  The Visible Infrared Imaging Radiometer Suite (VIIRS) has 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns. It provides the sensor data records for clouds, sea surface temperature, ocean color, and others. This IMG product primarily contains statistics of the VIIRS cloud mask and VIIRS L1B data within each CrIS footprint..",
         "license": "proprietary"
     },
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         "description": "The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. Infrared temperature sounders generate a large amount of Level-1B spectral data.    The purpose of the Calibration Data Subsets is extract key information from these data into a few daily files to:     1. Facilitate a quick evaluation of the absolute calibration of the instruments.     2. Facilitate an assessment of the instrument performance under clear, cloudy, and extreme hot and cold conditions.     3. Facilitate the evaluation of instrument trends and their significance relative to climate trends.     4. Facilitate the comparison of AIRS with CrIS using their equivalent data subsets.  The output files are constructed from Level-1B and MW brightness or antenna temperatures.  Each file contains selected observations taken from a nominal 24-hour period.   The S-NPP CrIS summary subset contains Level-1B BTs for all selection types but only for selected channels, while the S-NPP CrIS random calibration subset contains full Level-1B spectra for only the randomly selected observations.  ",
         "license": "proprietary"
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         "description": "The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. Infrared temperature sounders generate a large amount of Level-1B spectral data.    The purpose of the Calibration Data Subsets is extract key information from these data into a few daily files to:     1. Facilitate a quick evaluation of the absolute calibration of the instruments.     2. Facilitate an assessment of the instrument performance under clear, cloudy, and extreme hot and cold conditions.     3. Facilitate the evaluation of instrument trends and their significance relative to climate trends.     4. Facilitate the comparison of AIRS with CrIS using their equivalent data subsets.  The \u201csummary\u201d product includes a large set of cases of interest, including all identified spectra that match selection criteria detailed below for clear, special cloud classes, etc.  These amount to about 10% of all spectra.  But for each selected case only brightness temperatures (BTs) for selected key channels are saved.  The output files are constructed from Level-1B and MW brightness or antenna temperatures.  Each file contains selected observations taken from a nominal 24-hour period.   The S-NPP CrIS summary subset contains Level-1B BTs for all selection types but only for selected channels, while the S-NPP CrIS random calibration subset contains full Level-1B spectra for only the randomly selected observations.  ",
         "license": "proprietary"
     },
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         "license": "proprietary"
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov   The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  The CLIMCAPS algorithm uses data from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) as a first-guess for the atmospheric state.  Because MERRA-2 products typically have a latency from 3 to 7 weeks, so too do the CLIMCAPS products.   A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  ",
         "license": "proprietary"
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Full Spectral Resolution (FSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 2211 FSR infrared sounding channels covering the longwave (645-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2000-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.  The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.   The CLIMCAPS algorithm uses data from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) as a first-guess for the atmospheric state.  Because MERRA-2 products typically have a latency from 3 to 7 weeks, so too do the CLIMCAPS products.   ",
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         "description": "The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data.   Cloud clearing is the process of computing the clear column radiance for a given channel n, and represents what the channel would have observed if the entire scene were cloud free. The entire scene is defined as the ATMS field of regard (FOR) which includes and array of 3x3 CrIS field of views (FOV). The basic assumption of cloud-clearing is that if the observed radiances in each field-of-view are different, the differences in the observed radiances are solely attributed to the differences in the fractional cloudiness in each field of view while everything else (surface properties and atmospheric state) is uniform across the field of regard.  The CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection AIRI2CCR contains similar meteorological information to this CHART data collection and the CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) data collection SNDRSNIML2CCPCCRN contains CRIMSS data processed with an analogous algorithm. A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.",
         "license": "proprietary"
     },
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         "description": "The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.  The CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection AIRX2SUP contains similar meteorological information to this CHART data collection and the CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) data collection SNDRSNIML2CCPRETN contains CRIMSS data processed with an analogous algorithm.  A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.",
         "license": "proprietary"
     },
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         "description": "The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.  The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.   The CLIMCAPS algorithm uses data from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) as a first-guess for the atmospheric state.  Because MERRA-2 products typically have a latency from 3 to 7 weeks, so too do the CLIMCAPS products.   ",
         "license": "proprietary"
     },
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         "description": "The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Full Spectral Resolution (FSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 2211 FSR infrared sounding channels covering the longwave (645-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2000-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.  The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  A level 2 granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.   The CLIMCAPS algorithm uses data from the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) as a first-guess for the atmospheric state.  Because MERRA-2 products typically have a latency from 3 to 7 weeks, so too do the CLIMCAPS products.   ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2782356281-GES_DISC.html",
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         "description": "This level 2 standard product is generated by the SiFSAP (Single Field-of-View Sounder Atmospheric Products) algorithm. The SIFSAP algorithm provides retrieval for each sounder Field of View (FOV), therefore, it has 3-times higher horizontal spatial resolution and 9-time denser products compared to other current IR sounder products.  Since SiFSAP is an FOV-based algorithm, its product variables have an additional dimension which represents the number of FOVs. For CrIS instrument, there are 9 FOVs for each Field of Regard (FOR). The SiFSAP Level-2 retrieval products contain a variety of geophysical parameters retrieved from IR/MW sounder suites measurements, including profiles of temperature, water vapor and trace gas species as well as clouds and surface properties. This standard product provides retrievals on a reduced vertical profile (11 levels for water profiles and up to 27 for other profile variables). A level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2782339991-GES_DISC.html",
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         "description": "This level 2 support product is generated by the SiFSAP (Single Field-of-View Sounder Atmospheric Products) algorithm. The SIFSAP algorithm provides retrieval for each sounder Field of View (FOV), therefore, it has 3-times higher horizontal spatial resolution and 9-time denser products compared to other current IR sounder products.  Since SiFSAP is an FOV-based algorithm, its product variables have an additional dimension which represents the number of FOVs. For CrIS instrument, there are 9 FOVs for each Field of Regard (FOR). The SiFSAP Level-2 retrieval products contain a variety of geophysical parameters retrieved from IR/MW sounder suites measurements, including profiles of temperature, water vapor and trace gas species as well as clouds and surface properties. This support product provides height vertical sampling (up to 98 levels) and also includes more detailed Empirical Orthogonal Function (EOF) information like averaging kernels. A level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  ",
         "license": "proprietary"
     },
@@ -163041,7 +163301,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1692982078-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable and applying comprehensive QC methodology. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1692982085-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Full Spectral Resolution (FSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 2211 FSR infrared sounding channels covering the longwave (645-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2000-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.   This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633993917-GES_DISC.html",
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         "description": "The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the comprehensive quality control (QC) methodology. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.    The CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection with the TqJ suffix (TqJoint) from AIRX3SPD contains similar meteorological information to this CHART data collection and the CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) data collection SNDRSNIML3CDCCPN contains CRIMSS data processed with an analogous algorithm.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1692982080-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable and applying comprehensive QC methodology.  Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.  WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 48.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/48.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  If you were redirected to this page from a DOI from an older version, please note this is the current version of the product. Please contact the GES DISC user support if you need information about previous data collections.",
         "license": "proprietary"
     },
@@ -163093,7 +163353,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1692982087-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Full Spectral Resolution (FSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 2211 FSR infrared sounding channels covering the longwave (645-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2000-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.   This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables. ",
         "license": "proprietary"
     },
@@ -163106,7 +163366,7 @@
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         "description": "The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.  The monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the comprehensive quality control (QC) methodology to form a level-2 daily gridded product. The daily level-3 gridded products are averaged to create the monthly average. Comprehensive QC accepts a retrieval if the profile is good to the surface and ensures consistent analysis across all levels and variables.    The CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection with the TqJ suffix (TqJoint) from AIRX3STM contains similar meteorological information to this CHART data collection and the CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) data collection SNDRSNIML3CMCCPN contains CRIMSS data processed with an analogous algorithm.",
         "license": "proprietary"
     },
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         "description": "The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable and applying specific QC methodology. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 48.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/48.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov",
         "license": "proprietary"
     },
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Full Spectral Resolution (FSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 2211 FSR infrared sounding channels covering the longwave (645-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2000-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.   This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  ",
         "license": "proprietary"
     },
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         "description": "The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.   This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying profile level specific quality control (QC). Specific QC is defined per retrieved geophysical parameter at a given level within a profile. It accepts profile level data from the top of the atmosphere down to the level where the QC algorithm determines that the retrieval is good. Below this level, the data is rejected. Specific QC is designed to maximize the yield of each variable. This is the same methodology used by the AIRS Version 6 processing system.  The CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection AIRX3SPD contains similar meteorological information to this CHART data collection.",
         "license": "proprietary"
     },
@@ -163158,7 +163418,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2816205963-GES_DISC.html",
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         "description": "The SIFSAP (Single Field-of-View Sounder Atmospheric Products) algorithm provides retrieval for each sounder Field of View (FOV), therefore, it has 3-times higher horizontal spatial resolution and 9-time denser products compared to other current IR sounder products. Since SiFSAP is an FOV-based algorithm, its product variables have an additional dimension which represents the number of FOVs. For CrIS instrument, there are 9 FOVs for each Field of Regard (FOR). The SiFSAP L3 products contain a variety of geophysical parameters retrieved from IR/MW sounder suites measurements, including atmospheric temperature profiles, water vapor, ozone profiles, clouds, and surface properties.   This daily one half degree latitude by one half degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use). The Level-3 products maximize the yield of each individual variable and level by collecting all cases where the corresponding Level 2 quality control from the top of the atmosphere down to the level where the QC determines that the value is\u00a00\u00a0(best) or 1 (good). Below this level, the data is rejected. This gives the greatest possible yield for any given level and variable.   ",
         "license": "proprietary"
     },
@@ -163171,7 +163431,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1692982082-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.  This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable and applying specific QC methodology. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1692982089-GES_DISC.html",
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         "description": "WARNING: To users of the derived product \u201cco_mmr_midtrop\u201d (carbon monoxide mass mixing ratio to dry air [kg/kg] at ~500 hPa). This variable has a significant bias due to a conversion error: the molecular weight of carbon dioxide (CO2, 44.01 g/mol) was used instead of carbon monoxide (CO, 28.01 g/mol). To correct, simply multiply \u201cco_mmr_midtrop\u201d by 28.01/44.01. Alternatively, derive a profile of mass mixing ratio from scratch using the retrieved column density values (\u201cmol_lay/co_mol_lay\u201d) in the Level 2 files. For further questions or concerns please contact the Sounder SIPS at: sounder.sips@jpl.nasa.gov  The CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm is used to analyze data from the Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite). The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Full Spectral Resolution (FSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 2211 FSR infrared sounding channels covering the longwave (645-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2000-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CLIMCAPS algorithm uses an Optimal Estimation methodology and uses an a-priori first guess to start the process. A CLIMCAPS sounding is comprised of a set of parameters that characterizes the full atmospheric state and includes a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; carbon monoxide, methane, carbon dioxide, sulfur dioxide, nitrous oxide, and nitric acid.   This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable. Specific QC accepts profile level from the top of the atmosphere down to the level where the QC determines that it is still good. Below this level, the data is rejected.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633993925-GES_DISC.html",
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         "description": "The objective of this limited edition data collection is to examine products generated by the Climate Heritage AIRS Retrieval Technique (CHART) algorithm to analyze Cross-track Infrared Sounder/Advanced Technology Microwave Sounder (CrIS/ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite).  The CrIS/ATMS instruments used for this product are on board the Suomi National Polar-orbiting Partnership (SNPP) platform and use the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions. The ATMS instrument  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz.   The CHART algorithm is uses the  basic cloud clearing and retrieval methodologies used including the definition and derivation of Jacobians, the channel noise covariance matrix, and the use of constraints including the background term, are essentially identical to those of AIRS Version-6.6 and previous AIRS Science Team retrieval algorithms.  As with the Version-6.6 AIRS system, the CHART algorithm uses a Neural Network system as an initial guess. The sounding retrieval methodology characterizes the full atmospheric state and the retrievals contains a variety of geophysical parameters derived from the CrIMSS data. These include surface temperature and infrared emissivity; full atmosphere profiles of temperature, water vapor and ozone; infrared effective cloud top characteristics; outgoing longwave radiation (OLR); and an infrared-based precipitation estimate.   The monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products applying the specific quality control (QC) methodology to form a level-2 daily gridded product. Specific QC is defined per retrieved geophysical parameter at a given level within a profile. It accepts profile level data from the top of the atmosphere down to the level where the QC algorithm determines that the retrieval is good. Below this level, the data is rejected. This is the same methodology used by the AIRS Version 6 processing system. The daily level-3 gridded products are averaged to create the monthly average.    The CHART system was designed to serve as a seamless follow on to the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU) instrument processing system. For comparison, the AIRS/AMSU data collection from AIRX3STM contains similar meteorological information to this CHART data collection.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2816205998-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2816205998-GES_DISC.html",
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         "description": "The SIFSAP (Single Field-of-View Sounder Atmospheric Products) algorithm provides retrieval for each sounder Field of View (FOV), therefore, it has 3-times higher horizontal spatial resolution and 9-time denser products compared to other current IR sounder products. Since SiFSAP is an FOV-based algorithm, its product variables have an additional dimension which represents the number of FOVs. For CrIS instrument, there are 9 FOVs for each Field of Regard (FOR). The SiFSAP L3 products contain a variety of geophysical parameters retrieved from IR/MW sounder suites measurements, including atmospheric temperature profiles, water vapor, ozone profiles, clouds, and surface properties.   This monthly one half degree latitude by one half degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use). The Level-3 products maximize the yield of each individual variable and level by collecting all cases where the corresponding Level 2 quality control from the top of the atmosphere down to the level where the QC determines that the value is\u00a00\u00a0(best) or 1 (good). Below this level, the data is rejected. This gives the greatest possible yield for any given level and variable.    ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2560854342-GES_DISC.html",
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         "description": "This level 2 support product is generated by the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the Suomi-National Polar-orbiting Partnership (NPP) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II Level-2 retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties for six minutes of instrument observation at a time. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval  A level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  ",
         "license": "proprietary"
     },
@@ -163236,7 +163496,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2099190126-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2099190126-GES_DISC.html",
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         "description": "This SNDRSNM2RMS level 2 product is generated by the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm. Different from the CLIMCAPS (Community Long-term Infrared Microwave Coupled Product System) algorithm, the RAMSES II algorithm is a microwave only retrieval algorithm. While the CLIMCAPS uses measurements from both Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) instruments, also known as CrIMSS (Cross-track Infrared and Microwave Sounding Suite), the RAMSES II only uses observations from ATMS. The ATMS instrument used for this product  is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz on board the Suomi National Polar-orbiting Partnership (SNPP) platform. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval. A level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  For the initial release of version 1 RAMSES II, a test data set of 8 months is provided. This includes the months of January, April, July and October of the years 2013 and 2015. The dataset is designed to allow research and comparisons over a full seasonal cycle and comparisons of different phases of the ENSO cycle ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2559919298-GES_DISC.html",
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         "description": "This level 2 product is generated by the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the Suomi-National Polar-orbiting Partnership (NPP) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II Level-2 retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties for six minutes of instrument observation at a time. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval  A level 2 granule has been set as 6 minutes of data. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.  ",
         "license": "proprietary"
     },
@@ -163262,7 +163522,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2560864430-GES_DISC.html",
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         "description": "This level 3 daily product is generated from the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the Suomi-National Polar-orbiting Partnership (NPP) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval  This daily one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2560865554-GES_DISC.html",
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         "description": "This level 3 monthly product is generated from the RAMSES (Retrieval Algorithm for Microwave Sounders in Earth Science) II algorithm.The RAMSES II algorithm is a microwave only retrieval algorithm using observations from the Suomi-National Polar-orbiting Partnership (NPP) Advanced Technology Microwave Sounder (ATMS) instrument. The ATMS instrument used for this product is a cross-track scanner with 22 channels in spectral bands from 23 GHz through 183 GHz. The RAMSES II retrieval products contain a variety of geophysical parameters retrieved from ATMS measurements, including profiles of temperature, water in all phases as well as surface properties. The RAMSES II algorithm doesn't have a cloud clearing process and produces all weather retrieval  This monthly one degree latitude by one degree longitude level-3 product starts with level-2 retrieval products with QC values of 0 (best), 1 (good), and 2 (don't use) which are provided for each variable.  ",
         "license": "proprietary"
     },
@@ -164163,6 +164423,32 @@
         "description": "This data set consists of soil moisture and soil temperature measurements taken during the SnowEx 2021 field campaign. Soil moisture probes were deployed at 9 locations within the Montana Prairie Station study area and monitored soil properties at four different depths (5, 10, 20 and 50 cm).",
         "license": "proprietary"
     },
+    {
+        "id": "SNEX21_PS_DSM_1",
+        "title": "SnowEx21 Prairie Station Digital Surface Models from UAV-LiDAR V001",
+        "catalog": "NSIDC_ECS STAC Catalog",
+        "state_date": "2021-01-15",
+        "end_date": "2021-03-04",
+        "bbox": "-109.9595558, 47.0562694, -109.945955, 47.0655368",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3241729770-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3241729770-NSIDC_ECS.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjAgbGFzZXIgc25vdyBtaWNyb3N0cnVjdHVyZSBzcGVjaWZpYyBzdXJmYWNlIGFyZWEgZGF0YSB2MDAxXCIsXCJOU0lEQ19FQ1NcIixcIlNORVgyMF9TU0FcIixcIjFcIiwxOTcwNzU1MzE0LDg2XSIsInVtbSI6IltcInNub3dleDIwIGxhc2VyIHNub3cgbWljcm9zdHJ1Y3R1cmUgc3BlY2lmaWMgc3VyZmFjZSBhcmVhIGRhdGEgdjAwMVwiLFwiTlNJRENfRUNTXCIsXCJTTkVYMjBfU1NBXCIsXCIxXCIsMTk3MDc1NTMxNCw4Nl0ifQ%3D%3D/SNEX21_PS_DSM_1",
+        "description": "This dataset consists of Digital Surface Models (DSMs) derived from UAV-LiDAR acquired during the SnowEx 2021 field campaign at the Central Agricultural Research Center in central Montana (USA). The DSMs are at 0.3 m resolution and consist of one snow-off and seven snow-on flights.",
+        "license": "proprietary"
+    },
+    {
+        "id": "SNEX21_PS_MET_1",
+        "title": "SnowEx21 Prairie Station Hourly Meteorological Data V001",
+        "catalog": "NSIDC_ECS STAC Catalog",
+        "state_date": "2020-11-12",
+        "end_date": "2021-04-02",
+        "bbox": "-109.956783, 47.060545, -109.956783, 47.060545",
+        "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3241728800-NSIDC_ECS.umm_json",
+        "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3241728800-NSIDC_ECS.html",
+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjAgbGFzZXIgc25vdyBtaWNyb3N0cnVjdHVyZSBzcGVjaWZpYyBzdXJmYWNlIGFyZWEgZGF0YSB2MDAxXCIsXCJOU0lEQ19FQ1NcIixcIlNORVgyMF9TU0FcIixcIjFcIiwxOTcwNzU1MzE0LDg2XSIsInVtbSI6IltcInNub3dleDIwIGxhc2VyIHNub3cgbWljcm9zdHJ1Y3R1cmUgc3BlY2lmaWMgc3VyZmFjZSBhcmVhIGRhdGEgdjAwMVwiLFwiTlNJRENfRUNTXCIsXCJTTkVYMjBfU1NBXCIsXCIxXCIsMTk3MDc1NTMxNCw4Nl0ifQ%3D%3D/SNEX21_PS_MET_1",
+        "description": "This data set contains observations from a meteorological station installed at the Central Agricultural Research Center in Moccasin Montana as part of the NASA SnowEx 2021 Prairie Snow field campaign. Parameters include: air temperature, wind speed and direction, and barometric pressure. Data are available from 12 November 2020 through 2 March 2021.",
+        "license": "proprietary"
+    },
     {
         "id": "SNEX21_SSR_1",
         "title": "SnowEx21 Senator Beck Basin and Grand Mesa, CO AVIRIS-NG Surface Spectral Reflectance V001",
@@ -164198,7 +164484,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2854618795-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2854618795-NSIDC_ECS.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIiwidW1tIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIn0%3D/SNEX23_BCEF_TLS_1",
         "description": "This data set contains digital terrain models (DTMs) derived from terrestrial lidar scans (TLS) collected as part of the SnowEx 2023 campaign. Data were collected at the Bonanza Creek Experimental Forest near Fairbanks, Alaska in October 2022 (snow-off conditions) and March 2023 (snow-on conditions). The DTMs are provided as Geographic Tagged Image (GeoTIFF) files, where each file corresponds to a unique survey site. Unprocessed point cloud data from which these DTMs were derived are available as the <a href=\"https://doi.org/10.5067/OIBBFR49P0Q6\">SnowEx23 Bonanza Creek Experimental Forest Terrestrial Lidar Scans Raw, Version 1 (SNEX23_BCEF_TLS_Raw) data set</a>",
         "license": "proprietary"
     },
@@ -164211,7 +164497,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2856186714-NSIDC_ECS.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIiwidW1tIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIn0%3D/SNEX23_BCEF_TLS_Raw_1",
         "description": "This data set contains unprocessed point cloud data created from terrestrial lidar scans (TLS) collected during the SnowEx 2023 campaign from the Bonanza Creek Experimental Forest near Fairbanks, Alaska. Data were collected in October 2022 (snow-off) and March 2023 (snow-on). Digital terrain models (DTMs) derived from the raw point cloud data are available as the <a href=\"https://doi.org/10.5067/R466GRXNA61S\">SnowEx23 Bonanza Creek Experimental Forest Terrestrial Lidar Scans, Version 1 (SNEX23_BCEF_TLS) data set</a>",
         "license": "proprietary"
     },
@@ -164224,7 +164510,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3215566728-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3215566728-NSIDC_ECS.html",
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         "description": "This data set contains the results of 1 GHz ground-penetrating radar surveys conducted at the Upper Kuparuk/Toolik (UKT) site in northern Alaska, USA as part of the NASA SnowEx 2023 field campaign. Data were collected between 08 Mar 2023 to 15 Mar 2023, spatially coinciding with snow pit locations and along transects between snow pits. Data include two-way travel (TWT) time, calculated snow depth, and calculated snow water equivalent (SWE). Raw GPR data are available as <a href=\"https://nsidc.org/data/SNEX23_CRREL_GPR_Raw/versions/1\">SnowEx23 CRREL Ground Penetrating Radar Raw, Version 1</a>.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3227266712-NSIDC_ECS.html",
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         "description": "This data set contains the results of 1 GHz ground-penetrating radar surveys conducted at the Upper Kuparuk/Toolik (UKT) site in northern Alaska, USA as part of the NASA SnowEx 2023 field campaign. Data were collected between 08 Mar 2023 to 15 Mar 2023, spatially coinciding with snow pit locations and along transects between snow pits. Data include georeferenced multichannel ground-penetrating radargrams stored within .nc files. PRocessed GPR data are available as <a href=\"https://nsidc.org/data/SNEX23_CRREL_GPR/versions/1\">SnowEx23 CRREL Ground Penetrating Radar, Version 1</a>.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3184787416-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3184787416-NSIDC_ECS.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIiwidW1tIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIn0%3D/SNEX23_CSU_GPR_Raw_1",
         "description": "This data set contains the raw results of 1 GHz ground-penetrating radar surveys conducted as part of the NASA SnowEx23 field campaign in Alaska, USA. Surveys were conducted at three different field sites between 07 March 2023 and 16 March 2023: 1) Farmers Loop/Creamers Field, 2) the Bonanza Creek Experimental Forest, and 3) the Caribou/Poker Creek Research Watershed.",
         "license": "proprietary"
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@@ -164263,7 +164549,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2893208516-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2893208516-NSIDC_ECS.html",
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         "description": "This data set provides digital terrain models, snow depth, and canopy height, acquired by a scanning lidar system and derived from Point Cloud Digital Terrain Models (PCDTMs) from two regions of Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer\u2019s Loop/Creamer\u2019s Field) and a coastal tundra environment in the North Slope region of the northern Alaska coastal plain (Arctic coastal plain and Upper Kuparuk Toolik). The raw data from which these data are derived are available as <a href=\"https://nsidc.org/data/SNEX23_Lidar_Raw\">SnowEx23 Airborne Lidar Scans Raw, Version 1</a>.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3154261714-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3154261714-NSIDC_ECS.html",
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         "description": "The data set contains snow depth measurements from two regions of Alaska, USA collected during the March 2022 intensive observation period (IOP) as part of the NASA SnowEx 2023 field campaign. The study sites include three boreal forest sites in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer\u2019s Loop/Creamer\u2019s Field) and a coastal tundra site in the North Slope region (Arctic coastal plain). Snow depth measurements collected from the study sampling sites during the subsequent field season are available as <a href=\"https://nsidc.org/data/snex23_mar23_sd/versions/1\">SnowEx23 Mar23 IOP Snow Depth Measurements, Version 1</a>.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3172387010-NSIDC_ECS.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIiwidW1tIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIn0%3D/SNEX23_MAR23_SD_1",
         "description": "The data set contains snow depth measurements from five study sites in Alaska, USA; data were collected during the March 2023 intensive observation period (IOP) as part of the NASA SnowEx 2023 field campaign. The study sites include three boreal forest sites in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, Caribou Poker Creek watershed, and Farmer\u2019s Loop/Creamer\u2019s Field) and two coastal tundra sites in the North Slope region (Arctic coastal plain and Upper Kuparuk Toolik). Snow depth measurements collected from the study sampling sites during the previous field season are available as <a href=\"https://nsidc.org/data/snex23_mar22_sd/versions/1\">SnowEx23 Mar22 IOP Snow Depth Measurements, Version 1</a>.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2735033831-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2735033831-NSIDC_ECS.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIiwidW1tIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIn0%3D/SNEX23_SSA_1",
         "description": "This data set contains vertical profiles of snow reflectance and specific surface area (SSA) from the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, the Caribou Poker Creek watershed and Farmers Loop/Creamer\u2019s Field), and a coastal tundra environment in the North Slope region of northern Alaska (the Arctic coastal plain and Upper Kuparuk Toolik), collected as part of the NASA SnowEx 2023 field campaign in March 2023. Reflectance was measured in snow pits using three different integrating sphere laser devices: an A2 Photonic Sensor IceCube (1310 nm), an IRIS (InfraRed Integrating Sphere) system (1310 nm), and an InfraSnow SSA sensor (945 nm). Measured reflectance values were converted to SSA during data processing. It is recommended that data users work with either the IceCube or IRIS data, as the InfraSnow data was collected primarily for testing of the instrument\u2019s capabilities. Snow-off SSA data from these same study sites are available as <a href=\"https://nsidc.org/data/snex23_ssa_so/versions/1\">SnowEx23 Laser Snow Microstructure Specific Surface Area Snow-off Data, Version 1</a>.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2881748646-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2881748646-NSIDC_ECS.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIiwidW1tIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIn0%3D/SNEX23_SSA_SO_1",
         "description": "This data set reports vertical profiles of snow reflectance and specific surface area (SSA) from two study sites in Alaska, USA collected as part of the NASA SnowEx 2023 field campaign. The study sites include a boreal forest environment in the Fairbanks region of central Alaska (the Bonanza Creek Experimental Forest, the Caribou Poker Creek watershed and Farmers Loop/Creamer\u2019s Field), and a coastal tundra environment in the North Slope region of northern Alaska (the Arctic coastal plain and Upper Kuparuk Toolik). Reflectance was measured in situ using an A2 Photonic Sensor IceCube (1310 nm). Measured reflectance values were converted to SSA during data processing following the methods of Gallet et al., (2009). Snow-on SSA data from these same study sites were collected in March 2023 and are available as <a href=\"https://nsidc.org/data/snex23_ssa/versions/1\">SnowEx23 Laser Snow Microstructure Specific Surface Area Data, Version 1</a>.",
         "license": "proprietary"
     },
@@ -164341,7 +164627,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3041011983-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3041011983-NSIDC_ECS.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS/collections?cursor=eyJqc29uIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIiwidW1tIjoiW1wic25vd2V4MjMgYWlyYm9ybmUgbGlkYXIgc2NhbnMgcmF3IHYwMDFcIixcIk5TSURDX0VDU1wiLFwiU05FWDIzX0xpZGFyX1Jhd1wiLFwiMVwiLDI4OTM4MzUzMDYsNTFdIn0%3D/SNEX23_SWE_1",
         "description": "This data set presents snow depth, snow water equivalent (SWE), and bulk snow density data collected during the NASA SnowEx 2023 field campaign between March 13-16 2023. Samples were collected using an Adirondack snow sampler (SWE tube) from two study sites: Upper Kuparuk and Toolik (UKT), an arctic tundra environment in Northern Alaska, and Farmers Loop Creamers Field (FLCF), a boreal forest near Fairbanks, Alaska.",
         "license": "proprietary"
     },
@@ -164354,7 +164640,7 @@
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         "description": "The Cross-track Infrared Sounder (CrIS) Level 1B Normal Spectral Resolution (NSR) data files contain radiance measurements along with ancillary spacecraft, instrument, and geolocation data of the CrIS instrument on the Suomi National Polar-orbiting Partnership Project (SNPP). In December 2014, the CrIS instrument on the SNPP satellite doubled the spectral resolution of shortwave infrared data being transmitted to the ground.  In November 2015, additional points were included at the ends of the longwave and shortwave interferograms to improve the quality of the calibration.  Prior to November 2, 2015 the data are only available in Normal Spectral Resolution, after November 2, 2015 at 16:06 UTC, the data are available in both NSR and Full Spectral Resolution (FSR).   The NSR files have 1,317 channels: 163 shortwave channels from 3.9 to 4.7 microns (2555 to 2150 cm-1), 437 midwave channels from 5.7 to 8.05 microns (1752.5 to 1242.5 cm-1), and 717 longwave channels from 9.1 to 15.41 microns (1096.25 to 648.75 cm-1). Each CrIS field-of-regard (FOR) contains 9 field-of-views (FOVs) arranged in a 3X3 array. The Level 1B files contain 30 FORs in the cross track direction and 45 in the along track direction. Data products are constructed on six minute boundaries.  CrIS is designed to be used with the ATMS (Advanced Technology Microwave Sounder) instrument. Processing the data from both of these instruments together is referred to as CrIMSS (Cross-Track Infrared and Microwave Sounder Suite).   If you were redirected to this page from a DOI from an older version, please note this is the current version of the product. Please contact the GES DISC user support if you need information about previous data collections.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1442068517-GES_DISC.html",
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         "description": "The Cross-track Infrared Sounder (CrIS) Level 1B Full Spectral Resolution (FSR) data files contain radiance measurements along with ancillary spacecraft, instrument, and geolocation data of the CrIS instrument on the Suomi National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (SNPP). In December 2014, the CrIS instrument on the SNPP satellite doubled the spectral resolution of shortwave infrared data being transmitted to the ground.  In November 2015, additional points were included at the ends of the longwave and shortwave interferograms to improve the quality of the calibration.  Prior to November 2, 2015 the data are only available in Normal Spectral Resolution (NSR), after November 2, 2015 at 16:06 UTC, the data are available in both NSR and Full Spectral Resolution.   The FSR files have 2,223 channels: 637 shortwave channels from 3.9 to 4.7 microns (2555 to 2150 cm-1), 869 midwave channels from 5.7 to 8.05 microns (1752.5 to 1242.5 cm-1), and 717 longwave channels from 9.1 to 15.41 microns (1096.25 to 648.75 cm-1). Each CrIS field-of-regard (FOR) contains 9 field-of-views (FOVs) arranged in a 3X3 array. The Level 1B files contain 30 FORs in the cross track direction and 45 in the along track direction. Data products are constructed on six minute boundaries.  CrIS is designed to be used with the ATMS (Advanced Technology Microwave Sounder) instrument. Processing the data from both of these instruments together is referred to as CrIMSS (Cross-Track Infrared and Microwave Sounder Suite).  If you were redirected to this page from a DOI from an older version, please note this is the current version of the product. Please contact the GES DISC user support if you need information about previous data collections.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1952167468-GES_DISC.html",
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         "description": "The Cross-track Infrared Sounder (CrIS) Level 1B Full Spectral Resolution (FSR) data files contain radiance measurements along with ancillary spacecraft, instrument, and geolocation data of the CrIS instrument on the Suomi National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (SNPP). In December 2014, the CrIS instrument on the SNPP satellite doubled the spectral resolution of shortwave infrared data being transmitted to the ground.  In November 2015, additional points were included at the ends of the longwave and shortwave interferograms to improve the quality of the calibration.  Prior to November 2, 2015 the data are only available in Normal Spectral Resolution (NSR), after November 2, 2015 at 16:06 UTC, the data are available in both NSR and Full Spectral Resolution.   The FSR files have 2,223 channels: 637 shortwave channels from 3.9 to 4.7 microns (2555 to 2150 cm-1), 869 midwave channels from 5.7 to 8.05 microns (1752.5 to 1242.5 cm-1), and 717 longwave channels from 9.1 to 15.41 microns (1096.25 to 648.75 cm-1). Each CrIS field-of-regard (FOR) contains 9 field-of-views (FOVs) arranged in a 3X3 array. The Level 1B files contain 30 FORs in the cross track direction and 45 in the along track direction. Data products are constructed on six minute boundaries.  CrIS is designed to be used with the ATMS (Advanced Technology Microwave Sounder) instrument. Processing the data from both of these instruments together is referred to as CrIMSS (Cross-Track Infrared and Microwave Sounder Suite).  If you were redirected to this page from a DOI from an older version, please note this is the current version of the product. Please contact the GES DISC user support if you need information about previous data collections.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2278117672-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2278117672-GES_DISC.html",
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         "description": " This dataset includes SNPP VIIRS-CrIS collocation index product, within the framework of the Multidecadal Satellite Record of Water Vapor, Temperature, and Clouds (PI: Eric Fetzer) funded by NASA\u2019s Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program, 2017. The dataset is built upon work by Wang et al. (doi: 10.3390/rs8010076) and Yue (doi:10.5194/amt-15-2099-2022).  The short name for this collections is SNPP_CrIS_VIIRS750m_IND  ",
         "license": "proprietary"
     },
@@ -165056,7 +165342,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2515912673-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2515912673-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of soil organic carbon (SOC) in tidal wetlands for the northeastern United States. The data cover the period 1998-2018. Northeastern U.S. tidal wetlands and bordering areas were harmonized from government agencies [U.S. Department of Agriculture - Natural Resources Conservation Service (USDA-NRCS), National Cooperative Soil Survey (NCSS), USDA-NRCS - Rapid Carbon Assessment (RaCA), U.S. Environmental Protection Agency - National Wetland Condition and Assessment (EPA-NWCA)] and published studies. Point data for carbon stocks (in kg m-2) at four soil depths (0-5, 0-30, 0-100, and 0-200 cm) are included. SOC for the four depths was predicted for eight regional zones using regression models driven by environmental covariates. Two methods were used to estimate parameters for these models, a Random Forest (RF) Ranger method and a Quantile Regression Forest (QRF) model. The distribution of SOC was predicted for tidal wetland cover types mapped by Correll et al. (2019). Predictions and uncertainties are available at a 3 m resolution.",
         "license": "proprietary"
     },
@@ -165069,7 +165355,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517662316-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic3BhdGlvLXRlbXBvcmFsIGNoYXJhY3RlcmlzdGljcyBvZiByYWluZmFsbCBpbiBhZnJpY2EsIDAuMjUgZGVncmVlcywgZnJvbSAxOTk4LTIwMTJcIixcIk9STkxfQ0xPVURcIixcIkFmcmljYW5fUmFpbmZhbGxfUGF0dGVybnNfMTI2M1wiLFwiMVwiLDI3NzY4NzQ4NzMsMl0iLCJ1bW0iOiJbXCJzcGF0aW8tdGVtcG9yYWwgY2hhcmFjdGVyaXN0aWNzIG9mIHJhaW5mYWxsIGluIGFmcmljYSwgMC4yNSBkZWdyZWVzLCBmcm9tIDE5OTgtMjAxMlwiLFwiT1JOTF9DTE9VRFwiLFwiQWZyaWNhbl9SYWluZmFsbF9QYXR0ZXJuc18xMjYzXCIsXCIxXCIsMjc3Njg3NDg3MywyXSJ9/SOC_Stocks_Great_Plains_1603_1",
         "description": "This dataset provides estimates of total organic soil carbon (SOC), pyrogenic (PyC), particulate (POC), and other organic soil carbon (OOC) fractions in 473 surface layer soil samples collected from stratified-sampling locations in Colorado, Kansas, New Mexico, and Wyoming, USA. Terrain, climate, soil, fire, and land cover data used to predict and map SOC, PyC, POC, and OOC at 1 km resolution throughout the study region are also included. The estimates were derived using a best random forest regression model and cover the period 2007-05-01 to 2010-10-01.",
         "license": "proprietary"
     },
@@ -165472,7 +165758,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864144-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864144-ORNL_CLOUD.html",
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         "description": "This data set provides measurements of soil carbon dioxide (CO2) emission rates, soil moisture, relative humidity (RH), temperature, and litterfall from six types of tree plantations at the La Selva Biological Station, Costa Rica. Soil CO2 flux and related measurements were made 1) hourly during 2-day diel field campaigns and 2) as single daytime measurements during multiple survey campaigns, over the period 2004-2010. All measurements were made at the same sites to compare hourly, monthly, and inter-annual variations. Most of the emissions data represent a single soil CO2 flux measurement, with three to five measurements per plot. Litterfall was collected monthly from 2003-2009 and was sorted into fractions prior to drying.",
         "license": "proprietary"
     },
@@ -166031,7 +166317,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1993479683-GES_DISC.html",
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         "description": "The SORCE Combined XPS, SOLSTICE, and SIM Solar Spectral Irradiance 24-Hour Means product consists of daily averages of the solar spetra from 0.1 to 2412 nm. The SORCE instruments make measurements during each daytime orbit portion, 15 orbits per day. This product combines data from the XPS, SOLSTICE and SIM instruments and merges them into a daily averaged solar spectra. The spectral resolution of SIM varies between 1-34 nm, SOLSTICE is 1 nm, and XPS is 7 nm.  The SORCE combined data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date (calendar and Julian Day), min wavelength, max wavelength, instrument mode, input data version, spectral irradiance, irradiance uncertainty, and a data quality flag. Each row represents a separate day and wavelength.",
         "license": "proprietary"
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         "description": "Version 027 is the final version of this data product, and supersedes all previous versions.  The SORCE SIM Solar Spectral Irradiance (SSI) data product SOR3SIMD is constructed using measurements from the SIM instruments, which are combined into merged daily solar spectra over the spectral range from 240 to 2416 nm at a spectral resolution ranging from 1 to 27 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SIM absolute uncertainty is about 2%.  All of the SOR3SIMD data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SIM wavelength range, repeating for each day for the length of the measurement period.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2069458519-GES_DISC.html",
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         "description": "Version 002 is the most recent version of this data product, and supersedes all previous versions.  The SORCE SIM Level 3 TSIS-Adjusted Values Solar Spectral Irradiance 24-Hour Means data product (SOR3SIMD_TAV) uses the temporal overlap of the Solar Radiation and Climate Experiment (SORCE) and the Total and Spectral Solar Irradiance Sensor (TSIS-1) Spectral Irradiance Monitor (SIM) instruments to create an alternate SORCE-SIM irradiance calibration, known as the TSIS1 Adjusted Values (TAV). The SORCE-SIM Solar Spectral Irradiance (SSI) data products are provided on a fixed wavelength scale which varies in spectral resolution from 1-34 nm over the spectral range from 240 to 2401 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The TAV data is on the SORCE-SIM wavelength scale, with the exception that the longest TAV wavelength is 2401.4 nm.  All of the SOR3SIMD_TAV data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SIM wavelength range, repeating for each day for the length of the measurement period.",
         "license": "proprietary"
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         "description": "SORCE SOLSTICE FUV and MUV Level 3 Solar Spectral Irradiance 0.1nm Res 24-Hour Means data product (SOR3SOLD_HIGH) is constructed using measurements from the SOLSTICE FUV and MUV instrument, which is combined into merged daily solar spectra over the spectral range from 115 to 310 nm at a high spectral resolution of 0.1 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SOLSTICE absolute uncertainty better than 5%.  The SOR3SOLD_HIGH data are stored in netCDF files containing a full year of data. Each file contains variables with the date, Julian day, wavelength, irradiance value, irradiance uncertainty, and irradiance repeatability.",
         "license": "proprietary"
     },
@@ -166083,7 +166369,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1993479667-GES_DISC.html",
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         "description": "The SORCE SOLSTICE Level 3 MgII Core to Wing Ratio 24 Hour Means product consists of daily averages of the magnesium II core-to-wing index from the SOLSTICE instrument. The SOLSTICE instrument makes measurements during each daytime orbit portion, 15 orbits per day. This product has solar spectra averaged for a day. The spectral resolution of SOLSTICE is 0.1 nm, allowing the Mg-II doublet to be fully resolved and modeled with Gaussians. The Mg-II core-to-wing ratio is used as a measurement of solar activity.  The Mg-II data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date (calendar and Julian Day), the core/wing ratio, and the absolute uncertainty. The rows are arranged with one daily average measurment, repeating for each day for the length of the measurement period.",
         "license": "proprietary"
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         "description": "Version 018 is the final version of this data product, and supersedes all previous versions.  The SORCE SOLSTICE Far-UV Solar Spectral Irradiance (SSI) data product SOR3SOLFUVD is constructed using measurements from the SOLSTICE FUV instrument, which are combined into merged daily solar spectra over the spectral range from 115 to 180 nm at a spectral resolution of 1 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SOLSTICE absolute uncertainty better than 5%.  All of the SOR3SOLFUVD data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SOLSTICE FUV wavelength range, repeating for each day for the length of the measurement period.",
         "license": "proprietary"
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@@ -166109,7 +166395,7 @@
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         "description": "Version 018 is the final version of this data product, and supersedes all previous versions.  The SORCE SOLSTICE Mid-UV Solar Spectral Irradiance (SSI) data product SOR3SOLMUVD is constructed using measurements from the SOLSTICE MUV instrument, which are combined into merged daily solar spectra over the spectral range from 180 to 310 nm at a spectral resolution of 1 nm. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SOLSTICE absolute uncertainty better than 5%.  All of the SOR3SOLMUVD data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SOLSTICE FUV wavelength range, repeating for each day for the length of the measurement period.",
         "license": "proprietary"
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@@ -166122,7 +166408,7 @@
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         "description": "The SORCE SOLSTICE Level 3 Lyman-alpha Irradiance As-Measured Cadence product consists of all measurements of the Lyman-alpha irradiance from the SOLSTICE instrument. The SOLSTICE instrument makes measurements during each daytime orbit portion, 15 orbits per day. A complete solar spectrum is made in about 30 minutes, a quick scan mode in about 5 minutes. The spectral resolution of SOLSTICE is 0.1 nm.  The Lyman-alpha data are stored in netCDF files containing a full year of. Each days measurements are in a separate netCDF group. Each group contains variables for irradiance, uncertainty, repeatability, long x-ray flux, short x-ray flux, spacecraft height, latitude, longitude, time, wavelength and target zenith angle, with overr 3000 measurements.",
         "license": "proprietary"
     },
@@ -166135,7 +166421,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1993479669-GES_DISC.html",
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         "description": "The SORCE SOLSTICE Level 3 MgII Core to Wing Ratio As-Measured Cadence product consists of all measurements of the magnesium II core-to-wing index from the SOLSTICE instrument. The SOLSTICE instrument makes measurements during each daytime orbit portion, 15 orbits per day. A complete solar spectrum is made in about 30 minutes, a quick scan mode in about 5 minutes. The spectral resolution of SOLSTICE is 0.1 nm, allowing the Mg-II doublet to be fully resolved and modeled with Gaussians. The Mg-II core-to-wing ratio is used as a measurement of solar activity.  The Mg-II data are arranged in a single file in a tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date (calendar and Julian Day), the core/wing ratio, and the absolute uncertainty. The rows are arranged with one daily average measurment, repeating for each day for the length of the measurement period.",
         "license": "proprietary"
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@@ -166148,7 +166434,7 @@
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         "description": "SOR3TSI6 Version 019 is the final version of this data product, and supersedes all previous versions.  The Total Solar Irradiance (TSI) data set SOR3TSI6 contains the total solar irradiance (a.k.a solar constant) data collected by the Total Irradiance Monitor (TIM) instrument covering the full wavelength spectrum averaged at 6-hour intervals. The data are normalized to one astronomical unit (1 AU).  The TIM instrument measures the Total Solar Irradiance (TSI), monitoring changes in incident sunlight to the Earth's atmosphere using an ambient temperature active cavity radiometer to a designed absolute accuracy of 100 parts per million (ppm, 1 ppm=0.0001% at 1-sigma) and a precision and long-term relative accuracy of 10 ppm per year. Due to the small size these data and to maximize ease of use to end-users, each delivered TSI product contains science results for the entire mission. Updates to Level 3 TSI data occur monthly in order to reduce repeated delivery of data.",
         "license": "proprietary"
     },
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         "description": "SOR3TSID Version 019 is the final version of this data product, and supersedes all previous versions.  The Total Solar Irradiance (TSI) data set SOR3TSID contains the total solar irradiance (a.k.a solar constant) data collected by the Total Irradiance Monitor (TIM) instrument covering the full wavelength spectrum averaged at daily intervals. The data are normalized to one astronomical unit (1 AU).  The TIM instrument measures the Total Solar Irradiance (TSI), monitoring changes in incident sunlight to the Earth's atmosphere using an ambient temperature active cavity radiometer to a designed absolute accuracy of 100 parts per million (ppm, 1 ppm=0.0001% at 1-sigma) and a precision and long-term relative accuracy of 10 ppm per year. Due to the small size these data and to maximize ease of use to end-users, each delivered TSI product contains science results for the entire mission. Updates to Level 3 TSI data occur monthly in order to reduce repeated delivery of data.",
         "license": "proprietary"
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         "description": "The SORCE XUV Photometer System (XPS) Solar Spectral Irradiance (SSI) 6-Hour Data Product SOR3XPS6 contains solar extreme ultraviolet irradiances in the 0.1 to 27 nm range, as well as Lyman-alpha, in broad bands (7-10 nm resolution) as listed below:  * Diode  1:   0.1 -   7.0 nm * Diode  2:   0.1 -   7.0 nm * Diode  3:  17.0 -  23.0 nm * Diode  6:   0.1 -  11.0 nm * Diode  7:   0.1 -   7.0 nm * Diode  9:   0.1 -   7.0 nm * Diode 11: 121.0 - 122.0 nm  The data are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The accuracy for the XPS Level 3 irradiance is 12-30%, photometer dependent, and the long-term repeatability is 1% per year. The SOR3XPS6 data are arranged in a single tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, average measurement date, standard deviation of measurement date, diode number, minimum wavelength, maximum wavelength, instrument mode, data version number, median irradiance, mean irradiance, absolute uncertainty, measurement precision, calculation precision, degradation model, degradation version, and number of data points. The rows are arranged with data for each 6 hour time increment, repeating for each diode wavelength.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1684122437-GES_DISC.html",
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         "description": "The SORCE XUV Photometer System (XPS) Solar Spectral Irradiance (SSI) Daily Data Product SOR3XPSD contains solar extreme ultraviolet irradiances in the 0.1 to 27 nm range, as well as Lyman-alpha, in broad bands (7-10 nm resolution) as listed below:  * Diode  1:   0.1 -   7.0 nm * Diode  2:   0.1 -   7.0 nm * Diode  3:  17.0 -  23.0 nm * Diode  6:   0.1 -  11.0 nm * Diode  7:   0.1 -   7.0 nm * Diode  9:   0.1 -   7.0 nm * Diode 11: 121.0 - 122.0 nm  The data are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The accuracy for the XPS Level 3 irradiance is 12-30%, photometer dependent, and the long-term repeatability is 1% per year. The SOR3XPSD data are arranged in a single tabular ASCII text file which can be easily read into a spreadsheet application. The columns contain the date, Julian day, average measurement date, standard deviation of measurement date, diode number, minimum wavelength, maximum wavelength, instrument mode, data version number, median irradiance, mean irradiance, absolute uncertainty, measurement precision, calculation precision, degradation model, degradation version, and number of data points. The rows are arranged with data for each day, repeating for each diode wavelength.",
         "license": "proprietary"
     },
@@ -166200,7 +166486,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1993479675-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1993479675-GES_DISC.html",
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         "description": "The SORCE XPS Level 4 Solar Spectral Irradiance 0.1nm Res 5-Minute product (SOR4XPS5) contains modelled spectral extreme ultraviolet (XUV) irradiances based on calibrated SORCE XUV Photometer System (XPS) data and flare plasma temperature derived from the GOES XRS instrument. The model data are reported in the spectral range from 0-40 nm at a resolution of 0.1 nm about every 5 minutes. The XPS Level 2 data products, along with CHIANTI reference spectra, are used to construct the XPS Level 4 data products.  The SOR4XPS5 data are stored in netCDF files containing one year of data. Data variables stored in each file include: MODELFLUX: Array of solar irradiances [W/m2/nm] in 0.1 nm bins from 0.1 to 39.9 nm ERR_ABS:    Total combined standard uncertainty of the model flux irradiance results (accuracy) ERR_MEAS:   Count-rate based combined standard uncertainty of the XPS-1,-2 measurement (precision) DATE:       Year and day-of-year of observation (YYDDD) TIME:       Seconds of day for middle of observation XPS_QS:     Daily quiet-sun scale factor derived from XPS-1,-2 daily minimum XPS_AR:     Daily active-region scale factor derived from XPS-1,-2 daily minimum XPS_FLARE:  Flare scale factor for each XPS-1,-2 GOES_QS:    Daily quiet-sun scale factor derived from GOES XRS-B daily minimum GOES_AR:    Daily active-region scale factor derived from GOES XRS-B daily minimum GOES_FLARE: Flare scale factor for each GOES XRS-B integration FMTEMP:     Flare model temperature [log10(K)] derived from ratio of GOES XRS-B to XRS-A FMINDEX:    Index into flare model table FMWEIGHT:   Weight parameter for the flare model ",
         "license": "proprietary"
     },
@@ -166213,7 +166499,7 @@
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Shuttle Radar Topography Mission (SRTM), which includes the global 3 arc second (~90 meter) number product.      Ancillary one-byte (0 to 255) \u201cNUM\u201d (number) files were produced for NASA SRTM Version 3. These files have names corresponding to the elevation files, except with the extension \u201c.NUM\u201d (such as N37W105.NUM). The elevation files use the extension \u201c.HGT\u201d, meaning height (such as N37W105.HGT). The separate NUM file indicates the source of each DEM pixel; the number of ASTER scenes used (up to 100), if ASTER; and the number of SRTM data takes (up to 24), if SRTM. The NUM file for both 3 arc second products (whether sampled or averaged) references the 3 x 3 center pixel.  Note that NUMs less than 6 are water and those greater than 10 are land. The 3 arc second data was derived from the 1 arc second using sampling and averaging methods. (See Figure 3 in the User Guide (https://lpdaac.usgs.gov/documents/179/SRTM_User_Guide_V3.pdf).    The NASA SRTM data sets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. This collaboration aims to generate a near-global digital elevation model (DEM) of Earth using radar interferometry. SRTM was the primary (and virtually only) payload on the STS-99 mission of the Space Shuttle Endeavour, which launched February 11, 2000 and \ufb02ew for 11 days.    The SRTM swaths extended from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km), creating swaths ~225 km wide, and consisted of all land between 60\u00b0 N and 56\u00b0 S latitude to account for 80% of Earth\u2019s total landmass.    Improvements/Changes from Previous Versions   * Voids in the Version 3.0 products have been filled with ASTER Global Digital Elevation Model (GDEM) Version 2.0, the Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), and the National Elevation Dataset (NED).  ",
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         "license": "proprietary"
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Shuttle Radar Topography Mission (SRTM), which includes the global 3 arc second (~90 meter) product. The 3 arc second data was derived from the 1 arc second using averaging methods. (See Figure 3 in the User Guide (https://lpdaac.usgs.gov/documents/179/SRTM_User_Guide_V3.pdf).     The NASA SRTM data sets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. This collaboration aims to generate a near-global digital elevation model (DEM) of Earth using radar interferometry. SRTM was the primary (and virtually only) payload on the STS-99 mission of the Space Shuttle Endeavour, which launched February 11, 2000 and \ufb02ew for 11 days.    The SRTMGL3 data were generated from SRTM1GL (https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL1.003) data that fall within that tile. These elevation files use the extension \u201c.HGT\u201d, meaning height (such as N37W105.SRTMGL3.HGT). The primary goal of creating the Version 3 data was to eliminate gaps, or voids, that were present in earlier versions of SRTM data. In areas with limited data, existing topographical data were used to supplement the SRTM data to fill the voids. The source of each elevation pixel is identified in the corresponding SRTMGL3N (https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL3N.003) product (such as N37W105.SRTMGL3N.NUM).    The SRTM swaths extended from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km), creating swaths ~225 km wide, and consisted of all land between 60\u00b0 N and 56\u00b0 S latitude to account for 80% of Earth\u2019s total landmass. ",
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) SRTM, which includes the global 3 arc second (~90 meter) product. The 3 arc second data was derived from the 1 arc second using sampling and averaging methods. SRTMGL3_NC offers the data product in NetCDF.    NASA Shuttle Radar Topography Mission (SRTM) datasets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. The purpose of SRTM was to generate a near-global digital elevation model (DEM) of the Earth using radar interferometry. SRTM was a primary component of the payload on the Space Shuttle Endeavour during its STS-99 mission. Endeavour launched February 11, 2000 and \ufb02ew for 11 days.     SRTM collected data in swaths, which extend from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km). These swaths are ~225 km wide, and consisted of all land between 60\u00b0 North (N) and 56\u00b0 South (S) latitude. This accounts for about 80% of Earth\u2019s total landmass.    Improvements/Changes from Previous Versions   * Voids in the Version 3.0 products have been filled with ASTER Global Digital Elevation Model (GDEM) Version 2.0, the Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), and the National Elevation Dataset (NED).  ",
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Shuttle Radar Topography Mission (SRTM), which includes the global 1 arc second (~30 meter) combined (merged) image data product. (See User Guide (https://lpdaac.usgs.gov/documents/179/SRTM_User_Guide_V3.pdf) Section 2.2.2.)  The combined image data set contains mosaicked one degree by one degree images/tiles of uncalibrated radar brightness values at 1 arc second. To create a smooth mosaic image, each pixel in an output is an average of all the image pixels for a location. Pixels with a value of zero (voids) were not counted. Because SRTM imaged a given location with two like-polarization channels (VV = vertical transmit and vertical receive, and HH = horizontal transmit and horizontal receive) and at a variety of look and azimuth angles, the quantitative scattering information was lost in the pursuit of a smoother image product unlike the SRTM swath image product SRTMIMGR (https://doi.org/10.5067/MEaSUREs/SRTM/SRTMIMGR.003), which preserved the quantitative scattering information.  The NASA SRTM data sets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. This collaboration aims to generate a near-global digital elevation model (DEM) of Earth using radar interferometry. SRTM was the primary (and virtually only) payload on the STS-99 mission of the Space Shuttle Endeavour, which launched February 11, 2000 and \ufb02ew for 11 days.  The SRTM swaths extended from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km), creating swaths ~225 km wide, and consisted of all land between 60\u00b0 N and 56\u00b0 S latitude to account for 80% of Earth\u2019s total landmass.   Improvements/Changes from Previous Versions  * Voids in the Version 3.0 products have been filled with ASTER Global Digital Elevation Model (GDEM) Version 2.0, the Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), and the National Elevation Dataset (NED).",
         "license": "proprietary"
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments ([MEaSUREs](https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects)) Shuttle Radar Topography Mission (SRTM), which includes the global 1 arc second (~30 meter) swath (raw) image data product. (See [User Guide](https://lpdaac.usgs.gov/documents/179/SRTM_User_Guide_V3.pdf) Section 2.2.1)  The SRTM swath image data set consists of radar image files containing brightness values, as well as quality assurance (incidence angle) files for each of four overlapping sub-swaths that passes through a 1 degree by 1 degree tile.  Data from each sub-swath is included as a separate file. Some files may contain only partial data; however, every image pixel acquired by SRTM is included in this data set.  The NASA SRTM data sets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the National Geospatial-Intelligence Agency (NGA - previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. This collaboration aims to generate a near-global digital elevation model (DEM) of Earth using radar interferometry. SRTM was the primary (and virtually only) payload on the STS-99 mission of the Space Shuttle Endeavour, which launched February 11, 2000 and \ufb02ew for 11 days.  The SRTM swaths extended from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km), creating swaths ~225 km wide, and consisted of all land between 60\u00b0 N and 56\u00b0 S latitude to account for 80% of Earth\u2019s total landmass.    Improvements/Changes from Previous Versions  * Voids in the Version 3.0 products have been filled with ASTER Global Digital Elevation Model (GDEM) Version 2.0, the Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), and the National Elevation Dataset (NED).",
         "license": "proprietary"
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         "description": "The Land Processes Distributed Active Archive Center (LP DAAC) is responsible for the archive and distribution of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs)(https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Shuttle Radar Topography Mission (SRTM), which includes the Water Body Data Shapefiles and Raster Files (~30 m) product. Version 3.0 contains the vectorized coastline masks used by National Geospatial-Intelligence Agency (NGA) in the editing, called the SRTM Waterbody Data (SWBD), in shapefile and rasterized formats.  The NASA SRTM data sets result from a collaborative effort by the National Aeronautics and Space Administration (NASA) and the NGA (previously known as the National Imagery and Mapping Agency, or NIMA), as well as the participation of the German and Italian space agencies. This collaboration aims to generate a near-global digital elevation model (DEM) of Earth using radar interferometry. SRTM was the primary (and virtually only) payload on the STS-99 mission of the Space Shuttle Endeavour, which launched February 11, 2000 and \ufb02ew for 11 days.  The SRTM swaths extended from ~30 degrees off-nadir to ~58 degrees off-nadir from an altitude of 233 kilometers (km), creating swaths ~225 km wide, and consisted of all land between 60\u00b0 N and 56\u00b0 S latitude to account for 80% of Earth\u2019s total landmass. ",
         "license": "proprietary"
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         "description": "The Shuttle Solar Backscatter Ultraviolet (SSBUV) level-2 irradiance data are available for eight space shuttle missions flown between 1989 and 1996. SSBUV, a successor to the SBUV flown on the Nimbus-7 satellite, is nearly identical to the SBUV/2 instruments flown on the NOAA polar orbiting satellites. Data are available in an ASCII text format. UV irradiance data are available for the following days from the eight missions:  Flight #1: 1989 October 19, 20, 21 Flight #2: 1990 October 7, 8, 9 Flight #3: 1991 August 3, 4, 5, 6 Flight #4: 1992 March 29, 30 Flight #5: 1993 April 9, 11, 13, 15, 16 Flight #6: 1994 March 14, 15, 17 Flight #7: 1994 November 5, 7, 10, 13 Flight #8: 1996 January 12, 16, 18  The Shuttle SBUV (SSBUV) instrument measured solar spectral UV irradiance during the maximum and declining phase of solar cycle 22. The SSBUV data accurately represent the absolute solar UV irradiance between 200-405 nm, and also show the long-term variations during eight flights between October 1989 and January 1996. These data have been used to correct long-term sensitivity changes in the NOAA-11 SBUV/2 data, which provide a near-daily record of solar UV variations over the 170-400 nm region between December 1988 and October 1994. These data demonstrate the evolution of short-term solar UV activity during solar cycle 22.",
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         "description": "The Shuttle Solar Backscatter Ultraviolet (SSBUV) Level-2 Ozone data are available for eight space shuttle missions flown between 1989 and 1996. SSBUV, a successor to the SBUV flown on the Nimbus-7 satellite, is nearly identical to the SBUV/2 instruments flying on the NOAA satellites. Data are available in the ASCII AMES text format. Ozone profiles of the upper atmosphere and total column ozone values are available for the following time periods:  Flight #1:  1989 October 19, 20, 21. Flight #2:  1990 October 7, 8, 9. Flight #3:  1991 August 3, 4, 5, 6. Flight #4:  1992 March 29, 31. Flight #5:  1993 April 9, 11, 13, 15, 16. Flight #6:  1994 March 14, 15, 17. Flight #7:  1994 November 5, 7, 10, 13. Flight #8:  1996 January 12, 16, 18.  SSBUV measures spectral ultraviolet radiances backscattered by the earth's atmosphere. For the ozone measurements the instrument steps over wavelengths between 252.2 and 339.99 nm while viewing the earth in the nadir position (50 km x 50 km footprint at nadir) at 19 pressure levels between 0.3 mb and 100 mb.",
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         "description": "The Solar Spectral Flux Radiometer (SSFR) was deployed on the University of Washington CV-580 during the dry season component of the Southern African Regional Science Initiative, August 1 - September 20, 2000. The SSFR made simultaneous measurements of both downwelling and upwelling net solar spectral irradiance at varying flight levels.  Data have been provided for twenty flights in netcdf format for the period August 17 - September 16, 2000.For a complete detailed guide to the extensive measurements obtained aboard the UW Convair-580 aircraft in support of SAFARI 2000, see the UW Technical Report for the SAFARI 2000 Project.",
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         "description": "The SeaWiFS Deep Blue Level 3 monthly product contains monthly global gridded (0.5 x 0.5 deg) Version 4 data derived from SeaWiFS Deep Blue Level 3 daily gridded data at the same spatial resolution.    The primary data parameters are aerosol optical thickness, and Angstrom exponent.",
         "license": "proprietary"
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         "description": "This SeaWiFS Deep Blue Level 3 monthly product contains monthly global gridded (1 x 1 deg) data derived from SeaWiFS Deep Blue Level 3 daily gridded data at the same resolution.    The primary data parameters are aerosol optical thickness, and Angstrom exponent.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1239900191-GES_DISC.html",
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         "description": "The SeaWiFS Deep Blue Level 3 monthly climatology product contains monthly global climatology gridded (0.5 x 0.5 deg) data derived from SeaWiFS Deep Blue Level 3 monthly gridded data.    The primary data parameters are aerosol optical thickness.",
         "license": "proprietary"
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         "description": "The SeaWiFS Deep Blue Level 3 Monthly Climatology Product contains monthly global climatology gridded (1 x 1 deg) data derived from SeaWiFS Deep Blue Level 3 monthly gridded data.    The primary data parameters are aerosol optical thickness.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2756239079-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2756239079-ORNL_CLOUD.html",
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         "description": "This data set provides an estimate of the spatial and temporal extent of surface water at 250-m resolution over nine years (2003-2011) for the African Sahel region (10-20 degrees N) using imagery from the Moderate-resolution Imaging Spectroradiometer (MODIS). Water bodies were identified by a spectral analysis of MODIS vegetation indices with the aim to improve existing regional to global mapping products. This data set can be used to enhance the understanding of Earth system processes, and to support global change studies, agricultural planning, and disease prevention. These data provide a gridded (250-m) estimate of the number of years (during 2003-2011) that a pixel was covered by water. The data are presented in a single netCDF (*.nc) file.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2905454214-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2905454214-ORNL_CLOUD.html",
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         "description": "This dataset provides a comparison of forest extent agreement from seven remote sensing-based products across Mexico. These satellite-derived products include European Space Agency 2020 Land Cover Map for Mexico (ESA), Globeland30 2020 (Globeland30), Commission for Environmental Cooperation 2015 Land Cover Map (CEC), Impact Observatory 2020 Land Cover Map (IO), NAIP Trained Mean Percent Cover Map (NEX-TC), Global Land Analysis and Discovery Global 2010 Tree Cover (Hansen-TC), and Global Forest Cover Change Tree Cover 30 m Global (GFCC-TC). All products included data at 10-30 m resolution and represented the state of forest or tree cover from 2010 to 2020. These seven products were chosen based on: a) feedback from end-users in Mexico; b) availability and FAIR (findable, accessible, interoperable, and replicable) data principles; and c) products representing different methodological approaches from global to regional scales. The combined agreement map documents forest cover for each satellite-derived product at 30-m resolution across Mexico. The data are in cloud optimized GeoTIFF format and cover the period 2010-2020. A shapefile is included that outlines Mexico mainland areas.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2787710838-ORNL_CLOUD.html",
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         "description": "This dataset provides allometrically-estimated carbon stocks of 9,947,310,221 tree crowns derived from 50-cm resolution satellite images within the 0 to 1000 mm/year precipitation zone of Africa north of the equator and south of the Sahara Desert. These data are presented in GeoPackage (*.gpkg) format and are summarized in Cloud-Optimized GeoTIFF (COG) format. An interactive viewer application developed to display these carbon estimates at the individual tree level across the study area is available at: https://trees.pgc.umn.edu/app. The analysis utilized 326,523 Maxar multispectral satellite images collected between 2002 to 2021 for the early dry season months of November to March to identify tree crowns. Metadata from satellite image processing across the study area are presented in Shapefile (*.shp) format. Additionally, field measurements from destructive harvests used to derive allometry equations are contained in comma-separated values (*.csv) files. These data demonstrate a new tool for studying discrete semi-arid carbon stocks at the tree level with immediate applications provided by the viewer application. Uncertainty of carbon estimates are +/- 19.8%.",
         "license": "proprietary"
     },
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         "description": "This data set provides two landcover and vegetation maps for the Seward Peninsula, Alaska. These maps were produced from existing maps, Landsat imagery, and color infrared aerial photography covering the period 1976-06-01 to 1999-09-01.",
         "license": "proprietary"
     },
@@ -171322,7 +171608,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2162131297-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2162131297-ORNL_CLOUD.html",
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         "description": "This dataset contains estimates for aboveground shrub biomass and uncertainty at high spatial resolution (0.80-m) across three research areas near Toolik Lake, Alaska. The estimates for August of 2013 were generated and mapped using Random Forest modeling with input variables of optimized LiDAR-derived canopy volume and height, mean NDVI from 4-band RGB color and near-IR orthophotographs, and harvested biomass data. Uncertainty in the final shrub biomass maps was quantified by producing separate maps showing the coefficient of variation (CV) of the Random Forest map estimates. Shrub biomass was harvested at Toolik Lake in 2014 and used to optimize inputs and validate the final model and these biomass data are also provided.",
         "license": "proprietary"
     },
@@ -171335,7 +171621,7 @@
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         "description": "The Simple Biosphere Model, Version 3 (SiB3) was used to produce a global data set of hourly carbon fluxes between the atmosphere and the terrestrial biosphere for the years 1998-2006. This data set represents the global net ecosystem exchange (NEE) of carbon between the atmosphere and the terrestrial biosphere; specifically, the flux of CO2 between the planetary boundary layer (PBL) and the surface vegetation layer. Following atmospheric convention, flux is defined as positive into the atmosphere and negative into the surface vegetation.The data reported are 9 years of estimated hourly carbon flux for 14637 land points. Units are moles C/m2/sec.Data are provided in two NetCDF formats: The NetCDF format provided by the investigators -- format designed specifically to minimize disk storage volume that excludes water grid cells, and  A CF Compliant NetCDF format -- generated by the ORNL DAAC that includes both land and water grid cells.The investigator provided NetCDF formatted files can be processed using the provided  FORTRAN code (sib_process_flux.f90) and the land mask (sib_mask.nc) into hourly, daily-mean, or monthly-mean fluxes on a global 1x1 degree Cartesian grid. The monthly-mean SiB3 fluxes were compared to TransCom flux data available for years 2000-2005 (Gurney et al., 2008) as a means of evaluating overall behavior of the model. In general, SiB3 fluxes are within the error bars of the TransCom results.The CF compliant NetCDF format files have been processed by the ORNL DAAC and the hourly and summarized daily-mean and monthly-mean flux data files are provided. GeoTIFF format files:In addition, the CF convention NetCDF files were converted to GeoTIFF image files by the ORNL DAAC and are included with the data set. Companion file:Additional information about the data formats, methodology, and data quality is found in the companion file: SiB3_carbon_flux_readme.pdfAccess to GeoTIFF format files via WCS Interface:The ORNL DAAC also provides access to the GeoTIFF files via a Web Coverage Service Interface (WCS). The OpenGIS Web Coverage Service Interface Standard (WCS) defines a standard interface and operations that enables interoperable access to geospatial coverages.These data are a carbon cycle reanalysis, which may be thought of as analogous to NCEP meteorological reanalysis products. Carbon fluxes have been used by a large community of atmospheric transport modelers to create reanalysis of CO2 concentrations and the results have been evaluated against observations. In addition, the reanalyzed flux and CO2 fields are important for designing future observing strategies for the global carbon cycle.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2390248773-ORNL_CLOUD.html",
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         "description": "This dataset provides global daily output predicted by the Simple Biosphere Model, Version 4.2 (SiB4), at a 0.5-degree spatial resolution covering the time period 2000 through 2018. SiB4 is a mechanistic land surface model that integrates heterogeneous land cover, environmentally responsive phenology, dynamic carbon allocation, and cascading carbon pools from live biomass to surface litter to soil organic matter. Daily output includes carbon, carbonyl sulfide, and energy fluxes; solar-induced fluorescence; carbon pools; soil moisture and temperatures in the top three layers; total column soil water and plant available water; and environmental potentials used to scale photosynthesis. The SiB4 output is per plant functional type (PFT) within each 0.5-degree grid cell. SiB4 partitions variable output to 15 PFTs in each grid cell that are indexed by the \"npft\" dimension (01-15) in each data file. The PFT three-character abbreviations (\"pft_names\" variable) are listed in the same order as the \"npft\" dimension. To combine the PFT-specific output into grid cell totals, users must compute the area-weighted mean across the vector of PFT-specific values for each cell. Fractional areal coverages are given in the \"pft_area\" variable for each cell.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2392085682-ORNL_CLOUD.html",
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         "description": "This dataset provides global hourly output predicted from the Simple Biosphere Model, Version 4.2 (SiB4), at a 0.5-degree spatial resolution covering the time period 2000 through 2018. SiB4 is a mechanistic land surface model that integrates heterogeneous land cover, environmentally responsive phenology, dynamic carbon allocation, and cascading carbon pools from live biomass to surface litter to soil organic matter. Hourly output includes carbon fluxes, carbonyl sulfide (COS) fluxes, gross primary production, ecosystem respiration, solar-induced fluorescence (SIF), top-layer soil temperature and moisture, vegetation stress, photosynthetically active radiation (PAR), leaf and canopy-level carbon-dioxide partial pressures, and canopy conductance. The SiB4 output is per plant functional type (PFT) within each 0.5-degree grid cell. SiB4 partitions variable output to 15 PFTs in each grid cell that are indexed by the \"npft\" dimension (01-15) in each data file. The PFT three-character abbreviations (\"pft_names\" variable) are listed in the same order as the \"npft\" dimension. To combine the PFT-specific output into grid cell totals, users must compute the area-weighted mean across the vector of PFT-specific values for each cell. Fractional areal coverages are given in the \"pft_area\" variable for each cell.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345882961-ORNL_CLOUD.html",
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         "description": "This dataset provides global monthly output predicted by the Simple Biosphere Model, Version 4.2 (SiB4), at a 0.5-degree spatial resolution covering the time period 2000 through 2018. SiB4 is a mechanistic land surface model that integrates heterogeneous land cover, environmentally responsive phenology, dynamic carbon allocation, and cascading carbon pools from live biomass to surface litter to soil organic matter. Monthly output includes carbon, carbonyl sulfide (COS), and energy fluxes; solar-induced fluorescence (SIF); carbon pools; soil moisture and temperatures in the top three layers; total column soil water and plant available water; and environmental potentials used to scale photosynthesis. The SiB4 output is per plant functional type (PFT) within each 0.5-degree grid cell. SiB4 partitions variable output to 15 PFTs in each grid cell that are indexed by the \"npft\" dimension (01-15) in each data file. The PFT three-character abbreviations (\"pft_names\" variable) are listed in the same order as the \"npft\" dimension. To combine the PFT-specific output into grid cell totals, users must compute the area-weighted mean across the vector of PFT-specific values for each cell. Fractional areal coverages are given in the \"pft_area\" variable for each cell.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773255198-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773255198-ORNL_CLOUD.html",
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         "description": "This data set provides 30-meter resolution mapped estimates of Cajander larch (Larix cajanderi) aboveground biomass (AGB), circa 2007, and a map of burn perimeters for 116 forest fires that occurred from 1966-2007. The data cover ~100,000 km2 of the Kolyma River Basin in northeastern Siberia, Sakha Republic, Russia.",
         "license": "proprietary"
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         "description": "This data set provides mapped estimates of the stand age of young (less than 25 years old) larch forests across Siberia from 1989-2012 at 30-m resolution. The age estimates were derived from Landsat-based composites and tree cover for years 2000 and 2012 developed by the Global Forest Change (GFC) project and the stand-replacing fire mapping (SRFM) data set. This approach is based on the assumption that the relationship between the spectral signature of a burned or unburned forest stand acquired by Landsat ETM+ and TM sensors and stand age before and after the year 2000 is similar, thus allowing for training an algorithm on the data from the post-2000 era and applying the algorithm to infer stand age for the pre-2000 era. The output map combines the modeled forest disturbances before 2000 and direct observations of forest loss after 2000 to deliver a 24-year stand age distribution map.",
         "license": "proprietary"
     },
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         "description": "This dataset includes data from late-March snow surveys and hourly digital camera images from two study areas within the Wrangell St Elias National Park, Alaska. These data comprise snow density, stratigraphy, and temperature profiles obtained by snow pits; and snow depth data obtained from transects between snow pits. Daily snow depths, adjacent to each pit, were derived from hourly camera images of snow stakes placed adjacent to each pit. These data were collected to constrain and validate a physically-based, spatially-distributed snow evolution model used to simulate snow conditions in Dall sheep habitat. The two study areas are both located within the Jacksina Park Unit (JPU). The first study area, surveyed in 2017, included the northern end of Jaeger Mesa and an area near Rambler mine in the North East of the JPU. The second study area, surveyed in 2018, was within the upper watershed of Pass Creek in the North of the JPU. The remote cameras operated from September 2016 to August 2017 on Jaeger Mesa/Rambler Mine and from September 2017 to July 2018 at Pass Creek.",
         "license": "proprietary"
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@@ -171504,7 +171790,7 @@
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         "description": "This dataset contains three field seasons of snow-wildlife observations conducted at 707 sites from January 2021 to March 2023 in Washington and Alaska, spanning a broad range of snow conditions. Relatively fresh tracks (usually <24 h) of common large mammal predators (bobcats, coyotes, cougars, and wolves) and their ungulate prey (caribou, Dall sheep, moose, mule deer, and white-tailed deer) were investigated to determine how snow affects predator-prey interactions. The track sink depth and dimensions (width and length) of three consecutive footprints were measured from one individual. Age class was recorded for moose based either on visual confirmation of an individual creating snow tracks or based on track dimensions. The ability to differentiate age classes for smaller ungulates was more uncertain, so age classes for deer, caribou, or sheep were not specified. Animal gait was identified using a simple classification scheme. Data also include animal species, snow density, hardness, total ice, surface temperature, and vegetation type. To best capture snow hardness, surface penetrability and hand-hardness were measured throughout the snowpack. The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
@@ -171517,7 +171803,7 @@
         "bbox": "-180, 10, 0, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764725108-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764725108-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic25mIGZvcmVzdCB1bmRlcnN0b3J5IGNvdmVyIGRhdGFcIixcIk9STkxfQ0xPVURcIixcIlNORl9VTkRfQ1ZSXzE4MVwiLFwiMVwiLDI4ODQ5ODI4NDgsMl0iLCJ1bW0iOiJbXCJzbmYgZm9yZXN0IHVuZGVyc3RvcnkgY292ZXIgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwiU05GX1VORF9DVlJfMTgxXCIsXCIxXCIsMjg4NDk4Mjg0OCwyXSJ9/Snowmelt_timing_maps_V2_1712_2",
         "description": "This data set provides snowmelt timing maps (STMs), cloud interference maps, and a map with the count of calculated snowmelt timing values for North America. The STMs are based on the Moderate Resolution Imaging Spectroradiometer (MODIS) standard 8-day composite snow-cover product MOD10A2 collection 6 for the period 2001-01-01 to 2018-12-31. The STMs were created by conducting a time-series analysis of the MOD10A2 snow maps to identify the DOY of snowmelt on a per-pixel basis. Snowmelt timing (no-snow) was defined as a snow-free reading following two consecutive snow-present readings for a given 500-m pixel. The count of STM values is also reported, which represents the number of years on record in the STMs from 2001-2018.",
         "license": "proprietary"
     },
@@ -171543,7 +171829,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2345796019-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2345796019-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiZ2xvYmFsIGZvcmVzdCBlY29zeXN0ZW0gc3RydWN0dXJlIGFuZCBmdW5jdGlvbiBkYXRhIGZvciBjYXJib24gYmFsYW5jZSByZXNlYXJjaFwiLFwiT1JOTF9DTE9VRFwiLFwiZm9yZXN0X2NhcmJvbl9mbHV4Xzk0OVwiLFwiMVwiLDI3ODQ4OTA5MjcsMl0iLCJ1bW0iOiJbXCJnbG9iYWwgZm9yZXN0IGVjb3N5c3RlbSBzdHJ1Y3R1cmUgYW5kIGZ1bmN0aW9uIGRhdGEgZm9yIGNhcmJvbiBiYWxhbmNlIHJlc2VhcmNoXCIsXCJPUk5MX0NMT1VEXCIsXCJmb3Jlc3RfY2FyYm9uX2ZsdXhfOTQ5XCIsXCIxXCIsMjc4NDg5MDkyNywyXSJ9/SoilResp_HeterotrophicResp_1928_1",
         "description": "This dataset provides global gridded estimates of annual soil respiration (Rs) and soil heterotrophic respiration (Rh) and associated uncertainties at 1 km resolution. Mean soil respiration was estimated using a quantile regression forest model utilizing data from the global Soil Respiration Database Version 5 (SRDB-V5) and covariates of mean annual temperature, seasonal precipitation, and vegetative cover. The SRDB holds results of field studies of soil respiration from around the globe. A total of 4,115 records from 1,036 studies were selected from SRDB-V5. SRDB-V5 features more soil respiration data published in Russian and Chinese scientific literature for better global spatio-temporal coverage and improved global climate-space representation. These soil respiration records were combined with global meteorological, land cover, and topographic data and then evaluated with variable selection using random forests. The standard deviation and coefficient of variation of Rs are included and were also derived from the same model. Global heterotrophic respiration was calculated from Rs estimates. The data are produced in part from SRDB-V5 inputs that cover the period 1961-2016.",
         "license": "proprietary"
     },
@@ -171556,7 +171842,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736724942-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736724942-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic29pbCBtYXRyaWMgcG90ZW50aWFsLCBkaWVsZWN0cmljLCBhbmQgcGh5c2ljYWwgcHJvcGVydGllcywgYXJjdGljIGFsYXNrYSwgMjAxOFwiLFwiT1JOTF9DTE9VRFwiLFwiQXJjdGljX1NvaWxfUHJvcGVydGllc18yMTQ5XCIsXCIxXCIsMjczMjU5Mjc2NSwzXSIsInVtbSI6IltcInNvaWwgbWF0cmljIHBvdGVudGlhbCwgZGllbGVjdHJpYywgYW5kIHBoeXNpY2FsIHByb3BlcnRpZXMsIGFyY3RpYyBhbGFza2EsIDIwMThcIixcIk9STkxfQ0xPVURcIixcIkFyY3RpY19Tb2lsX1Byb3BlcnRpZXNfMjE0OVwiLFwiMVwiLDI3MzI1OTI3NjUsM10ifQ%3D%3D/SoilSCAPE_1339_1",
         "description": "This data set contains in-situ soil moisture profile and soil temperature data collected at 20-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and oPtimal Estimator) project sites in four states (California, Arizona, Oklahoma, and Michigan) in the United States. SoilSCAPE used wireless sensor technology to acquire high temporal resolution soil moisture and temperature data at up to 12 sites over varying durations since August 2011. At its maximum, the network consisted of over 200 wireless sensor installations (nodes), with a range of 6 to 27 nodes per site. The soil moisture sensors (EC-5 and 5-TM from Decagon Devices) were installed at three to four depths, nominally at 5, 20, and 50 cm below the surface. Soil conditions (e.g., hard soil or rocks) may have limited sensor placement. Temperature sensors were installed at 5 cm depth at six of the sites. Data collection started in August 2011 and continues at eight sites through the present. The data enables estimation of local-scale soil moisture at high temporal resolution and validation of remote sensing estimates of soil moisture at regional (airborne, e.g. NASA's Airborne Microwave Observation of Subcanopy and Subsurface Mission - AirMOSS) and national (spaceborne, e.g. NASA's Soil Moisture Active Passive - SMAP) scales.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2736725173-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736725173-ORNL_CLOUD.html",
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         "description": "This dataset contains in-situ soil moisture profile and soil temperature data collected at 30-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and oPtimal Estimator) project sites since 2021 in the United States and New Zealand. The SoilSCAPE network has used wireless sensor technology to acquire high temporal resolution soil moisture and temperature data over varying durations since 2011. Since 2021, the SoilSCAPE has upgraded the two previously active sites in Arizona and added several new sites in the United States and New Zealand. These new sites typically use the METER Teros-12 soil moisture sensor. At its maximum, the new network consisted of 57 wireless sensor installations (nodes), with a range of 6 to 8 nodes per site. Each SoilSCAPE site contains multiple wireless end-devices (EDs). Each ED supports up to five soil moisture probes typically installed at 5, 10, 20, and 30 cm below the surface. Sites in Arizona have soil moisture probes installed at up to 75 cm below the surface. Soil conditions (e.g., hard soil or rocks) may have limited sensor placement. The data enables estimation of local-scale soil moisture at high temporal resolution and validation of remote sensing estimates of soil moisture at regional and national (e.g. NASA's Cyclone Global Navigation Satellite System - CYGNSS and Soil Moisture Active Passive - SMAP) scales. The data are provided in NetCDF format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2143812328-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2143812328-ORNL_CLOUD.html",
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         "description": "This dataset provides gridded estimates of soil CO2 flux (g C m-2 d-1) for the winter non-growing season (NGS) across pan-Arctic and Boreal permafrost regions (>49 Deg N), at 25 km spatial resolution. The data are the daily average flux over a monthly period for two climate periods: the baseline climate period represents 2003-2018 and the future climate scenarios period represents 2018-2100 under Representative Concentration Pathways (RCP) 4.5 and 8.5. The data were produced by applying a Boosted Regression Tree machine learning approach to create gridded estimates of emissions based on in situ observations of NGS fluxes provided in a related dataset. The resulting monthly average flux data records can be used to calculate annual NGS soil CO2 flux budgets from 2003-2100.",
         "license": "proprietary"
     },
@@ -171608,7 +171894,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2633820284-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2633820284-ORNL_CLOUD.html",
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         "description": "This dataset includes hourly in-situ soil moisture measurements from data loggers in predominantly organic soils (very low bulk density) at two locations: 1) along the Sag River in Alaska, U.S., and 2) near Red Earth Creek in Alberta, Canada. The dataset also provides soil moisture probe periods, temperature probe readings, as well as calibration coefficients and soil profile measurements used to create per probe calibrations for derived volumetric moisture content. The Campbell Scientific CR200 data loggers used CS625 water content reflectometers and temperature probe 109. Further details to the derivation of the calibrations are provided in a supplementary document. The purpose of the dataset is to provide field measurements that can be used for calibration/validation for satellite-based soil moisture retrieval algorithms. With some interruptions, the dataset exists from July 2017 to July 2021. The data are provided in comma-separated values (CSV) format.",
         "license": "proprietary"
     },
@@ -171660,7 +171946,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389021440-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389021440-ORNL_CLOUD.html",
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         "description": "This data set provides estimates of above-ground woody biomass and uncertainty at 30-m spatial resolution for Sonoma County, California, USA, for the nominal year 2013. Biomass estimates, megagrams of biomass per hectare (Mg/ha), were generated using a combination of airborne LiDAR data and field plot measurements with a parametric modeling approach. The relationship between field estimated and airborne LiDAR estimated aboveground biomass density is represented as a parametric model that predicts biomass as a function of canopy cover and 50th percentile and 90th percentile LiDAR heights at a 30-m resolution. To estimate uncertainty, the biomass model was re-fit 1,000 times through a sampling of the variance-covariance matrix of the fitted parametric model. This produced 1,000 estimates of biomass per pixel. The 5th and 95th percentiles, and the standard deviation of these pixel biomass estimates, were calculated.",
         "license": "proprietary"
     },
@@ -172128,7 +172414,7 @@
         "bbox": "-180, -90, 180, 90",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1704861146-GES_DISC.html",
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         "description": "TCTE3TSI6 Version 004 is the final version of this data product, and supersedes all previous versions.  The Total Solar Irradiance (TSI) Calibration Transfer Experiment (TCTE) data set TCTE3TSI6 contains 6-hour averaged total solar irradiance (a.k.a solar constant) data collected by the Total Irradiance Monitor (TIM) instrument covering the full wavelength spectrum. The data are normalized to one astronomical unit (1 AU).  The TCTE/TIM instrument measures the Total Solar Irradiance (TSI), monitoring changes in incident sunlight to the Earth's atmosphere using an ambient temperature active cavity radiometer to a designed absolute accuracy of 350 parts per million (ppm, 1 ppm=0.0001% at 1-sigma), and a precision and long-term relative accuracy of 10 ppm per year. Due to the small size of these data and to maximize ease of use to end-users, each delivered TSI product contains science results for the entire mission in an ASCII column formatted file.  Early in the mission, between Dec 2013 and May 2014, TCTE acquired daily measurements to establish good overlap with the SORCE TIM. From May 2014 to Dec 2014, the TCTE measurements were reduced to weekly, which greatly subsample the true solar variability, and thus have little value for solar research. Beginning in Jan 2015, daily obervations were resumed. The mission ended June 30, 2019. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1704861169-GES_DISC.html",
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         "description": "TCTE3TSID Version 004 is the final version of this data product, and supersedes all previous versions.  The Total Solar Irradiance (TSI) Calibration Transfer Experiment (TCTE) data set TCTE3TSID contains daily averaged total solar irradiance (a.k.a solar constant) data collected by the Total Irradiance Monitor (TIM) instrument covering the full wavelength spectrum. The data are normalized to one astronomical unit (1 AU).  The TCTE/TIM instrument measures the Total Solar Irradiance (TSI), monitoring changes in incident sunlight to the Earth's atmosphere using an ambient temperature active cavity radiometer to a designed absolute accuracy of 350 parts per million (ppm, 1 ppm=0.0001% at 1-sigma), and a precision and long-term relative accuracy of 10 ppm per year. Due to the small size of these data and to maximize ease of use to end-users, each delivered TSI product contains science results for the entire mission in an ASCII column formatted file.  Early in the mission, between Dec 2013 and May 2014, TCTE acquired daily measurements to establish good overlap with the SORCE TIM. From May 2014 to Dec 2014, the TCTE measurements were reduced to weekly, which greatly subsample the true solar variability, and thus have little value for solar research. Beginning in Jan 2015, daily obervations were resumed. The mission ended June 30, 2019. ",
         "license": "proprietary"
     },
@@ -172479,7 +172765,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2930727817-LARC_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2930727817-LARC_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/TEMPO_CLDO4_L3_V03",
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         "description": "O2-O2 cloud Level 3 files provide cloud information on a regular grid covering the TEMPO field of regard for nominal TEMPO observations. Level 3 files are derived by combining information from all Level 2 files constituting a TEMPO East-West scan cycle. The files are provided in netCDF4 format, and contain information on effective cloud fraction, cloud optical centroid pressure, and ancillary data. The re-gridding algorithm uses an area-weighted approach.",
         "license": "proprietary"
     },
@@ -172531,7 +172817,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2930761273-LARC_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2930761273-LARC_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/LARC_CLOUD/collections/TEMPO_HCHO_L3_V03",
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         "description": "Formaldehyde Level 3 files provide trace gas information on a regular grid covering the TEMPO field of regard for nominal TEMPO observations. Level 3 files are derived by combining information from all Level 2 files constituting a TEMPO East-West scan cycle. The files are provided in netCDF4 format, and contain information on formaldehyde vertical columns, ancillary data used in air mass factor calculations and reference sector or de-striping corrections, and retrieval quality flags. The re-gridding algorithm uses an area-weighted approach.",
         "license": "proprietary"
     },
@@ -172544,7 +172830,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2842851180-LARC_CLOUD.html",
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         "description": "Level 1 reference irradiance files provide solar irradiance measured using the reference solar diffuser. Each file includes the measured solar irradiance for all the North-South cross-track pixels. The files are provided in netCDF4 format, and contain information on radiometrically and wavelength calibrated solar irradiance for the UV and visible bands, corresponding noise, parameterized wavelength grid, solar viewing geometry, quality flags and other ancillary information. The product is produced using the L0-1b processor which includes multiple steps: (1) Image processing to produce radiometrically calibrated radiance, and (2) Additional wavelength calibration to improve wavelength registration. Please refer to the ATBD for details.  These data are beta. Beta maturity is defined as: the product is minimally validated but may still contain significant errors; it is based on product quick looks using the initial calibration parameters.  Because the products at this stage have minimal validation, users should refrain from making conclusive public statements regarding science and applications of the data products until a product is designated at the provisional validation status.  The TEMPO Level 1 ATBD is still being finalized. For access to Version 1.0 ATBD, please contact the ASDC at larc-dl-asdc-tempo@mail.nasa.gov.",
         "license": "proprietary"
     },
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         "description": "Level 1 reference irradiance files provide solar irradiance measured using the reference solar diffuser. Each file includes the measured solar irradiance for all the North-South cross-track pixels. The files are provided in netCDF4 format, and contain information on radiometrically and wavelength calibrated solar irradiance for the UV and visible bands, corresponding noise, parameterized wavelength grid, solar viewing geometry, quality flags and other ancillary information. The product is produced using the L0-1b processor which includes multiple steps: (1) Image processing to produce radiometrically calibrated radiance, and (2) Additional wavelength calibration to improve wavelength registration.",
         "license": "proprietary"
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@@ -172570,7 +172856,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2842852230-LARC_CLOUD.html",
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         "description": "Level 1 irradiance files provide solar irradiance measured using the working solar diffuser. Each file includes the measured solar irradiance for all the North-South cross-track pixels. The files are provided in netCDF4 format, and contain information on radiometrically and wavelength calibrated solar irradiance for the UV and visible bands, corresponding noise, parameterized wavelength grid, solar viewing geometry, quality flags and other ancillary information. The product is produced using the L0-1b processor which includes multiple steps: (1) Image processing to produce radiometrically calibrated radiance, and (2) Additional wavelength calibration to improve wavelength registration. Please refer to the ATBD for details.  These data are beta. Beta maturity is defined as: the product is minimally validated but may still contain significant errors; it is based on product quick looks using the initial calibration parameters.  Because the products at this stage have minimal validation, users should refrain from making conclusive public statements regarding science and applications of the data products until a product is designated at the provisional validation status.  The TEMPO Level 1 ATBD is still being finalized. For access to Version 1.0 ATBD, please contact the ASDC at larc-dl-asdc-tempo@mail.nasa.gov.",
         "license": "proprietary"
     },
@@ -172583,7 +172869,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2930757598-LARC_CLOUD.html",
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         "description": "Level 1 irradiance files provide solar irradiance measured using the working solar diffuser. Each file includes the measured solar irradiance for all the North-South cross-track pixels. The files are provided in netCDF4 format, and contain information on radiometrically and wavelength calibrated solar irradiance for the UV and visible bands, corresponding noise, parameterized wavelength grid, solar viewing geometry, quality flags and other ancillary information. The product is produced using the L0-1b processor which includes multiple steps: (1) Image processing to produce radiometrically calibrated radiance, and (2) Additional wavelength calibration to improve wavelength registration.",
         "license": "proprietary"
     },
@@ -172596,7 +172882,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2930725014-LARC_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2930725014-LARC_CLOUD.html",
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         "description": "Nitrogen dioxide Level 2 files provide trace gas information at TEMPO\u2019s native spatial resolution, ~10 km^2 at the center of the Field of Regard (FOR), for individual granules. Each granule covers the entire North-South TEMPO FOR but only a portion of the East-West FOR. The files are provided in netCDF4 format, and contain information on tropospheric, stratospheric and total nitrogen dioxide vertical columns, ancillary data used in air mass factor and stratospheric/tropospheric separation calculations, and retrieval quality flags. The retrieval uses a three-step approach: (1) spectral fitting of slant columns, (2) air mass factor calculation and derivation of vertical columns, and (3) stratospheric/tropospheric separation.",
         "license": "proprietary"
     },
@@ -172609,7 +172895,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2930763263-LARC_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2930763263-LARC_CLOUD.html",
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         "description": "Nitrogen dioxide Level 3 files provide trace gas information on a regular grid covering the TEMPO field of regard for nominal TEMPO observations. Level 3 files are derived by combining information from all Level 2 files constituting a TEMPO East-West scan cycle. The files are provided in netCDF4 format, and contain information on tropospheric, stratospheric and total nitrogen dioxide vertical columns, ancillary data used in air mass factor and stratospheric/tropospheric separation calculations, and retrieval quality flags. The re-gridding algorithm uses an area-weighted approach.",
         "license": "proprietary"
     },
@@ -172622,7 +172908,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2930726639-LARC_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2930726639-LARC_CLOUD.html",
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         "description": "Total ozone Level 2 files provide ozone information at TEMPO\u2019s native spatial resolution, ~10 km^2 at the center of the Field of Regard (FOR), for individual granules. Each granule covers the entire North-South TEMPO FOR but only a portion of the East-West FOR. The files are provided in netCDF4 format, and contain information on total column ozone and some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, effective cloud fraction, effective cloud pressure, radiative cloud fraction, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The retrieval is based on the OMI TOMS V8.5 algorithm adapted for TEMPO.",
         "license": "proprietary"
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@@ -172635,7 +172921,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2930764281-LARC_CLOUD.html",
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         "description": "Total ozone Level 3 files provide ozone information on a regular grid covering the TEMPO field of regard for nominal TEMPO observations. Level 3 files are derived by combining information from all Level 2 files constituting a TEMPO East-West scan cycle. The files are provided in netCDF4 format, and contain information on total column ozone and some auxiliary derived and ancillary input parameters including effective cloud fraction, effective cloud pressure, radiative cloud fraction, SO2 index, and terrain pressure. The re-gridding algorithm uses an area-weighted approach.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768941787-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768941787-ORNL_CLOUD.html",
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         "description": "This data set reports concentrations of biogenic volatile organic compounds (BVOCs) collected from tethered balloon-sampling platforms above selected forest and pasture sites in the Brazilian Amazon in March 1998, February 1999, and February 2000. The air samples were collected from forested sites in Brazil: the Tapajos forest (Para) in the Tapajos/Xingu moist forest; Balbina (Amazonas) in the Uatuma moist forest; and Jaru (Rondonia) in the Purus/Madeira moist forest. Two other sites were also located in Rondonia: at a forest reserve (Rebio Jaru) and a pasture (Fazenda Nossa Senhora Aparecida). The BVOCs measured included isoprene, alpha and beta pinene, camphene, sabinene, myrcene, limonene, and other monoterpenes. Approximately 24 to 40 soundings, including as many as four VOC samples collected simultaneously at various altitudes, were made at each site. There is one comma-delimited data file with this data set.",
         "license": "proprietary"
     },
@@ -172713,7 +172999,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2768942874-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2768942874-ORNL_CLOUD.html",
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         "description": "This data set includes aerosol optical thickness measurements from the CIMEL sunphotometer for 22 sites in Brazil during the period from 1993-2005. The AERONET (AErosol RObotic NETwork) program is an inclusive federation of ground-based remote sensing aerosol networks established by AERONET and  the PHOtometrie pour le Traitement Operationnel de Normalisation Satellitaire (PHOTONS) and greatly expanded by AEROCAN (the Canadian sunphotometer network) and other agency, institute and university partners. The goal is to assess aerosol optical properties and validate satellite retrievals of aerosol optical properties. The network imposes standardization of instruments, calibration, and processing. Data from this collaboration provides globally distributed observations of spectral aerosol optical depths, inversion products, and precipitable water in geographically diverse aerosol regimes. Three levels of data are available from the AERONET website: Level 1.0 (unscreened), Level 1.5 (cloud-screened), and Level 2.0 (cloud-screened and quality-assured). Data provided here are Level 2.0. There are 22 comma-delimited data files with this data set and one companion text file which contains the latitude, longitude, and elevation of the 22 sites.",
         "license": "proprietary"
     },
@@ -172726,7 +173012,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781384398-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781384398-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0xMSBmb3Jlc3QgZGFtYWdlIGZvbGxvd2luZyByZWR1Y2VkIGltcGFjdCBsb2dnaW5nLCBudyBtYXRvIGdyb3NzbywgYnJhemlsXCIsXCJPUk5MX0NMT1VEXCIsXCJORDExX0xvZ2dpbmdfRGFtYWdlX01UXzk3N1wiLFwiMVwiLDI3Nzc4MTQxMjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTExIGZvcmVzdCBkYW1hZ2UgZm9sbG93aW5nIHJlZHVjZWQgaW1wYWN0IGxvZ2dpbmcsIG53IG1hdG8gZ3Jvc3NvLCBicmF6aWxcIixcIk9STkxfQ0xPVURcIixcIk5EMTFfTG9nZ2luZ19EYW1hZ2VfTVRfOTc3XCIsXCIxXCIsMjc3NzgxNDEyMSwyXSJ9/TG03_Aeronet_Solar_Flux_1137_1",
         "description": "This data set includes solar surface irradiance from Kipp and Zonen CM-21 pyranometers, both total unfiltered and filtered (RG695), and photosynthetically active radiation (PAR) from Skye-Probetech SKE-510 PAR sensors. Measurements were made at six sites acrosss the Brazilian Amazon during the period from 1999 to 2004. These sites were co-located with AERONET (AErosol RObotic NETwork) program sites. There are 17 comma-delimited data files (.csv) with this data set. The AERONET program is an inclusive federation of ground-based remote sensing aerosol networks established by AERONET and  the PHOtometrie pour le Traitement Operationnel de Normalisation Satellitaire (PHOTONS) and greatly expanded by AEROCAN (the Canadian sunphotometer network) and other agency, institute and university partners. The goal is to assess aerosol optical properties and validate satellite retrievals of those properties. The network imposes standardization of instruments, calibration, and processing. ",
         "license": "proprietary"
     },
@@ -172739,7 +173025,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773195548-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773195548-ORNL_CLOUD.html",
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         "description": "This data set provides maps produced from model output data from the National Aeronautics and Space Administration-Carnegie Ames Stanford Approach (NASA-CASA) model and other modeling approaches. The maps include estimated annual Net Primary Production (ANPP), leaf (live) biomass carbon, wood (live) biomass carbon, fine root (live) biomass carbon, metabolic leaf litter (dead) carbon, structural leaf litter (dead) carbon, woody detritus (dead) carbon, and slow soil carbon, gridded at half-degree spatial resolution for the years 1982-1998, and 2001 (NPP data) for Brazil. Maps are provided at one-degree resolution for monthly soil emissions and soil uptake of N2O, NO, CO, and CH4. In addition, there are maps in 8-km resolution for soil texture, soil carbon, soil pH, soil maximum plant available water (paw), and net primary productivity (NPP).There are three files with this data set in tar.gz format. The files are in half-degree, one-degree, and 8-km resolution. When expanded, the half degree and one degree files contain 83 map files in GeoTIFF (.tif) format. The third file (8-km resolution) contains the soil and productivity maps. When expanded, this file contains 22 files in GeoTIFF (.tif) format.",
         "license": "proprietary"
     },
@@ -172752,7 +173038,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2781566236-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2781566236-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyBuZC0xMSBmb3Jlc3QgZGFtYWdlIGZvbGxvd2luZyByZWR1Y2VkIGltcGFjdCBsb2dnaW5nLCBudyBtYXRvIGdyb3NzbywgYnJhemlsXCIsXCJPUk5MX0NMT1VEXCIsXCJORDExX0xvZ2dpbmdfRGFtYWdlX01UXzk3N1wiLFwiMVwiLDI3Nzc4MTQxMjEsMl0iLCJ1bW0iOiJbXCJsYmEtZWNvIG5kLTExIGZvcmVzdCBkYW1hZ2UgZm9sbG93aW5nIHJlZHVjZWQgaW1wYWN0IGxvZ2dpbmcsIG53IG1hdG8gZ3Jvc3NvLCBicmF6aWxcIixcIk9STkxfQ0xPVURcIixcIk5EMTFfTG9nZ2luZ19EYW1hZ2VfTVRfOTc3XCIsXCIxXCIsMjc3NzgxNDEyMSwyXSJ9/TG06_Vertical_Profiles_1175_1",
         "description": "This data set contains measurements of atmospheric carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), hydrogen (H2), nitrous oxide (N2O), and sulfur hexafluoride (SF6) collected from December 2000-November 2005 as vertical profiles above three sites in Brazil: Fortaleza, Santarem, and Manaus. At Santarem, ascending profiles were made above the Tapajos National Forest, near the km 67 Tower Site. At Manaus, ascending profiles were made above the K34 flux tower (aka, ZF2 km 34 tower) to the northwest of the city of Manaus. Descending profiles were flown nearby, but at locations upwind of population centers to avoid possible pollution. Fortaleza samples were collected off the coast, over the Atlantic Ocean to sample background air before it flows over the Amazon Basin.Air samples were collected as discrete samples aboard light aircraft and shipped to laboratories for analysis relative to internationally accepted calibration standards.There are three comma-delimited (.csv) data files with this data set.",
         "license": "proprietary"
     },
@@ -172765,7 +173051,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834917-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784834917-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhLWVjbyB0Zy0wNyBncm91bmQtYmFzZWQgYmlvbWV0cnkgZGF0YSBhdCBrbSA4MyBzaXRlLCB0YXBham9zIG5hdGlvbmFsIGZvcmVzdDogMTk5N1wiLFwiT1JOTF9DTE9VRFwiLFwiVEcwN19GRlRfU3VydmV5X0ttODNfOTIzXCIsXCIxXCIsMjc3Nzc1MDI4NSwyXSIsInVtbSI6IltcImxiYS1lY28gdGctMDcgZ3JvdW5kLWJhc2VkIGJpb21ldHJ5IGRhdGEgYXQga20gODMgc2l0ZSwgdGFwYWpvcyBuYXRpb25hbCBmb3Jlc3Q6IDE5OTdcIixcIk9STkxfQ0xPVURcIixcIlRHMDdfRkZUX1N1cnZleV9LbTgzXzkyM1wiLFwiMVwiLDI3Nzc3NTAyODUsMl0ifQ%3D%3D/TG07_Autochamber_Soil_CO2_Flux_Km67_927_1",
         "description": "Measurements of the soil-atmosphere flux of CO2 were made at the km 67 flux tower site in the Tapajos National Forest, Santarem, Para, Brazil. Eight chambers were set up to measure trace gas exchange between the soil and atmosphere about 5 times a day (during daylight and night) at this undisturbed forest site from April 2001 to April 2003. CO2 soil efflux data are reported in one ASCII comma separated file.The automated chamber system consisted of 8 automatically opening and closing aluminum chambers with an infrared gas analyzer. The chambers were installed in a 0.5 ha area close to the flux tower on patches of ground without apparent photosynthetic vegetation. Each chamber was sequentially closed, sampled, and re-opened 5 times per day (closed 7% of the day). The maximum daily average flux was 4.3 and the minimum was 1.3 umol CO2 m-2 s-1.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742959-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779742959-ORNL_CLOUD.html",
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         "description": "Canopy measurements in an undisturbed eastern Amazon forest (Cauxi, Para, Brazil. See Figure 1) were derived from a one-time event in 2000 using a hand-held laser range finder, and diameter at breast height (DBH) was determined manually. Parameters reported include: Crown Width, Crown Depth, Tree Height, and DBH. There is one comma-delimited ASCII data file with this data set. In addition, these manually derived measurements were compared to the IKONOS satellite data of crown dimensions that were acquired on 2 November 2000, from an orbital altitude of 680 km. The data from a 600 x 600 m block of undisturbed forest, including the 50 ha area surveyed in the field, were analyzed in a combined image processing and geographic information system environment.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products. KNOWN PROBLEMS: Only the general location for this study was identified -- Cauaxi, Para, Brazil. The tree measurement data are of limited use because coordinates for the study site, coordinates of the beginning and end of the transects, and coordinates of the measured trees were not provided. Also, the area that the IKONOS image captured was not provided and the IKONOS image is not available due to restricted distribution.",
         "license": "proprietary"
     },
@@ -172791,7 +173077,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750285-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750285-ORNL_CLOUD.html",
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         "description": "A field inventory of trees was conducted in March of 1997 in a logging concession at the Tapajos National Forest, south of Santarem, Para, Brazil. The inventory was conducted by the foresters and technicians of the Tropical Forest Foundation (FFT) and included all trees with diameter at breast height greater than or equal to 35 cm. Four blocks of approximately 100 ha each within the 3,200 ha concession were inventoried. Within each block, parallel trails 50 m apart were established, and the location of each tree measured was recorded to the nearest meter using an orthogonal coordinate system based on these trails. Field data for each tree includes: identification number, ground position, diameter, common name, scientific name and qualitative estimates of bole and canopy quality. Data are provided in one ASCII comma separated file. These data were used to calculate above-ground live biomass as described in Keller et al. (2001), but biomass data are not included in this data set.",
         "license": "proprietary"
     },
@@ -172804,7 +173090,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777830142-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777830142-ORNL_CLOUD.html",
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         "description": "This data set reports the characterization of fallen necromass as the volume and density of coarse woody debris (CWD), and standing necromass as the volume and density of standing dead trees. Measurements were made in undisturbed and logged forest areas of the Tapajos National Forest, and Cauaxi Forest, Para, Brazil,  and Juruena Forest, Mato Grosso, Brazil from 2002-2004. Fallen and standing necromass were classified into one of five categories according to its state of decomposition. There are two comma-delimited ASCII data files with this data set: two files contain the sampling information, decomposition state, and DBH measurements. There are also two files provided as companion data files which provide sampling transect descriptions.  ",
         "license": "proprietary"
     },
@@ -172817,7 +173103,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750382-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750382-ORNL_CLOUD.html",
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         "description": "The goal of this study was to determine the effects of soil phosphorus (P) status on litter decomposition rates using two factors: soil texture (with associated differences in soil P pools) and fertilization, in a fully factorial design. Mass and nutrient pools in litter from a single species, Marupa (Simaruba amara (Aubl.)), were measured quarterly between March 2000 and February 2001 in an undisturbed mature forest within the Tapajos National Forest at the kilometer 83 site. Reported here are litter mass and nutrients (carbon, nitrogen and phosphorus) as both raw values (grams for mass, percent for carbon and nitrogen and mg per kg for phosphorus), and as proportion of the initial mass and nutrient pool. Data are provided in a comma separated ASCII format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777845832-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777845832-ORNL_CLOUD.html",
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         "description": "Trace gas fluxes of carbon dioxide, methane, nitrous oxide, and nitric oxide (CO2, CH4, N2O, and NO) from surface soil were measured manually in an undisturbed forest at the Tapajos National Forest Seca-Floresta Site, which is within the footprint of the km 67 eddy flux tower. Measurements were made in January 2000 through April 2004, approximately twice per month. On each sampling date, up to four sets of 30-m lines were established off the existing transects at the Seca-Floresta site. Along each line eight chambers were installed for gas collection. In addition soil samples were collected for analysis of soil moisture as water-filled pore space (WFPS). There is one comma-delimited ASCII file with this data set.",
         "license": "proprietary"
     },
@@ -172843,7 +173129,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750323-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750323-ORNL_CLOUD.html",
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         "description": "This data set reports the results of an experiment that tested the short-term effects of root mortality on the soil-atmosphere fluxes of nitrous oxide, nitric oxide, methane, and carbon dioxide in a tropical evergreen forest. Weekly trace gas fluxes are provided for treatment and control plots on sand and clay tropical forest soils in two comma separated ASCII files.The study site in the Tapajos National Forest (TNF) is near km 83 on the Santarem-Cuiaba Highway south of Santarem, Para, Brazil. Root mortality was induced by isolating blocks of land to 1 m depth using trenching and root exclusion screening. Gas fluxes were measured weekly for ten weeks following the trenching treatment and monthly for the remainder of the year. Monthly data are not included at this time.",
         "license": "proprietary"
     },
@@ -172856,7 +173142,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780918120-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780918120-ORNL_CLOUD.html",
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         "description": "This data set reports measurements of trace gas fluxes of methane (CH4), nitric oxide (N2O), nitrous oxide (NO), carbon dioxide (CO2) from soils at a study site in the Tapajos National Forest (TNF), near the km 83 on the Santarem-Cuiaba Highway south of Santarem, Para, Brazil. Data for root mass and carbon content, soil nitrogen (N), nitrification, and moisture content are also provided. There are five comma-delimited data files with this data set.The research was conducted to test the effects of root mortality on the soil-atmosphere trace-gas fluxes over the course of one year. Root mortality was induced by isolating blocks of land to 1 m depth using trenching and root exclusion screening. Gas fluxes were measured weekly for ten weeks following the trenching treatment and monthly for the remainder of the year.Note: The related  data set LBA-ECO TG-07 Soil Trace Gas Flux and Root Mortality, Tapajos National Forest contains the same flux data that were measured weekly for ten weeks following the trenching treatment. This data set also provides the monthly data for the remainder of the year. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777337441-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777337441-ORNL_CLOUD.html",
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         "description": "This data set provides the results of a GLAS (the Geoscience Laser Altimeter System) forest structure validation survey conducted in Santarem and Sao Jorge, Para during November 2004 (Lefsky et al., 2005). DBH, total height, commercial height, canopy width and canopy class description were measured for 11 primary forest sites in Santarem along two 75m transects per GLAS measurement. For 10 secondary forest sites in Sao Jorge, the number of stems 0-2cm, 2-5cm, 5-10cm, and greater than 10cm were measured. For all stems greater than 10cm the DBH was measured, and for all sites, the maximum height was recorded. The basal area was calculated for all trees with DBH greater than 10cm within our transects, and biomass was calculated using the Brown, 1997 formula.Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750487-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777750487-ORNL_CLOUD.html",
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         "description": "Trace gas fluxes of carbon dioxide, methane, nitrous oxide, and nitric oxide were measured manually at undisturbed and logged forest sites in the Tapajos National Forest, near Santarem, Para, Brazil. Manual measurements were made approximately weekly at both the undisturbed and logged sites. Fluxes from clay and sand soils were completed at the undisturbed sites. Fluxes were measured at the deck (patio), skid trail, clearing and forest at the logged sites. Soil moisture is reported as daily average water-filled pore space (WFPS) for the undisturbed forest clay and sand soils. Data are reported in three ASCII comma separated files.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780117658-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780117658-ORNL_CLOUD.html",
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         "description": "This data set reports phosphorus (P), carbon (C), and nitrogen (N) nutrient pool concentrations for forest soils and roots and P pool concentrations for forest floor litter, soil solutions, and microbial extracts. Soils samples were also extracted using the Hedley sequential fractionation method and the extracts analyzed for P. Nutrient pool concentrations are presented on an areal basis of 1 hectare to a depth of 10 cm, as calculated from soil bulk densities and respective pool biomass quantities. There is one comma-delimited ASCII file with this data set. These measurements were made during a soil P addition fertilization experiment conducted at the km 83 site, Tapajos National Forest, Para, Brazil. Control and fertilized plots were established in both sandy loam and clay soils. Soil cores were collected every 4 months from August 1999 through April 2000 (McGroddy et al. 2008). ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780891006-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780891006-ORNL_CLOUD.html",
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         "description": "This data set provides concentrations of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) from air samples collected at several heights on towers at three locations in upland old growth forests in the Brazilian Amazon during the wet and dry seasons of 2004 and 2005. Towers are located in the Caxiuana National Forest, in the state of Amazonas; the Manaus, Para, site in the Cuieiras Reserve; and the Sinop site, located north of that city in the state of Mato Grosso. Two sampling campaigns were conducted at each location. Samples were collected from each height 3-5 times on several nights and at least once during well-mixed daytime conditions during each campaign for a total of 75 profiles on 19 dates. There is one comma-delimited ASCII file with this data set. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780809181-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780809181-ORNL_CLOUD.html",
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         "description": "This data set provides nitric oxide (NO), nitrous oxide (N2O), carbon dioxide (CO2) flux measurements, nitrogen (N) and phosphorus (P) pools, net N mineralization and nitrification rates, and measurements of soil moisture, in response to nitrogen and phosphorus soil fertilization treatments. The research was conducted in a mature moist tropical forest and an 11-year pasture at Nova Vida in Rondonia, in the Brazilian Amazon, in 1998 and 1999. There is one comma-delimited ASCII data file with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780156624-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780156624-ORNL_CLOUD.html",
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         "description": "This data set includes the results of measurements of the soil gas fluxes of nitric oxide (NO), nitrous oxide (N2O), and carbon dioxide (CO2), soil moisture, soil temperature, and soil pools of ammonium and nitrate in response to a simulated rain event. Study sites were soils in mature forests and pastures of two ages (11 and 26 yrs old). The study took place during the dry season in August 1998 at Fazenda Nova Vida, Rondonia in the Brazilian Amazon. There is one comma-delimited ASCII file with this data set. This study investigated how changes in soil moisture (i.e., rains at the end of the dry season) affected the fluxes of NO, N20 and CO2 from forest and pasture soils in the southwestern Brazilian Amazon (Garcia-Montiel, et al., 2003). The main objectives were to measure the short-term dynamics of soil emissions of NO, N20, and CO2 in forest and pasture soils associated with soil wetting after prolonged dryness; and quantify the contribution of the pulses of N oxide fluxes resulting from soil wetting to dry season and annual fluxes. ",
         "license": "proprietary"
     },
@@ -172947,7 +173233,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777838247-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777838247-ORNL_CLOUD.html",
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         "description": "This data set reports the results of carbon, nitrogen, and oxygen isotopic analyses of soil, soil water, and N2O soil gas samples; total soil carbon and nitrogen concentrations; and soil texture and bulk density. Samples were collected from the km 83 Logged Forest Tower Site and the km 67 Seca-Floresta Site in the Tapajos National Forest (TNF) near Santarem, Para, Brazil. Soil samples were collected in July of 2000 and soil gas samples were collected in 2001 and 2002. Soil and gas samples were collected from various soil types at each site and from several depths in specially constructed pits. There is one comma-delimited ASCII data file with this data set. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773193196-ORNL_CLOUD.html",
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         "description": "This data set provides derived emission factors (EFs), reported in grams of compound emitted per kilogram of dry fuel (g/kg), for PM10 (particulate matter up to 10 micrometers in size), O3, CO2, CO, NO, NO2, HONO, HCN, NH3, OCS, DMS, CH4, and up to 48 non-methane organic compounds (NMOC) from the Tropical Forest and Fire Emissions Experiment (TROFFEE). TROFFEE used laboratory measurements followed by airborne and ground based field campaigns in Mato Grosso, Para, and Amazonas, Brazil during the 2004 Amazon dry season to quantify the emissions from pristine tropical forest and several plantations as well as the emissions, fuel consumption, and fire ecology of tropical deforestation fires. EFs were determined for 19 tropical deforestation fires in August and September, 2004. The combined output of these fires created a massive megaplume more than 500-km wide and covered a large area in Brazil, Bolivia, and Paraguay for about one month. For the megaplume, the EFs (reported in grams of compound emitted per kilogram of dry fuel (g/kg)) represented the effective emissions factor measured downwind from the source.There are two comma-delimited data files (.csv) and one text file (.txt) with this data set. The text file contains information regarding the fuel/fire sources, latitude and longitudes (also provided in the data files).",
         "license": "proprietary"
     },
@@ -172986,7 +173272,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652159-GES_DISC.html",
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         "description": "THIRN4IMCH67 is the Nimbus-4 Temperature-Humidity Infrared Radiometer (THIR) data product consisting of daily montages of brightness temperatures measured at 6.7 microns on 70 mm photofacsimile film strips. Daytime and nighttime orbital swaths are displayed in strips, each corresponding to a distance approximately from pole to pole and a width from horizon to horizon. The ground resolution of 22.6 km at nadir decreases as the horizontal distance from the subsatellite track increases. Each film strip is gridded with geographic coordinates and is identified by orbit number, time, and an indication of whether it is daytime (D) or nighttime (N). The images are saved as JPEG 2000 digital files. About 1 week of images are archived into a TAR file. Additional information can be found in section 3.4.1 of \"The Nimbus IV User's Guide\".  The THIR instrument was designed to detect emitted thermal radiation in both the 10.5- to 12.5-micrometer region (IR window) and the 6.5- to 7.0-micrometer region (water vapor). The window channel measured cloudtop temperatures day and night. The other channel operated primarily at night to map the water vapor distribution in the upper troposphere and stratosphere. The THIR experiment made measurements from April 18, 1970 until April 8, 1971.  This product was previously available from the NSSDC with the identifier ESAD-00194 (old ID 70-025A-02B).",
         "license": "proprietary"
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         "description": "THIRN4L1CH115 is the Nimbus-4 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Meteorological Radiation Data at 11.5 microns product and contains radiances expressed in units of equivalent brightness temperature measured in the 10.5 - 12.5 (11.5) micron channel. The data, originally written on IBM 360 machines, were recovered from magnetic tapes, also referred to as Nimbus Meteorological Radiation Tapes (NMRT-THIR). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The Nimbus-4 satellite was successfully launched on December 11, 1972. The THIR experiment on Nimbus-4 replaced the measurements made by the HRIR and MRIR instruments flown on previous Nimbus satellites. The THIR instrument is a two channel high resolution scanning radiometer designed to perform two major functions:* The 11.5 micron channel provides both day and night cloud top or surface temperatures. The ground resolution at the sub-point is 8 km and operates day and night.* The 6.7 micron channel gives information on the moisture content of the upper troposphere and stratosphere and the location of jet streams and frontal systems. The water vapor channel has a resolution of the sub-point is 22 km and operates mostly at night.  The THIR Principal Investigator was Andrew W. McCulloch from NASA Goddard Space Flight Center. The Nimbus-4 THIR data are available from April 13, 1970 (day of year 103) through April 1, 1971 (day of year 91). The THIRN4L1CH67 product contains the 6.7 micron channel data.  This product was previously available from the NSSDC with the identifier ESAD-00004 (old ID 70-025A-02D).",
         "license": "proprietary"
     },
@@ -173012,7 +173298,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652201-GES_DISC.html",
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         "description": "THIRN4L1CH67 is the Nimbus-4 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Meteorological Radiation Data at 6.7 microns product contains radiances expressed in units of equivalent brightness temperature measured in the 6.7 micron channel. The data, originally written on IBM 360 machines, were recovered from magnetic tapes, also referred to as Nimbus Meteorological Radiation Tapes (NMRT-THIR). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The Nimbus-4 satellite was successfully launched on April 8, 1970. The THIR experiment on Nimbus-4 replaced the measurements made the HRIR and MRIR instruments flown on previous Nimbus satellites. The THIR instrument is a two channel high resolution scanning radiometer designed to perform two major functions:* The 11.5 micron channel provides both day and night cloud top or surface temperatures. The ground resolution at the sub-point is 8 km and operates day and night.* The 6.7 micron channel gives information on the moisture content of the upper troposphere and stratosphere and the location of jet streams and frontal systems. The water vapor channel has a resolution of the sub-point is 22 km and operates mostly at night.  The THIR Principal Investigator was Andrew W. McCulloch from NASA Goddard Space Flight Center. The Nimbus-4 THIR data are available from April 14, 1970 (day of year 104) through March 25, 1971 (day of year 84). The THIRN4L1CH115 product contains the 11.5 micron channel data.  This product was previously available from the NSSDC with the identifier ESAD-00071 (old ID 70-025A-02E).",
         "license": "proprietary"
     },
@@ -173025,7 +173311,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652199-GES_DISC.html",
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         "description": "THIRN5L1CH115 is the Nimbus-5 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Meteorological Radiation Data at 11.5 microns product and contains radiances expressed in units of equivalent brightness temperature measured in the 10.5 - 12.5 (11.5) micron channel. The data, originally written on IBM 360 machines, were recovered from magnetic tapes, also referred to as Nimbus Meteorological Radiation Tapes (NMRT-THIR). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The Nimbus-5 satellite was successfully launched on December 11, 1972. The THIR experiment on Nimbus-5 continued the measurements made by its predecessor flown on Nimbus-4. The THIR instrument is a two channel high resolution scanning radiometer designed to perform two major functions:* The 11.5 micron channel provides both day and night cloud top or surface temperatures. The ground resolution at the sub-point is 8 km and operates day and night.* The 6.7 micron channel gives information on the moisture content of the upper troposphere and stratosphere and the location of jet streams and frontal systems. The water vapor channel has a resolution of the sub-point is 22 km and operates mostly at night. The THIR Principal Investigator was Andrew W. McCulloch from NASA Goddard Space Flight Center. The Nimbus-5 THIR data are available from December 19, 1972 (day of year 354) through March 1, 1975 (day of year 60). The THIRN5L1CH67 product contains the 6.7 micron channel data.  This product was previously available from the NSSDC with the identifier ESAD-00020 (old ID 72-097A-08C).",
         "license": "proprietary"
     },
@@ -173038,7 +173324,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652169-GES_DISC.html",
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         "description": "THIRN5L1CH67 is the Nimbus-5 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Meteorological Radiation Data at 6.7 microns product and contains radiances expressed in units of equivalent brightness temperature measured in the 6.7 micron channel. The data, originally written on IBM 360 machines, were recovered from magnetic tapes, also referred to as Nimbus Meteorological Radiation Tapes (NMRT-THIR). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The Nimbus-5 satellite was successfully launched on December 11, 1972. The THIR experiment on Nimbus-5 continued the measurements made by its predecessor flown on Nimbus-4. The THIR instrument is a two channel high resolution scanning radiometer designed to perform two major functions:* 11.5 micron channel provides both day and night cloud top or surface temperatures. The ground resolution at the sub-point is 8 km and operates day and night.* 6.7 micron channel gives information on the moisture content of the upper troposphere and stratosphere and the location of jet streams and frontal systems. The water vapor channel has a resolution of the sub-point is 22 km and operates mostly at night.  The THIR Principal Investigator was Andrew W. McCulloch from NASA Goddard Space Flight Center. The Nimbus-5 THIR data are available from December 19, 1972 (day of year 354) through August 26, 1974 (day of year 238). The THIRN5L1CH115 product contains the 11.5 micron channel data.  This product was previously available from the NSSDC with the identifier ESAD-00167 (old ID 72-097A-08D).",
         "license": "proprietary"
     },
@@ -173051,7 +173337,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652220-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652220-GES_DISC.html",
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         "description": "The THIRN6IM data product consists of daily montages of brightness temperatures on 70 mm photofacsimile film strips from the Nimbus-6 Temperature-Humidity Infrared Radiometer measured at 6.7 and 11.5 microns. Daytime and nighttime orbital swaths are displayed in strips, each corresponding to a distance approximately from pole to pole and a width from horizon to horizon. The ground resolution of 22.6 km for 6.7 microns and 8.2 km for 11.5 microns at nadir decreases as the horizontal distance from the subsatellite track increases. Each film strip is gridded with geographic coordinates and is identified by orbit number, time, and an indication of whether it is daytime (D) or nighttime (N). The images are saved as JPEG 2000 digital files. About 1 week of images are archived into a TAR file. Additional information can be found in section 2.4.1 of \"The Nimbus 6 User's Guide.\"  The Nimbus 6 Temperature-Humidity Infrared Radiometer (THIR) was designed to detect emitted thermal radiation in both the 10.5- to 12.5-micron region (IR window) and the 6.5- to 7.0-micron region (water vapor). The window channel measured cloudtop temperatures day and night. The other channel operated primarily at night to map the water vapor distribution in the upper troposphere and stratosphere. The THIR experiment made measurements from June 18, 1975 until May 6, 1976.",
         "license": "proprietary"
     },
@@ -173064,7 +173350,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652170-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652170-GES_DISC.html",
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         "description": "THIRN6L1CH115 is the Nimbus-6 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Meteorological Radiation Data at 11.5 microns product and contains radiances expressed in units of equivalent brightness temperature measured in the 10.5 - 12.5 (11.5) micron channel. The data, originally written on IBM 360 machines, were recovered from magnetic tapes, also referred to as Nimbus Meteorological Radiation Tapes (NMRT-THIR). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The Nimbus-6 satellite was successfully launched on June 18, 1975. The THIR experiment on Nimbus-6 continued the measurements made by its predecessors flown on Nimbus-4 and Nimbus-5. The THIR instrument is a two channel high resolution scanning radiometer designed to perform two major functions:  1) The 11.5 micron channel provides both day and night cloud top or surface temperatures, with a resolution at nadir of 8 km, and operates day and night. 2) The 6.7 micron channel gives information on the water vapor content of the upper troposphere and stratosphere and the location of jet streams and frontal systems, with a resolution at nadir of 22 km, and operates mostly at night.  The THIR Principal Investigator was Andrew W. McCulloch from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00125 (old ID 75-052A-12C).",
         "license": "proprietary"
     },
@@ -173077,7 +173363,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652221-GES_DISC.html",
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         "description": "THIRN6L1CH67 is the Nimbus-6 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Meteorological Radiation Data at 6.7 microns product and contains radiances expressed in units of equivalent brightness temperature measured in the 6.7 micron (water vapor) channel. The data, originally written on IBM 360 machines, were recovered from magnetic tapes, also referred to as Nimbus Meteorological Radiation Tapes (NMRT-THIR). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The Nimbus-6 satellite was successfully launched on June 18, 1975. The Temperature-Humidity Infrared Radiometer (THIR) experiment on Nimbus-6 continues the measurements made by its predecessors flown on Nimbus-4 and Nimbus-5. The THIR instrument is a two channel high resolution scanning radiometer designed to perform two major functions:  1) The 11.5-12.5 micron channel provides both day and night cloud top or surface temperatures, with a resolution at nadir of 8 km, and operates day and night. 2) The 6.7 micron channel gives information on the water vapor content of the upper troposphere and stratosphere and the location of jet streams and frontal systems, with a resolution at nadir of 22 km, and operates mostly at night.  The THIR Principal Investigator was Andrew W. McCulloch from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00164 (old ID 75-052A-12D).",
         "license": "proprietary"
     },
@@ -173090,7 +173376,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652171-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652171-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widGhpci9uaW1idXMtNSBsZXZlbCAxIG1ldGVvcm9sb2dpY2FsIHJhZGlhdGlvbiBkYXRhIGF0IDYuNyBtaWNyb25zIHYwMDEgKHRoaXJuNWwxY2g2NykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUSElSTjVMMUNINjdcIixcIjFcIiwxMjczNjUyMTY5LDI3XSIsInVtbSI6IltcInRoaXIvbmltYnVzLTUgbGV2ZWwgMSBtZXRlb3JvbG9naWNhbCByYWRpYXRpb24gZGF0YSBhdCA2LjcgbWljcm9ucyB2MDAxICh0aGlybjVsMWNoNjcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVEhJUk41TDFDSDY3XCIsXCIxXCIsMTI3MzY1MjE2OSwyN10ifQ%3D%3D/THIRN7IM_001",
         "description": "THIRN7IM is the Nimbus-7 Temperature-Humidity Infrared Radiometer (THIR) data product consisting of daily montages of brightness temperatures measured at 6.7 and 11.5 microns. Each montage contains either a daytime or nighttime assembly of up to 14 individual swaths. Each swath corresponds to a distance approximately from pole to pole and a width from horizon to horizon. The ground resolution is 22.6 km for 6.7 microns and 8.2 km for 11.5 microns at nadir and decreases as the horizontal distance from the subsatellite track increases. Below each swath is information describing the orbit number, and the equator crossing longitude and time.  The THIR instrument was designed to detect emitted thermal radiation in both the 10.5 to 12.5 micron region (IR window) and the 6.5 to 7.0 micron region (water vapor). The window channel measured cloudtop temperatures day and night. The other channel operated primarily at night to map the water vapor distribution in the upper troposphere and stratosphere. The THIR experiment made measurements from Oct. 30, 1978 to May 9, 1985 when the instrument was turned off to conserve power. Additional information can be found in section 9 of \"The Nimbus 7 User's Guide,\" and the \"Nimbus 7 Temperature-Humidity Infrared Radiometer (THIR) Data User's Guide.\"  This product was previously available from the NSSDC as two products with the identifiers ESAD-00174 and ESAD-00239 (old ID 78-098A-10A and 78-098A-10B).",
         "license": "proprietary"
     },
@@ -173103,7 +173389,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1415263464-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1415263464-GES_DISC.html",
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         "description": "THIRN7L1BCLT is the Nimbus-7 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Cloud Data for SBUV/TOMS (BCLT) product and contains total cloud amounts; radiances at three cloud altitudes: low (below 2km), middle (2 to 7 km depending on latitude), and height (above the middle cloud layer); cirrus and deep convective clouds; and mean and RMS deviations of cloud and surface radiances. Data are averaged orbit by orbit onto each of the Nimbus 7 TOMS IFOV, which vary from 50 km to 50 km at nadir to 200 km x 200 km at the edges, as well as SBUV 180 km x 180 km IFOVs. The BCLT product includes improved cloud estimation compared to the earlier CLT product.  Each file contains one day of data (~14 orbits per day). Spatial coverage is global. The data are available from October 31, 1978 (day of year 304) through October 27, 1984 (day of year 301).  This product was previously available from the NSSDC with the identifier ESAD-00196 (old ID 78-098A-10E)",
         "license": "proprietary"
     },
@@ -173116,7 +173402,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652204-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273652204-GES_DISC.html",
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         "description": "THIRN7L1CLDT is the Nimbus-7 Temperature-Humidity Infrared Radiometer (THIR) Level 1 Calibrated Located Radiation Data (CLDT) at 6.7 and 11.5 microns product and contains radiances expressed in units of W/m2/sr measured in the 10.5 - 12.5 (11.5) micron and 6.5 - 7.0 (6.7) micron channels. The data, originally written on IBM 360 machines, were recovered from magnetic 9-track tapes. The data are archived in their original proprietary format.  The Nimbus-7 satellite was successfully launched on October 28, 1978. The Temperature-Humidity Infrared Radiometer (THIR) experiment on Nimbus-7 is basically identical to its predecessors flown on Nimbus-4, -5 and -6, except that the data were digitized on board. The THIR instrument is a two channel high resolution scanning radiometer designed to perform two major functions:* The 11.5 micron channel provides both day and night cloud top or surface temperatures. The ground resolution at the sub-point is 6.7 km and operates day and night.* The 6.7 micron channel gives information on the moisture content of the upper troposphere and stratosphere and the location of jet streams and frontal systems. The water vapor channel has a resolution of the sub-point is 20 km and operates mostly at night.  The THIR Principal Investigator was Dr. Larry L. Stowe from NOAA NESDIS. The Nimbus-7 THIR data are available from October 30, 1979 (day of year 303) through May 13, 1985 (day of year 133).  This product was previously available from the NSSDC with the identifier ESAD-00107 (old ID 78-098A-10C).",
         "license": "proprietary"
     },
@@ -173142,7 +173428,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2046458866-GES_DISC.html",
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         "description": "TIROS-2 Medium-Resolution Scanning Radiometer Level 1 Final Meteorological Radiation Data (FMRT) product contains radiances expressed in five infrared/visible wavelength regions, expressed in either equivalent blackbody temperature (IR channels 1 and 2) or effective radiant emmitance (visible channels 3 and 5). The data will trace an elliptical, parabolic, or hyperbolic pattern on the ground due to the rotating of the instrument about the satellite spin axis. There is one orbit per file. The data were originally written on IBM 7094 machines, and these have been recovered from magnetic tapes, referred to as the Final Meteorological Radiation Tapes (FMRT). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The TIROS-2 satellite was successfully launched on November 23, 1960. The Medium-Resolution Scanning Radiometer experiment successfully returned data for about five months, becoming the first radiometer to make meteorlogical measurements from space. Three follow-on instruments were flown on TIROS-3, -4 and -7. Initially, all channels performed normally. However, channels 1 and 4 gradually deteriorated and by January 1961 were useless. The signal to noise ratio of channels 3 and 5 was extremely low, and the output was highly questionable. The instrument is a five channel radiometer with a 55 km footprint at nadir with the following characteristics:  Channel 1: 6.0 to 6.5 microns - water vapor absorption Channel 2: 8.0 to 12.0 microns - atmospheric window Channel 3: 0.2 to 6.0 microns - reflected solar radiation Channel 4: 8.0 to 30 microns - terrestial radiation Channel 5: 0.55 to 0.75 microns - response to the TV system  The Principal Investigator for these data was Joseph D. Barksdale from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00113 (old ID 60-016A-02A).",
         "license": "proprietary"
     },
@@ -173155,7 +173441,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2071514571-GES_DISC.html",
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         "description": "TIROS-3 Medium-Resolution Scanning Radiometer Level 1 Final Meteorological Radiation Data (FMRT) product contains radiances expressed in five infrared/visible wavelength regions, expressed in either equivalent blackbody temperature (IR channels 1, 2 and 4) or effective radiant emmitance (visible channels 3 and 5). The data will trace an elliptical, parabolic, or hyperbolic pattern on the ground due to the rotating of the instrument about the satellite spin axis. There is one orbit per file. The data were originally written on IBM 7094 machines, and these have been recovered from magnetic tapes, referred to as the Final Meteorological Radiation Tapes (FMRT). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The TIROS-3 satellite was successfully launched on July 12, 1961. The Medium-Resolution Scanning Radiometer experiment returned data for about two and a half months. A previous instrument flew on TIROS-2 and two follow-on instruments were flown on TIROS-4 and -7. Response characteristics of all channels degraded rapidly after launch. The greatest uncertainty in the radiation measurements is due to the apparent shift in the zero radiation level. Data are usable for channels 1, 2,  3, 4, and 5 up to orbits 118, 875, 875, 130 and 300, respectively. The instrument is a five channel radiometer with a 55 km footprint at nadir with the following characteristics:  Channel 1: 6.0 to 6.5 microns - water vapor absorption Channel 2: 8.0 to 12.0 microns - atmospheric window Channel 3: 0.2 to 6.0 microns - reflected solar radiation Channel 4: 8.0 to 30 - terrestial radiation Channel 5: 0.55 to 0.75 microns - response to the TV system  The Principal Investigator for these data was Joseph D. Barksdale from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00141 (old id 61-017A-03A).",
         "license": "proprietary"
     },
@@ -173168,7 +173454,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2152905384-GES_DISC.html",
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         "description": "The TIROS-3 Low-Resolution Omnidirectional Radiometer Level 1 Temperature Data product contains the black and white sensor temperature values in degrees Celsius. The experiment consisted of two sets of bolometers in the form of hollow aluminum hemispheres, mounted on opposite sides of the spacecraft, and whose optical axes were parallel to the spin axis. The bolometers were thermally isolated from but in close proximity to reflecting mirrors so that the hemispheres behaved like isolated spheres in space. The experiment was designed to measure the amount of solar energy absorbed, reflected, and emitted by the earth and its atmosphere in order to calculate the Earth's radiation budget. The data were originally written on IBM 7094 machines, and these have been recovered from magnetic tapes, referred to as the Omnidirectional Radiometer Temperature (ORT) tapes. The data are archived in their original text format.  The TIROS-3 satellite was successfully launched on July 12, 1961. The Low-Resolution Omnidirectional Radiometer experiment returned data for about three months. Two follow-on instruments were flown on TIROS-4 and -7, while a similar instrument flew on Explorer-7.  The Principal Investigator for these data was Verner E. Suomi from the University of Wisconsin. This product was previously available from the NSSDC with the identifier ESAD-00187 (old id 61-017A-01A).",
         "license": "proprietary"
     },
@@ -173181,7 +173467,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2038742346-GES_DISC.html",
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         "description": "TIROS-4 Medium-Resolution Scanning Radiometer Level 1 Final Meteorological Radiation Data (FMRT) product contains radiances expressed in five infrared/visible wavelength regions, expressed in either equivalent blackbody temperature (IR channels 1 and 2) or effective radiant emmitance (visible channels 3 and 5). The data will trace an elliptical, parabolic, or hyperbolic pattern on the ground due to the rotating of the instrument about the satellite spin axis. There is one orbit per file. The data were originally written on IBM 7094 machines, and these have been recovered from magnetic tapes, referred to as the Final Meteorological Radiation Tapes (FMRT). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The TIROS-4 satellite was successfully launched on February 8, 1962. The Medium-Resolution Scanning Radiometer experiment successfully returned data for about five months, continuing the measurements made by its predecessors flown on TIROS-2, and -3. A follow-on instrument was flown on TIROS-7. Degradation of the instrument after launch results in a departure of the data from the pre-launch calibration. The instrument is a five channel radiometer with a 55 km footprint at nadir with the following characteristics:  Channel 1: 6.0 to 6.5 microns - water vapor absorption Channel 2: 8.0 to 12.0 microns - atmospheric window Channel 3: 0.2 to 6.0 microns - reflected solar radiation Channel 4: unused - transmitted redundant time reference signals Channel 5: 0.55 to 0.75 microns - response to the TV system  The Principal Investigator for these data was Joseph D. Barksdale from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00139 (old ID 62-002A-03A).",
         "license": "proprietary"
     },
@@ -173194,7 +173480,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170993234-GES_DISC.html",
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         "description": "The TIROS-4 Low-Resolution Omnidirectional Radiometer Level 1 Radiance Data product contains the longwave radiation values in Langleys/min derived from the black and white sensors. The experiment consisted of two sets of bolometers in the form of hollow aluminum hemispheres, mounted on opposite sides of the spacecraft, and whose optical axes were parallel to the spin axis. The bolometers were thermally isolated from but in close proximity to reflecting mirrors so that the hemispheres behaved like isolated spheres in space. The experiment was designed to measure the amount of solar energy absorbed, reflected, and emitted by the earth and its atmosphere in order to calculate the Earth's radiation budget. The data were originally written on IBM 7094 machines, and these have been recovered from magnetic tapes, referred to as the Omnidirectional Radiometer Radiance (ORR) tapes. The data are archived in their text format.  The TIROS-4 satellite was successfully launched on February 8, 1962. The Low-Resolution Omnidirectional Radiometer experiment returned data for about five months. A previous instrument flew on TIROS-3 and a follow-on instrument was flown on TIROS-7, while a similar instrument flew on Explorer-7.  The Principal Investigator for these data was Verner E. Suomi from the University of Wisconsin. This product was previously available from the NSSDC with the identifier ESAD-00152 (old id 62-002A-01B).",
         "license": "proprietary"
     },
@@ -173207,7 +173493,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2152905392-GES_DISC.html",
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         "description": "The TIROS-4 Low-Resolution Omnidirectional Radiometer Level 1 Temperature Data product contains the black and white sensor temperature values in degrees Celsius. The experiment consisted of two sets of bolometers in the form of hollow aluminum hemispheres, mounted on opposite sides of the spacecraft, and whose optical axes were parallel to the spin axis. The bolometers were thermally isolated from but in close proximity to reflecting mirrors so that the hemispheres behaved like isolated spheres in space. The experiment was designed to measure the amount of solar energy absorbed, reflected, and emitted by the earth and its atmosphere in order to calculate the Earth's radiation budget. The data were originally written on IBM 7094 machines, and these have been recovered from magnetic tapes, referred to as the Omnidirectional Radiometer Temperature (ORT) tapes. The data are archived in their text format.  The TIROS-4 satellite was successfully launched on February 8, 1962. The Low-Resolution Omnidirectional Radiometer experiment returned data for about five months. A previous instrument flew on TIROS-3 and a follow-on instrument was flown on TIROS-7, while a similar instrument flew on Explorer-7.  The Principal Investigator for these data was Verner E. Suomi from the University of Wisconsin. This product was previously available from the NSSDC with the identifier ESAD-00252 (old id 62-002A-01A).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2020911863-GES_DISC.html",
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         "description": "TIROS-7 Medium-Resolution Scanning Radiometer Level 1 Final Meteorological Radiation Data (FMRT) product contains radiances expressed in five infrared/visible wavelength regions, expressed in either equivalent blackbody temperature (IR channels 1,2 and 4) or effective radiant emmitance (visible channels 3 and 5). The data will trace an elliptical, parabolic, or hyperbolic pattern on the ground due to the rotating of the instrument about the satellite spin axis. There is one orbit per file. The data were originally written on IBM 7094 machines, and these have been recovered from magnetic tapes, referred to as the Final Meteorological Radiation Tapes (FMRT). The data are archived in their original IBM 36-bit word proprietary format, also referred to as a binary TAP file.  The TIROS-7 satellite was successfully launched on June 19, 1963. The Medium-Resolution Scanning Radiometer experiment successfully returned data for two years, continuing the measurements made by its predecessors flown on TIROS-2, -3 and -4. The instrument is a five channel radiometer with a 55 km footprint at nadir with the following characteristics:  Channel 1: 14.8 to 15.5 microns - carbon dioxide absorption Channel 2: 8.0 to 12.0 microns - atmospheric window Channel 3: 0.2 to 6.0 microns - reflected solar radiation Channel 4: 8.0 to 30 microns - thermal radiation from the earth and atmosphere Channel 5: 0.55 to 0.75 microns - response to the TV system  The Principal Investigator for these data was Joseph D. Barksdale from NASA Goddard Space Flight Center. This product was previously available from the NSSDC with the identifier ESAD-00217 (old ID 63-024A-02A).",
         "license": "proprietary"
     },
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         "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this projects describes a multi-decadal Fundamental Climate Data Record (FCDR) of calibrated radiances as well as an Earth System Data Record (ESDR) of aerosol properties over the continents derived from a 32-year record of satellite near-UV observations by three sensors.    The TOMS Earth Probe version 2 Level-2 orbital data product consists of cloud fraction, cloud optical depth, normalized radiance, reflectivity, residue, and UV aerosol index at approximately 40x40 km resolution (at nadir). This product also contains ancillary variables for ocean corrected surface albedo and terrain pressure.  Total Ozone Mapping Spectrometer (TOMS) instruments have been successfully flown in orbit aboard the Nimbus-7(Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (June 1996 - December 2005), and ADEOS (Sep. 1996 - June 1997) satellites.  These Level-2 data are stored in the Hierarchical Data Format 5 (HDF5) and are available from the Goddard Earth Sciences (GES) Data and Information Services Center (DISC).",
         "license": "proprietary"
     },
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         "description": "The Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) version 8 orbital swath data product contains total column ozone, UV aerosol index, and Lambertian effective surface reflectivity (Rayleigh corrected) at approximately 50x50 km2 resolution (at nadir). This product also contains some auxiliary derived and ancillary parameters including N-values, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and data quality flags. These data are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5).  The TOMS data were produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 614).",
         "license": "proprietary"
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         "license": "proprietary"
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         "description": "This Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) version 8 daily global gridded data product contains UV aerosol index values. The data are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in an ASCII format.  The TOMS data were produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 614).",
         "license": "proprietary"
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         "description": "This Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) version 8 daily global gridded data product contains UV-B erythemal local noon irradiance values. The data are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in an ASCII format.  The TOMS data were produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 614).",
         "license": "proprietary"
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         "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this projects describes a multi-decadal Fundamental Climate Data Record (FCDR) of calibrated radiances as well as an Earth System Data Record (ESDR) of aerosol properties over the continents derived from a 40-year record of satellite near-UV observations by three sensors.    The TOMS Nimbus 7 version 2 Level-2 orbital data product consists of cloud fraction, cloud optical depth, normalized radiance, reflectivity, residue, and UV aerosol index at approximately 50x50 km resolution (at nadir). This product also contains ancillary variables for ocean corrected surface albedo and terrain pressure.  Total Ozone Mapping Spectrometer (TOMS) instruments have been successfully flown in orbit aboard the Nimbus-7(Nov. 1978 - May 1993), Meteor-3 (Aug. 1991 - Dec. 1994), Earth Probe (June 1996 - December 2005), and ADEOS (Sep. 1996 - June 1997) satellites.  These Level-2 data are stored in the Hierarchical Data Format 5 (HDF5) and are available from the Goddard Earth Sciences (GES) Data and Information Services Center (DISC).",
         "license": "proprietary"
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         "description": "Version 3 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 3. The goal of this data set is to create and archive a Level 2 SO2 Earth Science Data Record (ESDR)  from backscatter Ultraviolet (BUV) measurements from Total Ozone Mapping Spectrometer (TOMS) flown on NASA's Nimbus - 7 satellite in 1978-1993. We apply TOMS ozone team  calibration techniques and consistent MEaSUREs SO2 (MS_SO2) algorithm, to obtain the best measurement-based ESDR of volcanic and anthropogenic SO2 masses and emissions.   As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, the Goddard Earth Science (GES) Data and Information Data Center (DISC) has released a new SO2 Earth System Data Record (ESDR), TOMSN7SO2, re-processed using new 4 UV wavelength bands MS_SO2 algorithm that spans the full Nimbus 7 data period. TOMSN7SO2 is a Level 2 orbital swath product, which will be used to study the fifteen-year SO2 record from the Nimbus-7 TOMS and to expand the historical database of known volcanic eruptions.   Sulfur Dioxide (SO2) is a short-lived gas primarily produced by volcanoes, power plants, refineries, metal smelting and burning of fossil fuels. Where SO2 remains near the Earth s surface, it is toxic, causes acid rain, and degrades air quality. Where SO2 is lofted into the free troposphere, it forms aerosols that can alter cloud reflectivity and precipitation. In the stratosphere, volcanic SO2 forms sulfate aerosols that can result in climate change. ",
         "license": "proprietary"
     },
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         "description": "Daily Aerosol Index (AI) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 12-September 25, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TOMS AI is formed directly from measured TOMS radiances in two channels. It is a measure of how much the wavelength dependence of backscattered UV radiation from an atmosphere containing aerosols (Mie scattering, Rayleigh scattering, and absorption) differs from that of a pure molecular atmosphere (pure Rayleigh scattering). Quantitatively, the AI is defined at http://toms.gsfc.nasa.gov/aerosols/AI_definition/ai_ep_definition.pdf. Positive values represent absorbing aerosols (dust and smoke); negative values represent non-absorbing aerosols. The identification is not perfect because of geophysical reasons (e.g., when aerosols are too low to the ground).The data from TOMS records have been used increasingly to understand the behavior of aerosols within the atmosphere. The TOMS is the first instrument to allow observation of aerosols as the particles cross the land/sea boundary. Using these data it is possible to observe a wide range of phenomena such as desert dust storms, forest fires, and biomass burning.The TOMS AI data are a daily gridded Level-3 product (ASCII .dat format) that covers the area of 40 deg. S to the Equator and 40 deg. W to 80 deg. E. There is also a JPEG image of each data file.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789742026-ORNL_CLOUD.html",
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         "description": "Tropical Tropospheric Ozone (TTO) data from Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) for the period of August 8-September 29, 2000 were processed and provided by the Atmospheric Chemistry and Dynamics Branch at NASA/GSFC for the SAFARI 2000 Dry Season Aircraft Campaign.The TTO measurement is derived from TOMS total ozone (Thompson and Hudson, 1999; Thompson et al., 2001) using the modified-residual method to separate stratospheric ozone from tropospheric ozone. The tropospheric ozone column thickness is reported in Dobson Units (DU).EP TOMS is currently the only NASA spacecraft on orbit specializing in ozone retrieval. EP TOMS was launched in 1996 into an orbit 500 km rather than the 950 km that was originally planned. The Earth Probe satellite was boosted to 740 km in 1997 when the ADEOS satellite failed. The lower orbit of EP TOMS decreased the size of the footprint of each measurement, which increased the resolution and also increased the ability to make measurements over cloudless scenes. This orbit was chosen to improve the ability of the TOMS instrument to make measurements of UV-absorbing aerosols in the troposphere and enhanced the capability of converting the TOMS aerosol measurements into geophysical quantities such as optical depth. Tropospheric aerosols play a major role in the Earth's climate and the capability to measure them from a TOMS instrument had recently been developed using data from Nimbus-7 and Meteor-3 TOMS.The TOMS Tropospheric Ozone data are 9-day averaged, gridded (1-degree by 2-degree) ASCII products. There is also a GIF image of each data file. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2736753162-LARC_ASDC.html",
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         "description": "TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 is the in situ collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data from the Multiple-Angle Spectrometer Probe (MASP), 2D-C Aerosol Probe, and FSSP Aerosol Size distributions are featured in this data product. Data collection is complete.    The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts.    Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.",
         "license": "proprietary"
     },
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         "description": "TOTE-VOTE_Aerosol_AircraftInSitu_DC8_Data_1 is the in situ collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data from the Multiple-Angle Spectrometer Probe (MASP), 2D-C Aerosol Probe, and FSSP Aerosol Size distributions are featured in this data product. Data collection is complete.    The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts.    Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.",
         "license": "proprietary"
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         "description": "TOTE-VOTE_AircraftRemoteSensing_DC8_DIAL_Data_1 is the remotely sensed Differential Absorption Lidar (DIAL) data collected onboard the DC-8 aircraft during the Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign. Data collection is complete.  The Tropical Ozone Transport Experiment \u2013 Vortex Ozone Transport Experiment (TOTE-VOTE) campaign was conducted by NASA from December 1995 to February 1996. TOTE-VOTE took place in the Pacific region with the goal of gaining a better understanding of background transport processes from tropical/polar regions to midlatitudes. Nineteen flights were conducted using the NASA DC-8 aircraft and balloon sondes with the purpose of measuring the transport of filaments of air moved in or out of the arctic polar vortex and the tropical stratospheric reservoir. TOTE-VOTE also utilized ground-based instruments along with aircrafts.  Various instrumentation was used during TOTE-VOTE in order to achieve the mission objectives. The DC-8 aircraft was equipped with the NCAR NOxyO3 instrument, the NASA Langley Airborne Differential Absorption Lidar (DIAL) system, the Forward Scattering Spectrometer Probe (FSSP), the Microwave Temperature Profiler (MTP), the Multiple-Angle Aerosol Spectrometer Probe (MASP), and the diode laser spectrometer system, historically known as the Differential Absorption Carbon monOxide Measurement (DACOM). The NCAR NOxyO3 is a type of 4-channel chemiluminescence instrument that was used to quantify NOx (NO and NO2), NOy (total reactive nitrogen), and ozone (O3) in the air. The DIAL system used four lasers to make DIAL O3 profiles, along with collecting data on aerosol backscattering, aerosol depolarization ratio, aerosol extinction, and aerosol optical depth. The FSSP is an optical particle counter that measured particle size distribution. The MTP is a passive microwave radiometer that measured natural thermal emissions and was used during TOTE-VOTE to record temperature. The MASP spectrometer collected in-situ measurements of particle concentration, particle size distribution, and particle extinction. Along with the MASP\u2019s in-situ measurements, the DACOM spectrometer utilized three diode lasers at different wavelengths to take in-situ measurements of N2O, CO, CH4, and CO2 for TOTE-VOTE. Ground-based instruments collected lidar data while balloon sondes gathered information on wind direction, wind speed, atmospheric pressure, and air temperature.",
         "license": "proprietary"
     },
@@ -175846,7 +176132,7 @@
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         "description": "NOAA's TIROS (Television Infrared Observation Satellite) Operational Vertical Sounder (TOVS) is a suite of three sensors: the Microwave Sounding Unit (MSU), the High resolution Infrared Radiation Sounder (HIRS), and the Stratospheric Sounding Unit (SSU) aboard the NOAA series of polar-orbiting operational meteorological satellites. TOVS-derived data provide a means to investigate long-term climate change and interannual variability and study local and periodic phenomena such as El Nino and stratospheric warmings. A set of the derived meteorological parameters for southern Africa have been selected by SAFARI 2000.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777741400-ORNL_CLOUD.html",
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         "description": "This data set contains atmospheric chemistry and meteorological data from the NASA Transport and Atmospheric Chemistry near the Equator-Atlantic (TRACE-A) field study. The NASA TRACE-A study took place in August 1992 to determine the cause and source of high concentrations of ozone that accumulate over the Atlantic ocean between southern Africa and South America during the months of August through October. The processed, quality controlled and integrated data in the documented Pre-LBA Data sets were originally published as a set of three CD-ROMs (Marengo and Victoria, 1998) but have now been archived individually. ",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2813511488-LARC_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2813511488-LARC_CLOUD.html",
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         "description": "TRACE-A_AircraftRemoteSensing_DC8_DIAL_Data is the remotely sensed Differential Absorption Lidar (DIAL) data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2813530054-LARC_CLOUD.html",
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         "description": "TRACE-A_Brazil_Data is the aircraft and rawinsonde data collected in Brazil during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data from the Advanced Very High Resolution Radiometer (AVHRR) is featured in this collection. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2813514891-LARC_CLOUD.html",
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         "description": "TRACE-A_Merge_Data is merge data files created from data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2813523553-LARC_CLOUD.html",
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         "description": "TRACE-A_MetNav_AircraftInSitu_DC8_Data is the in situ meteorology and navigation data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data collection for this product is complete.    TRACE-A_TraceGas_AircraftInSitu_DC8_Data is the in-situ trace gas data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data from the Two Photon - Laser Induced Fluorescence (TP-LIF) and Differential Absorption of CO, CH4, N2O Measurements (DACOM) instruments are featured in this collection. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2813538048-LARC_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2813538048-LARC_CLOUD.html",
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         "description": "TRACE-A_Satellite_Data is the supplementary satellite data collected  during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data from the NOAA 10, 11, and 12 satellites and the Total Ozone Mapping Spectrometer (TOMS) satellite instrument are featured in this collection. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
         "license": "proprietary"
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@@ -176548,7 +176834,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2813533459-LARC_CLOUD.html",
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         "description": "TRACE-A_Sondes_Data is the balloonsonde and ozonesonde data collected during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
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         "description": "TRACE-A_TraceGas_AircraftInSitu_DC8_Data is the in-situ trace gas data collected onboard the DC-8 aircraft during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data from the Two Photon - Laser Induced Fluorescence (TP-LIF) and Differential Absorption of CO, CH4, N2O Measurements (DACOM) instruments are featured in this collection. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
         "license": "proprietary"
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         "description": "TRACE-A_Trajectory_Data is the kinematic trajectory data collected during the Transport and Atmospheric Chemistry near the Equator - Atlantic (TRACE-A) suborbital campaign. Data from the Two Photon - Laser Induced Fluorescence (TP-LIF) and Differential Absorption of CO, CH4, N2O Measurements (DACOM) instruments are featured in this collection. Data collection for this product is complete.    The TRACE-A mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-A was conducted in the Atlantic from September 21 to October 24, 1992. TRACE-A had the objective of determining the cause and source of the high concentrations of ozone that accumulated over the Atlantic Ocean between southern Africa and South America from August to October.\u202fNASA partnered with the Brazilian Space Agency (INPE) to accomplish this goal.\u202f     The NASA DC-8 aircraft\u202fand\u202fozonesondes\u202fwere\u202futilized during TRACE-A to collect the necessary data. The DC-8 was equipped with 19 instruments. A few\u202finstruments on the DC-8 include the Differential Absorption Lidar (DIAL),\u202fthe Laser-Induced Fluorescence, the O3-NO Ethylene/Forward Scattering Spectrometer, the Modified\u202fLicor, and the DACOM IR Laser Spectrometer. The DIAL was responsible for a variety of measurements, which include Nadir IR aerosols, Nadir UV aerosols, Zenith IR aerosols, Zenith VS aerosols, ozone,\u202fand ozone column. The Laser-Induced Fluorescence instrument\u202fcollected measurements on\u202fNxOy\u202fin the atmosphere. Measurements of ozone were recorded by the O3-NO Ethylene/Forward Scattering Spectrometer while the Modified\u202fLicor\u202frecorded CO2. Finally, the DACOM IR Laser Spectrometer gathered an assortment of data points, including CO, O3, N2O, CH4, and CO2.\u202fOzonesondes\u202fplayed a role in data collection for TRACE-A along with the DC-8 aircraft. The sondes were dropped from the DC-8 aircraft in order to gather data on ozone, temperature, and atmospheric pressure.\u202f",
         "license": "proprietary"
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         "description": "TRACE-P_Aerosol_AircraftInSitu_P3B_Data is the in-situ aerosol data collected onboard the P-3B aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data from the Chemical Ionization Mass Spectrometer (CIMS) and the Differential Absorption of CO, CH4, N2O Measurements (DACOM) instruments are featured in this collection. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
         "license": "proprietary"
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         "description": "TRACE-P_Cloud_AircraftInSitu_DC8_Data is the in-situ cloud data collected onboard the DC-8 aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_Ground_Data is the ground site data collected during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign.  Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_Merge_Data is the merge data files created from data collected during during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_MetNav_AircraftInSitu_DC8_Data is the in situ meteorology and navigation data collected onboard the DC-8 aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data from the Diode Laser Hygrometer (DLH) instrument is featured in this collection. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_MetNav_Aircraft_InSitu_P3B_Data is the in situ meteorology and navigation data collected onboard the P-3B aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data from the P-3B Turbulent Air Motion Measurement System (TAMMS) is featured in this collection. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_Model_Data is the model data collected during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
         "license": "proprietary"
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         "license": "proprietary"
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         "description": "TRACE-P_Sondes_Data is the balloonsonde and ozonesonde data collected during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_TraceGas_AircraftInSitu_DC8_Data is the in-situ trace gas data collected onboard the DC-8 aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data from the Two Photon - Laser Induced Fluorescence (TP-LIF) and Differential Absorption of CO, CH4, N2O Measurements (DACOM) instruments are featured in this collection. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_TraceGas_AircraftInSitu_P3B_Data is the in-situ trace gas data collected onboard the P-3B aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data from the Chemical Ionization Mass Spectrometer (CIMS) and the Differential Absorption of CO, CH4, N2O Measurements (DACOM) instruments are featured in this collection. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_Trajectory_DC8_Data is the trajectory data collected onboard the DC-8 aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
         "license": "proprietary"
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         "description": "TRACE-P_Trajectory_P3B_Data is the trajectory data collected onboard the P-3B aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data from the Chemical Ionization Mass Spectrometer (CIMS) and the Differential Absorption of CO, CH4, N2O Measurements (DACOM) instruments are featured in this collection. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
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         "description": "TRACE-P_jValue_AircraftInSitu_DC8_Data is the photolysis frequencies (j-values) measured along the DC-8 flight during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
         "license": "proprietary"
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         "description": "TRACE-P_jValue_AircraftInSitu_P3B_Data is the photolysis frequencies (j-values) measured along the P-3B flight aircraft during the Transport and Chemical Evolution over the Pacific (TRACE-P) suborbital campaign. Data collection for this product is complete.    The NASA TRACE-P mission was a part of NASA\u2019s Global Tropospheric Experiment (GTE) \u2013 an assemblage of missions conducted from 1983-2001 with various research goals and objectives.\u202fTRACE-P was a multi-organizational campaign with NASA, the National Center for Atmospheric Research (NCAR), and several US universities.\u202fTRACE-P deployed\u202fits payloads in the Pacific between the months of March and April 2001 with the goal of studying the air chemistry emerging\u202ffrom Asia\u202fto the western Pacific.\u202fAlong with this, TRACE-P had the objective\u202fstudying\u202fthe chemical evolution of the air as it moved away from Asia.\u202f     In order to accomplish its goals, the NASA DC-8 aircraft and NASA P-3B aircraft were deployed, each equipped with various instrumentation.\u202fTRACE-P also relied on ground sites,\u202fand\u202fsatellites\u202fto collect data. The DC-8 aircraft was equipped with 19 instruments in total\u202fwhile the P-3B\u202fboasted\u202f21 total instruments.\u202fSome instruments on the DC-8 include the Nephelometer, the GCMS, the Nitric Oxide Chemiluminescence, the Differential Absorption Lidar (DIAL), and the Dual Channel Collectors and Fluorometers, HPLC. The Nephelometer was utilized to gather data on various\u202fwavelengths\u202fincluding\u202faerosol\u202fscattering\u202f(450, 550, 700nm), aerosol absorption (565nm), equivalent BC mass, and air density ratio. The GCMS was responsible for capturing a multitude of compounds in the atmosphere, some of which include CH4, CH3CHO, CH3Br, CH3Cl, CHBr3, and C2H6O.\u202fDIAL was used for a variety of measurements, some of which include aerosol wavelength dependence (1064/587nm), IR aerosol scattering ratio (1064nm),\u202ftropopause heights and ozone columns, visible aerosol scattering ratio, composite tropospheric ozone cross-sections, and visible aerosol depolarization. Finally, the Dual Channel Collectors and Fluorometers, HPLC collected data on H2O2, CH3OOH, and CH2O in the atmosphere.\u202fThe P-3B aircraft was equipped with various instruments for TRACE-P, some of which include\u202fthe MSA/CIMS, the Non-dispersive IR Spectrometer, the PILS-Ion Chromatograph, and the\u202fCondensation particle counter and Pulse Height Analysis (PHA). The\u202fMSA/CIMS measured OH, H2SO4, MSA, and HNO3. The Non-dispersive IR Spectrometer took measurements on CO2 in the atmosphere. The PILS-Ion Chromatograph recorded measurements of compounds and elements in the atmosphere, including sodium, calcium, potassium, magnesium, chloride, NH4, NO3, and SO4. Finally, the Condensation particle counter and PHA was used to gather data on total UCN, UCN 3-8nm, and UCN 3-4nm. Along with the aircrafts, ground stations measured air quality from China along with C2H2, C2H6, CO, and HCN.\u202fFinally, satellites imagery was used to collect a multitude of data, some of the uses were to observe the history of lightning flashes,\u202fSeaWiFS\u202fcloud imagery, 8-day exposure to TOMS aerosols, and\u202fSeaWiFS\u202faerosol optical thickness. The imagery was used to best aid in planning for the aircraft deployment.\u202f\u202f ",
         "license": "proprietary"
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         "description": "This TRMM Visible and Infrared Scanner (VIRS) Level 1B Calibrated Radiance Product (1B01) contains calibrated radiances and auxiliary geolocation information from the five channels of the VIRS instrument, for each pixel of each scan. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the VIRS measurements. A file contains a single orbit of data with a file size of about 95 MB. The EOSDIS \"swath\" structure is used to accommodate the actual geophysical data arrays. There are 16 files of VIRS 1B01 data produced per day.  For channels 1 and 2, Level 1B radiances are derived from the Level 1A (1A01) sensor counts by computing calibration parameters (gain and offset) derived from the counts registered during space and solar and/or lunar views. New calibration parameters are produced every one to four weeks. Channels 3, 4, and 5 are calibrated using the internal blackbody and the space view. These calibration parameters, together with a quadratic term determined pre-launch, are used to generate a counts vs. radiance curve for each band, which is then used to convert the earth-view pixel counts to spectral radiances.  Geolocation and channel data are written out for each pixel along the scan, whereas the time stamp, scan status (containing scan quality information), navigation, calibration coefficients, and solar/satellite geometry are specified on a per-scan basis. There are in general 18026 scans along the orbit pre-boost and 18223 post-boost, with each scan consisting of 261 pixels. The scan width is about 720 km pre-boost and 833 km post-boost.  Changes in horizontal resolution resulting from the TRMM boost that occurred on 24 August 2001:  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 720 km; Horizontal Resolution: 2.2 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 833 km; Horizontal Resolution: 2.4 km \t",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282110402-GES_DISC.html",
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         "description": " The new version of these data is in GPM-like format (consistent with the GPM Microwave Imager data format), and can be found under the name GPM_1BTMI (search by keyword GPM_1BTMI).   This dataset contains TRMM Micrwave Imager (TMI) L1B calibrated radiances in terms of Brightness Temperatures.  The TMI calibration algorithm (1B11) converts the radiometer counts to antenna temperatures by applying a linear relationship of the form Ta = c1 + c2 x count. The coefficients are provided by the instrument contractor. Antenna temperatures are corrected for cross-polarization and spill over to produce brightness temperatures (Tb), but no antenna beam pattern correction or sample to pixel averaging are performed. Temperatures are provided at 104 scan positions for the low frequency channels and 208 scan positions at 85 GHz. There are four samples per pixel (3 -dB beamwidth) at 10 GHz, two samples at 19, 22, and 37 GHz, and one sample per pixel for the 85 GHz. Data Flow Description   Changes in horizontal resolution resulting from the TRMM boost that occurred on 24 August 2001:  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 760 km; Horizontal Resolution: 4.4 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 878 km; Horizontal Resolution: 5.1 km ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282110505-GES_DISC.html",
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         "description": "The TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines  the layer depth of the precipitation.            The 1B21 calculates the received power at the PR receiver input point from the Level-0 count value which is linearly proportional to the logarithm of the PR receiver output power. To convert the count value to the input power, extensive internal calibrations are applied, which are mainly based upon the system model, temperature dependence of model parameters and many temperature sensors attached at various locations of the PR. Periodically the input-output characteristics are measured using an internal calibration loop for the IF unit and later receiver stages. To make an absolute calibration, an Active Radar Calibrator (ARC) is placed at Kansai Branch of CRL and overall system gain of the PR is being measured every 2 months.  Using the transfer function based on the above internal and external calibrations, the PR received power is obtained. Note that the value assumes that the signal follows the Rayleigh fading, so if the fading characteristics of a scatter is different, a small bias error may occur (within 1 or 2 dB). \t Changes in horizontal resolution resulting from the TRMM boost that occurred on 24 August 2001:  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 215 km; Horizontal Resolution: 4.3 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 247 km; Horizontal Resolution: 5.0 km",
         "license": "proprietary"
     },
@@ -176964,7 +177250,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654209-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654209-GES_DISC.html",
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         "description": "The TRMM_1B51 product displays the existence of rain in the radar volume scan. 'Existence' is the fraction of the radar FOV which has measurable precipitation. The GV radar FOV is defined as a base scan (i.e., the lowest level sweep).  Each product file has the Existence data of one site (not one radar) for one month.   A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -176977,7 +177263,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282110521-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282110521-GES_DISC.html",
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         "description": "The TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines  the layer depth of the precipitation.            The 1C21 calculates the effective radar reflectivity factor at 13.8 GHz without any propagation loss (due to rain or any other atmospheric gas) correction (Zm). Therefore, the Zm value can be calculated just by applying a radar equation for volume scatter with PR system parameters. The noise-equivalent Zm is about 21 dBZ. Through the subtraction of the system noise, the Zm value as small as 16 or 18 dBZ are still usable although the data quality is marginal.  In 1C21, all echoes stored in 1B21 are converted to \"dBZ\" unit. This is not relevant for \"non-rain\" echo; however, this policy is adopted so that the 1B21 and 1C21 product format should be as close as possible except for the following points:          - Radar quantity is Zm in dBZ unit instead of received power (dBm). - Data at echo-free range bins judged in 1B21 are replaced with a dummy value.  Changes in horizontal resolution resulting from the TRMM boost that occurred on 24 August 2001:  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 215 km; Horizontal Resolution: 4.3 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 247 km; Horizontal Resolution: 5.0 km ",
         "license": "proprietary"
     },
@@ -176990,7 +177276,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1352386182-GES_DISC.html",
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         "description": "This dataset is part of the University of Washington TRMM Ground Validation products. Files are in \"Universal Format\", described in BAMS, Vol 61, No 11, November 1980, pp. 1401-1404.  The purpose of the 1C51UW algorithm is to remove non-meteorological radar echoes that adversely affect the quality of higher level products, such as clutter associated with insects, birds, chaff, wildfires, antenna towers, and anomalous propagation (AP). Eight adjustable parameters, three echo height thresholds and five radar reflectivity thresholds, are used to optimize the performance of the algorithm. Optimum performance is time consuming and requires an analyst to select different sets of parameters on a per volume scan basis, and on occasions performing several iterations while adjusting one or more of the parameters.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177003,7 +177289,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654210-GES_DISC.html",
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         "description": "The purpose of the 1C51 algorithm is to remove non-meteorological radar echoes that adversely affect the quality of higher level products, such as clutter associated with insects, birds, chaff, wildfires, antenna towers, and anomalous propagation (AP). Eight adjustable parameters, three echo height thresholds and five radar reflectivity thresholds, are used to optimize the performance of the algorithm. Optimum performance is time consuming and requires an analyst to select different sets of parameters on a per volume scan basis, and on occasions performing several iterations while adjusting one or more of the parameters.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177016,7 +177302,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060543-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060543-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_2A12_7",
         "description": "The new version of these data is in GPM-like format and can be found under the name GPM_2AGPROFTRMMTMI_CLIM.  This dataset, 2A12, \u201dTMI Profiling\u201d, generates surface rainfall and vertical hydrometeor profiles on a pixel by pixel basis from the TRMM Microwave Imager (TMI) brightness temperature data using the Goddard Profiling algorithm GPROF2010. Because the vertical information comes from a radiometer, it is not written out in independent vertical layers like the TRMM Precipitation Radar. Instead, the output is referenced to one of 100 typical structures for each hydrometeor or heating profile. These vertical structures are referenced as clusters in the output structure. Vertical hydrometeor profiles can be reconstructed to 28 layers by knowing the cluster number (i.e. shape) of the profile and a scale factor that is written for each pixel.  This product contains hydrometeor profiles of cloud liquid water, precipitation water, cloud ice water, precipitation ice, rainfall type, and latent heating in 28 atmospheric layers.   Changes in horizontal resolution resulting from the TRMM boost that occurred on 24 August 2001:  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 760 km; Horizontal Resolution: 4.4 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 878 km; Horizontal Resolution: 5.1 km ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060544-GES_DISC.html",
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         "description": "The new version of these data is in GPM-like format (consistent with the GPM Dual-frequency Radar data format), and can be found under the name GPM_2APR.  This is the sigma zero algorithm, which inputs the PR power (1B21) and computes estimates of the path attenuation and its reliability by using the surface as a reference target. It also computes the spatial and temporal statistics of the surface scattering cross section and classifies the cross sections into land/ocean and rain/no rain categories. Changes in horizontal resolution resulting from the TRMM boost that occurred on 24 August 2001:  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 215 km; Horizontal Resolution: 4.3 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 247 km; Horizontal Resolution: 5.0 km ",
         "license": "proprietary"
     },
@@ -177042,7 +177328,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060545-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060545-GES_DISC.html",
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         "description": "The new version of these data is in GPM-like format (consistent with the GPM Dual-frequency Radar data format), and can be found under the name GPM_2APR.  The TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning single-frequency radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines the layer depth of the precipitation.  PR 2A23 produces a rain/no-rain flag. Its main objectives are (1) to detect bright band (BB), (2) to classify rain type, and (3) to detect warm rain.  2A23 uses two different methods for classifying rain type: (1) vertical profile method (V-method) and (2) horizontal pattern method (H-method).  Both methods classify rain into three categories: stratiform, convective, and other. To make the results user-friendly, 2A23 outputs a unified rain type. Further information about 2A23 can be found in Awaka et al. (1998).  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 215 km; Horizontal Resolution: 4.3 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 247 km; Horizontal Resolution: 5.0 km ",
         "license": "proprietary"
     },
@@ -177055,7 +177341,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060508-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060508-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_2A25_7",
         "description": "The new version of these data is in GPM-like format (consistent with the GPM Dual-frequency Radar data format), and can be found under the name GPM_2APR.  The TRMM 2A25 data are estimates of the three-dimensional distribution of rain from the TRMM Precipitation Radar. The average rainfall rate between two pre-defined altitudes is calculated for each beam position. Other output data include parameters of Z-R relationships, integrated rain rate of each beam, range bin numbers of rain layer boundaries, and many intermediate parameters. Iguchi and Meneghini (1994) describe this algorithm.  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 215 km; Horizontal Resolution: 4.3 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 247 km; Horizontal Resolution: 5.0 km \t",
         "license": "proprietary"
     },
@@ -177068,7 +177354,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654211-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654211-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_2A52_7",
         "description": "The TRMM_2A52 product displays the existence of rain in the radar volume scan. 'Existence' is the fraction of the radar FOV which has measurable precipitation. The GV radar FOV is defined as a base scan (i.e., the lowest level sweep).  Each product file has the Existence data of one site (not one radar) for one month.   A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177081,7 +177367,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506692-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506692-GES_DISC.html",
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         "description": "This dataset is part of the University of Washington TRMM Ground Validation products.  Instantaneous rain rate cartesian grid based on baseUW and 2A54UW. Units are mm/hr. Min range is 17 km, max range is 150 km. Note that in the netCDF files, \"alt\" (altitude) is assigned the elevation angle of the lowest sweep (which is used to create baseUW) and \"z_spacing\" has no meaning.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177094,7 +177380,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654212-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654212-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_2A53_7",
         "description": "'Radar Site Rain Map', is an instantaneous surface rain rate map in Cartesian coordinates with a 2 km horizontal resolution. At single radar sites, the map covers an area of 300km x 300km. For the multiple radar site in Texas, the map covers a region of 724 km x 568 km, and in Florida 512 km x 704 km.   A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177107,7 +177393,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506693-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506693-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_2A54UW_7",
         "description": "This dataset is part of the University of Washington TRMM Ground Validation products.  Instantaneous convective-stratiform cartesian grid based on baseUW. Values are 0 (no echo), 1 (stratiform), and 2 (convective). Min range is 17 km, max range is 150 km. Note that in the netCDF files, \"alt\" (altitude) is assigned the elevation angle of the lowest sweep (which is used to create baseUW) and \"z_spacing\" has no meaning.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177120,7 +177406,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654097-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654097-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_2A54_7",
         "description": "'Radar Site Convective/Stratiform Map', is an instantaneous map in Cartesian coordinates with a 2 km resolution. At single radar sites, the map covers an area of 300 km x 300 km. For the multiple radar site in Texas, the map covers a region of 724 km x 568 km, and in Florida 512 km x 704 km. The map identifies the surface precipitation as convective or stratiform.   A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177133,7 +177419,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506694-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506694-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgbW9udGhseSBncmlkcyBmcm9tIG5vYWEtMTAgdjAxICh0b3ZzYm1uZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUT1ZTQk1OR1wiLFwiMVwiLDEyNzQ2MjU2ODcsMjRdIiwidW1tIjoiW1widG92cyBsbWQgbW9udGhseSBncmlkcyBmcm9tIG5vYWEtMTAgdjAxICh0b3ZzYm1uZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUT1ZTQk1OR1wiLFwiMVwiLDEyNzQ2MjU2ODcsMjRdIn0%3D/TRMM_2A55UW_7",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgZGFpbHkgZ3JpZHMgZnJvbSBub2FhLTEyIHYwMSAodG92c2JkbmQpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVE9WU0JETkRcIixcIjFcIiwxMjc0NjI1Njg0LDIyXSIsInVtbSI6IltcInRvdnMgbG1kIGRhaWx5IGdyaWRzIGZyb20gbm9hYS0xMiB2MDEgKHRvdnNiZG5kKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRPVlNCRE5EXCIsXCIxXCIsMTI3NDYyNTY4NCwyMl0ifQ%3D%3D/TRMM_2A55UW_7",
         "description": "This dataset is part of the University of Washington TRMM Ground Validation products.  Multiple-level cartesian grid containing output of NCAR SPRINT interpolation of CZ and VR fields of 1C51UW. Horizontal extent is 150x150km and resolution is 2km. Vertical range is 2-15km and resolution is 1km. Unlike other products, 2A55UW is not created for every volume but only for volumes of interest. These are defined as volumes within +/-15 minutes of overpass times and volumes with significant rainfall (areal rainfall rate greater or equal  0.15mm/hr).  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177146,7 +177432,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654098-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654098-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgbW9udGhseSBncmlkcyBmcm9tIG5vYWEtMTAgdjAxICh0b3ZzYm1uZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUT1ZTQk1OR1wiLFwiMVwiLDEyNzQ2MjU2ODcsMjRdIiwidW1tIjoiW1widG92cyBsbWQgbW9udGhseSBncmlkcyBmcm9tIG5vYWEtMTAgdjAxICh0b3ZzYm1uZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUT1ZTQk1OR1wiLFwiMVwiLDEyNzQ2MjU2ODcsMjRdIn0%3D/TRMM_2A55_7",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgZGFpbHkgZ3JpZHMgZnJvbSBub2FhLTEyIHYwMSAodG92c2JkbmQpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVE9WU0JETkRcIixcIjFcIiwxMjc0NjI1Njg0LDIyXSIsInVtbSI6IltcInRvdnMgbG1kIGRhaWx5IGdyaWRzIGZyb20gbm9hYS0xMiB2MDEgKHRvdnNiZG5kKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRPVlNCRE5EXCIsXCIxXCIsMTI3NDYyNTY4NCwyMl0ifQ%3D%3D/TRMM_2A55_7",
         "description": "'Radar Site 3-D Reflectivities', is composed of 3 different fields. The first field has an array of 3-D reflectivities in Cartesian coordinates with a 2 km horizontal resolution over an area of 300 km x 300 km for single radar sites, and 724 km x 568 km for Texas multiple radar site, 512 km x 704 km for Florida multiple radar site. It has a vertical resolution of 1.5km and a height range up to 19.5 km. The second field has an array of vertical profiles based on the first field, and the third field has an array of the Contoured Frequency by Altitude Diagram (CFAD) data based on the first and second field.   A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177159,7 +177445,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654213-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654213-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIHJhaW4gcmF0ZSBtYXAgbDIgMSBob3VyIDIga20gdjcgKHRybW1fMmE1MykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUk1NXzJBNTNcIixcIjdcIiwxMzMyNjU0MjEyLDQwXSIsInVtbSI6IltcInRybW0gZ3JvdW5kIHZhbGlkYXRpb24gcmFkYXIgc2l0ZSByYWluIHJhdGUgbWFwIGwyIDEgaG91ciAyIGttIHY3ICh0cm1tXzJhNTMpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTUzXCIsXCI3XCIsMTMzMjY1NDIxMiw0MF0ifQ%3D%3D/TRMM_2A56_7",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_2A56_7",
         "description": "The program rgmin generates 1-minute hourly rain rates from discrete tipping bucket rain gauge data by applying an interpolation algorithm. The interpolating routine is based on the cubic spline routine published in the book \"Numerical Recipes\". The mathematical theory underlying this algorithm is presented in section 3.3 of the book along with a copy of the source code. The mathematics involved will not be described in any detail, rather the spline will be described in context with its application to the broader algorithm being applied in rgmin.   A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177172,7 +177458,7 @@
         "bbox": "-180, -38, 180, 38",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060546-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282060546-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgbW9udGhseSBncmlkcyBmcm9tIG5vYWEtMTAgdjAxICh0b3ZzYm1uZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUT1ZTQk1OR1wiLFwiMVwiLDEyNzQ2MjU2ODcsMjRdIiwidW1tIjoiW1widG92cyBsbWQgbW9udGhseSBncmlkcyBmcm9tIG5vYWEtMTAgdjAxICh0b3ZzYm1uZykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUT1ZTQk1OR1wiLFwiMVwiLDEyNzQ2MjU2ODcsMjRdIn0%3D/TRMM_2B31_7",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgZGFpbHkgZ3JpZHMgZnJvbSBub2FhLTEyIHYwMSAodG92c2JkbmQpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVE9WU0JETkRcIixcIjFcIiwxMjc0NjI1Njg0LDIyXSIsInVtbSI6IltcInRvdnMgbG1kIGRhaWx5IGdyaWRzIGZyb20gbm9hYS0xMiB2MDEgKHRvdnNiZG5kKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRPVlNCRE5EXCIsXCIxXCIsMTI3NDYyNTY4NCwyMl0ifQ%3D%3D/TRMM_2B31_7",
         "description": "The TRMM combined algorithm (2B31) combines data from the TMI and PR to produce the best rain estimate for TRMM. This combined rainfall product is derived from vertical hydrometeor profiles using data from the PR radar and TMI. It also includes computed correlation-corrected, mass-weighted, mean drop diameter and its standard deviation, and latent heating data.  Pre-Boost (before 7 August 2001): Temporal Resolution: 91.5 min/orbit ~ 16 orbits/day; Swath Width: 215 km; Horizontal Resolution: 4.3 km   Post-Boost (after 24 August 2001): Temporal Resolution: 92.5 min/orbit ~ 16 orbits/day; Swath Width: 247 km; Horizontal Resolution: 5.0 km \t",
         "license": "proprietary"
     },
@@ -177185,7 +177471,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032623-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032623-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIHJhaW4gcmF0ZSBtYXAgbDIgMSBob3VyIDIga20gdjcgKHRybW1fMmE1MykgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUk1NXzJBNTNcIixcIjdcIiwxMzMyNjU0MjEyLDQwXSIsInVtbSI6IltcInRybW0gZ3JvdW5kIHZhbGlkYXRpb24gcmFkYXIgc2l0ZSByYWluIHJhdGUgbWFwIGwyIDEgaG91ciAyIGttIHY3ICh0cm1tXzJhNTMpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTUzXCIsXCI3XCIsMTMzMjY1NDIxMiw0MF0ifQ%3D%3D/TRMM_3A11_7",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_3A11_7",
         "description": "The new equivalent for this dataset should be searched for as \"GPM_3GPROFTRMMTMI_CLIM\".  The TMI Gridded Oceanic Rainfall Product, also known as TMI Emission, consists of 5 degree by 5 degree monthly oceanic rainfall maps using TMI Level 1 data as input. Statistics of the monthly rainfall, including number of samples, standard deviation, goodness-of-fit (of the brightness temperature histogram to the lognormal rainfall distribution function) and rainfall probability are also included in the output for each grid box.  TMI brightness temperature histograms at 1 degree intervals are generated based on the 19, 21 and 19-21 GHz combination channels obtained from the Level 1B (calibrated brightness temperature) TMI product. Monthly rainfall indices over the ocean are derived by statistically matching monthly histograms of brightness temperatures with model calculated rainfall Probability Distribution Functions (PDF) using the 19-21 GHz combination data. Retrieved monthly rainfall data must pass a quality test based on the quality of the PDF fit.",
         "license": "proprietary"
     },
@@ -177198,7 +177484,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032625-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032625-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_3A12_7",
         "description": "The new equivalent for this dataset should be searched for as \"GPM_3GPROFTRMMTMI_CLIM\".  This product contains global monthly means of surface precipitation rate, rain rate, convective surface precipitation rate and 28 vertical layers of hydrometeor contents (cloud liquid water, rain water, cloud ice liquid water, snow liquid water, graupel liquid water and latent heating) on 0.5 x 0.5 degree grids.",
         "license": "proprietary"
     },
@@ -177211,7 +177497,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032627-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032627-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBwcmVjaXBpdGF0aW9uIHJhZGFyIHN1cmZhY2UgY3Jvc3Mtc2VjdGlvbiBsMiAxLjUgaG91cnMgIHY3ICh0cm1tXzJhMjEpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTIxXCIsXCI3XCIsMTI4MjA2MDU0NCw0NV0iLCJ1bW0iOiJbXCJ0cm1tIHByZWNpcGl0YXRpb24gcmFkYXIgc3VyZmFjZSBjcm9zcy1zZWN0aW9uIGwyIDEuNSBob3VycyAgdjcgKHRybW1fMmEyMSkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUk1NXzJBMjFcIixcIjdcIiwxMjgyMDYwNTQ0LDQ1XSJ9/TRMM_3A25_7",
         "description": "The new version of these data is in GPM-like format (consistent with the GPM Dual-frequency Radar data format), and can be found under the name GPM_3PR.  This product consists of monthly statistics of the PR measurements at both a low (5 degrees x 5 degrees) and a high (0.5 degrees x 0.5 degrees) horizontal resolution. The low resolution grids are in the Planetary Grid 1 structure and include 1) mean and standard deviation of the rain rate, reflectivity, path-integrated attenuation (PIA), storm height, Xi, bright band height and the NUBF (Non-Uniform Beam Filling) correction; 2) rain fractions; 3) histograms of the storm height, bright-band height, snow-ice layer, reflectivity, rain rate, path-attenuation and NUBF correction; 4) correlation coefficients. The high resolution grids are in the Planetary Grid 2 structure and contain mean rain rate along with standard deviation and rain fractions. \t",
         "license": "proprietary"
     },
@@ -177224,7 +177510,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032628-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032628-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBwcmVjaXBpdGF0aW9uIHJhZGFyIHN1cmZhY2UgY3Jvc3Mtc2VjdGlvbiBsMiAxLjUgaG91cnMgIHY3ICh0cm1tXzJhMjEpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTIxXCIsXCI3XCIsMTI4MjA2MDU0NCw0NV0iLCJ1bW0iOiJbXCJ0cm1tIHByZWNpcGl0YXRpb24gcmFkYXIgc3VyZmFjZSBjcm9zcy1zZWN0aW9uIGwyIDEuNSBob3VycyAgdjcgKHRybW1fMmEyMSkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUk1NXzJBMjFcIixcIjdcIiwxMjgyMDYwNTQ0LDQ1XSJ9/TRMM_3A26_7",
         "description": "The new version of these data is in GPM-like format (consistent with the GPM Dual-frequency Radar data format), and can be found under the name GPM_3PR.  This dataset contains distributions of monthly surface rainfall. These data were derived from rain rate statistics and include the estimated values of the probability distribution function of the space-time rain rates at four levels (2 km, 4 km, 6 km, and path-averaged) and the mean, standard deviation, and probability of rain derived from these distributions. Three different rain rate estimates are used as input to the algorithm: (1) the standard Z-R (or 0th-order estimate having no attenuation correction); (2) the Hitschfield-Bordan (H-B); and (3) the rain rates taken from 2A25. \t",
         "license": "proprietary"
     },
@@ -177237,7 +177523,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654181-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654181-GES_DISC.html",
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         "description": "This is the 5-day accumulation of the 2A53 product, 'Radar Site Rain Map', which originally is an instantaneous surface rain rate map in Cartesian coordinates with a 2 km horizontal resolution. At single radar sites, the map covers an area of 300km x 300km. For the multiple radar site in Texas, the map covers a region of 724 km x 568 km, and in Florida 512 km x 704 km.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177250,7 +177536,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506695-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506695-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_3A54UW_7",
         "description": "This dataset is part of the University of Washington TRMM Ground Validation products.  Monthly rain accumulation cartesian grid based on 2A53UW. Units are mm. Min range is 17 km, max range is 150 km. Horizontal extent is 150x150km and resolution is 2km. Note that in the netCDF files, \"alt\" (altitude) is assigned the elevation angle of the lowest sweep (which is used to create baseUW) and \"z_spacing\" has no meaning.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177263,7 +177549,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654182-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654182-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBncm91bmQgdmFsaWRhdGlvbiByYWRhciBzaXRlIDNkIHJlZmxlY3Rpdml0eSBsMiAxIGhvdXIgdjcgKHRybW1fMmE1NXV3KSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRSTU1fMkE1NVVXXCIsXCI3XCIsMTM1NjUwNjY5NCwzNF0iLCJ1bW0iOiJbXCJ0cm1tIGdyb3VuZCB2YWxpZGF0aW9uIHJhZGFyIHNpdGUgM2QgcmVmbGVjdGl2aXR5IGwyIDEgaG91ciB2NyAodHJtbV8yYTU1dXcpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTU1VVdcIixcIjdcIiwxMzU2NTA2Njk0LDM0XSJ9/TRMM_3A54_7",
         "description": "The 3A54 product, 'Site Rainfall Map', is a map of monthly surface rain totals derived from the instantaneous rain rate maps (2A53). The map is in Cartesian coordinates with a 2 km horizontal resolution and covers an area of 300km x 300km at single radar sites while the covered area varies for multiple radar sites - 724 km x 568 km at Texas site and 512 km x 704 km at Florida site. This monthly rainfall map is not a simple accumulation of the instantaneous maps as gaps in the data must be factored into the calculation.   A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177276,7 +177562,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654214-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1332654214-GES_DISC.html",
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         "description": "The 3A55, 'Monthly 3-D Structure', provides radar site monthly 3-D structure information obtained from 2A55.  The 2A55 'Radar Site 3-D Reflectivities', is composed of 3 different fields. The first field has an array of 3-D reflectivities in Cartesian coordinates with a 2 km horizontal resolution over an area of 300 km x 300 km for single radar sites, and 724 km x 568 km for Texas multiple radar site, 512 km x 704 km for Florida multiple radar site. It has a vertical resolution of 1.5km and a height range up to 19.5 km. The second field has an array of vertical profiles based on the first field, and the third field has an array of the Contoured Frequency by Altitude Diagram (CFAD) data based on the first and second field.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177289,7 +177575,7 @@
         "bbox": "-180, -40, 180, 40",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032614-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032614-GES_DISC.html",
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         "description": "This is a combined rainfall product. 3B31 uses the high quality retrievals done for the narrow swath in 2B31 to calibrate the wide swath retrievals generated in 2A12. For each 0.5 degree box and each vertical layer, an adjustment ratio is calculated for the swath overlap region for one month. Only TMI pixels with 2A12 pixelStatus equal to zero are included in monthly averages, which effectively removes sea ice. \t",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032617-GES_DISC.html",
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         "description": "TMPA (3B40RT) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG datasets (doi: 10.5067/GPM/IMERG/3B-HH-E/06, 10.5067/GPM/IMERG/3B-HH-L/06).   These data were output from the TRMM Multi-satellite Precipitation Analysis (TMPA), the Near Real-Time (RT) processing stream.  The latency was about seven hours from the observation time, although processing issues may delay or prevent this schedule. Users should be mindful that the price for the short latency of these data is the reduced quality as compared to e.g. research quality product 3B42.  This particular dataset is an intermediate high-quality (HQ) estimate from merged Microwave precipitation estimates.  Data files start with a header consisteing  of a 2880-byte header record containing ASCII characters. The header line makes the file nearly self-documenting, in particular spelling out the variable and version names, and giving the units of the variables. Immediately after the header follow the data fields.  All fields are 1440x720 grid boxes (0-360\ufffdE,90\ufffdN-S). The first grid box center is at (0.125\ufffdE,89.875\ufffdN).  The grid increments most rapidly to the east.  Grid boxes without valid data are filled with the (2-byte integer) \"missing\" value -31999. Estimates are only computed for the band 70\ufffdN-S. This binary data sets are in IEEE ?big-endian? floating-point format.  Files are produced every 3 hours on synoptic observation hours (00, 03, ..., 21 UTC) as an accumulation of all HQ swath data observed within +/-90 minutes of the nominal file time. I.e. Each file is a snapshot considered to represent the three-hour period centered on the \"nominal\" file time.  So, e.g., 00 UTC nominally represents the period from 2230 UTC of the previous day to 0130 UTC of the current day.",
         "license": "proprietary"
     },
@@ -177315,7 +177601,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032567-GES_DISC.html",
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         "description": "TMPA (3B41RT) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG datasets (doi: 10.5067/GPM/IMERG/3B-HH-E/06, 10.5067/GPM/IMERG/3B-HH-L/06).  These data were output from the TRMM Multi-satellite Precipitation Analysis (TMPA), the Near Real-Time (RT) processing stream.  The latency was about seven hours from the observation time, although processing issues may delay or prevent this schedule. Users should be mindful that the price for the short latency of these data is the reduced quality as compared to the research quality product 3B42. This particular dataset is an intermediate variable (VAR) rainrate IR estimate.  Data files start with a header consisting  of a 2880-byte record containing ASCII characters. The header line makes the file nearly self-documenting, in particular spelling out the variable and version names, and giving the units of the variables.   Immediately after the header follow 3 data fields, \"precip\", \"error\",\"# pixels\",  with byte count correspondingly 1382400,1382400,691200. First two are 2-byte integers, and the third is 1-byte.  All fields are 1440x480 grid boxes (0-360E,60N-S). The first grid box center is at (0.125E,59.875N).  The grid increments most rapidly to the east.  Grid boxes without valid data are filled with the (2-byte integer) \"missing\" value -31999. Valid estimates are only provided in the band 50N-S. This binary data sets are in IEEE \"big-endian\" floating-point format.    ",
         "license": "proprietary"
     },
@@ -177328,7 +177614,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1231627223-GES_DISC.html",
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         "description": "TMPA (3B42RT) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG datasets (doi: 10.5067/GPM/IMERG/3B-HH-E/06, 10.5067/GPM/IMERG/3B-HH-L/06).  These data were output from the TRMM Multi-satellite Precipitation Analysis (TMPA), the Near Real-Time (RT) processing stream.  The latency was about seven hours from the observation time, although processing issues may delay or prevent this schedule. Users should be mindful that the price for the short latency of these data is the reduced quality as compared to the research quality product.  Each file is a snapshot considered to represent the three-hour period centered on the \"nominal\" file time.  So, e.g., 00 UTC nominally represents the period from 2230 UTC of the previous day to 0130 UTC of the current day. Estimates outside the band 50 degree N-S are considered highly experimental.   GES DISC initially receives these data from the Precipitation Processing System (PPS) in binary format.  However, before archiving, the data are scaled to real numbers, and re-arranged to a standard grid so that the first grid cell is at 180W, 60S. Thus formatted, data are stored  into CF-1.6 compliant netCDF-4 files and archived. This format is machine-independent, self-explanatory,  provides extremely efficient seamless compression, and gives various options for previewing the data without downloading it.  Apart from these technical differences, all other science content details remain the same, and users are strongly encouraged to read the provider's documentation that is linked to from here.",
         "license": "proprietary"
     },
@@ -177341,7 +177627,7 @@
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         "description": "TMPA (3B42RT_Daily) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERGDE/DAY/06; 10.5067/GPM/IMERGDL/DAY/06).  This daily accumulated precipitation product is generated from the Near Real-Time  3-hourly TRMM Multi-Satellite Precipitation Analysis TMPA (3B42RT). It is produced at the NASA GES DISC, as a value added product.  Simple summation of valid retrievals in a grid cell is applied for the data day. The result is given in (mm). Although the grid is from 60S to 60N, the high latitudes (beyond 50S/N) near real-time retrievals are considered very unreliable and thus are screened out from the daily accumulations. The beginning and ending time for every daily granule are listed in the file global attributes, and are taken correspondingly from the first and the last 3-hourly granules participating in the aggregation. Thus the time period covered by one daily granule amounts to 24 hours, which can be inspected in the file global attributes.    Counts of valid retrievals for the day are provided for every variable, making it possible to compute conditional and unconditional mean precipitation for grid cells where less than 8 retrievals for the day are available.  Efforts have been made to make the format of this  derived product as similar as possible to the new Global Precipitation Measurement CF-compliant file format.   The latency of this derived daily product is about 7 hours after the UTC day is closed. Users should be mindful that the price for the short latency of these data is the reduced quality as compared to the research quality product.  The information provided here on the TRMM mission, and on the original 3-hr 3B42 product, remain relevant for this derived product. Note, however, this product is in netCDF-4 format.    The following describes the derivation in more details.  The daily accumulation is derived by summing *valid* retrievals in a grid cell for the data day. Since the 3-hourly source data are in mm/hr, a factor of 3 is applied to the sum. Thus, for every grid cell we have  Pdaily     = 3 * SUM{Pi * 1[Pi valid]}, i=[1,Nf] Pdaily_cnt = SUM{1[Pi valid]}  where: Pdaily          - Daily accumulation (mm) Pi              - 3-hourly input, in (mm/hr) Nf              - Number of 3-hourly files per day, Nf=8 1[.]            - Indicator function; 1 when Pi is valid, 0 otherwise Pdaily_cnt      - Number of valid retrievals in a grid cell per day.  Grid cells for which Pdaily_cnt=0, are set to fill value in the Daily files. Note that Pi=0 is a valid value.   On occasion, the 3-hourly source data have fill values for Pi in a very few grid cells. The total accumulation for such grid cells is still issued, inspite of the likelihood that thus resulting accumulation has a larger uncertainty in representing the \"true\" daily total. These events are easily detectable using \"counts\" variables that contain Pdaily_cnt, whereby users can screen out any grid cells for which  Pdaily_cnt less than Nf.   There are various ways the accumulated daily error could be estimated from the source 3-hourly error. In this release, the daily error provided in the data files is calculated as follows. First, squared 3-hourly errors are summed, and then square root of the sum is taken. Similarly to the precipitation, a factor of 3 is finally applied:  Perr_daily = 3 * { SUM[ (Perr_i * 1[Perr_i valid])^2 ] }^0.5 , i=[1,Nf] Ncnt_err   = SUM( 1[Perr_i valid] )  where: Perr_daily\t- Magnitude of the daily accumulated error power, (mm) Ncnt_err\t- The counts for the error variable  Thus computed Perr_daily represents the worst case scenario that assumes the error in the 3-hourly source data, which is given in mm/hr, is accumulating within the 3-hourly period of the source data and then during the day. These values, however, can easily be conveted to root mean square error estimate of the rainfall rate:  rms_err =   { (Perr_daily/3) ^2 / Ncnt_err }^0.5\t(mm/hr)   This estimate assumes that the error given in the 3-hourly files is representative of the error of the rainfall rate (mm/hr) within the 3-hour window of the files, and it is random throughout the day. Note, this should be interpreted as the error of the rainfall rate (mm/hr) for the day, not the daily accumulation.    ",
         "license": "proprietary"
     },
@@ -177354,7 +177640,7 @@
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         "description": "TMPA (3B42) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERG/3B-HH/06).  This dataset was the output from the TMPA (TRMM Multi-satellite Precipitation Analysis) Algorithm. It provides precipitation estimates in the TRMM regions that have the (nearly-zero) bias of the \u201dTRMM Combined Instrument\u201d precipitation estimate and the dense sampling of high-quality microwave data with fill-in using microwave-calibrated infrared estimates. The granule temporal coverage is 3 hours. ",
         "license": "proprietary"
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@@ -177367,7 +177653,7 @@
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         "description": "TMPA (3B42_Daily) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERGDF/DAY/06).  This daily accumulated precipitation product is generated from the research-quality 3-hourly TRMM Multi-Satellite Precipitation Analysis TMPA (3B42). It is produced at the NASA GES DISC, as a value added product.  Simple summation of valid retrievals in a grid cell is applied for the data day. The result is given in (mm). The beginning and ending time for every daily granule are listed in the file global attributes, and are taken correspondingly from the first and the last 3-hourly granules participating in the aggregation. Thus the time period covered by one daily granule amounts to 24 hours, which can be inspected in the file global attributes.   Counts of valid retrievals for the day are provided for every variable, making it possible to compute conditional and unconditional mean precipitation for grid cells where less than 8 retrievals for the day are available.  Efforts have been made to make the format of this  derived product as similar as possible to the new Global Precipitation Measurement CF-compliant file format.  The information provided here on the TRMM mission, and on the original 3-hr 3B42 product, remain relevant for this derived product. Note, however, this product is in netCDF-4 format.    The following describes the derivation in more details.  The daily accumulation is derived by summing *valid* retrievals in a grid cell for the data day. Since the 3-hourly source data are in mm/hr, a factor of 3 is applied to the sum. Thus, for every grid cell we have  Pdaily     = 3 * SUM{Pi * 1[Pi valid]}, i=[1,Nf] Pdaily_cnt = SUM{1[Pi valid]}  where: Pdaily          - Daily accumulation (mm) Pi              - 3-hourly input, in (mm/hr) Nf              - Number of 3-hourly files per day, Nf=8 1[.]            - Indicator function; 1 when Pi is valid, 0 otherwise Pdaily_cnt      - Number of valid retrievals in a grid cell per day.  Grid cells for which Pdaily_cnt=0, are set to fill value in the Daily files. Note that Pi=0 is a valid value.   On occasion, the 3-hourly source data have fill values for Pi in a very few grid cells. The total accumulation for such grid cells is still issued, inspite of the likelihood that thus resulting accumulation has a larger uncertainty in representing the \"true\" daily total. These events are easily detectable using \"counts\" variables that contain Pdaily_cnt, whereby users can screen out any grid cells for which  Pdaily_cnt less than Nf.   There are various ways the accumulated daily error could be estimated from the source 3-hourly error. In this release, the daily error provided in the data files is calculated as follows. First, squared 3-hourly errors are summed, and then square root of the sum is taken. Similarly to the precipitation, a factor of 3 is finally applied:  Perr_daily = 3 * { SUM[ (Perr_i * 1[Perr_i valid])^2 ] }^0.5 , i=[1,Nf] Ncnt_err   = SUM( 1[Perr_i valid] )  where: Perr_daily\t- Magnitude of the daily accumulated error power, (mm) Ncnt_err\t- The counts for the error variable  Thus computed Perr_daily represents the worst case scenario that assumes the error in the 3-hourly source data, which is given in mm/hr, accumulates first within the 3-hour period of the source data, and then continues to accumulate during the day. These values, however, can easily be converted to root mean square error estimate of the rainfall rate:  rms_err =   { (Perr_daily/3) ^2 / Ncnt_err }^0.5\t(mm/hr)   This estimate assumes that the error given in the 3-hourly files is representative of the error of the rainfall rate (mm/hr) within the 3-hour window of the files, and it is random throughout the day. Note, this should be interpreted as the error of the rainfall rate (mm/hr) for the day, not the daily accumulation.   ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032631-GES_DISC.html",
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         "description": "TMPA (3B43) dataset have been discontinued as of Dec. 31, 2019, and users are strongly encouraged to shift to the successor IMERG dataset (doi: 10.5067/GPM/IMERG/3B-MONTH/06).  The 3B43 dataset is the monthly version of the 3B42 dataset.  This product was created using TRMM-adjusted merged microwave-infrared precipitation rate (in mm/hr) and root-mean-square (RMS) precipitation-error estimates. It provides a \"best\" precipitation estimate in a latitude band covering 50o N to 50o S, an expansion of the TRMM region, from all global data sources, namely high-quality microwave data, infrared data, and analyses of rain gauges. The granule size is one month.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032615-GES_DISC.html",
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         "description": "3G25, \"Gridded Orbital Spectral Latent Heating\", produces 0.5 degree x 0.5 degree latent heating, Q1-QR, and Q2 profiles from Precipitation Radar (PR) rain. The granule size is one orbit.",
         "license": "proprietary"
     },
@@ -177406,7 +177692,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032565-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJtbSBwcmVjaXBpdGF0aW9uIHJhZGFyIHN1cmZhY2UgY3Jvc3Mtc2VjdGlvbiBsMiAxLjUgaG91cnMgIHY3ICh0cm1tXzJhMjEpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVFJNTV8yQTIxXCIsXCI3XCIsMTI4MjA2MDU0NCw0NV0iLCJ1bW0iOiJbXCJ0cm1tIHByZWNpcGl0YXRpb24gcmFkYXIgc3VyZmFjZSBjcm9zcy1zZWN0aW9uIGwyIDEuNSBob3VycyAgdjcgKHRybW1fMmEyMSkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJUUk1NXzJBMjFcIixcIjdcIiwxMjgyMDYwNTQ0LDQ1XSJ9/TRMM_3G31_7",
         "description": "3G31, Gridded Orbital Convective Stratiform Heating from Combined, produces 0.5 degree x 0.5 degree orbital apparent heating profiles from surface convective rainfall rate and surface stratiform rainfall rate. The granule size is one orbit.",
         "license": "proprietary"
     },
@@ -177419,7 +177705,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032633-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032633-GES_DISC.html",
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         "description": "3H25, \"Monthly Spectral Latent Heating\", produces 0.5 degree x 0.5 degree latent heating, Q1-QR, and Q2 profiles from PR rain",
         "license": "proprietary"
     },
@@ -177432,7 +177718,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032616-GES_DISC.html",
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         "description": "3H31, \"Monthly Convective Stratiform Heating from Combined\", produces 0.5 deg x 0.5 deg monthly apparent heating profiles from surface convective rainfall rate and surface stratiform rainfall rate. The PI is Dr. Wei-Kuo Tao. The granule size is one month.",
         "license": "proprietary"
     },
@@ -177445,7 +177731,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032566-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1282032566-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgZGFpbHkgZ3JpZHMgZnJvbSBub2FhLTEyIHYwMSAodG92c2JkbmQpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVE9WU0JETkRcIixcIjFcIiwxMjc0NjI1Njg0LDIyXSIsInVtbSI6IltcInRvdnMgbG1kIGRhaWx5IGdyaWRzIGZyb20gbm9hYS0xMiB2MDEgKHRvdnNiZG5kKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRPVlNCRE5EXCIsXCIxXCIsMTI3NDYyNTY4NCwyMl0ifQ%3D%3D/TRMM_CSH_6",
         "description": "This is a discontinued TRMM product from the old version '6' suite that is in a state of permament preservation. The most recent replacement can be found by following this DOI: 10.5067/GPM/PRTMI/TRMM/CSH/3B-MONTH/07. The latter should also be better cross-calibrated with the continuation GPM combined Dual-Frequency Precipitation Radar and GPM Microwave Imager latent heating product: 10.5067/GPM/DPRGMI/CSH/3B-MONTH/07.    The version '6'  dataset is output from the old Goddard Convective-Stratiform Heating (CSH) algorithm. The dataset contains  global 0.5 x 0.5 monthly latent heating profiles from surface convective rain rate and surface stratiform rain rate.",
         "license": "proprietary"
     },
@@ -177718,7 +178004,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506691-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1356506691-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widG92cyBsbWQgZGFpbHkgZ3JpZHMgZnJvbSBub2FhLTEyIHYwMSAodG92c2JkbmQpIGF0IGdlcyBkaXNjXCIsXCJHRVNfRElTQ1wiLFwiVE9WU0JETkRcIixcIjFcIiwxMjc0NjI1Njg0LDIyXSIsInVtbSI6IltcInRvdnMgbG1kIGRhaWx5IGdyaWRzIGZyb20gbm9hYS0xMiB2MDEgKHRvdnNiZG5kKSBhdCBnZXMgZGlzY1wiLFwiR0VTX0RJU0NcIixcIlRPVlNCRE5EXCIsXCIxXCIsMTI3NDYyNTY4NCwyMl0ifQ%3D%3D/TRMM_baseUW_7",
         "description": "This dataset is part of the University of Washington TRMM Ground Validation products.  Data contains single level, cartesian grids containing output of NCAR SPRINT interpolation of lowest sweep of 1C51UW. Horizontal extent is 150x150km and horizontal resolution is 2km. Note that in the netCDF files, \"alt\" (altitude) is assigned the elevation angle of the lowest sweep (which is used to create this product) and \"z_spacing\" has no meaning.  A key component of the TRMM project is the Ground Validation (GV) effort which consists of collecting data from ground-based radar, rain gauges and disdrometers. The data is quality-controlled, and then validation products are produced for comparison with TRMM satellite products.  The four primary GV sites are:  + Darwin, Australia;  + Houston, Texas;  + Kwajalein, Republic of the Marshall Islands; + Melbourne, Florida.   A significant effort is also being supported at NASA Wallops Flight Facility (WFF) and vicinity to provide high quality, long-term measurements of rain rates (via a network of rain gauges collocated with National Weather Service gauges), as well as drop size distributions (DSD) using a variety of instruments, including impact-type Joss Waldvogel, laser-optical Parsivel, as well as two-dimensional video disdrometers.  DSD measurements are also being collected at Melbourne and Kwajalein using Joss-Waldvogel disdrometers. ",
         "license": "proprietary"
     },
@@ -177731,7 +178017,7 @@
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+        "title": "TROPICS03\u00a0Pathfinder\u00a0L2B Instantaneous Surface Rain Rate (ISRR) V1.0",
         "catalog": "GES_DISC STAC Catalog",
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         "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS03 satellite, as the Validated Stage-1 version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.",
         "license": "proprietary"
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         "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. ",
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         "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. ",
         "license": "proprietary"
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         "description": "The \"Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats\" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS07 satellite, as the Provisional version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.",
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         "description": "As part of the NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, this projects describes a multi-decadal Fundamental Climate Data Record (FCDR) of calibrated radiances as well as an Earth System Data Record (ESDR) of aerosol properties over the continents derived from a 32-year record of satellite near-UV observations by three sensors.    The Corpenicus Sentinel-5P TROPOMI Near UV (version 1) Aerosol Optical Depth and Single Scattering Albedo data product consists of aerosol absorption optical depth, aerosol total optical depth, aerosol layer height, aerosol UV index, and aerosol single scattering albedo at approximately 7.5kmx3km. This product also contains ancillary data for ocean corrected surface albedo and terrain pressure.  Data since July 19, 2022 (orbit 24688) has been processed with the most recent calibrated L1B radiance data (version 2.0.1). Data prior to July 19, 2022, data was processed with version 2.0.0 L1B radiances. Soon, the entire record will be reprocessed using version 2.0.1 L1B data. Any upgrades will be posted here.   These Level-2 data are stored in the NetCDF-4 format and are available from the Goddard Earth Sciences (GES) Data and Information Services Center (DISC).",
         "license": "proprietary"
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         "license": "proprietary"
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         "license": "proprietary"
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         "description": "The TROPESS CrIS-SNPP L2 Methane for Australian Fires, Standard Product contains the vertical distribution of the retrieved atmospheric state of methane (CH4), formal uncertainties, and diagnostic information measured by the CrIS instrument on the Suomi-NPP satellite. This product focuses on the Australia region (60S-0S; 100E-177.5E) for the time period from 2019-11-01 to 2020-01-31, during the outbreak of Austrailan wildfires. The NASA TRopospheric Ozone and Precursors from Earth System Sounding (TROPESS) project, uses an optimal estimation algorithm, known as the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES).  The data files are written in the netCDF version 4 file format, and each file contains one day of data. The data have a spatial resolution of 14 km (CrIS nadir FOV), and are reported at 26 vertical levels from the surface to 0.1 hPa. The principal investigator for the TROPESS project is Kevin W. Bowman.",
         "license": "proprietary"
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         "description": "Version 12 is the current release of this data product, and supercedes all previous versions.  The TSIS SIM Level 3 Solar Spectral Irradiance (SSI) 12-Hour Means data product (TSIS_SSI_L3_12HR) uses measurements from the Spectal Irradiance Monitor (SIM) instrument, and averages them over a 12-hour period. TSIS-1 was launched on December 15, 2017 and mounted on the International Space Station (ISS) on December 30, 2017. Solar spectra are measured over the spectral range from 200 to 2400 nm at a spectral resolution ranging from 2 nm (<0.28 microns) to 45 nm (>0.4 microns). Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SIM absolute uncertainty is about 0.2%.  All of the data from this product are arranged into a single file in a tabular ASCII text format which can be easily read into a spreadsheet application. New data are appended to the file on a daily basis. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SIM wavelength range, repeating for each day for the length of the mission.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2881895235-GES_DISC.html",
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         "description": "Version 12 is the current release of this data product, and supercedes all previous versions.  The TSIS SIM Level 3 Solar Spectral Irradiance (SSI) 24-Hour Means data product (TSIS_SSI_L3_24HR) uses measurements from the Spectral Irradiance Monitor (SIM) instrument, and averages them over a 24-hour period. TSIS-1 was launched on December 15, 2017 and mounted on the International Space Station (ISS) on December 30, 2017. Solar spectra are measured over the spectral range from 200 to 2400 nm at a spectral resolution ranging from 2 nm (<0.28 microns) to 45 nm (>0.4 microns). Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun. The SIM absolute uncertainty is about 0.2%.  All of the data from this product are arranged into a single file in a tabular ASCII text format which can be easily read into a spreadsheet application. New data are appended to the file on a daily basis. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full SIM wavelength range, repeating for each day for the length of the mission.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2797642655-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2797642655-GES_DISC.html",
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         "description": "Version 04 is the current release of this data product, and supercedes all previous versions.  The TSIS TIM Level 3 Total Solar Irradiance (TSI) 6-Hour Means data product (TSIS_TSI_L3_06HR) uses measurements from the Total Irradiance Monitor (TIM) instrument over the entire spectrum, and averages them over a 6-hour period. TSIS-1 was launched on December 15, 2017 and mounted on the International Space Station (ISS) on December 30, 2017. TIM instrument has long-term repeatability with estimated uncertainties less than 0.014 W/m^2/yr (10 ppm/yr). Accuracy is currently reported as 0.48 W/m^2 (350 ppm), but expected to decrease as calibrations are refined and incorporated. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun.  All of the data from this product are arranged into a single file in a tabular ASCII text format which can be easily read into a spreadsheet application. New data are appended to the file on a daily basis. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full TIM wavelength range, repeating for each day for the length of the mission.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2797642674-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2797642674-GES_DISC.html",
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         "description": "Version 04 is the current release of this data product, and supercedes all previous versions.  The TSIS TIM Level 3 Total Solar Irradiance (TSI) 24-Hour Means data product (TSIS_TSI_L3_24HR) uses measurements from the Total Irradiance Monitor (TIM) instrument over the entire spectrum, and averages them over a 24-hour period. TSIS-1 was launched on December 15, 2017 and mounted on the International Space Station (ISS) on December 30, 2017. TIM instrument has long-term repeatability with estimated uncertainties less than 0.014 W/m^2/yr (10 ppm/yr). Accuracy is currently reported as 0.48 W/m^2 (350 ppm), but expected to decrease as calibrations are refined and incorporated. Irradiances are reported at a mean solar distance of 1 AU and zero relative line-of-sight velocity with respect to the Sun.  All of the data from this product are arranged into a single file in a tabular ASCII text format which can be easily read into a spreadsheet application. New data are appended to the file on a daily basis. The columns contain the date, Julian day, minimum wavelength, maximum wavelength, instrument mode, data version number, irradiance value, irradiance uncertainty, and data quality. The rows are arranged with data at each wavelength over the full TIM wavelength range, repeating for each day for the length of the mission.",
         "license": "proprietary"
     },
@@ -180175,7 +180461,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784383956-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784383956-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1widG9wb2dyYXBoaWMgYW5kIHNvaWwgY2FyYm9uIHJlY29uc3RydWN0aW9ucyBpbiBhZ3JpY3VsdHVyYWwgZmllbGRzLCBpb3dhXCIsXCJPUk5MX0NMT1VEXCIsXCJUaWxsYWdlRXJvc2lvbl9TT0NSZWRpc3RyaWJ1dGVfMTk0NFwiLFwiMVwiLDI1NzU0MjIwMTksNV0iLCJ1bW0iOiJbXCJ0b3BvZ3JhcGhpYyBhbmQgc29pbCBjYXJib24gcmVjb25zdHJ1Y3Rpb25zIGluIGFncmljdWx0dXJhbCBmaWVsZHMsIGlvd2FcIixcIk9STkxfQ0xPVURcIixcIlRpbGxhZ2VFcm9zaW9uX1NPQ1JlZGlzdHJpYnV0ZV8xOTQ0XCIsXCIxXCIsMjU3NTQyMjAxOSw1XSJ9/Taiga_Tundra_Tree_Cover_1218_1",
         "description": "This data set provides a map of selected areas with defined tree canopy cover over the circumpolar taiga-tundra ecotone (TTE). Canopy cover was derived from the 500-meter MODIS Vegetation Continuous Fields (VCF) product as averaged over six years from 2000-2005 and processed as described in Ranson et al. (2011). This process identified patches of low tree canopy cover which are indicative of the transition from forest to tundra and differentiate the circumpolar taiga-tundra ecotone for the 2000-2005 period. The TTE is the Earth's longest vegetation transition zone and stretches for more than 13,400 km around Arctic North America, Scandinavia, and Eurasia. In Eurasia, the map extends from 60 degrees N to 70 degrees N, and in North America from 50 degrees N to 70 degrees N, excluding Baffin Island in northeastern Canada and the Aleutian Peninsula in southwestern Alaska. Note that for this product, taiga is being used one and the same as boreal forest.This circumpolar TTE area was classified according to VCF tree canopy cover.",
         "license": "proprietary"
     },
@@ -180318,7 +180604,7 @@
         "bbox": "-122.75, 25.08, -69.93, 47.12",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082183-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389082183-ORNL_CLOUD.html",
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         "description": "This dataset provides 30m resolution maps of the fraction of green vegetation within tidal marshes for six estuarine regions of the conterminous United States: Cape Cod, MA; Chesapeake Bay, MD; Everglades, FL; Mississippi Delta, LA; San Francisco Bay, CA; and Puget Sound, WA. Maps were derived from a 1m classification of 2013 to 2015 National Agriculture Imagery Program (NAIP) images as tidal marsh green vegetation, non-vegetation, and open water. Using this high-resolution map, the percent of each class within Landsat pixel extents was calculated to produce a 30m fraction of green vegetation map for each region.",
         "license": "proprietary"
     },
@@ -180331,7 +180617,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517345906-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517345906-ORNL_CLOUD.html",
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         "description": "This dataset provides a synthesis of soil organic carbon (SOC) estimates and a variety of other environmental information from tidal wetlands within estuaries in the conterminous United States for the period 1972-2015. The data were compiled from several existing data resources and include the following: soil organic carbon stock estimates, the proportion of the catchment area containing the wetlands that is barren, tidal wetland area, nontidal wetland land, open water, saltwater zone, mixed zone, agricultural, urban, forest, and wetland areas, land elevation, ocean salinity, sea surface temperature, ocean dissolved inorganic phosphorus, estuary latitude, longitude, depth, perimeter, salinity, and estuary volume, river flow, carbon, nitrogen, and phosphorus river flux, sediment organic carbon content, windspeed, mean temperature, daily and mean precipitation, frost days, and the population within each catchment. Estuaries were also classified to one of six typological categories. Coastal locations were determined by natural environmental and political divisions within the US. The data were used to investigate how tidal wetland soil organic carbon density is distributed across the continental US among various coastal locations, estuarine typologies, vegetation types, water regimes, and management regimes, and to identify whether SOC density is correlated with different environmental variables. The analytical results are not included with this dataset.",
         "license": "proprietary"
     },
@@ -180344,7 +180630,7 @@
         "bbox": "-128.03, 23.5, -65.9, 47.7",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389119490-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389119490-ORNL_CLOUD.html",
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         "description": "This dataset provides mapped tidal wetland gross primary production (GPP) estimates (g C/m2/day) derived from multiple wetland types at 250-m resolution across the conterminous United States at 16-day intervals from March 5, 2000, through November 17, 2019. GPP was derived with the spatially explicit Blue Carbon (BC) model, which combined tidal wetland cover and field-based eddy covariance (EC) tower GPP data into a single Bayesian framework along with Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) datasets. Tidal wetlands are a critical component of global climate regulation. Tidal wetland-based carbon, or \"blue carbon,\" is a valued resource that is increasingly important for restoration and conservation purposes.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2389101861-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2389101861-ORNL_CLOUD.html",
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         "description": "This dataset provides modeled estimates of soil carbon stocks for tidal wetland areas of the Conterminous United States (CONUS) for the period 2006-2010. Wetland areas were determined using both 2006-2010 Coastal Change Analysis Program (C-CAP) raster maps and the National Wetlands Inventory (NWI) vector data. All 30 x 30-meter C-CAP pixels were extracted that are coded as estuarine emergent, scrub/shrub, or forested in either 2006 or 2010. A soil database for model fitting and validation was compiled from 49 different studies with spatially explicit empirical depth profile data and associated metadata, totaling 1,959 soil cores from 18 of the 22 coastal states. Reported estimates of carbon stocks were derived with modeling approaches that included (1) applying a single average carbon stock value from the compiled soil core data, (2) applying models fit using the empirical data and applied spatially using soil, vegetation and salinity maps, (3) relying on independently generated soil carbon maps from The United States Department of Agriculture (USDA)'s Soil Survey Geographic Database (SSURGO), and the NWI that intersected with mapped tidal wetlands, and (4) using a version of SSURGO bias-corrected for bulk density. Comparisons of uncertainty, precision, and accuracy among these four approaches are also provided.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2575422019-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2575422019-ORNL_CLOUD.html",
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         "description": "This dataset contains model predictions of soil erosion and soil organic carbon (SOC) redistribution caused by agricultural practices such as tillage erosion. Soil erosion diminishes agricultural productivity by driving the loss of SOC. This model addresses a growing need to predict soil organic carbon transport, loss, and deposition. The model was applied to three sites containing paired prairie grassland and field plots in Iowa, and predicts SOC redistribution between 1859 to 2019. The model was developed by incorporating a SOC mixing model with a landscape evolution model that simulates tillage erosion.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2170970462-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2170970462-ORNL_CLOUD.html",
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         "description": "This data set provides the spatial distributions of vegetation types, soil carbon, and physiographic features in the Toolik Lake area, Alaska. Specific attributes include vegetation, percent water, glacial geology, soil carbon, a digital elevation model (DEM), surficial geology and surficial geomorphology.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864353-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216864353-ORNL_CLOUD.html",
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         "description": "This dataset provides estimates of topsoil loss and economic loss associated with decreased crop productivity resulting from topsoil loss at county- and state-levels across the Corn Belt region of the Midwestern USA. Intermediate products used to derive topsoil loss are provided and include 4 m gridded estimates of study sites elevation, curvature, slope, soil organic carbon index (SOCI), and the probability of exposed B-horizon soil. Topsoil loss at the county- and state-levels was derived from analyses of agricultural land at selected sites across the study area. From WorldView imagery, 759 fields were identified that had exposed bare soil (210 km2) and were grouped into 28 sites. Gridded estimates of the SOCI and of the probability of exposed B-horizon soil were determined for each field within the sites. Topography measures, including elevation (m), curvature (m-1), and slope (deg), were extracted over the entire study area from LiDAR-derived digital elevation models at a 4 m resolution acquired from 2003-2018. Within each of the 28 study sites, the SOCI and topographic curvature values were extracted from co-located pixels. Topsoil loss was estimated from the relationship between subsoil exposure and topography and averaged across each site.The relationship between topsoil loss and topographic curvature was used to up-scale and predict topsoil and economic losses at the county and state-levels across the entire 375,000 km2 study area. The data have been used to demonstrate a robust and scalable method for estimating the magnitude of erosion in agricultural landscapes.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2192619509-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2192619509-ORNL_CLOUD.html",
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         "description": "This dataset includes daily averaged solar-induced chlorophyll fluorescence (SIF) in the red (680-686 nm) and far-red (745-758 nm) wavelength ranges, relative SIF (SIF/Intensity), chlorophyll-carotenoid index (CCI), photochemical reflectance index (PRI), near-infrared vegetation index (NIRv), and normalized difference vegetation index (NDVI) for both black spruce (Picea mariana) and larch (Larix laricina) targets. The study site (Southern Old Black Spruce, SOBS Fluxnet ID CA-Obs) is located near the southern limit of the boreal forest ecotone in Saskatchewan, Canada. Data were collected for the spring transition in both 2019 and 2020 using PhotoSpec. Species-specific averages were calculated over each 30-minute period, then averaged again to report daily averages of SIF relative and reflectance measurements for both black spruce and larch.",
         "license": "proprietary"
     },
@@ -180448,7 +180734,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2612824717-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2612824717-ORNL_CLOUD.html",
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         "description": "The data set provides multi-year (2016-2018) percent tree cover (TC) estimates for entire Mexico at 30 m spatial resolution. The TC data (hereafter, NEX-TC) was derived from the 30 m Landsat Collection 1 product and a hierarchical deep learning approach (U-Net) developed in a previous CMS effort for the conterminous United States (CONUS) (Park et al., 2022). The hierarchical U-Net framework first developed a U-Net model for very high-resolution aerial images (NAIP) using training labels derived from previous work based on an interactive image segmentation tool and iterative updates with expert knowledge (Basu et al., 2015). The developed NAIP U-Net model and NAIP data produced 1-m NAIP TC across all lower 48 CONUS states. A Landsat U-Net model was developed for multi-year and large-scale TC mapping based on the very high-resolution NAIP TC made in the earlier stage. The Landsat U-Net model developed was adopted over the CONUS for testing its transferability, validation, and improvement across Mexico. This dataset provides national-scale percent tree cover estimates over Mexico and can be helpful for studies of carbon cycling, land cover and land use change, etc. The team has been working on improving temporal stability of the product and will update the product once the next version is ready to be shared.",
         "license": "proprietary"
     },
@@ -180461,7 +180747,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2767487834-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2767487834-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1widG9wb2dyYXBoaWMgYW5kIHNvaWwgY2FyYm9uIHJlY29uc3RydWN0aW9ucyBpbiBhZ3JpY3VsdHVyYWwgZmllbGRzLCBpb3dhXCIsXCJPUk5MX0NMT1VEXCIsXCJUaWxsYWdlRXJvc2lvbl9TT0NSZWRpc3RyaWJ1dGVfMTk0NFwiLFwiMVwiLDI1NzU0MjIwMTksNV0iLCJ1bW0iOiJbXCJ0b3BvZ3JhcGhpYyBhbmQgc29pbCBjYXJib24gcmVjb25zdHJ1Y3Rpb25zIGluIGFncmljdWx0dXJhbCBmaWVsZHMsIGlvd2FcIixcIk9STkxfQ0xPVURcIixcIlRpbGxhZ2VFcm9zaW9uX1NPQ1JlZGlzdHJpYnV0ZV8xOTQ0XCIsXCIxXCIsMjU3NTQyMjAxOSw1XSJ9/Tree_Mortality_Western_US_1512_1.1",
         "description": "This dataset provides annual estimates of tree mortality due to fires and bark beetles from 2003 to 2012 on forestland in the continental western United States. Tree mortality was estimated at 1-km spatial resolution by combining tree aboveground carbon (AGC) and disturbance datasets derived largely from remote sensing. Tree mortality is expressed as the amount of AGC stored in trees killed by disturbance (Mg carbon per km2). The dataset also includes annual uncertainty maps that were generated using a Monte Carlo approach in which tree biomass, biomass carbon content, and disturbance severity were iteratively varied by their uncertainty.",
         "license": "proprietary"
     },
@@ -180500,7 +180786,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2840820936-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2840820936-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic3BhdGlvLXRlbXBvcmFsIGNoYXJhY3RlcmlzdGljcyBvZiByYWluZmFsbCBpbiBhZnJpY2EsIDAuMjUgZGVncmVlcywgZnJvbSAxOTk4LTIwMTJcIixcIk9STkxfQ0xPVURcIixcIkFmcmljYW5fUmFpbmZhbGxfUGF0dGVybnNfMTI2M1wiLFwiMVwiLDI3NzY4NzQ4NzMsMl0iLCJ1bW0iOiJbXCJzcGF0aW8tdGVtcG9yYWwgY2hhcmFjdGVyaXN0aWNzIG9mIHJhaW5mYWxsIGluIGFmcmljYSwgMC4yNSBkZWdyZWVzLCBmcm9tIDE5OTgtMjAxMlwiLFwiT1JOTF9DTE9VRFwiLFwiQWZyaWNhbl9SYWluZmFsbF9QYXR0ZXJuc18xMjYzXCIsXCIxXCIsMjc3Njg3NDg3MywyXSJ9/TundraTransect_VegRefl_Soil_2232_1",
         "description": "This dataset provides visible-near infrared spectral reflectance, descriptions of vegetation cover, surface temperature, the total fraction of absorbed photosynthetically active radiation (fAPAR, 2001 only), permafrost active layer depth, elevation, and soil temperature at 5 cm depth. Measurements were made at every meter along a 100-m transect aligned mainly in an east-west direction, located approximately 300 m southeast of the National Oceanic and Atmospheric Administration (NOAA) Global Monitoring Laboratory (GML) baseline observatory near Utqiagvik, Alaska. Reflectance measurements were collected at nearly weekly intervals through the growing seasons of 2000 to 2002 to describe characteristics of green-up, peak growth, and senescence. Reflectance measurements were also collected once near peak growth in 2022. Ancillary measurements were collected at intervals through the 2001 and 2002 growing seasons.",
         "license": "proprietary"
     },
@@ -180513,7 +180799,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2262495116-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2262495116-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1widG9wb2dyYXBoaWMgYW5kIHNvaWwgY2FyYm9uIHJlY29uc3RydWN0aW9ucyBpbiBhZ3JpY3VsdHVyYWwgZmllbGRzLCBpb3dhXCIsXCJPUk5MX0NMT1VEXCIsXCJUaWxsYWdlRXJvc2lvbl9TT0NSZWRpc3RyaWJ1dGVfMTk0NFwiLFwiMVwiLDI1NzU0MjIwMTksNV0iLCJ1bW0iOiJbXCJ0b3BvZ3JhcGhpYyBhbmQgc29pbCBjYXJib24gcmVjb25zdHJ1Y3Rpb25zIGluIGFncmljdWx0dXJhbCBmaWVsZHMsIGlvd2FcIixcIk9STkxfQ0xPVURcIixcIlRpbGxhZ2VFcm9zaW9uX1NPQ1JlZGlzdHJpYnV0ZV8xOTQ0XCIsXCIxXCIsMjU3NTQyMjAxOSw1XSJ9/TundraVeg_Reflectance_Soil_CO2_1960_1",
         "description": "This dataset provides measurements at tundra plots collected near Utqiagvik and Atqasuk, AK, including visible-near infrared spectral reflectance, chamber gas exchange measurements of CO2, pulse amplitude modulated (PAM) fluorometry, chlorophyll pigment contents, along with surface temperature, permafrost active layer depth, and soil temperature at 5 cm, through the growing seasons of 2001 and 2002. At all plots, spectral reflectance was measured using a portable spectrometer configured with a straight fiber optic foreoptic, surface temperatures were measured using a handheld Everest Infrared Thermometer, and thaw depth (or active layer depth) was measured using a metal rod graduated in centimeter intervals. At small plots (~15 cm) at Utqiagvik (referred to as Patch plots) chambers were constructed that enclosed an individual patch to determine photosynthetic rate and estimate respiration rate (made by covering the chamber in a dark cloth). Efficiency using PAM fluorometer, ambient yield estimations, and rapid light curve measurements were taken. Chlorophyll concentration was measured with a portable spectrometer configured as a spectrophotometer. At larger plots (approximately 1 m2) which were part of the International Tundra EXperiment (ITEX plots) at Utqiagvik (referred to as Barrow) and Atqasuk, a sub-sample of five control and five warmed plots at each site were fitted with 0.45 m diameter polyvinyl chloride collars for chamber flux measurements. To determine the total fraction of absorbed photosynthetically active radiation (fAPAR), a series of photosynthetically active radiation (PAR) measurements were made using a custom-made light bar consisting of a linear array of GaAsP sensors mounted within an aluminum U-bar under a white plastic diffuser. In addition, a visual estimate was made of the fraction of standing dead vegetation based on percent cover. The data are provided in comma-separated values (*.csv) format.  In addition, photographs of plots and instruments are provided.",
         "license": "proprietary"
     },
@@ -180552,7 +180838,7 @@
         "bbox": "-156.6, 64.83, -147.81, 71.31",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2262495547-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2262495547-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1widG9wb2dyYXBoaWMgYW5kIHNvaWwgY2FyYm9uIHJlY29uc3RydWN0aW9ucyBpbiBhZ3JpY3VsdHVyYWwgZmllbGRzLCBpb3dhXCIsXCJPUk5MX0NMT1VEXCIsXCJUaWxsYWdlRXJvc2lvbl9TT0NSZWRpc3RyaWJ1dGVfMTk0NFwiLFwiMVwiLDI1NzU0MjIwMTksNV0iLCJ1bW0iOiJbXCJ0b3BvZ3JhcGhpYyBhbmQgc29pbCBjYXJib24gcmVjb25zdHJ1Y3Rpb25zIGluIGFncmljdWx0dXJhbCBmaWVsZHMsIGlvd2FcIixcIk9STkxfQ0xPVURcIixcIlRpbGxhZ2VFcm9zaW9uX1NPQ1JlZGlzdHJpYnV0ZV8xOTQ0XCIsXCIxXCIsMjU3NTQyMjAxOSw1XSJ9/Tundra_Leaf_Spectra_2005_1",
         "description": "This dataset provides leaf-level visible-near infrared spectral reflectance, chlorophyll fluorescence spectra, species, plant functional type (PFT), and chlorophyll content of common high latitude plant samples collected near Fairbanks, Utqiagvik, and Toolik, Alaska, U.S., during the summers of 2019, 2020, and 2021. A FluoWat leaf clip was used to measure leaf-level visible-near infrared spectral reflectance and chlorophyll fluorescence spectra. Fluorescence yield (Fyield) was calculated as the ratio of the emitted fluorescence divided by the absorbed radiation for the wavelengths from 400 nm up to the wavelength of the cut off for the FluoWat low pass filter (either 650 or 700 nm). Chlorophyll content of samples was measured using a CCM-300 Chlorophyll Content. The data are provided in comma-separated values (.csv) format.",
         "license": "proprietary"
     },
@@ -180812,7 +181098,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348582-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348582-GES_DISC.html",
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         "description": "The Cryogenic Limb Array Etalon Spectrometer (CLAES) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, N2O, NO, NO2, N2O5, HNO3, ClONO2, HCl, CF2Cl2 (CFC-12), CFCl3 (CFC-11), and aerosol absorption coefficients. The instrument measured infrared thermal emissions at wavelengths from 3.5 to 12.7 microns. CLAES was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the chemical composition of the stratosphere and mesosphere, and also investigated the depletion of stratospheric ozone and ozone chemistry. Limb measurements were made in the altitude range between 10 and 60 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The CLAES Level 3AL data were processed with the version 9 algorithm, except H2O which is version 7.  The CLAES level 3AL product consists of 20 granules per day. A data granule is one CLAES species or subtype per day. Data are on the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180825,7 +181111,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348583-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348583-GES_DISC.html",
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         "description": "The Cryogenic Limb Array Etalon Spectrometer (CLAES) Level 3AT data product consists of daily, 65.536 second interval time-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, N2O, NO, NO2, N2O5, HNO3, ClONO2, HCl, CF2Cl2 (CFC-12), CFCl3 (CFC-11), and aerosol absorption coefficients. The instrument measured infrared thermal emissions at wavelengths from 3.5 to 12.7 microns. CLAES was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the chemical composition of the stratosphere and mesosphere, and also investigated the depletion of stratospheric ozone and ozone chemistry. Limb measurements were made in the altitude range between 10 and 60 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The CLAES Level 3AT data were processed with the version 9 algorithm, except H2O which is version 7.  The CLAES level 3AL product consists of 20 granules per day. A data granule is one CLAES species or subtype per day. Data are on the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180838,7 +181124,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348497-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348497-GES_DISC.html",
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         "description": "The Halogen Occultation Experiment (HALOE) Level 2 data product consists of daily vertical profiles of temperature, aerosol extinciton and pressure, as well as concentrations of HCl, HF, CH4, NO by gas filter correlation radiometry and H2O, NO2, O3 and CO2 by broadband filter radiometry. The instrument measured atmospheric infrared absorption at wavelengths from 2.43 to 10.25 microns. HALOE was flown on NASA's Upper Atmosphere Research Satellite (UARS) to investigate upper atmosphere chemistry, dynamics and radiative processes, particlarly stratospheric ozone destruction and chlorofluromethane impact on ozone. HALOE is a solar occultation experiment which typically views 15 sunrise and sunset events each day. Limb measurements were made in the altitude range between 3 km and 130 km (depending on channel) with less than 1 km resolution. For a given day, the profiles were in two distinct latitude bands, for the sunset and sunrise events. Coverage across the full range of latitudes between 80S and 80N was achieved on a time period ranging from about two to six weeks, depending on the time of year. The HALOE Level 2 data were processed with the version 19 algorithm.  The HALOE level 2 product consists of a single granule or file per day. A data granule contains all measured HALOE species and subtypes, and ancillary information. Aerosol extinction coefficients are measured in units of 1/km, chemical species are given in mixing ratios, and temperature is in units of degrees Kelvin. HALOE level 2 data are on 491 instrument resolution altitude levels. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180851,7 +181137,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348584-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348584-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGljczA2wqBwYXRoZmluZGVywqBsMmIgaW5zdGFudGFuZW91cyBzdXJmYWNlIHJhaW4gcmF0ZSAoaXNycikgdjEuMFwiLFwiR0VTX0RJU0NcIixcIlRST1BJQ1MwNlBSUFNMMkJcIixcIjEuMFwiLDMyNTQ4Mzk3MjEsM10iLCJ1bW0iOiJbXCJ0cm9waWNzMDbCoHBhdGhmaW5kZXLCoGwyYiBpbnN0YW50YW5lb3VzIHN1cmZhY2UgcmFpbiByYXRlIChpc3JyKSB2MS4wXCIsXCJHRVNfRElTQ1wiLFwiVFJPUElDUzA2UFJQU0wyQlwiLFwiMS4wXCIsMzI1NDgzOTcyMSwzXSJ9/UARHA3AT_019",
         "description": "The Halogen Occultation Experiment (HALOE) Level 3AT data product consists of daily vertical profiles of temperature, aerosol extinction and concentrations of HCl, HF, CH4, NO by gas filter correlation radiometry and H2O, NO2, O3 by broadband filter radiometry. The instrument measured atmospheric infrared absorption at wavelengths from 2.43 to 10.25 microns. HALOE was flown on NASA's Upper Atmosphere Research Satellite (UARS) to investigate upper atmosphere chemistry, dynamics and radiative processes, particlarly stratospheric ozone destruction and chlorofluromethane impact on ozone. HALOE is a solar occultation experiment which typically views 15 sunrise and sunset events each day. Limb measurements were made in the altitude range between 15 km and 60 - 130 km (depending on channel) with about 2.5 km resolution. For a given day, the profiles were in two distinct latitude bands, for the sunset and sunrise events. Coverage across the full range of latitudes between 80S and 80N was achieved on a time period ranging from about two to six weeks, depending on the time of year. The HALOE Level 3AT data were processed with the version 19 algorithm.  The HALOE level 3AT product consists of 13 granules per day. A data granule is one HALOE species or subtype per day. HALOE data are on the UARS standard pressure levels (in mbars) given by:  P(i) =  1000 * 10**(-i/6)  for i = 0, 1, 2, ... 54  Each of the 13 HALOE granules is accompanied by 2 additional parameter files, designated as level 3TP. The first parameter file, subtype LAT, contains the latitude values for each pressure level of each event for the day. The second parameter file, subtype LON, contains the longitude values. The level 3AT files only contain the latitude/longitude location corresponding to the 30 km retrieval point. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180864,7 +181150,7 @@
         "bbox": "-180, -76, 180, 76",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348585-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348585-GES_DISC.html",
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         "description": "The High Resolution Doppler Imager (HRDI) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of meridional and zonal wind components, temperature and volume emmission rate of O2. The instrument measured Doppler shifts of spectral lines in the visible and near-IR between 400 and 800 nm. HRDI was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure winds and other parameters in the mesosphere and lower thermosphere by primarily observing the Doppler shift of emitted light, and in the stratosphere by observing the Doppler shift of atmospheric absorption features. Measurements were made in the mesosphere between 50 and 115 km, and in the stratosphere between 10 and 40 km at about 2.5 km resolution. Data were collected between latitude 40S and 76N and 76S and 40N, alternating each satellite yaw cycle of about 36 days. The HRDI Level 3AL data were processed with the version 11 algorithm.  The HRDI level 3AL product consists of 8 granules per day. A data granule is one HRDI species or subtype per day.  Data are on the UARS standard altitude levels (in km) given by:  z(i) = 5*i                for i<=12 z(i) = 60 + (i-12)*3      for 13 <= i <= 32 z(i) = 120 + (i-32)*5     for 33 <= i <= 88  as well as the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180877,7 +181163,7 @@
         "bbox": "-180, -76, 180, 76",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348586-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348586-GES_DISC.html",
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         "description": "The High Resolution Doppler Imager (HRDI) Level 3AT data product consists of daily, 65.536 second interval time-ordered vertical profiles of meridional and zonal wind components, temperature and volume emmission rate of O2. The instrument measured Doppler shifts of spectral lines in the visible and near-IR between 400 and 800 nm. HRDI was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure winds and other parameters in the mesosphere and lower thermosphere by primarily observing the Doppler shift of emitted light, and in the stratosphere by observing the Doppler shift of atmospheric absorption features. Measurements were made in the mesosphere between 50 and 115 km, and in the stratosphere between 10 and 40 km at about 2.5 km resolution. Data were collected between latitude 40S and 76N and 76S and 40N, alternating each satellite yaw cycle of about 36 days. The HRDI Level 3AT data were processed with the version 11 algorithm.  The HRDI level 3AT product consists of 8 granules per day. A data granule is one HRDI species or subtype per day.  Data are on the UARS standard altitude levels (in km) given by:  z(i) = 5*i                for i<=12 z(i) = 60 + (i-12)*3      for 13 <= i <= 32 z(i) = 120 + (i-32)*5     for 33 <= i <= 88  as well as the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180890,7 +181176,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348587-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348587-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGljczA2wqBwYXRoZmluZGVywqBsMmIgaW5zdGFudGFuZW91cyBzdXJmYWNlIHJhaW4gcmF0ZSAoaXNycikgdjEuMFwiLFwiR0VTX0RJU0NcIixcIlRST1BJQ1MwNlBSUFNMMkJcIixcIjEuMFwiLDMyNTQ4Mzk3MjEsM10iLCJ1bW0iOiJbXCJ0cm9waWNzMDbCoHBhdGhmaW5kZXLCoGwyYiBpbnN0YW50YW5lb3VzIHN1cmZhY2UgcmFpbiByYXRlIChpc3JyKSB2MS4wXCIsXCJHRVNfRElTQ1wiLFwiVFJPUElDUzA2UFJQU0wyQlwiLFwiMS4wXCIsMzI1NDgzOTcyMSwzXSJ9/UARIS3AL_010",
         "description": "The Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, CO, N2O, N2O5, NO2, and aerosol absorption coefficients. The insrument measured infrared molecular emmissions in the spectral region from 4.6 to 16.6 microns. ISAMS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the global temperature and composition profiles in the stratosphere and mesosphere. Limb measurements were made in the altitude range between 15 and 60 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The ISAMS Level 3AL data were processed with the version 10 algorithm, except H2O which is version 9.  The ISAMS level 3AL product consists of 10 granules per day. A data granule is one ISAMS species or subtype per day.  Data are on the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  Each of the 10 ISAMS granules is accompanied by its own additional parameter file, designated as level 3LP. The parameter file, contains the additional ancillary and quality information not found in the 3AL file. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180903,7 +181189,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348588-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348588-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGljczA2wqBwYXRoZmluZGVywqBsMmIgaW5zdGFudGFuZW91cyBzdXJmYWNlIHJhaW4gcmF0ZSAoaXNycikgdjEuMFwiLFwiR0VTX0RJU0NcIixcIlRST1BJQ1MwNlBSUFNMMkJcIixcIjEuMFwiLDMyNTQ4Mzk3MjEsM10iLCJ1bW0iOiJbXCJ0cm9waWNzMDbCoHBhdGhmaW5kZXLCoGwyYiBpbnN0YW50YW5lb3VzIHN1cmZhY2UgcmFpbiByYXRlIChpc3JyKSB2MS4wXCIsXCJHRVNfRElTQ1wiLFwiVFJPUElDUzA2UFJQU0wyQlwiLFwiMS4wXCIsMzI1NDgzOTcyMSwzXSJ9/UARIS3AT_010",
         "description": "The Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AT data product consists of daily, 65.536 second interval time-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, CO, N2O, N2O5, NO2, and aerosol absorption coefficients. The insrument measured infrared molecular emmissions in the spectral region from 4.6 to 16.6 microns. ISAMS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the global temperature and composition profiles in the stratosphere and mesosphere. Limb measurements were made in the altitude range between 15 and 60 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The ISAMS Level 3AT data were processed with the version 10 algorithm, except H2O which is version 9.  The ISAMS level 3AT product consists of 10 granules per day. A data granule is one ISAMS species or subtype per day.  Data are on the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  Each of the 10 ISAMS granules is accompanied by its own additional parameter file, designated as level 3TP. The parameter file, contains the additional ancillary and quality information not found in the 3AT file. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180916,7 +181202,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348589-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348589-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGljczA2wqBwYXRoZmluZGVywqBsMmIgaW5zdGFudGFuZW91cyBzdXJmYWNlIHJhaW4gcmF0ZSAoaXNycikgdjEuMFwiLFwiR0VTX0RJU0NcIixcIlRST1BJQ1MwNlBSUFNMMkJcIixcIjEuMFwiLDMyNTQ4Mzk3MjEsM10iLCJ1bW0iOiJbXCJ0cm9waWNzMDbCoHBhdGhmaW5kZXLCoGwyYiBpbnN0YW50YW5lb3VzIHN1cmZhY2UgcmFpbiByYXRlIChpc3JyKSB2MS4wXCIsXCJHRVNfRElTQ1wiLFwiVFJPUElDUzA2UFJQU0wyQlwiLFwiMS4wXCIsMzI1NDgzOTcyMSwzXSJ9/UARML3AL_005",
         "description": "The Microwave Limb Sounder (MLS) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of temperature, geopotential height, concentrations of O3, H2O, CH3CN, ClO, HNO3, and SO2. The insrument measures in the microwave spectral region at frequencies of 63, 183 and 205 GHz. MLS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the chemical composition of the stratosphere and mesosphere, relationship between chlorine monoxide and ozone destruction. Limb measurements were made in the altitude range between 10 and 85 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The MLS Level 3AL data were processed with the version 5 algorithm, except SO2 which remained version 4. Note: H2O and O3 at 183 GHz data are available only through April 15, 1993 when the 183 GHz radiometer failed.  The MLS level 3AL product consists of 9 granules per day. A data granule is one MLS species or subtype per day.  Data are on the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  Each of the 9 MLS granules is accompanied by an additional parameter file, designated as level 3LP. The parameter file, contains the additional ancillary and quality information, as well as total column amounts not found in the 3AL files. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180929,7 +181215,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348590-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348590-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARML3AT_005",
         "description": "The Microwave Limb Sounder (MLS) Level 3AT data product consists of daily, 4 degree increment latitude-ordered vertical profiles of temperature, geopotential height, concentrations of O3, H2O, CH3CN, ClO, HNO3, and SO2, as well as upper tropospheric humidity (UTH). The insrument measures in the microwave spectral region at frequencies of 63, 183 and 205 GHz. MLS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the chemical composition of the stratosphere and mesosphere, relationship between chlorine monoxide and ozone destruction. Limb measurements were made in the altitude range between 10 and 85 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The MLS Level 3AT data were processed with the version 5 algorithm, except H2O and HNO3 which are version 6, and SO2 and UTH which remained version 4. Note: H2O and O3 at 183 GHz data are available only through April 15, 1993 when the 183 GHz radiometer failed.  The MLS level 3AT product consists of 10 granules per day. A data granule is one MLS species or subtype per day.  Data are on the UARS standard pressure levels (in mbars) given by:  P(i) = 1000 * 10**(-i/6)  for i = 0, 1, 2, ...  Each of the 10 MLS granules is accompanied by an additional parameter file, designated as level 3TP. The parameter file, contains the additional ancillary and quality information, as well as total column amounts not found in the 3AT files. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -180942,7 +181228,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348592-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348592-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE2AXIS1_001",
         "description": "The UARS Particle Environment Monitor (PEM) level 2 Atmosphere X-Ray Imaging Spectrometer (AXIS) unit 1 daily product contains the X-ray high-resolution spectral data converted to number intensity units from the AXIS1 pixels mounted on the UARS body. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The PEM AXIS1 X-ray data cover roughly the energy range from 2 keV to 300 keV. There are eight AXIS1 pixels mounted in the AXIS1 housing, each viewing different directions. The AXIS1 pixels are aligned on the spacecraft to project about 45 degrees toward the +x-axis direction from the Earthward pointing direction (+z-axis). Each pixel of AXIS1 is staggered about the 45 degree direction in an every-other fashion. Pixel 1 is closest to the center line of the spacecraft and Pixel 8 is furtherest away; however, their ground projection is dependent on the spacecraft orientation.  There is one data file per day for the PEM AXIS1 product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the AXIS1 product ranges between -80 and +80 degrees latitude. The AXIS1 data files are written in network binary format. For more information please review the PEM AXIS1 data format guide.",
         "license": "proprietary"
     },
@@ -180955,7 +181241,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348499-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348499-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE2AXIS2_001",
         "description": "The UARS Particle Environment Monitor (PEM) level 2 Atmosphere X-Ray Imaging Spectrometer (AXIS) unit 2 daily product contains the X-ray high-resolution spectral data converted to number intensity units from the AXIS2 pixels mounted on the UARS body. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The PEM AXIS2 X-ray data cover roughly the energy range from 2 keV to 300 keV. There are eight AXIS2 pixels mounted in the AXIS2 housing, each viewing different directions. The AXIS2 pixels are aligned on the spacecraft to project about 45 degrees toward the +x axis direction from the Earthward pointing direction (+z axis). Each pixel of AXIS2 is staggered about the 45 degree direction in an every-other fashion. Pixel 1 is closest to the center line of the spacecraft and Pixel 8 is furtherest away; however, their ground projection is dependent on the spacecraft orientation.  There is one data file per day for the PEM AXIS2 product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the AXIS2 product ranges between -80 and +80 degrees latitude. The AXIS2 data files are written in network binary format. For more information please review the PEM AXIS2 data format guide.",
         "license": "proprietary"
     },
@@ -180968,7 +181254,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348593-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348593-GES_DISC.html",
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         "description": "The Particle Environment Monitor (PEM) level 2 High-Energy Particle Spectrometer (HEPS) A daily product contains electron high-resolution spectral data converted to number intensity units from the HEPS telescopes mounted on the zenith UARS boom. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The PEM HEPS electron data covers roughly the energy range from 35 keV to 5 MeV. There are four telescopes mounted in different directions. These measure -15 deg, +15 deg, +45 deg, and +90 degrees with respect to the spacecraft -z-axis and along the spacecraft +x-axis. The HEPS electron units accumulate a spectrum in 4.086 seconds. There are two HEPS units in these data product files (labeled HEPS1 and HEPS2), each containing two telescopes (labeled telescope 1 and telescope 2). Each telescope contains a stack of solid state crystals. The signals from each of the crystals are combined by energy processing electronics of the instrument to yield two logical crystals or detectors, called the DE and EE detectors. The DE detector has the rough energy range from 35 keV to 300 keV and the EE detector rough energy range is from 300 keV to 5 MeV.  There is one data file per day for the PEM HEPSA product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the HEPSA product ranges between -57 and +57 degrees latitude. The HEPSA data files are written in network binary format. For more information please review the PEM HEPSA data format guide.",
         "license": "proprietary"
     },
@@ -180981,7 +181267,7 @@
         "bbox": "-180, -57.15, 180, 57.15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348594-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348594-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE2HEPSB_001",
         "description": "The Particle Environment Monitor (PEM) level 2 High-Energy Particle Spectrometer (HEPS) B daily product contains the electron high-resolution spectral data converted to number intensity units from the HEPS telescopes mounted on the nadir UARS boom, and the proton high-resolution spectral data converted to number intensity units from the HEPS telescopes mounted on the zenith boom. There are no HEPS proton measuring instruments on the nadir boom. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The PEM HEPS nadir boom electron data covers the rough range from 35 keV to 5 MeV. There are two telescopes mounted in different directions. These measure -165 and +165 degrees with respect to the spacecraft -z-axis and along the spacecraft +x-axis. The HEPS electron units accumulate a spectrum in 16.384 sec. The PEM HEPS zenith boom proton data covers the rough range from 70 keV to 150 MeV for mounting angles less than 30 degrees and 500 keV to 150 MeV for mounting angles greater than 30 deg. There are six telescopes mounted in four different directions. These measure -15 deg, +15 deg, +45 deg, and +90 degrees with respect to the spacecraft -z-axis and along the spacecraft +x-axis. The PEM HEPS proton units accumulate a spectrum in 16.384 sec. The nadir HEPS electron unit in this file (labeled HEPS3) contains two telescopes (labeled telescope 1 and telescope 2). Each telescope contains a stack of solid state crystals. The signals from each of the crystals are combined by energy processing electronics of the instrument to yield two logical crystals or detectors, called the DE and EE detectors. The DE detector has the rough energy range from 35 keV to 300 keV and the EE detector rough energy range is from 300 keV to 5 MeV. These designations are used in the description of HEPS electron data.  There is one data file per day for the PEM HEPSB product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the HEPSB product ranges between -57 and +57 degrees latitude. The HEPSB data files are written in network binary format. For more information please review the PEM HEPSB data format guide.",
         "license": "proprietary"
     },
@@ -180994,7 +181280,7 @@
         "bbox": "-180, -57.15, 180, 57.15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348596-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348596-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE2MEPS_001",
         "description": "The Particle Environment Monitor (PEM) level 2 Medium-Energy Particle Spectrometer (MEPS) daily product contains the electron and proton high-resolution spectral data converted to number intensity units from the MEPS sensors mounted on both the zenith and nadir UARS booms. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The PEM MEPS data covers roughly the energy range from 1 eV - 5 eV to 32 keV, where the lower energy cutoff is determined by internal instrument protection potentials. There are five analyzers mounted in different directions on the zenith boom, each of which contains an electron and ion sensor. These analyzers are mounted at -23.7 deg, +6.3 deg, +21.3 deg, +36.3 deg, and +66.3 degrees with respect to the spacecraft -z axis and along the spacecraft +y axis. There are three analyzers mounted in different directions on the nadir boom, each of which contain only an electron sensor. These analyzers are mounted at -158.7 deg, +156.3 deg, and +126.3 deg, with respect to the spacecraft -z axis and along the spacecraft +y axis. All MEPS analyzers accumulate a spectrum in 2.046 sec.  There is one data file per day for the PEM MEPS product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the MEPS product ranges between -57 and +57 degrees latitude. The MEPS data files are written in network binary format. For more information please review the PEM MEPS data format guide.",
         "license": "proprietary"
     },
@@ -181007,7 +181293,7 @@
         "bbox": "-180, -57.15, 180, 57.15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348620-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348620-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhdCB2MDA1ICh1YXJtbDNhdCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBVFwiLFwiNVwiLDEyNzMzNDg1OTAsMjFdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhdCB2MDA1ICh1YXJtbDNhdCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBVFwiLFwiNVwiLDEyNzMzNDg1OTAsMjFdIn0%3D/UARPE2VMAGAC_001",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE2VMAGAC_001",
         "description": "The Particle Environment Monitor (PEM) level 2 Vector Magnetometer (VMAG) AC daily product contains the Vector Magnetic Field AC component. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The VMAG DC magnetic field measurements are limited to frequencies less than 2.5 Hz by an 18 db/octave antialiasing filter. Higher frequencies are measured with a peak detector and are the Vector Magnetic Field AC component. The AC value is derived from each vector field component where the sensor output is pass band filtered from 2.5 to 50 Hz. The resultant signal is then half wave rectified and passed to an RC circuit with a time constant of 4.7 s. The voltage across the RC circuit is the peak detector output which therefore represents the peak positive amplitude of the 2.5-50 Hz filtered sensor output occurring during the previous 5 seconds; however, the peak detector is determined at a rate of about every second (the VMAG AC data has been adjusted for this time offset). The X and Z peak detectors have full scale of 1oo nT peak to peak (= 5 Volts) and the Y peak detector has a full scale of 10 nT peak to peak (= 5 Volts). The analog 0 to 5 Volts peak detector outputs are sent directly to the PEM central electronics package where they are digitized into a 265 binary word. This is the raw value in the data. No in-flight calibration of the AC peak detection electronics is provided. The VMAG unit is located on the zenith boom of UARS.  There is one data file per day for the PEM VMAG AC product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the VMAG AC product ranges between -57 and +57 degrees latitude. The VMAG AC data files are written in network binary format. For more information please review the PEM VMAG AC data format guide.",
         "license": "proprietary"
     },
@@ -181020,7 +181306,7 @@
         "bbox": "-180, -57.15, 180, 57.15",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348602-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348602-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhdCB2MDA1ICh1YXJtbDNhdCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBVFwiLFwiNVwiLDEyNzMzNDg1OTAsMjFdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhdCB2MDA1ICh1YXJtbDNhdCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBVFwiLFwiNVwiLDEyNzMzNDg1OTAsMjFdIn0%3D/UARPE2VMAGDC_001",
+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE2VMAGDC_001",
         "description": "The Particle Environment Monitor (PEM) level 2 Vector Magnetometer (VMAG) DC daily product contains the Vector Magnetic Field component, UARS Aspect Magnetometers component, and UARS Torquer Bars component data converted to nanoTesla and milliAmp units. PEM was flown on the UARS spacecraft to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere.  The VMAG DC data range is from -65000 nT to +65000 nT, with 2 nT resolution. Measurements were from the three vector components, X, Y, and Z with respect to the UARS spacecraft orientation. The VMAG sensor consists of three orthogonal ring-core fluxgate sensors, surrounded by a thermal sphere. Stray magnetic fields from the spacecraft can be accounted for by use of the UARS torquer bar currents. The VMAG unit is located on the zenith boom of UARS. The UARS aspect magnetometers and torquer bars are located on the body of the UARS spacecraft.  There is one data file per day for the PEM VMAG DC product, and the temporal coverage is from Oct. 1, 1991 to Aug. 23, 2005. Spatial coverage for the VMAG DC product ranges between -57 and +57 degrees latitude. The VMAG DC data files are written in network binary format. For more information please review the PEM VMAG DC data format guide.",
         "license": "proprietary"
     },
@@ -181033,7 +181319,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348591-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348591-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE3AT_004",
         "description": "The Particle Environment Monitor (PEM) Level 3AT data product consists of daily, 65.536 second interval time-ordered, vertical profiles of electron, proton and x-ray energy deposition rates. PEM was made up of four instruments: the Atmospheric X-Ray Imaging Spectrometer (AXIS), the High Energy Particle Spectrometer (HEPS), the Medium Energy Spectrometer (MEPS), and the Vector Magnetometer (VMAG). PEM was flown on NASA's Upper Atmosphere Research Satellite (UARS) to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere. The PEM electron and proton data are processed with the version 4 algorithm, while the x-ray data remained version 3.  The PEM level 3AT data consist of 18 granules per day. A data granule is defined as one PEM subtype per day. The x-ray pixel subtypes are grouped together in a single tar file for each day, the electron and proton are available as individual files per day.  Data are on the UARS standard altitude levels (in km) given by:  z(i) = 5 * i,                i <= 12 z(i) = 60 + (i - 12) * 3,    13 <= i <= 32 z(i) = 120 + (i - 32) * 10,  33 <= i <= 50  The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -181046,7 +181332,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348498-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348498-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhbCB2MDA1ICh1YXJtbDNhbCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBTFwiLFwiNVwiLDEyNzMzNDg1ODksMjBdIn0%3D/UARPE3TP_004",
         "description": "The Particle Environment Monitor (PEM) Level 3TP data product consists of daily, 65.536 second and 2.048 interval time-ordered, vertical profiles of electron and proton rates. PEM was made up of four instruments: the Atmospheric X-Ray Imaging Spectrometer (AXIS), the High Energy Particle Spectrometer (HEPS), the Medium Energy Spectrometer (MEPS), and the Vector Magnetometer (VMAG). PEM was flown on NASA's Upper Atmosphere Research Satellite (UARS) to measure the type, amount, energy, and distribution of charged particles injected into the Earth's thermosphere, mesosphere, and stratosphere. The PEM Level 3TP data are processed with the version 4 algorithm.  The PEM level 3TP data are a special data product, providing higher temporal resolution than the level 3AT data, with the HEPS and MEPS instrument data in separate files. The HEPS profiles are made every 65.536 seconds, and the MEPS profiles are made every 2.048 seconds.  Data are on the UARS standard altitude levels (in km) given by:  z(i) = 5 * i,                i <= 12 z(i) = 60 + (i - 12) * 3,    13 <= i <= 32 z(i) = 120 + (i - 32) * 10,  33 <= i <= 50  The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -181059,7 +181345,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348628-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348628-GES_DISC.html",
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         "description": "The Solar-Stellar Irradiance Comparison Experiment (SOLSTICE) Level 3BS data product consists of daily, 1 nm resolution, solar spectral irradiances and selected solar parameters. The instrument was a three-channel ultraviolet spectrometer that measured the magnitude of solar and spectral irradiances in the wavelength range from 119 to 420 nm. The design of the instrument allowed for observations of both the sun and bright blue stars, whose spectra is assumed to be constant. SOLSTICE was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the full disk solar irradiance with high precision and accuracy to follow short-term (minutes to hours), intermediate-term (days to weeks), and long-term (11 year sunspot, and 22 year solar magnetic field cycles) variations in the solar output. The SORCE Level 3BS data were processed with the version 18 algorithm.  The SOLSTICE Level 3BS data consists of 1 granule per day. The data are normalized to an earth-sun distance of 1 AU, and instrument degradation have been applied to the data. Included with the primary solar spectral irradiance values are daily average integrated intensities of Lyman alpha (121.6 nm), O-I (130.4 nm), C-IV (154.8 nm) and C-I (156.1 and 165.6 nm), and core-wing ratios of Mg-II (280.0 nm) and Ca-II (393.3 nm), as well as Carrington latitude and longitudes. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -181072,7 +181358,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348625-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348625-GES_DISC.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhdCB2MDA1ICh1YXJtbDNhdCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBVFwiLFwiNVwiLDEyNzMzNDg1OTAsMjFdIiwidW1tIjoiW1widWFycyBtaWNyb3dhdmUgbGltYiBzb3VuZGVyIChtbHMpIGxldmVsIDNhdCB2MDA1ICh1YXJtbDNhdCkgYXQgZ2VzIGRpc2NcIixcIkdFU19ESVNDXCIsXCJVQVJNTDNBVFwiLFwiNVwiLDEyNzMzNDg1OTAsMjFdIn0%3D/UARSU3BS_022",
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         "description": "The Solar Ultraviolet Spectral Irradiance Monitor (SUSIM) Level 3BS data product consists of daily, 1 nm resolution, solar spectral irradiances and selected solar parameters. The instrument consisted of two identical double-dispersion scanning spectrometers, seven detectors (5 photodiodes, 2 photon counters), and solar ultraviolet calibration sources measuring in the wavelength range from 110 to 410 nm. One spectrometer measured the solar disk while the other was for calibration using high-precision deuterium lamps calibrated by NIST. SUSIM was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the full disk solar irradiance with high precision and accuracy to follow short-term (minutes to hours), intermediate-term (days to weeks), and long-term (11 year sunspot, and 22 year solar magnetic field cycles) variations in the solar output. The SUSIM Level 3BS data were processed with the version 22 algorithm.  The SUSIM Level 3BS data consists of 1 granule per day. The data are normalized to an earth-sun distance of 1 AU, and instrument degradation have been applied to the data. Included with the primary solar spectral irradiance values are the following solar indices: Lyman alpha, O-I (130 nm), C-II (134 nm) and C-IV (155 nm), Al Edge, and core-wing ratios of Mg-I and Mg-II. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -181085,7 +181371,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348633-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348633-GES_DISC.html",
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         "description": "The Wind Imaging Interferometer (WINDII) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of meridional and zonal wind components, and temperature. The instrument was a Michelson interferometer designed to measure Doppler shifts of spectral lines in the visible between 550 and 780 nm. WINDII was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure wind, temperature and emission rates in the mesosphere and thermosphere between 80 and 300 km at about 5 km resolution. Data were collected between latitude 40S and 72N and 72S and 40N, alternating each satellite yaw cycle of about 36 days. The WINDII Level 3AL data were processed with the version 11 algorithm.  The WINDII level 3AL product consists of 3 granules per day. A data granule is one WINDII species or subtype per day.  Data are on the UARS standard altitude levels (in km) given by:  z(i) = 5*i for  1 <= i <= 12 z(i) = 60 + (i-12)*3       for 13 <= i <= 32 z(i) = 120 + (i-32)*5      for 33 <= i <= 88  Each of the 3 WINDII granules is accompanied by an additional parameter file, designated as level 3LP. The parameter file, contains additional ancillary and quality information not found in the 3AL files. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -181098,7 +181384,7 @@
         "bbox": "-180, -80, 180, 80",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348636-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348636-GES_DISC.html",
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         "description": "The Wind Imaging Interferometer (WINDII) Level 3AT data product consists of daily, 65.536 second interval time-ordered vertical profiles of meridional and zonal wind components, and temperature. The instrument was a Michelson interferometer designed to measure Doppler shifts of spectral lines in the visible between 550 and 780 nm. WINDII was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure wind, temperature and emission rates in the mesosphere and thermosphere between 80 and 300 km at about 5 km resolution. Data were collected between latitude 40S and 72N and 72S and 40N, alternating each satellite yaw cycle of about 36 days. The WINDII Level 3AT data were processed with the version 11 algorithm.  The WINDII level 3AT product consists of 3 granules per day. A data granule is one WINDII species or subtype per day.  Data are on the UARS standard altitude levels (in km) given by:  z(i) = 5*i for  1 <= i <= 12 z(i) = 60 + (i-12)*3       for 13 <= i <= 32 z(i) = 120 + (i-32)*5      for 33 <= i <= 88  Each of the 3 WINDII granules is accompanied by an additional parameter file, designated as level 3TP. The parameter file, contains additional ancillary and quality information not found in the 3AT files. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -181111,7 +181397,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348496-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348496-GES_DISC.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections?cursor=eyJqc29uIjoiW1widHJvcGljczA2wqBwYXRoZmluZGVywqBsMmIgaW5zdGFudGFuZW91cyBzdXJmYWNlIHJhaW4gcmF0ZSAoaXNycikgdjEuMFwiLFwiR0VTX0RJU0NcIixcIlRST1BJQ1MwNlBSUFNMMkJcIixcIjEuMFwiLDMyNTQ4Mzk3MjEsM10iLCJ1bW0iOiJbXCJ0cm9waWNzMDbCoHBhdGhmaW5kZXLCoGwyYiBpbnN0YW50YW5lb3VzIHN1cmZhY2UgcmFpbiByYXRlIChpc3JyKSB2MS4wXCIsXCJHRVNfRElTQ1wiLFwiVFJPUElDUzA2UFJQU0wyQlwiLFwiMS4wXCIsMzI1NDgzOTcyMSwzXSJ9/UARZCNMC_001",
         "description": "The UARS Correlative assimilation data from NOAA's National Meteorological Center (NMC) consists of daily model runs at 12 GMT as a means of providing an independent analysis for comparison with data from the UARS instruments. The NMC data product includes temperature (Kelvin), humidity (%), geopotential height (m), and zonal and meridional wind components (m/s).  Geopotential height and atmospheric temperature data are derived from two analysis systems: 1) tropospheric fields from 1000 to 100 mb, and 2) stratospheric analyses from 70 to 0.4 mb. The tropospheric fields are the 12 GMT gridded fields which are part of the Global Daily Assimilation System (GDAS), where data from radiosondes, aircraft, satellites, ships, bouys, or any other conventional means are assimilated and merged into meteorological fields (heights, temperature, winds). The stratospheric analyses are 12 GMT operational analyses at the 70 - 0.4 mb pressure levels produced from satellite temperature retrievals and RAOBS via a modified Cressman analysis. Tropospheric temperature analyses use combined NOAA-10 and NOAA-11 data. Moisture (northern hemisphere only) and Winds data are obtained from the NMC GDAS.  The gridded fields are on the standard 65 x 65 NMC polar stereographic grid oriented 80W (grid increment 381 km at 60N), and 100E (grid increment 381 km at 60S); Pole at (33,33). The NMC uses 18 standard pressure levels for data at 1000, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 10, 5, 2, 1, 0.4 millibars. Height and temperature data are produced at all 18 pressure levels from 1000 mb to 0.4 mb. Moisture data are only produced in the northern hemisphere for the 6 lowest altitude pressure levels. Wind data are produced for the 12 lowest altitude levels in the northern hemisphere, and at the 4 levels 1000, 500, 300, and 250 mb in the southern hemisphere.  There are four data files representing each subtype per day. Included in the NMC correlative data set will be a geographical data richness file. This file is used by the NMC access routines, and indicates the radiosonde coverage for each point on the NMC grid. The data files are available in a binary record oriented format.",
         "license": "proprietary"
     },
@@ -181124,7 +181410,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1273348581-GES_DISC.umm_json",
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         "description": "This dataset provides maps of coastal wetland carbon and methane fluxes and coastal wetland surface elevation from 2006 to 2011 at 30 m resolution for coastal wetlands of the conterminous United States. Total coastal wetland carbon flux per year per pixel was calculated by combining maps of wetland type and change with soil, biomass, and methane flux data from a literature review. Uncertainty in carbon flux was estimated from 10,000 iterations of a Monte Carlo analysis. In addition to the uncertainty analysis, this dataset also provides a probabilistic map of the extent of tidal elevation, as well as the geospatial files used to create that surface, and a land cover and land cover change map of the coastal zone from 2006 to 2011 with accompanying estimated median soil, biomass, methane, and total CO2 equivalent annual fluxes, each with reported 95% confidence intervals, at 30 m resolution. Land cover was quantified using the Coastal Change Analysis Program (C-CAP), a Landsat-based land cover mapping product.",
         "license": "proprietary"
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         "license": "proprietary"
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         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Vegetation Index and Phenology (VIP) global datasets were created using Advanced Very High Resolution Radiometer (AVHRR) N07, N09, N11, and N14 datasets (1981 - 1999) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra MOD09 surface reflectance data (2000 - 2014). The VIP Vegetation Index (VI) product was developed to provide consistent measurements of the Normalized Difference Vegetation Index (NDVI) and modified Enhanced Vegetation Index (EVI2) spanning more than 30 years of data from multiple sensors. The EVI2 is a backward extension of AVHRR. Vegetation indices such as NDVI and EVI2 are useful for assessing the biophysical properties of the land surface, and are used to characterize vegetation phenology. Phenology tracks the seasonal life cycle of vegetation, and provides information on the biotic response to environmental changes.     The VIP07 VI data product is a composite of seven daily images with 0.05 degree (5600 meter (m)) spatial resolution in geographic (Lat/Lon) grid format. The data are stored in Hierarchical Data Format-Earth Observing System (HDF-EOS) file format. The VIP07 VI product contains 12 Science Datasets (SDS), which include the calculated VIs (NDVI and EVI2) as well as quality assurance/pixel reliability, the input Visible/Near Infrared (VNIR) surface reflectance data, and viewing geometry. The Blue and Middle Infrared (MIR) surface reflectance data are only available for the MODIS era (2000 - 2014). Gaps in the daily product are filled using long term mean VI records derived from the more than 30 year time series of data, and are indicated as gap-filled in the Pixel Reliability SDS. A low resolution browse image showing NDVI as a color map is also available.",
         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Vegetation Index and Phenology (VIP) global datasets were created using Advanced Very High Resolution Radiometer (AVHRR) N07, N09, N11, and N14 datasets (1981 - 1999) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra MOD09 surface reflectance data (2000 - 2014). The VIP Vegetation Index (VI) product was developed to provide consistent measurements of the Normalized Difference Vegetation Index (NDVI) and modified Enhanced Vegetation Index (EVI2) spanning more than 30 years of data from multiple sensors. The EVI2 is a backward extension of AVHRR. Vegetation indices such as NDVI and EVI2 are useful for assessing the biophysical properties of the land surface, and are used to characterize vegetation phenology. Phenology tracks the seasonal life cycle of vegetation, and provides information on the biotic response to environmental changes.   The VIP15 VI data product is provided twice monthly at 0.05 degree (5600 meter (m)) spatial resolution in geographic (Lat/Lon) grid format. The data are stored in Hierarchical Data Format-Earth Observing System (HDF-EOS) file format. The VIP15 VI product contains 12 Science Datasets (SDS) which include the calculated VIs (NDVI and EVI2) as well as quality assurance/pixel reliability, the input Visible/Near Infrared (VNIR) surface reflectance data, and viewing geometry. The Blue and Middle Infrared (MIR) surface reflectance data are only available for the MODIS era (2000 - 2014). Gaps in the daily product are filled using long term mean VI records derived from the more than 30 year time series of data, and are indicated as gap-filled in the Pixel Reliability SDS. A low resolution browse image showing NDVI as a color map is also available.  The VIP15 dataset includes two composites per month. The first composite is generated from day 1 to 15, and the second composite includes the remaining days of the month. This dataset consists of 24 files per year.",
         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Vegetation Index and Phenology (VIP) global datasets were created using Advanced Very High Resolution Radiometer (AVHRR) N07, N09, N11, and N14 datasets (1981 - 1999) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra MOD09 surface reflectance data (2000 - 2014). The VIP Vegetation Index (VI) product was developed to provide consistent measurements of the Normalized Difference Vegetation Index (NDVI) and modified Enhanced Vegetation Index (EVI2) spanning more than 30 years of data from multiple sensors. The EVI2 is a backward extension of AVHRR. Vegetation indices such as NDVI and EVI2 are useful for assessing the biophysical properties of the land surface, and are used to characterize vegetation phenology. Phenology tracks the seasonal life cycle of vegetation, and provides information on the biotic response to environmental changes.     The VIP30 VI data product is provided monthly at 0.05 degree (5600 meter (m)) spatial resolution in geographic (Lat/Lon) grid format. The data are stored in Hierarchical Data Format-Earth Observing System (HDF-EOS) file format. The VIP30 VI product contains 12 Science Datasets (SDS), which include the calculated VIs (NDVI and EVI2) as well as quality assurance/pixel reliability, the input Visible/Near Infrared (VNIR) surface reflectance data, and viewing geometry. The Blue and Middle Infrared (MIR) surface reflectance data are only available for the MODIS era (2000 - 2014). Gaps in the product are filled using long term mean VI records derived from the more than 30 year time series of data, and are indicated as gap-filled in the Pixel Reliability SDS.    The VIP30 dataset consists of 12 monthly composites annually representing each calendar month of the year.",
         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Vegetation Index and Phenology (VIP) global datasets were created using Advanced Very High Resolution Radiometer (AVHRR) N07, N09, N11, and N14 datasets (1981 - 1999) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra MOD09 surface reflectance data (2000 - 2014). The VIP Vegetation Index (VI) product was developed to provide consistent measurements of the Normalized Difference Vegetation Index (NDVI) and modified Enhanced Vegetation Index (EVI2) spanning more than 30 years of data from multiple sensors. The EVI2 is a backward extension of AVHRR. Vegetation indices such as NDVI and EVI2 are useful for assessing the biophysical properties of the land surface, and are used to characterize vegetation phenology. Phenology tracks the seasonal life cycle of vegetation, and provides information on the biotic response to environmental changes.     The VIP30 VI data product is provided monthly at 0.05 degree (5600 meter (m)) spatial resolution in geographic (Lat/Lon) grid format. The data are stored in Hierarchical Data Format-Earth Observing System (HDF-EOS) file format. The VIP30 VI product contains 12 Science Datasets (SDS), which include the calculated VIs (NDVI and EVI2) as well as quality assurance/pixel reliability, the input Visible/Near Infrared (VNIR) surface reflectance data, and viewing geometry. The Blue and Middle Infrared (MIR) surface reflectance data are only available for the MODIS era (2000 - 2014). Gaps in the product are filled using long term mean VI records derived from the more than 30 year time series of data, and are indicated as gap-filled in the Pixel Reliability SDS.    The VIP30 dataset consists of 12 monthly composites annually representing each calendar month of the year.",
         "license": "proprietary"
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         "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Vegetation Index and Phenology (VIP) global datasets were created using surface reflectance data from the Advanced Very High Resolution Radiometer (AVHRR) N07, N09, N11, and N14 datasets (1981 \u2013 1999) and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra MOD09 surface reflectance data (2000 - 2014).  The VIP Vegetation Index (VI) product was developed to provide consistent measurements of the Normalized Difference Vegetation Index (NDVI) and modified Enhanced Vegetation Index (EVI2) spanning more than 30 years of data from multiple sensors. The EVI2 is a backward extension of AVHRR. Vegetation indices such as NDVI and EVI2 are useful for assessing the biophysical properties of the land surface, and are used to characterize vegetation phenology. Phenology tracks the seasonal life cycle of vegetation, and provides information on the biotic response to environmental changes.     The VIPPHEN data product is provided globally at 0.05 degree (5600 meter) spatial resolution in geographic (Lat/Lon) grid format. The data are stored in Hierarchical Data Format-Earth Observing System (HDF-EOS) file format. The VIPPHEN phenology product contains 26 Science Datasets (SDS) which include phenological metrics such as the start, peak, and end of season as well as the rate of greening and senescence. The product also provides the maximum, average, and background calculated VIs. The VIPPHEN SDS are based on the daily VIP product series and are calculated using a 3-year moving window average to smooth out noise in the data. A reliability SDS is included to provide context on the quality of the input data. ",
         "license": "proprietary"
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         "description": "VISSRGOES1IMIR is the Visible Infrared Spin-Scan Radiometer (VISSR) Infrared Imagery on 70mm Film data product from the first Geostationary Operational Environmental Satellite (GOES-1). This set of IR imagery (10.5 to 12.5 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The GOES-1 satellite was parked over the equator at longitude 115W on Dec 18, 1975 viewing the hemisphere below the satellite. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00247 (old ID 75-100A-01B).",
         "license": "proprietary"
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         "description": "VISSRGOES1IMVIS is the Visible Infrared Spin-Scan Radiometer (VISSR) Visible Imagery on 70mm Film data product from the first Geostationary Operational Environmental Satellite (GOES-1). This set of visible imagery (0.55 to 0.70 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The GOES-1 satellite was parked over the equator at longitude 115W on Dec 18, 1975 viewing the hemisphere below the satellite. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00247 (old ID 75-100A-01B).",
         "license": "proprietary"
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         "description": "VISSRGOES2IMIR is the Visible Infrared Spin-Scan Radiometer (VISSR) Infrared Imagery on 70mm Film data product from the second Geostationary Operational Environmental Satellite (GOES-2). This set of IR imagery (10.5 to 12.5 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The GOES-2 satellite was parked over the equator at longitude 75W from 1977 through 1978 viewing the hemisphere below the satellite. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00028 (old ID 77-048A-01C).",
         "license": "proprietary"
     },
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         "description": "VISSRGOES2IMVIS is the Visible Infrared Spin-Scan Radiometer (VISSR) Visible Imagery on 70mm Film data product from the second Geostationary Operational Environmental Satellite (GOES-2). This set of visible imagery (0.55 to 0.70 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The GOES-2 satellite was parked over the equator at longitude 75W from 1977 through 1978 viewing the hemisphere below the satellite. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00087 (old ID 77-048A-01B).",
         "license": "proprietary"
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         "description": "VISSRGOES3IMIR is the Visible Infrared Spin-Scan Radiometer (VISSR) Infrared Imagery on 70mm Film data product from the third Geostationary Operational Environmental Satellite (GOES-3). This set of IR imagery (10.5 to 12.5 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The GOES-3 satellite was parked over the equator at longitude 135W from 1978 through 1981 viewing the hemisphere below the satellite. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00105 (old ID 75-100A-01C).",
         "license": "proprietary"
     },
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         "description": "VISSRGOES3IMVIS is the Visible Infrared Spin-Scan Radiometer (VISSR) Visible Imagery on 70mm Film data product from the third Geostationary Operational Environmental Satellite (GOES-3). This set of visible imagery (0.55 to 0.70 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The GOES-3 satellite was parked over the equator at longitude 135W from 1978 through 1981 viewing the hemisphere below the satellite. It was moved to its final operational position at 135W on Dec 19, 1975. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00247 (old ID 75-100A-01B).",
         "license": "proprietary"
     },
@@ -194709,7 +194995,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2386924897-GES_DISC.html",
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         "description": "VISSRSMS1IMIR is the Visible Infrared Spin-Scan Radiometer (VISSR) Infrared Imagery on 70mm Film data product from the first Synchronous Meteorological Satellite (SMS-1). This set of IR imagery (10.5 to 12.5 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The SMS-1 satellite was initially parked over the equator at longitude 45W on June 7, 1974 viewing the hemisphere below the satellite to support the GARP Atlantic Tropical Experiment (GATE). It was moved to its operational position at 75W on Nov 15, 1974 where it remained until GOES-1 was launched, after which SMS-1 was moved to 105W and placed in stand-by-mode as a backup to GOES-1 or SMS-2. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00068 (old ID 74-033A-01C).",
         "license": "proprietary"
     },
@@ -194722,7 +195008,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2386910832-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2386910832-GES_DISC.html",
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         "description": "VISSRSMS1IMVIS is the Visible Infrared Spin-Scan Radiometer (VISSR) Visible Imagery on 70mm Film data product from the first Synchronous Meteorological Satellite (SMS-1). This set of visible imagery (0.55 to 0.70 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The SMS-1 satellite was initially parked over the equator at longitude 45W on June 7, 1974 viewing the hemisphere below the satellite to support the GARP Atlantic Tropical Experiment (GATE). It was moved to its operational position at 75W on Nov 15, 1974 where it remained until GOES-1 was launched, after which SMS-1 was moved to 105W and placed in stand-by-mode as a backup to GOES-1 or SMS-2. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00040 (old ID 74-033A-01B).",
         "license": "proprietary"
     },
@@ -194735,7 +195021,7 @@
         "bbox": "-135, -90, 45, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1720172416-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1720172416-GES_DISC.html",
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         "description": "VISSRSMS1L1AOIPS is the Visible Infrared Spin-Scan Radiometer (VISSR) Level 1 Atmospheric and Oceanographic Image Processing System (AOIPS) data product from the first Synchronous Meteorological Satellite (SMS-1). There are typically three data files for a scene of the Earth with radiances that were measured in the visible (0.55 to 0.70 micrometer) and/or IR (10.5 to 12.6 micrometer) wavelengths with a spatial resolution of 0.9 and 8 km, respectively. Files also include time, geolocation, orbit, attitude, and telemetry information. There are three types of data files in this product: one contains IR data, one contains the IR grid information (blank before 1974/10/29), and another contains VIS data. Each data file is structured with an AOIPS label, followed by an IPD label, and then an optional 8 telemetry records followed by a set of data records. Visible data are typically 3904 pixels by either 4000 or 2000 scan lines (5 or 2.5 minute scenes respectively). IR data are typically 976 pixels by either 500 or 250 scan lines (5 or 2.5 minute scenes respectively). A full scan of the Earth was made every 20 minutes.  The data were used to make 70mm film negatives and 9.5\u201d positive prints on a Dicomed Image Recording System.  Data for this product are available from 1974/07/01 through 1979/04/19 (with gaps plus no data between 1975/08/20 and 1979/02/17). The SMS-1 satellite was initially parked over the equator at longitude 45W on June 7, 1974 viewing the hemisphere below the satellite to support the GARP Atlantic Tropical Experiment (GATE). It was moved to its operational position at 75W on Nov 15, 1974 where it remained until GOES-1 was launched, after which SMS 1 was moved to 105W and placed in stand-by-mode as a backup to GOES-1 or SMS-2. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00018 (old ID 74-033A-01D).",
         "license": "proprietary"
     },
@@ -194748,7 +195034,7 @@
         "bbox": "-135, -90, 45, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1695766381-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1695766381-GES_DISC.html",
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         "description": "VISSRSMS1L1EHT is the Visible Infrared Spin-Scan Radiometer (VISSR) Level 1 Experimenter History Tape (EHT) data product from the first Synchronous Meteorological Satellite (SMS-1). Each data file contains a segment of the Earth with radiances that were measured in the visible (0.55 to 0.70 micrometer) and/or IR (10.5 to 12.6 micrometer) wavelengths with a spatial resolution of 0.9 and 8 km, respectively. Files also include time, geolocation, orbit, attitude, and telemetry information. A data file is structured with a header, followed by an IR scan line and then 8 visible scan lines (although some files only contain IR scans). Visible scans are at full resolution of 15288 pixels and a file will contain several hundred scan lines. IR scans are at 3822 pixels and up to a hundred scan lines. A full scan of the Earth was made every 20 minutes.  Data for this product are only available for 9 days: 1974/08/23 (IR only), 1974/08/27 (IR only), 1974/08/31, 1974/09/01, 1974/09/02, 1974/09/05, 1974/09/24 (IR only), 1975/01/10, and 1975/02/17. The SMS-1 satellite was initially parked over the equator at longitude 45W on June 7, 1974 viewing the hemisphere below the satellite to support the GARP Atlantic Tropical Experiment (GATE). It was moved to its operational position at 75W on Nov 15, 1974 where it remained until GOES-1 was launched, after which SMS 1 was moved to 105W and placed in stand-by-mode as a backup to GOES-1 or SMS-2. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00126 (old ID 74-033A-01A).",
         "license": "proprietary"
     },
@@ -194761,7 +195047,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2386956718-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2386956718-GES_DISC.html",
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         "description": "VISSRSMS2IMIR is the Visible Infrared Spin-Scan Radiometer (VISSR) Infrared Imagery on 70mm Film data product from the second Synchronous Meteorological Satellite (SMS-2). This set of IR imagery (10.5 to 12.5 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The SMS-2 satellite was initially parked over the equator at longitude 105W on Feb 22, 1975 viewing the hemisphere below the satellite. It was moved to its final operational position at 135W on Dec 19, 1975. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00038 (old ID 75-011A-04C).",
         "license": "proprietary"
     },
@@ -194774,7 +195060,7 @@
         "bbox": "135, -90, -25, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2386944039-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2386944039-GES_DISC.html",
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         "description": "VISSRSMS2IMVIS is the Visible Infrared Spin-Scan Radiometer (VISSR) Visible Imagery on 70mm Film data product from the second Synchronous Meteorological Satellite (SMS-2). This set of visible imagery (0.55 to 0.70 micrometer) was originally produced on commercial image-generation equipment from digital tapes and was made available on 70-mm film, from which they were later scanned to digital TIFF image files. Each TIFF scan contains 2 or 3 pictures, and there are several hundred scans from an original 70 mm film roll which are combined into a ZIP file. Each picture contains a title on the top boundary and a 33-level gray scale on the right boundary that represents brightness temperatures. It may have a combination of the following options: 1) contrast enhancement, 2) image sectorization, and 3) 1/16-size imagery. The maximum effective size covers 500 sq km, represented by 4000 by 3904 pixels. Each element has a maximum resolution of 3.7 km. The title contains the satellite identification, picture number, picture type, coordinate numbers of the top left pixel relative to the visible sensor, start time of sectorized image, and pixel scaling and sector size identification.  The SMS-2 satellite was initially parked over the equator at longitude 105W on Feb 22, 1975 viewing the hemisphere below the satellite. It was moved to its final operational position at 135W on Dec 19, 1975. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00202 (old ID 75-011A-04B).",
         "license": "proprietary"
     },
@@ -194787,7 +195073,7 @@
         "bbox": "155, -90, -65, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1886381718-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1886381718-GES_DISC.html",
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         "description": "VISSRSMS2L1AOIPS is the Visible Infrared Spin-Scan Radiometer (VISSR) Level 1 Atmospheric and Oceanographic Image Processing System (AOIPS) data product from the second Synchronous Meteorological Satellite (SMS-2). There are typically three data files for a scene of the Earth with radiances that were measured in the visible (0.55 to 0.70 micrometer) and/or IR (10.5 to 12.6 micrometer) wavelengths with a spatial resolution of 0.9 and 8 km, respectively. Files also include time, geolocation, orbit, attitude, and telemetry information. There are three types of data files in this product: one contains IR data, one contains the IR grid information, and another contains VIS data. Each data file is structured with an AOIPS label, followed by an IPD label, and then an optional 8 telemetry records followed by a set of data records. Visible data are typically 3904 pixels by either 4000 or 2000 scan lines (5 or 2.5 minute scenes respectively). IR data are typically 976 pixels by either 500 or 250 scan lines (5 or 2.5 minute scenes respectively). A full scan of the Earth was made every 20 minutes.  The data were used to make 70mm film negatives and 9.5\u201d positive prints on a Dicomed Image Recording System.  Data for this product are available from 1975/04/27 through 1980/08/22 (with gaps plus no data between 1975/07/31 and 1979/05/10). The SMS-2 satellite was initially parked over the equator at longitude 105W on Feb 22, 1975 viewing the hemisphere below the satellite. It was moved to its final operational position at 135W on Dec 19, 1975. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00095 (old ID 75-011A-04D).",
         "license": "proprietary"
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         "description": "VISSRSMS2L1EHT is the Visible Infrared Spin-Scan Radiometer (VISSR) Level 1 Experimenter History Tape (EHT) data product from the second Synchronous Meteorological Satellite (SMS-2). Each data file contains a segment of the Earth with radiances that were measured in the visible (0.55 to 0.70 micrometer) and/or IR (10.5 to 12.6 micrometer) wavelengths with a spatial resolution of 0.9 and 8 km, respectively. Files also include time, geolocation, orbit, attitude, and telemetry information. A data file is structured with a header, followed by an IR scan line and then 8 visible scan lines (although some files only contain IR scans). Visible scans are at full resolution of 15288 pixels and a file will contain several hundred scan lines. IR scans are at 3822 pixels and up to a hundred scan lines. A full scan of the Earth was made every 20 minutes.  Data for this product are only available for 5 days: 1975/02/17, 1975/04/24, 1975/04/25, 1975/05/06, and 1975/08/28. The SMS-2 satellite was initially parked over the equator at longitude 105W on Feb 22, 1975 viewing the hemisphere below the satellite. It was moved to its final operational position at 135W on Dec 19, 1975. The VISSR experiment was operated by the NOAA National Environmental Satellite Data and Information Service (NESDIS), as well as scientists from NASA Goddard Space Flight Center.  This product was previously available from the NSSDC with the identifier ESAD-00039 (old ID 75-011A-04A).",
         "license": "proprietary"
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         "license": "proprietary"
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         "license": "proprietary"
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         "description": "The Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) daily surface reflectance Climate Modeling Grid (VJ109CMG) Version 2 product provides an estimate of land surface reflectance from the NOAA-20 VIIRS sensor. Data are provided for three imagery bands (I1-I3) and nine moderate resolution bands (M1-M5, M7, M8, M10, M11) at 0.05 degree (~5,600 meter) resolution. The data are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. This product uses a weighted average of the best quality observation and is formatted as a CMG for use in climate simulation models. This product includes the twelve reflectance bands, five moderate resolution brightness temperature bands (M12-M16) and information layers representing relative azimuth angle, sensor zenith angle, solar zenith angle, reflectance band quality, time of day, and number mapping.   ",
         "license": "proprietary"
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         "description": "The Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) daily surface reflectance (VJ109GA) Version 2 product provides an estimate of land surface reflectance from the NOAA-20 VIIRS sensor. Data are provided for three imagery bands (I1-I3) at nominal 500 meter resolution (~463 meter) and nine moderate resolution bands (M1-M5, M7, M8, M10, M11) at nominal 1 kilometer (~926 meter) resolution. The 500 meter and 1 kilometer datasets are derived through resampling the native 375 meter and 750 meter VIIRS resolutions, respectively, in the Level 2 input product. These bands are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols.     The inputs to the surface reflectance algorithm are top-of-atmosphere reflectance for the VIIRS visible bands,the VIIRS cloud mask and aerosol product, aerosol optical thickness and atmospheric data obtained from the NOAA National Centers for Environmental Prediction (NCEP) reanalysis system. Along with the twelve reflectance bands are reflectance band quality, sensor azimuth angle, solar azimuth angle, sensor zenith angle, solar zenith angle, and observations layers. The reflectance layers from the VNP09GA data product are used as input data for many of the VIIRS land products. ",
         "license": "proprietary"
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         "description": "The 8-day Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) Surface Reflectance (VJ109H1) Version 2 composite product provides an estimate of land surface reflectance from the NOAA-20 VIIRS sensor for three imagery bands (I1, I2, I3) at nominal 500 meter resolution (~463 meter). The 500 meter dataset is derived through resampling the native 375 meter VIIRS resolution in the L2 input product. The data are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. Each pixel represents the best possible Level 2G observation during an 8-day period, which is selected on the basis of high observation coverage, low sensor angle, the absence of clouds or cloud shadow, and aerosol loading. The three reflectance bands, this product includes a state quality assurance (QA) layer and a reflectance band quality layer.     ",
         "license": "proprietary"
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         "description": "This data set reports the location of snow cover using radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Joint Polar Satellite System's first satellite (JPSS-1). Snow cover is identified using the Normalized Difference Snow Index (NDSI) and a series of quality control screens.",
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         "license": "proprietary"
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         "description": "The Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) Thermal Anomalies (VJ114) Version 2 product is produced in 6-minute temporal satellite increments (swaths) at 750 meter resolution from the VIIRS sensor located on the NOAA-20 satellite. This product is designed after the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire data products to promote the continuity of the Earth Observation System (EOS) mission. This data product can enable users to understand the location and intensity of fire events as well as identifying thermal anomalies.     The VJ114 product includes 31 science dataset layers to analyze key factors in fire detection, including atmospheric conditions (e.g., atmospheric reflectance, solar zenith angle, brightness temperature) and fuel type for the event. The fire mask layer in the VJ114 product is the primary layer and can be used to identify fires and other thermal anomalies such as volcanoes. In addition to the fire mask, brightness temperature is provided for VIIRS channels M5, M7, M11, M13, M15, and M16.      Each swath of data is approximately 3,060 kilometers along track (long) and 3,060 kilometers across track (wide). The VJ114 product is also used to generate higher-level fire data products.    Use of the (VJ103MODLL) (https://doi.org/10.5067/viirs/vj103modll.021) data product is required to apply accurate geolocation information to the VJ114 Science Datasets (SDS).  ",
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         "license": "proprietary"
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         "license": "proprietary"
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         "description": "The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) Land Surface Temperature and Emissivity (LST&E) 8-day Climate Modeling Grid Version 2 product (VJ121C2) combines the daily (VJ121A1D) (http://doi.org/10.5067/VIIRS/VJ121A1D.002) and (VJ121A1N) (http://doi.org/10.5067/VIIRS/VJ121A1N.002) products over an 8-day compositing period into a single product. The VJ121C2 dataset is an 8-day composite LST&E product at 0.05 degree (~5,600 meter) resolution that uses an algorithm based on a simple-averaging method and is formatted as a CMG for use in climate simulation models. The algorithm calculates the average from all the cloud-free VJ121A1D and VJ121A1N daily acquisitions from the 8-day period. Unlike the VJ121A1 datasets where the daytime and nighttime acquisitions are separate products, the VJ121C2 contains both daytime and nighttime acquisitions as separate science dataset (SDS) layers within a single Hierarchical Data Format (HDF) file. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/sites/default/files/public/product_documentation/vnp21_atbd.pdf.  ",
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         "description": "The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) Land Surface Temperature and Emissivity (LST&E) monthly Climate Modeling Grid Version 2 product (VJ121C3) provides LST&E by a process of selecting the best available pixel over a monthly acquisition period at 0.05 degree (~5,600 meter) resolution. The VJ121C3 dataset is a monthly composite LST&E product that uses an algorithm based on a simple averaging method and is formatted as a CMG for use in climate simulation models. The algorithm calculates the average from all the cloud free VJ121A1D (http://doi.org/10.5067/VIIRS/VJ121A1D.002) and VJ121A1N (http://doi.org/10.5067/VIIRS/VJ121A1N.002) daily acquisitions from the monthly period. Unlike the VJ121A1 data sets where the daytime and nighttime acquisitions are separate products, the VJ121C3 contains both daytime and nighttime acquisitions as separate Science Dataset (SDS) layers within a single Hierarchical Data Format (HDF) file. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/1332/VNP21_ATBD_V1.pdf).  ",
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         "description": "The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) Version 2 swath product (VJ121) is produced daily in 6-minute temporal increments of satellite acquisition. The VJ121 product uses a physics-based algorithm to dynamically retrieve both the LST and emissivity simultaneously for VIIRS thermal infrared bands M14 (8.55 \u00b5m), M15 (10.76 \u00b5m), and M16 (12 \u00b5m) at a spatial resolution of 750 meters.    The VJ121 product is developed synergistically with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST&E Version 6.1 product (MOD21) (https://doi.org/10.5067/MODIS/MOD21.061) using the same input atmospheric products and algorithmic approach based on the ASTER Temperature Emissivity Separation (TES) technique. The TES algorithm is combined with an improved Water Vapor Scaling (WVS) atmospheric correction scheme to stabilize the retrieval during very warm and humid conditions. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 2 (L2) product are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/1332/VNP21_ATBD_V1.pdf).    Provided in the VJ121 product are layers for LST, quality control, emissivity for bands M14, M15, and M16, LST&E errors, view angle, ASTER Global Emissivity Dataset (GED), Precipitable Water Vapor (PWV), ocean-land mask, latitude, and longitude. A low-resolution browse image for LST is also available for each VJ121 granule.  ",
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         "description": "The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Water Reservoir 8-day Level 3 (L3) Global (VJ128C2) Version 2 product provides current data for 151 man-made reservoirs and 13 regulated natural lakes for a total of 164 reservoirs.    The VJ128C2 data product provides an 8-day time series of surface area, elevation, and water storage.  Datasets are combined with pre-established Area-Elevation (A-E) curves and image classifications of near-infrared (NIR) reflectance from the surface reflectance product acquired by the VIIRS satellite (VJ109H1).    The VJ128C2 data product consists of a single layer with information about the reservoir identifier, dam location (longitude and latitude), reservoir surface area, elevation, and water storage capacity.   ",
         "license": "proprietary"
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         "description": "The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Water Reservoir Monthly Level 3 (L3) Global (VJ128C3) Version 2 product provides current data for 151 man-made reservoirs and 13 regulated natural lakes for a total of 164 reservoirs.    The VJ128C3 data product is a composite of the 8-day area classifications from VJ128C2 which is converted to provide monthly elevation and water storage. The Lake Temperature and Evaporation Model (LTEM) with input from VIIRS Land Surface Temperature and Emissivity (VJ121A2) and meteorological data from Global Land Data Assimilation System (GLDAS) are used to produce monthly evaporation rates and volume losses.    The VJ128C3 data product provides a monthly time series that consists of a single layer with information about the reservoir identifier, dam location (longitude and latitude), reservoir surface area, elevation, water storage capacity, evaporation rate, and evaporation volume.   ",
         "license": "proprietary"
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         "license": "proprietary"
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         "description": "This data set reports sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.  VIIRS flies on board the Joint Polar Satellite System 1 (JPSS-1), also known as NOAA-20.",
         "license": "proprietary"
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         "description": "This data set reports sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.  VIIRS flies on board the Joint Polar Satellite System 1 (JPSS-1), also known as NOAA-20.",
         "license": "proprietary"
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         "description": "This data set reports sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS) onboard the Joint Polar Satellite System's first satellite (JPSS-1). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.",
         "license": "proprietary"
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         "description": "The Visible Infrared Imaging Radiometer Suite (VIIRS) Moderate Resolution Terrain Correction Geolocation (VNP03MODLL) Version 2 product from the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS sensor is produced in 6 minute temporal satellite increments (swaths) at 750 meter resolution.  Intersecting the VIIRS line of sight vector with Earth's geoid and the World Geodetic System (WGS) ellipsoid, this product is based on the SRTM30 Version 2 digital elevation model (DEM), which uses GTOPO30 data for areas from 60\u00b0 North to 60\u00b0 South. VNP03MODLL is a terrain correction geolocation product that provides the spatial location for various VIIRS data products.  Each swath of data is approximately 3,060 kilometers along track (long) and 3,060 kilometers across track (wide). Provided in the VNP03MODLL product are layers for height, latitude, and longitude. These Science Data Sets (SDS) layers are used in conjunction with the VNP14 swath product for accurate geolocation information.",
         "license": "proprietary"
     },
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         "description": "The 8-day Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) surface reflectance (VNP09A1) Version 2 composite product provides an estimate of land surface reflectance from the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS sensor for nine moderate resolution bands (M1 - M5, M7, M8, M10, M11) at nominal 1 kilometer resolution (~926 meter). The 1 kilometer dataset is derived through resampling the native 750 meter VIIRS resolution in the Level 2 input product. The data are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. Each pixel represents the best possible Level 2G observation during an 8-day period that is selected on the basis of high observation coverage, low sensor angle, the absence of clouds or cloud shadow, and aerosol loading. Included in the product along with the nine reflectance bands are day of year, reflectance band quality, control, reflectance state quality assurance, relative azimuth angle, sensor zenith angle, and solar zenith angle layers.     ",
         "license": "proprietary"
     },
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         "description": "This data set contains daily snow cover derived from radiance data acquired by the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (NPP) satellite. The data is a gridded composite, generated from 6 minute swaths, and projected to a 375 m Sinusoidal grid. Snow cover is identified using the Normalized Difference Snow Index (NDSI) and a series of screens designed to alleviate errors and flag uncertain snow cover detections.",
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         "description": "This global Level-3 data set provides the percentage of snow-covered land and cloud-covered land observed daily, within 0.05\u00b0 (approx. 5 km) MODIS/VIIRS Climate Modeling Grid (CMG) cells. Percentages are computed from snow cover observations in the 'VIIRS/NPP Snow Cover Daily L3 Global 375m SIN Grid' data set (DOI:10.5067/45VDCKJBXWEE).",
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         "description": "This data set reports the location of snow cover using radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (NPP) satellite. Snow cover is identified using the Normalized Difference Snow Index (NDSI) and a series of quality control screens.",
         "license": "proprietary"
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         "description": "The Visible Infrared Imaging Radiometer Suite (VIIRS) Active Fires (VNP14IMG) Version 2 product is produced in 6-minute temporal satellite increments (swaths) at 375 meter resolution from the VIIRS sensor aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. This Level 2 product is designed after the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire data products to promote the continuity of the Earth Observation System (EOS) mission. This data product can enable users to understand the location and intensity of fire events. Due to its higher spatial resolution, the VNP14IMG active fire product provides greater response over fires of relatively small areas, as well as improved mapping of large fire perimeters in comparison to the VNP14 fire data product.    The VNP14IMG product includes 26 science dataset layers to analyze key factors in fire detection, including atmospheric conditions (e.g., radiance, solar zenith angle, brightness temperature) and fuel type for the event. The fire mask layer in the VNP14IMG product is the primary layer and can be used to identify fires and other thermal anomalies such as volcanoes.     Each swath of data is approximately 3,060 kilometers along track (long) and 3,060 kilometers across track (wide). The VNP14IMG product is also used to generate higher-level fire data products.    Use of the (VNP03MODLL) data product is required to apply accurate geolocation information to the VNP14IMG Science Datasets (SDS).  ",
         "license": "proprietary"
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         "description": "The Visible Infrared Imaging Radiometer Suite (VIIRS) (https://lpdaac.usgs.gov/dataset_discovery/viirs) Thermal Anomalies (VNP14) Version 2 product is produced in 6-minute temporal satellite increments (swaths) at 750 meter resolution from the VIIRS sensor located on the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. This product is designed after the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire data products to promote the continuity of the Earth Observation System (EOS) mission. This data product can enable users to understand the location and intensity of fire events as well as identifying thermal anomalies.     The VNP14 product includes 31 science dataset layers to analyze key factors in fire detection, including atmospheric conditions (e.g., atmospheric reflectance, solar zenith angle, brightness temperature) and fuel type for the event. The fire mask layer in the VNP14 product is the primary layer and can be used to identify fires and other thermal anomalies such as volcanoes. In addition to the fire mask, brightness temperature is provided for VIIRS channels M5, M7, M11, M13, M15, and M16.      Each swath of data is approximately 3,060 kilometers along track (long) and 3,060 kilometers across track (wide). The VNP14 product is also used to generate higher-level fire data products.    Use of the (VNP03MODLL) (https://doi.org/10.5067/viirs/vnp03modll.002) data product is required to apply accurate geolocation information to the VNP14 Science Datasets (SDS).  ",
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         "license": "proprietary"
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         "description": "The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) Day Version 2 product (VNP21A1D) is compiled daily from daytime Level 2 Gridded (L2G) intermediate products.      The L2G process maps the daily (VNP21) (https://doi.org/10.5067/VIIRS/VNP21.002) swath granules onto a sinusoidal MODIS grid and stores all observations overlapping a gridded cell for a given day. The VNP21A1 algorithm sorts through all these observations for each cell and estimates the final LST value as an average from all cloud-free observations that have good LST accuracies. The daytime average is weighted by the observation coverage for that cell. Only observations having observation coverage more than a certain threshold (15%) are considered for this averaging. The 1 kilometer dataset is derived through resampling the native 750 meter VIIRS resolution in the input product.    The VNP21A1D product is developed synergistically with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST&E Version 6.1 product (MOD21A1D) (https://doi.org/10.5067/MODIS/MOD21A1D.061)) using the same input atmospheric products and algorithmic approach. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/1332/VNP21_ATBD_V1.pdf). VIIRS LST&E products are available 2 months after acquisition due to latency of data inputs.    The VNP21A1D product contains seven Science Datasets (SDS): LST, quality control, emissivity for bands M14, M15, and M16, view zenith angle, and time of observation. A low-resolution browse image for LST is also available for each VNP21A1D granule.  ",
         "license": "proprietary"
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         "description": "The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) Night Version 2 product (VNP21A1N) is compiled daily from nighttime Level 2 Gridded (L2G) intermediate products.      The L2G process maps the daily (VNP21) (https://doi.org/10.5067/VIIRS/VNP21.002) swath granules onto a sinusoidal MODIS grid and stores all observations overlapping a gridded cell for a given night. The VNP21A1 algorithm sorts through all these observations for each cell and estimates the final LST value as an average from all cloud-free observations that have good LST accuracies. The nighttime average is weighted by the observation coverage for that cell. Only observations having observation coverage more than a certain threshold (15%) are considered for this averaging. The 1 kilometer dataset is derived through resampling the native 750 meter VIIRS resolution in the input product.    The VNP21A1N product is developed synergistically with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST&E Version 6.1 product (MOD21A1N) (https://doi.org/10.5067/MODIS/MOD21A1N.061) using the same input atmospheric products and algorithmic approach. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/1332/VNP21_ATBD_V1.pdf).    The VNP21A1N product contains seven Science Datasets (SDS): LST, quality control, emissivity for bands M14, M15, and M16, view zenith angle, and time of observation. A low-resolution browse image for LST is also available for each VNP21A1N granule.  ",
         "license": "proprietary"
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         "description": "The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) 8-day product (VNP21A2) combines the daily (VNP21A1D) (http://doi.org/10.5067/VIIRS/VNP21A1D.002) and (VNP21A1N) (http://doi.org/10.5067/VIIRS/VNP21A1N.002) products over an 8-day compositing period into a single product.    The VNP21A2 dataset is an 8-day composite LST&E product at 1 kilometer resolution that uses an algorithm based on a simple-averaging method. The algorithm calculates the average from all the cloud-free VNP21A1D and VNP21A1N daily acquisitions from the 8-day period. Unlike the VNP21A1 datasets where the daytime and nighttime acquisitions are separate products, the VNP21A2 contains both daytime and nighttime acquisitions as separate science dataset (SDS) layers within a single Hierarchical Data Format (HDF) file.    The VNP21A2 product is developed synergistically with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST&E Version 6.1 product (MOD21A2) (https://doi.org/10.5067/MODIS/MOD21A2.061) using the same input atmospheric products and algorithmic approach. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/1332/VNP21_ATBD_V1.pdf).    The VNP21A2 product contains 11 Science Datasets (SDS): LST, quality control, view zenith angle, and time of observation for both day and night observations along with emissivity for bands M14, M15, and M16. Low-resolution browse images for day and night LST are also available for each VNP21A2 granule.  ",
         "license": "proprietary"
     },
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         "description": "The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) Version 2 swath product (VNP21) is produced daily in 6-minute temporal increments of satellite acquisition. The VNP21 product uses a physics-based algorithm to dynamically retrieve both the LST and emissivity simultaneously for VIIRS thermal infrared bands M14 (8.55 \u00b5m), M15 (10.76 \u00b5m), and M16 (12 \u00b5m) at a spatial resolution of 750 meters.    The VNP21 product is developed synergistically with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST&E Version 6.1 product (MOD21) (https://doi.org/10.5067/MODIS/MOD21.061) using the same input atmospheric products and algorithmic approach based on the ASTER Temperature Emissivity Separation (TES) technique. The TES algorithm is combined with an improved Water Vapor Scaling (WVS) atmospheric correction scheme to stabilize the retrieval during very warm and humid conditions. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. VIIRS LST&E products are available two months after acquisition due to latency of data inputs. Additional details regarding the method used to create this Level 2 (L2) product are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/1332/VNP21_ATBD_V1.pdf).    Provided in the VNP21 product are layers for LST, quality control, emissivity for bands M14, M15, and M16, LST&E errors, view angle, ASTER Global Emissivity Dataset (GED), Precipitable Water Vapor (PWV), ocean-land mask, latitude, and longitude. A low-resolution browse image for LST is also available for each VNP21 granule.  ",
         "license": "proprietary"
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         "license": "proprietary"
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         "description": "This data set reports sea ice cover/extent derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes sea ice cover using Normalized Difference Snow Index (NDSI).  VIIRS flies on board the Suomi National Polar-orbiting Partnership (NPP) satellite.",
         "license": "proprietary"
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         "description": "This data set reports the location of sea ice cover derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, Sea Ice is detected using the Normalized Difference Snow Index. The VIIRS instrument flies onboard the Suomi National Polar-orbiting Partnership (NPP) satellite.",
         "license": "proprietary"
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         "description": "This data set reports the location of sea ice cover derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) satellite. Following the approach used by MODIS, Sea Ice is detected using the Normalized Difference Snow Index.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2317045292-NSIDC_ECS.html",
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         "description": "This data set estimates of sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.  VIIRS flies on board the Suomi National Polar-orbiting Partnership (NPP) satellite.",
         "license": "proprietary"
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         "description": "This data set reports sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.  VIIRS flies on board the Suomi National Polar-orbiting Partnership (NPP) satellite.",
         "license": "proprietary"
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         "description": "This data set reports sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS). Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.  VIIRS flies on board the Suomi National Polar-orbiting Partnership (NPP) satellite.",
         "license": "proprietary"
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         "description": "This data set reports sea ice surface temperature (IST) derived from radiance data acquired by the Visible Infrared Imager Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (NPP) satellite. Following the approach used by MODIS, the algorithm converts VIIRS calibrated radiances into brightness temperature and computes IST using a split-window technique.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517710454-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517710454-ORNL_CLOUD.html",
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         "description": "This data set provides Vegetation Photosynthesis Respiration Model (VPRM) net ecosystem exchange (NEE) parameter values optimized to 65 flux tower sites across North America. The parameters include the basal rate of ecosystem respiration (beta), the slope of respiration with respect to temperature (alpha), light-use efficiency (LUE) (lambda), and LUE curve half-saturation (PAR_0). Observed eddy covariance data from the 65 tower sites, locally observed temperature and photosynthetically active radiation (PAR) along with satellite-derived phenology and moisture were used as input data to optimize the VPRM parameters for the 65 sites. The data are provided by individual site, plant functional types (PFTs), and all sites together, and as monthly, annual, and all available data. The data are for the conterminous USA, Alaska, and Canada for the period 2000 to 2006.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2143403456-ORNL_CLOUD.html",
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         "description": "This dataset contains vegetation community maps at 20 cm resolution for three landscapes near the Toolik Lake research area in the northern foothills of the Brooks Range, Alaska, USA. The maps were built using a Random Forest modeling approach using predictor layers derived from airborne lidar data and high-resolution digital airborne imagery collected in 2013, and vegetation community training data collected from 800 reference field plots across the lidar footprints in 2014 and 2015. Vegetation community descriptions were based on the commonly used classifications of existing Toolik area vegetation maps.",
         "license": "proprietary"
     },
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         "description": "This dataset contains 731 ground-based nadir vegetation community and ground surface photographs of selected field plots taken as ground reference data for vegetation classification studies at three areas near Toolik Lake, Alaska during the summers of 2014 and 2015. The largest area, 'Toolik', (approximately 6 km2) covers research areas near Toolik Field Station at Toolik Lake, including Arctic LTER installations. The other two areas are each roughly 3 km2: the 'Pipeline' area: a stretch of the Trans-Alaska Pipeline, and the 'Imnavait' area: along Imnavait Creek roughly 10 km east of Toolik Lake.",
         "license": "proprietary"
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@@ -198843,7 +199129,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2482184416-ORNL_CLOUD.html",
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         "description": "This dataset contains estimates of tree canopy cover presence at high resolution (0.5m) across the state of Vermont for 2016 in Cloud-Optimized GeoTIFF (*.tif) format. Tree canopy was derived from 2016 high-resolution remotely sensed data as part of the Vermont High-Resolution Land Cover mapping project. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and trees using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to ensure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:3000 and all observable errors were corrected. Tree canopy assessments have been conducted for numerous communities throughout the U.S. where the results have been instrumental in helping to establish tree canopy goals.",
         "license": "proprietary"
     },
@@ -198908,7 +199194,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517350332-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517350332-ORNL_CLOUD.html",
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         "description": "The Vulcan version 3.0 annual dataset provides estimates of annual carbon dioxide (CO2) emissions from the combustion of fossil fuels (FF) and CO2 emissions from cement production for the conterminous United States and the State of Alaska. Referred to as FFCO2, the emissions from Vulcan are categorized into 10 source sectors including; residential, commercial, industrial, electricity production, onroad, nonroad, commercial marine vessel, airport, rail, and cement. Data are gridded annually on a 1-km grid for the years 2010 to 2015. These data are annual sums of hourly estimates. Also provided are estimates of the upper 95% confidence interval and the lower 95% confidence interval boundaries for each emission estimate. For each uncertainty level, there are 10 individual sector files and one total file.  These data are designed to be used as emission estimates in atmospheric transport modeling, policy, mapping, and other data analyses and applications.",
         "license": "proprietary"
     },
@@ -198921,7 +199207,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2516155224-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2516155224-ORNL_CLOUD.html",
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         "description": "The Vulcan version 3.0 hourly dataset quantifies hourly emissions at a 1-km resolution for the 2010-2015 time period. Estimates are provided of hourly carbon dioxide (CO2) emissions from the combustion of fossil fuels (FF) and CO2 emissions from cement production for the conterminous United States and the state of Alaska. Referred to as FFCO2, the emissions from Vulcan are categorized into 10 source sectors including; residential, commercial, industrial, electricity production, onroad, nonroad, commercial marine vessel, airport, rail, and cement. Files for hourly total emissions are also available.  Data are represented in space on a 1 km x 1 km grid as hourly totals for 2010-2015. This dataset provides the first bottom-up U.S.-wide FFCO2 emissions data product at 1 km2/hourly for multiple years and is designed to be used as emission estimates in atmospheric transport modeling, policy, mapping, and other data analyses and applications.",
         "license": "proprietary"
     },
@@ -199090,7 +199376,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2764722720-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764722720-ORNL_CLOUD.html",
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         "description": "The WAVeTrends dataset is a 0.05 degree (5.55 km) vegetation change product, spanning the West African Sudano-Sahel region. It provides pixel-wise information on concurrent woody and herbaceous vegetation trends over a 32-year period (1982-2013). Change in woody vegetation was derived using long-term rain use efficiency (RUE) sensitivity, i.e., the per-pixel comparison of the difference of mean RUE between the first and last decades of the 32-year time series. Herbaceous vegetation change was defined by short-term RUE sensitivity, i.e., comparing the slope of the RUE relationship (productivity vs. precipitation) between both decades using per-pixel Analysis of Covariance (ANCOVA). Categorical vegetation change was then determined for each pixel using the direction of the change and a significance level of p<0.05. The use of RUE (the amount of biomass produced per unit of precipitation) for vegetation trend analysis in savanna regions relies on the assumption that rainfall is a significant positive driver of net production in drylands. Testing of this long-term productivity-rainfall relationship revealed that the assumption was not always met, therefore, validity flags are included for each pixel location.",
         "license": "proprietary"
     },
@@ -199233,7 +199519,7 @@
         "bbox": "-180, -50, 180, 50",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1242287793-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1242287793-GES_DISC.html",
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         "description": "TMI/TRMM precipitation and uncertainty (TMPA) L3 3 hour 0.25 degree x 0.25 degree V001 provides estimates of accumulated precipitation from the Tropical Rainfall Measuring Mission (TRMM) and Other Data Precipitation Data Set (TRMM 3B42; Huffman et al., 2007), along with estimates of the uncertainty in the TRMM 3B42 made by Bytheway and Kummerow (2013). The data set covers both ocean and land from 50 degree North to 50 degree South.",
         "license": "proprietary"
     },
@@ -199246,7 +199532,7 @@
         "bbox": "-180, -90, 180, 90",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1371013470-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1371013470-GES_DISC.html",
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         "description": "SRB/GEWEX evapotranspiration (Penman-Monteith) L4 3 hour 0.5 degree x 0.5 degree V1 is a global, 24-year (1984-2007), satellite-derived evapotranspiration over land data set. It is based on the Penman-Monteith model. Evapotranspiration provides the critical link between the water and energy cycles within the Earth system. Better representation of the spatial distribution and temporal development of surface evapotranspiration is needed not only to improve the description of water vapor exchanges for global water budget estimation but also to advance our understanding of the climate system.  Input data sets include (1) vegetation index data, i.e., Leaf Area Index (LAI), derived from the Advanced Very High Resolution Radiometer (AVHRR) sensors onboard the NOAA-7, NOAA-9, NOAA-11, NOAA-14, and NOAA-16 satellites and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the EOS-Terra and EOS-Aqua satellites; (2) meteorology data from the latest version of the Princeton University global forcing data sets and from the Variable Infiltration Capacity (VIC) land surface model output; and (3) radiative data from the NASA Global Energy and Water Exchanges (GEWEX) Surface Radiation Budget Project.",
         "license": "proprietary"
     },
@@ -199350,7 +199636,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789781977-GES_DISC.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789781977-GES_DISC.html",
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         "description": "The Western Land Data Assimilation System (WLDAS), developed at Goddard Space Flight Center (GSFC) and funded by the NASA Western Water Applications Office, provides water managers and stakeholders in the western United States with a long-term record of near-surface hydrology for use in drought assessment and water resources planning. WLDAS leverages advanced capabilities in land surface modeling and data assimilation to furnish a system that is customized for stakeholders\u2019 needs in the region. WLDAS uses NASA\u2019s Land Information System (LIS) to configure and drive the Noah Multiparameterization (Noah-MP) Land Surface Model (LSM) version 3.6 to simulate land surface states and fluxes. WLDAS uses meteorological observables from the North American Land Data Assimilation System (NLDAS-2) including precipitation, incoming shortwave and longwave radiation, near surface air temperature, humidity, wind speed, and surface pressure along with parameters such as vegetation class, soil texture, and elevation as inputs to a model that simulates land surface energy and water budget processes. Outputs of the model include soil moisture, snow depth and snow water equivalent, evapotranspiration, soil temperature, as well as derived quantities such as groundwater recharge and anomalies of the state variables. ",
         "license": "proprietary"
     },
@@ -199402,7 +199688,7 @@
         "bbox": "-169.5, 10.5, -50.5, 69.5",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517698238-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517698238-ORNL_CLOUD.html",
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         "description": "This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) footprint data products for two receptors located in Boston, Massachusetts, USA, for July 2013 - December 2014. The data are gridded footprints on a 1-km grid congruent with the ACES emissions inventory. Meteorological fields from version 3.5.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the \"receptor\" location), to create the adjoint of the transport model in the form of a \"footprint\" field. The footprint, with units of mixing ratio, quantifies the influence of upwind surface fluxes on CO2 and CH4 concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume.",
         "license": "proprietary"
     },
@@ -199415,7 +199701,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2517667717-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2517667717-ORNL_CLOUD.html",
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         "description": "This dataset provides Weather Research and Forecasting (WRF) Stochastic Time-Inverted Lagrangian Transport (STILT) particle trajectory data and footprint products for two receptors located in Boston, Massachusetts, USA, for July 2013 - December 2014. Meteorological fields from version 3.6.1 of the Weather Research and Forecasting model are used to drive STILT. STILT applies a Lagrangian particle dispersion model backwards in time from a measurement location (the \"receptor\" location), to create the adjoint of the transport model in the form of a \"footprint\" field. The footprint, with units of mixing ratio (ppm) per surface flux (umol m-2 s-1), quantifies the influence of upwind surface fluxes on CO2 and CH4 concentrations measured at the receptor and is computed by counting the number of particles in a surface-influenced volume and the time spent in that volume. Footprints are provided for the two receptors at two temporal and spatial scales: three days of surface influence over the whole North American coverage area at 1-degree resolution and 24 hours of surface influence within a smaller region close to the measurement locations ('near field') at 0.1-degree resolution.",
         "license": "proprietary"
     },
@@ -199467,7 +199753,7 @@
         "bbox": "-125, 31, -102, 49",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2253727823-NSIDC_ECS.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2253727823-NSIDC_ECS.html",
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         "description": "This Western United States snow reanalysis data set contains daily estimates of posterior snow water equivalent (SWE), fractional snow-covered area (fSCA) and snow depth (SD) at 16 arc-second (~500 m) resolution from water years 1985 to 2021. This data set was developed to be compared to SnowEx data sets but its utility reaches beyond that since its spatial and temporal bounds extend over the entire Western U.S. and over several decades.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2674700048-LPCLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2674700048-LPCLOUD.html",
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         "description": "This dataset provides daily historical Water Balance Model outputs from a Thornthwaite-type, single bucket model.  Climate inputs to the model are from GridMet daily temperature and precipitation for the Continental United States (CONUS). The Water Balance Model output variables include the following: Potential Evapotranspiration (PET, mm), Actual Evapotranspiration (AET, mm), Moisture Deficit (Deficit, mm), Soil Water (soilwater, mm), Runoff (mm), Rain (mm), and Accumulated Snow Water Equivalent (accumswe, mm). The dataset covers the period from January 1 to December 31 for years 1980 through 2023 for the CONUS. Water Balance Model variables are provided as individual files, by variable and year, at a 1 km x 1 km spatial resolution and a daily temporal resolution. Data are in a North America Lambert Conformal Conic projection and are distributed in a standardized Climate and Forecast (CF)-compliant NetCDF file format.",
         "license": "proprietary"
     },
@@ -199662,7 +199948,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863033-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863033-ORNL_CLOUD.html",
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         "description": "A standardized global data set of soil horizon thicknesses and textures (particle size distributions).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863502-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216863502-ORNL_CLOUD.html",
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         "description": "This data set provides a soil map with estimates of soil carbon (C) in g C/m2 for 20-cm layers from the surface to one meter depth for the conterminous United States.STATSGO v.1 (State Soil Geographic Database, Soil Survey Staff, 1994) data were used to estimate by 20-cm intervals to a 1-m depth the mean soil carbon for each of the STATSGO-delineated soil map units. These map units are the polygons represented in the provided Shapefile data product. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2951683862-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2951683862-ORNL_CLOUD.html",
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         "description": "This dataset contains estimates of soil organic carbon stocks and wetland intrinsic potential (WIP) across the Hoh River Watershed in the Olympic Peninsula, WA, USA in 2012-2013. Estimates were derived from an equation based on wetland intrinsic potential and geology type (Stewart et al., 2023). Wetland intrinsic potential estimates the likelihood that that an area is a wetland using a random forest model built on vegetation, hydrology, and soil data (Halabisky et al., 2022). SOC estimates at 1 m and 30 cm, SOC standard deviations, and WIP are presented in Cloud-Optimized GeoTIFF (*.tif) format at 4-m resolution. Also included are 36 field observations of SOC collected from 2020-08-01 to 2022-06-29. These are contained in a comma separated (*.csv) file.",
         "license": "proprietary"
     },
@@ -199766,7 +200052,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784383305-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784383305-ORNL_CLOUD.html",
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         "description": "The overall purpose in this research was to identify the regions of the world best suited for long-term monitoring of biospheric responses to climate change, i.e., monitoring land surface phenology. The user is referred to White et al. [2005] for further details. Using global 8 km 1982 to 1999 Normalized Difference Vegetation Index (NDVI) data and an eight-element monthly climatology, we identified pixels consistently dominated by annual cycles and then created phenologically and climatically self-similar clusters, which we term phenoregions. We then ranked and screened each phenoregion as a function of landcover homogeneity and consistency, evidence of human impacts, and political diversity.This dataset contains material providing users with direct access to data used to construct the figures in White et al. [2005]. Users are referred to this reference for additional information. Data files include ASCII and binary versions of the image files for the 500 elemental phenoregions and the 136 final monitoring phenoregions (shown in figure below) and a corresponding .jpg map. Also included are the classification data in tabular ACSII format for each of  the 500 elemental phenoregions.Selected monitoring phenoregions. Phenoregions with fewer than 100 pixels or dominated by crop, urban or barren landcover removed. The 136 remaining phenoregions are those passing the screening factors in Table 1 and are shown with normalized rankings by landcover. (From White et al., 2005)",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3234724704-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3234724704-ORNL_CLOUD.html",
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         "description": "This dataset contains simulations of net primary production (NPP), heterotrophic respiration (RH), net ecosystem production (NEP), and soil temperature data in North American boreal forests for the period 1986-2020. Data sources included historical fire sources and Landsat data. The delta Normalized Burn Ratio (dNBR), which can be used to represent burn severity for a fire, was calculated for each individual fire over the time period. The interactions between canopy, fire and soil thermal dynamics were modelled using a soil surface energy balance model  incorporated into a previous Terrestrial Ecosystem Model (TEM). Using the revised TEM, two regional simulations were conducted with and without fire disturbance. Fire polygons were dissected into each unit with unique fire history and then intersected with each grid cell to measure fire impacts. The output values for each grid cell are the area-weighted mean of each fire polygon and unburned area within the cell. Two extra simulations without a canopy energy balance scheme were also conducted to quantify the impact of the canopy. Soil temperature was simulated with and without the canopy energy balance scheme in the model in addition to considering fire impacts.",
         "license": "proprietary"
     },
@@ -200104,7 +200390,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2764687115-ORNL_CLOUD.html",
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         "description": "This dataset provides daily average land surface net radiation (Rnet) as an 8-day time series at approximately 0.5 km resolution for the upper Xingu River Basin in Mato Grosso, Brazil, from 2000-02-18 to 2012-11-16. The parameters needed to calculate Rnet, including albedo, downward shortwave radiation (RSnet), upward longwave radiation (RLnet[up]) and downward longwave radiation (RLnet[down]) were derived from MODIS products (MOD43A3, MOD11A2, MOD08E3) and local weather station data. Parameters were estimated under all sky conditions. These parameters are also provided for the Xingu Basin but at varying spatial and temporal resolutions.",
         "license": "proprietary"
     },
@@ -200130,7 +200416,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2773252554-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2773252554-ORNL_CLOUD.html",
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         "description": "This data set provides the distribution of young forests (forests less than 27 years of age) and their estimated stand ages across the full extent of Russia at 500-m resolution for the year 2012. The distribution of young forests was modeled with MODIS 500-m records for 12- to 27-year-old forests and augmented with the 0- to 11-year-old forest distribution as aggregated from 30 m resolution contemporary Landsat imagery.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216862657-ORNL_CLOUD.html",
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         "description": "A compilation of worldwide soil carbon and nitrogen data for more than 3500 soil profiles.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777326924-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777326924-ORNL_CLOUD.html",
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         "description": "The data set contains a subset of a global organic soil carbon and nitrogen data set (Zinke et al. 1986). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The point data are available in three formats: a comma-delimited ASCII file (*.csv), an ESRI shapefile, and an ESRI export file (*.e00).The data for the global data set (Zinke et al. 1986) were obtained from soil surveys conducted by Zinke in 1965-1984 and from soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations. Many samples reported in the literature did not have uniform soil increments or bulk density determinations. Only soil profiles that had been sampled either to a meter in depth or to actual depth were included in this database from soil survey literature. When carbon content was known but bulk densities were absent from soil samples reported in the literature, densities were estimated by regression analysis on the basis of the relationship between organic carbon content and measured bulk density in 1800 soil profiles for which bulk densities were known.Further information can be found at ftp://daac.ornl.gov/data/lba/carbon_dynamics/Zinke_soil/comp/zinke_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
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         "description": "A global data set of soil types is available at 0.5-degree latitude by 0.5-degree longitude resolution. There are 106 soil units, based on Zobler's (1986) assessment of the FAO/UNESCO Soil Map of the World. This data set is a conversion of the Zobler 1-degree resolution version to a 0.5-degree resolution.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2216862716-ORNL_CLOUD.html",
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         "description": "A global digital data base of soil properties is available at 1 degree longitude resolution.  For each land cell, the data base includes major and associated soil units, surface texture, and slope; phase and miscellaneous land units are included where available. The data base was compiled as part of an effort to improve modeling of the hydrologic cycle in the GISS Genreal Circulation Model.",
         "license": "proprietary"
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         "description": "A SAFARI 2000 data set of soil types is available at 0.5-degree latitude by 0.5-degree longitude resolution. There are 106 soil units, based on Zobler's (1986) assessment of the FAO/UNESCO Soil Map of the World. This data set is a conversion of the Zobler 1-degree resolution version to a 0.5-degree resolution. The resolution of the data set was not actually increased. Rather, the 1-degree squares were divided into four 0.5-degree squares with the necessary adjustment of continental boundaries and islands.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789011485-ORNL_CLOUD.html",
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         "description": "SAFARI 2000 provided an opportunity to study aerosol particles produced by savanna burning. We used analytical transmission electron microscopy (TEM), including energy-dispersive X-ray spectrometry (EDS) and electron energy-loss spectroscopy (EELS), to study aerosol particles from several smoke and haze samples and from a set of cloud samples. These aerosol particle samples were collected using the University of Washington Convair CV-580 research aircraft (Posfai et al., 2003).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784383572-ORNL_CLOUD.html",
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         "description": "This data set includes the soil and vegetation characteristics, herbivore estimates, and precipitation measurement data for the 854 sites described and analyzed in Sankaran et al., 2005. Savannas are globally important ecosystems of great significance to human economies. In these biomes, which are characterized by the co-dominance of trees and grasses, woody cover is a chief determinant of ecosystem properties. The availability of resources (water, nutrients) and disturbance regimes (fire, herbivory) are thought to be important in regulating woody cover but perceptions differ on which of these are the primary drivers of savanna structure. Analyses of data from 854 sites across Africa (Figure 1) showed that maximum woody cover in savannas receiving a mean annual precipitation (MAP) of less than approximately 650 mm is constrained by, and increases linearly with, MAP. These arid and semi-arid savannas may be considered stable systems in which water constrains woody cover and permits grasses to coexist, while fire, herbivory and soil properties interact to reduce woody cover below the MAP-controlled upper bound. Above a MAP of approximately 650 mm, savannas are unstable systems in which MAP is sufficient for woody canopy closure, and disturbances (fire, herbivory) are required for the coexistence of trees and grass. These results provide insights into the nature of African savannas and suggest that future changes in precipitation may considerably affect their distribution and dynamics (Sankaran et al., 2005).This data set includes the site characteristics and measurement data for the 854 sites described and analyzed in Sankaran et al., 2005.  The data are provided in two formats, *.xls and *.csv. See the data format section below for more information. A companion document composed of the supplemental documentation and figures provided with Sankaran et al., 2005 is also included (ftp://daac.ornl.gov/data/global_vegetation/african_woody_savanna/comp/Woody_Cover.pdf).",
         "license": "proprietary"
     },
@@ -201326,7 +201612,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785340637-ORNL_CLOUD.html",
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         "description": "This data set contains the calculated net ocean-air carbon dioxide (CO2) flux and sea-air CO2 partial pressure (pCO2) difference. The estimates are based on approximately one million measurements made for the pCO2 in surface waters of the global ocean since the International Geophysical Year, 1956-1959. Only the ocean water pCO2 values measured using direct gas-seawater equilibration methods were used. The results represent the climatological distributions under non-El Nino conditions. Since the measurements were made in different years, during which the atmospheric pCO2 was increasing, they were corrected to a single reference year (arbitrarily chosen to be 1995) on the basis of the following assumptions: -Surface waters in subtropical gyres mix vertically at slow rates with subsurface waters due to the presence of strong stratification at the base of the mixed layer. This will allow a long contact time with the atmosphere to exchange CO2. Therefore, their CO2 chemistry tends to follow the atmospheric CO2 increase. Accordingly, the pCO2 measured in a given month and year is corrected to the same month of the reference year 1995 using changes in the atmospheric CO2 concentration occurred during this period.-Oceanic pCO2 measurements made after the beginning of 1979 have been corrected to 1995 using the atmospheric CO2 concentration data from the GLOBALVIEW-CO2 database (2000), in which the zonal mean atmospheric concentrations (for each 0.05 in sine of latitude) within the planetary boundary layer are summarized for each month since 1979 to 2000.-Pre-1979 oceanic pCO2 data were corrected to 1979 using the annual mean trend for the global mean atmospheric CO2 concentration constructed from the Mauna Loa data of Keeling and Whorf (2000), and then from 1979 to 1995 using the GLOBALVIEW-CO2 database. -Measurements for pCO2 made in the following areas have been corrected for the time of observation; 45 degrees N, 50  degrees S, in the Atlantic Ocean, north of 50 degrees S in the Indian Ocean, 40 degrees N, 50 degrees S in the western Pacific west of the date line, and 40 degrees N, 60 degrees S, in the eastern Pacific east of the date line. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804769299-ORNL_CLOUD.html",
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         "description": "Airborne sunphotometer data collected on 8/13-15/90 used to provide quantitative atmospheric correction to remotely sensed data of forest reflectance and radiance",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789740161-ORNL_CLOUD.html",
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         "description": "A tandem pair of Advanced Land Imager (ALI) and Landsat Enhanced Thematic Mapper Plus (ETM+) scenes covering the same part of Kruger National Park (KNP), South Africa (including the Skukuza tower site and rest camp), were acquired about a minute apart on May 30, 2001. The ALI is one of three instruments aboard NASA's first New Millennium Program Earth Observing 1 (EO-1) satellite. ALI is a technology validation testbed that employs novel wide-angle optics and a highly integrated multispectral and panchromatic spectroradiometer.The tandem pair was produced to evaluate the differences between ALI and ETM+ and determine if technology similar to that of the ALI is suitable for future land imaging that will continue the observations begun by the Landsat satellites in 1972.The ALI and ETM+ images are false color composites combining shortwave infrared, near infrared, and visible wavelengths, displayed as red, green, and blue, respectively. Dense vegetation appears green. The similarity of the images demonstrates the ability of the ALI to produce data comparable to ETM+. Several SAFARI 2000 field campaigns conducted in KNP provided ground-based data needed to evaluate measurements from the satellite sensors.Each band is stored as an individual binary file. A metadata file accompanies each set of ALI and ETM+ band files to document the path and row number, sample and line counts, band file names, and sun azimuth and elevation angles. There is also a calibration parameter file that was used for 1R processing.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788351532-ORNL_CLOUD.html",
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         "description": "The NASA Ames Airborne Tracking 14-channel Sunphotometer (AATS-14) was operated successfully aboard the University of Washington CV-580 for 24 data flights during the dry-season airborne campaign from August 13 to September 25, 2000. Flights originated from Pietersburg, South Africa; Kasane, Botswana; and Walvis Bay, Namibia. The AATS-14 instrument measures the transmission of the direct solar beam at 14 discrete wavelengths (350-1558 nm) from which we derived spectral aerosol optical depths (AOD) and columnar water vapor (CWV).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808089826-ORNL_CLOUD.html",
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         "description": "Contains data from 1993 from the Atmospheric Environment Service Campbell Scientific autostations collecting continuous fifteen minute data for BOREAS.  ",
         "license": "proprietary"
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         "description": "Contains data from 1994 from the Atmospheric Environment Service Campbell Scientific autostations collecting continuous fifteen minute data for BOREAS.  ",
         "license": "proprietary"
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         "description": "Contains data from 1995 from the Atmospheric Environment Service Campbell Scientific autostations collecting continuous fifteen minute data for BOREAS.  ",
         "license": "proprietary"
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         "description": "Contains data from 1996 from the Atmospheric Environment Service Campbell Scientific autostations collecting continuous fifteen minute data for BOREAS.  ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785296327-ORNL_CLOUD.html",
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         "description": "The Continental Atmospheric CO2 Consumption data set represents gridded estimates for the riverine export of carbon and of sediments based on empirical models. All data exist for the overall continental area in a spatial resolution of 0.5 x 0.5 degree longitude/ latitude. The units are tC/km2/yr for all carbon species, and t/km2/yr for sediment fluxes. There are two data files (*.zip) with this data set which describe the following: dissolved organic carbon (DOC) export, particulate organic carbon (POC) export, bicarbonate export, export of bicarbonate being of atmospheric origin (also called atmospheric CO2 consumption by rock weathering), and sediment export.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804805089-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804805089-ORNL_CLOUD.html",
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         "description": "The Global Inventory Mapping and Modeling (GIMMS) group at NASA/GSFC provided SAFARI 2000 with remotely sensed satellite data products at the site and regional level. These AVHRR data contain two main sets of data: site extracts of SAFARI core sites (Mongu, Etosha, Kasungu, Maun, Skukuza, and Tshane), and regional 15-day composites from sets of single-day images. These AVHRR data contain four main sets of data:1.5 km daily site extracts of SAFARI core sites (2000)1.5 km 15-day composites of SAFARI core sites (1998-2000)1.5 km 15-day composites of the southern African region (Mar, Sept 2000)6 km 15-day composites of the southern African region (1998-2000)The primary data layers for site extracts and regional composites are fire pixel counts and maximum NDVI. The fire product is different for the daily and for the composited products (see readme file) and a fire product is not included in the 1.5 km regional data set.  NDVI composite-associated data layers for the regional data sets include land surface temperature, reflectance, solar zenith angle, view zenith angle, and relative azimuth angle. NDVI composite-associated data layers for the site extracts include these same variables as well as brightness temperature, fire mask composite, latitude, and longitude. The data are stored in binary image format files. There is a metadata file for each site and date/compositing period, in ASCII format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784840966-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784840966-ORNL_CLOUD.html",
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         "description": "This Albedo and BRDF (Bidirectional Reflectance Distribution Function) data set contains three files containing BRDF parameters, white- sky albedo and black-sky albedo at solar noon for three bands ((350-680nm, 680-3000nm, and 350-30000nm)derived from AVHRR (Advanced Very High Resolution Radiometer). These data are available at spatial resolutions of quarter, half, and one degree. Black-sky albedo (direct beam contribution) and white-sky (Completely diffuse contribution) can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon. ",
         "license": "proprietary"
     },
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         "description": "This data set is an expanded version of the Costa et al. (2000) data set and consists of a single grid with values of 1 for cells within the basins and 0 for cells outside. The resolution of the data set is 5 x 5 min (approximately 9 x 9 km). The area of this data set is consistent with the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data file is in ASCII GRID format.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779734738-ORNL_CLOUD.html",
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         "description": "The Southern African Regional Science Initiative (SAFARI 2000) was conducted in part to investigate the impacts of the large-scale transport and deposition of increasingly anthropogenic emissions on southern African biogeochemical cycling. Aerosol samples from the Mongu site in eastern Zambia were collected and analyzed to identify chemical biomarkers during the SAFARI 2000 dry season field campaign. Total suspended particulate aerosol samples were collected diurnally for a period of two weeks during August and September of 2000.These data include bulk organic carbon, nitrogen and sulfur stable isotopic measurements of total suspended particulate aerosols and gas chromatography/mass spectrometry (GC/MS) analysis of fatty acids extracted from collected aerosols. These data were used to chemically describe temporal variability in aerosol compositions.",
         "license": "proprietary"
     },
@@ -203406,7 +203692,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789024961-ORNL_CLOUD.html",
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         "description": "Domestic biomass fuels (biofuels) are estimated to be the second largest source of carbon emissions from global biomass burning. Wood and charcoal provide approximately 90% and 10% of domestic energy in tropical Africa, respectively. As part of the Southern Africa Regional Science Initiative (SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively.",
         "license": "proprietary"
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@@ -203536,7 +203822,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2929130809-ORNL_CLOUD.html",
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         "description": "This biomass density image covers almost the entire BOREAS SSA.  The pixels for which biomass density is computed include areas that are in conifer land cover classes only.  The biomass density values represent the amount of overstory biomass (i.e., tree biomass only) per unit area.  It is derived from a Landsat-5 TM image collected on 02-Sep-1994.  The technique that was used to create this image is very similar to the technique that was used to create the physical classification of the SSA.",
         "license": "proprietary"
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@@ -203900,7 +204186,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789024214-ORNL_CLOUD.html",
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         "description": "Biomass burning is a major source for gaseous and particulate atmospheric pollution over southern Africa and globally. The purpose of this study was to quantify biomass burning emissions in an attempt to better understand and predict associated environmental impacts. Sixty biomass burning experiments were carried out November 2000-January 2001 in three regions of southern Africa that are representative of major regional ecosystem types: Etosha National Park (Namibia), Kruger National Park (South Africa), and woodland sites in Zambia and Malawi.",
         "license": "proprietary"
     },
@@ -203913,7 +204199,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2780105326-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2780105326-ORNL_CLOUD.html",
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         "description": "Biogenic volatile organic compound (BVOC) emissions were measured in a Colophospermum mopane woodland near Maun, Botswana, and in a Combretum-Acacia savanna in Kruger National Park, 13 km from Skukuza, Republic of South Africa (RSA) during the 2001 wet season campaign of SAFARI 2000. In addition, relaxed eddy accumulation (REA) measurements of BVOC fluxes were made on flux towers at these sites, where net CO2 emissions were also measured simultaneously.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784880272-ORNL_CLOUD.html",
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         "description": "The photosynthetic composition (C3 or C4) of vegetation on the land surface is essential for accurate simulations of biosphere-atmosphere exchanges of carbon, water, and energy. C3 and C4 plants have different responses to light, temperature, CO2, and nitrogen; they also differ in physiological functions like stomatal conductance and isotope fractionation. A fine-scale distribution of these plant types is essential for earth science modeling.The C4 percentage is determined from data sets that describe the continuous distribution of plant growth forms (i.e., the percent of a grid cell covered by herbaceous or woody vegetation), climate classifications, the fraction of a grid cell covered in croplands, and national crop type harvest area statistics. The staff from the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II have made the original data set consistent with the ISLSCP-2 land/water mask. This data set contains a single file in ArcInfo ASCIIGRID format.This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776831590-ORNL_CLOUD.html",
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         "description": "The nitrogen and chlorophyll concentrations of constructed Douglas-fir and bigleaf maple seedling canopies were determined. Canopy reflectance spectra were measured before foliage samples were collected.",
         "license": "proprietary"
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         "description": "The reflectance spectra of Douglas-fir and bigleaf maple seedling canopies were measured. Canopies varied in fertilizer treatment and leaf area density respectively.",
         "license": "proprietary"
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         "description": "The CENTURY model, Version 4, is a general model of plant-soil nutrient cycling that is being used to simulate carbon and nutrient dynamics for different types of ecosystems including grasslands, agricultural lands, forests and savannas. CENTURY is composed of a soil organic matter/ decomposition submodel, a water budget model, a grassland/crop submodel, a forest production submodel, and management and events scheduling functions.",
         "license": "proprietary"
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         "description": "Canopy characteristics: leaf chemistry, specific leaf area, LAI, PAR, IPAR, NPP, standing biomass--see also: Meteorology (OTTER) for associated meteorological conditions",
         "license": "proprietary"
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         "description": "This data set contains decadal (1950, 1960, 1970, 1980, 1990 and 1995) estimates of gridded fossil-fuel emissions, expressed in 1,000 metric tons C per year per one degree latitude by one degree longitude. The CO2 emissions are the summed emissions from fossil-fuel burning, hydraulic cement production and gas flaring. The years 1950 to 1990 were developed and compiled using somewhat different procedures and information than the 1995 data. The national annual estimates (Boden et al., 1996) from 1950 to 1990 were allocated to one degree grid cells based on gridded information on national boundaries and political units, and a 1984 gridded human population map (Andres et al., 1996). For the 1995 data, the population data base developed by Li (1996a) and documented by CDIAC (DB1016: Li, 1996b) was used as proxy to grid the 1995 emission estimates. There is one *.zip data file with this data set at 1.0 degree spatial resolution.",
         "license": "proprietary"
     },
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         "description": "This data set contains the ISLSCP II fixed land/water masks and percentages of land or water in each cell. There are seven zip data files: four produced from a 1-km land/water mask compiled at the Jet Propulsion Laboratory (JPL) in support of NASA's Earth Observing System;  two files of a land outline overlay created from the land/water mask files created at NASA's Goddard Space Flight Center; and one file which is a latitude grid coordinate file and longitude grid coordinate file produced by the ISLSCP II staff. All of these data are provided at three spatial resolutions of .25, 0.5 and 1-degree in latitude and longitude and on a common Earth grid.",
         "license": "proprietary"
     },
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         "description": "The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788400595-ORNL_CLOUD.html",
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         "description": "The effect of clouds and aerosols on regional and global climate is of great importance. Two longstanding elements of the NASA climate and radiation science program are field studies incorporating airborne remote-sensing and in-situ measurements of clouds and aerosols. is Data products include: (1) cloud profiling with 30-m vertical and 200-m horizontal resolution at 1064 nm, 532 nm, and 355 nm;(2) aerosol, boundary layer, and smoke plume profiling;(3) optical depth estimates (column and by layer); and(4) extinction profiles. The CPL provides information to permit a comprehensive analysis of radiative and optical properties of optically thin clouds. Data users are asked to read and abide by the CPL data usage policy found at [http://virl.gsfc.nasa.gov/cpl/cpl_register.htm].",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804823994-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804823994-ORNL_CLOUD.html",
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         "description": "This data set is a subset of Cramer and Leeman's (1999) global mean monthly climatology . The subset is for the area of southern Africa within the following bounds: 5 N to 35 S and 5 E to 60 E. The data are available in ASCII grid and binary image formats.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751948433-ORNL_CLOUD.html",
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         "description": "This data set contains a single data file (.csv format) that provides gridded values of net primary productivity (NPP) for cropland in eight counties in the central United States for the year 1992 and estimates of interannual cropland NPP in Iowa for years from 1982 through 1996. The data file also includes climate, soil texture, and land cover data for each 0.5 degree grid cell. The magnitude and interannual variation in NPP was estimated using crop area and yield data from the U.S. Department of Agriculture, National Agricultural Statistics Service (NASS). The major harvested commodities were corn, soybean, sorghum, sunflower, oats, barley, wheat, and hay. Total NPP estimates include both above- and below-ground components. County-level NPP in 1992 ranged from 195 to 760 gC/m2/year. The area of highest NPP, ranging from 650 to 760 gC/m2/year, was found in a band extending across Iowa, through northern Illinois, Indiana, and southwestern Ohio. Areas of moderate NPP, from 550 to 650 gC/m2/year, occurred mostly in Michigan and Wisconsin, while large areas of low NPP, from 200 to 550 gC/m2/year, occurred in North Dakota, southern Illinois, and Minnesota. The area of highest production was also the area with the largest proportion of land sown with corn and soybean. NPP for counties in Iowa varied among years (1982-1996) by a factor of 2, with the lowest NPP in 1983 (which had an unusually wet spring), in 1988 (which was a drought year), and in 1993 (which experienced floods). Revision Notes: The documentation for this data set has been modified, and the data files have been reformatted. The data files have been checked for accuracy and the contents are identical to those originally published in 2001. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785289548-ORNL_CLOUD.html",
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         "description": "This data set contains monthly climate time series data created by the Climatic Research Unit (CRU) at the University of East Anglia, U.K.,for every year covering the period 1986 to 1995. This time series is a subset of a larger CRU monthly data set that covers the period of 1901 to 1996.  The data comprise a suite of six climate elements: precipitation, mean temperature, diurnal temperature range, wet-day frequency, vapor pressure, and cloud cover. There are 13 files in this data set provided at 0.5 and 1.0 degree spatial resolutions. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785293782-ORNL_CLOUD.html",
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         "description": "This data set contains a mean monthly climatology for several climate variables averaged over the period from 1961 to 1990,  and constructed from a data set of station 1961-1990 climatological normals, numbering between 19,800 (precipitation) and 3,615 (windspeed; see New et al, 1999 for details). The station data were interpolated as a function of latitude, longitude and elevation using thin-plate splines. The data comprise a suite of climate elements: precipitation, mean, maximum, and minimum  temperature, frost frequency, diurnal temperature range, radiation, wet-day frequency, vapor pressure, wind, and cloud cover. There are 23 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.  ",
         "license": "proprietary"
     },
@@ -205837,7 +206123,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789731186-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789731186-ORNL_CLOUD.html",
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         "description": "The Microwave InfraRed Algorithm (MIRA) is used to produce an imagery data set of daily mean rain rates at 0.1 degree spatial resolution over southern Africa for the period 1993-2001. MIRA combines passive microwave (PMW) from the Special Sensor Microwave/Imager (SSM/I) on board the DMSP F10 and F14 satellites at a resolution of 0.5 degrees and infrared (IR) data from the Meteosat 4, 5, 6, and 7 satellites in 2-hour slots at a resolution of 5 km. This approach accounts for the limitations of both data types in estimating precipitation. Rainfall estimates are produced at the high spatial and temporal frequency of the IR data using rainfall information from the PMW data. An IR/rain rate relationship, variable in space and time, is derived from coincident observations of IR and PMW rain rate (accumulated over a calibration domain) using the probability matching method. The IR/rain rate relationship is then applied to IR imagery at full temporal resolution. The results presented here are the daily means of those derived rain rates at 0.1 degree spatial resolution.The rainfall data sets are flat binary images with no headers. They are compressed band sequential (bsq) files that contain all of the daily images for the given year. Each image is an array of 401 lines, each with 341 binary floating-point numbers, containing rainfall at 0.1 degree resolution for the area 10 to 50 degrees longitude and 0 to -34 degrees latitude. The number of band sequential images in each annual file and the associated dates can be found in the file MIRA_data_dates.csv.",
         "license": "proprietary"
     },
@@ -206565,7 +206851,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789729353-ORNL_CLOUD.html",
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         "description": "This data set contains monthly mean values of diffuse irradiance fraction [f(Ediff), or ratio of diffuse-to-total irradiance] at ground level for a 30-degree solar zenith angle and in seven spectral bands (MODIS bands 1-7) as well broadband visible (400-700 nm), near-infrared (700-3000 nm) and shortwave (400-3000 nm). Values are provided for eight SAFARI 2000 core sites, including Ghanzi/Okwa River Crossing, Maun (Main and Floodplain Towers), Pandamatenga, and Tshane, Botswana; Skukuza, South Africa; Etosha National Park, Namibia; and Mongu, Zambia. The fractions were estimated with the 6S radiative transfer model, given the mean aerosol optical depth (AOT) values from AERONET sunphotometer measurements. Where sunphotometers were not deployed at a SAFARI 2000 core site, the nearest neighbor sunphotometer data were used. A rough estimate of the likely spatial extrapolation error is provided. These data can be used to estimate typical surface albedo (blue sky conditions) from the theoretical black-sky and white-sky albedo values provided in the MODIS albedo product (MOD43), as well as in other applications.Data for all eight sites are contained in one ASCII file, in csv format. The data file provides the ratio of diffuse (atmospherically-scattered) irradiance to total irradiance, both at ground level, for the eight sites in southern Africa. Mean values are provided for each of 12 months in 10 spectral bands between 0.4 and 4.0 microns, computed for a 30-degree solar zenith angle.  The native resolution of the AERONET sunphotometer data varies, but is typically less than 1 hour. Information about the site location, IGBP classification, and nearest AERONET sunphotometer site is also provided.",
         "license": "proprietary"
     },
@@ -207241,7 +207527,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2556025141-ORNL_CLOUD.html",
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         "description": "This data set contains forest canopy scan data from the Echidna? Validation Instrument (EVI) and field measurements data from three campaigns conducted in the United States: 2007 New England Campaign; 2008 Sierra National Forest Campaign; and 2009 New England Campaign. The New England field sites were located in Harvard Forest (Massachusetts), Howland Research Forest (Maine), and the Bartlett Experimental Forest (New Hampshire).The objective of the research was to evaluate the ability of the EVI ground-based, scanning near-infrared lidar to retrieve stem diameter, stem count density, stand height, leaf area index, foliage profile, foliage area volume density, and other useful forest structural parameters rapidly and accurately.The EVI scan data are Andrieu Transpose (AT) Projection images in ENVI *.img and *.hdr file pairs. There are 28 images from the 2007 New England Campaign, 30 images from the 2008 Sierra National Forest Campaign, and 54 images from the 2009 New England Campaign. There are range-weighted mean preview image files (.jpg format) for each AT Projection image.Manual measurements of tree structural properties were made during each campaign at EVI scan locations. The field measurements are provided in one file for each campaign (.csv format). Parameters include species identification, DBH, tree height, crown base, etc. organized by field plot. There is also a data file (.csv format) which compares EVI derived measurements to the field measured data (DBH, stem density, basal area, biomass, and LAI) from the 2007 New England Campaign.",
         "license": "proprietary"
     },
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         "description": "This data set for the ISLSCP Initiative II data collection provides meteorology data with fixed, monthly, monthly-6-hourly, 6-hourly, and 3-hourly temporal resolutions. The data were derived from the European Centre for Medium-range Weather Forecasts (ECMWF) near-surface meteorology data set, 40-year re-analysis, or ERA-40 (Simmons and Gibson, 2000), which covers the years 1957 to 2001. The data were processed onto the ISLSCP II Earth grid with a spatial resolution of 1-degree in both latitude and longitude, and span the common ISLSCP II period from 1986 to 1995.The ECMWF forecast system is called the Integrated Forecasting System (IFS) and was developed in co-operation with Meteo-France. For ERA40 it is used with 60 levels from the top of the model at 10 Pa to the lowest level at about 10 m above the surface. There are 46 compressed (.tar.gz) data files with this data set. Each uncompressed file contains space-delimited text (.asc) data files.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784847849-ORNL_CLOUD.html",
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         "description": "The goal of this study was to predict the global distribution of plant rooting depths based on data about global aboveground vegetation structure and climate. Vertical root distributions influence the fluxes of water, carbon, and soil nutrients and the distribution and activities of soil fauna. Roots transport nutrients and water upwards, but they are also pathways for carbon and nutrient transport into deeper soil layers and for deep water infiltration. Roots also affect the weathering rates of soil minerals. For calculating such processes on a global scale, data on vertical root distributions are needed as inputs to global biogeochemistry and vegetation models. In the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS), rooting depth and vertical soil characteristics were the most important factors explaining scatter for simulated transpiration among 14 land-surface models. Recently, the Terrestrial Observation Panel for Climate of the Global Climate Observation System (GCOS) identified the 95% rooting depth as a key variable needed to quantify the interactions between the climate, soil, and plants, stating that the main challenge was to find the correlation between rooting depth and soil and climate features (GCOS/GTOS Terrestrial Observation Panel for Climate 1997). In response to this challenge, a data set of vertical rooting depths was collected from the literature in order to construct maps of global ecosystem rooting depths.The parameters included in these data sets are estimates for the soil depths containing 50% and 95% of all roots, termed 50% and 95% rooting depths (D50 and D95, respectively). Together, these variables can be used to calculate estimates for vertical root distributions, using a logistic equation provided in this documentation. The data represent mean ecosystem rooting depths for 1 by 1 degree grid cells. Related data sets: The ORNL DAAC offers related data sets by Jackson et al. (2003), Gordon and Jackson (2003), Schenk and Jackson (2003), and Gill and Jackson (2003).This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.",
         "license": "proprietary"
     },
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         "description": "This data set describes the geographic distributions of 17 classes of land cover based on the International Geosphere-Biosphere DISCover land cover legend (Loveland and Belward 1997) and the 15 classes of the SiB model processed at the USGS EROS Data Center (EDC). Specifically, the resampled DISCover datasets were derived from the 1km DISCover data set compiled by the USGS. The 1km data sets for each classification scheme were aggregated to 1, 0.5 and 0.25 degree spatial resolutions for this ISLSCP II data collection. Each layer of the aggregated products corresponds to a single DISCover land cover category and the values represent the percentage of the coarse resolution cell (1 degree, etc...)occupied by that land cover category. The dominant class data show the land cover category that occupies the majority of the cell and is derived from the percentage files for each cover type. The objective of this study was to create a land cover map derived from 1 kilometer AVHRR data using a full year of data (April 1992-March 1993). This thematic map was resampled to 0.25, 0.5 and 1.0 degree grids for the International Satellite Land Surface Climatology Project (ISLSCP) data initiative II. During this re-processing, the original EDC land cover type and fraction maps were adjusted to match the water/land fraction of the ISLSCP II land/water mask. These maps were generated for use by global modelers and others. This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785350291-ORNL_CLOUD.html",
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         "description": "The EDGAR (Emission Database for Global Atmospheric Research) database project is a comprehensive task carried out jointly by the National Institute for Public Health (RIVM) and the Netherlands Organization for Applied Scientific Research (TNO) and stores global emission inventories of direct and indirect greenhouse gases from anthropogenic sources including halocarbons and aerosols both on a per country and region basis as well as on a grid (see http://www.rivm.nl/edgar/). For the ISLSCP Initiative II data collection, gridded global annual anthropogenic emissions for the greenhouse gases CO2, CH4, N2O are provided on a 1.0 degree by 1.0 degree grid for the years 1970, 1980, 1990, and 1995 and for the tropospheric ozone precursor gases CO, NOx, NMVOC (Non-Methane Volatile Organic Compounds) and SO2 for the years 1990 and 1995. There are 2 *.zip data files with this data set.",
         "license": "proprietary"
     },
@@ -208242,7 +208528,7 @@
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         "description": "Aerial photography from the NASA ER-2 high-altitude aircraft was collected to provide detailed and spatially extensive documentation over parts of the SAFARI study area. The ER-2 aerial photography consists of 3,046 color-infrared (IR) transparencies collected during the SAFARI 2000 Dry Season Aircraft Campaign in August and September of 2000. ORNL DAAC has archived scanned subsets of the ER-2 aerial photography. In addition, 515 image frames have been scanned from copies of the original level-0 ER-2 aerial photography by the University of the Witwatersrand (Wits), in Pretoria, South Africa. ORNL DAAC has archived subsets of the available imagery from ARC and Wits.",
         "license": "proprietary"
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@@ -208372,7 +208658,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784882228-ORNL_CLOUD.html",
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         "description": "This data set, ISLSCP II Earth Radiation Budget Experiment (ERBE) Monthly Albedo, 1986-1990, contains both the original ERBE albedo data at 2.5 degree spatial resolution, and the International Land Surface Climatology Project Initative II (ISLSCP Initiative II) albedo product re-gridded to 1 degree resolution. The goals of the ERBE were (1) to understand the radiation balance between the Sun, Earth, atmosphere, and space and (2) to establish an accurate, long-term baseline data set for detection of climate changes. Earth Radiation Budget (ERB) data are fundamental to the development of realistic climate models and to the understanding of natural and anthropogenic perturbations of the climate system. As part of ERBE, measurements of broadband shortwave radiation reflected from the Earth-atmosphere system were obtained, from which top of atmosphere albedo values were calculated. In addition, values from scenes determined to be free of clouds were analyzed separately and clear-sky albedos were derived. For this study, only the clear-sky albedos are included. The ERBE data sets for ISLSCP Initiative II contain global, top of atmosphere, clear sky albedo data from January 1986 to February 1990.",
         "license": "proprietary"
     },
@@ -208411,7 +208697,7 @@
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         "description": "With modern computer power now capable of making mesoscale model output available in real time in the operational environment, increased attention has been given to utilizing these models in order to improve the forecasting ability of meteorologists. The National Centers for Environmental Prediction (NCEP) has developed a step-mountain eta coordinate model generally known as the ETA Model.This NCEP ETA data assimilation and prediction system (see Mesinger et al., 1988; Black, 1994) has been used by the South African Weather Bureau/Service (SAWS) to provide operational regional forecast guidance since November 1993. SAWS used this model to produce the basic meteorological data for the SAFARI project. The SAWS ETA model is a hydrostatic model with a horizontal grid spacing of approximately 48 km and 38 vertical levels, with layer depths that range from 20 m in the planetary boundary layer to 2 km at 50 mb. There have been several major ETA Model upgrades at SAWS: in March 1996, August 1998, November 1999, and August 2001.",
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         "description": "The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data set and derived biophysical parameter fields were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. This multiple resolution (1/4, 1/2 and 1 degree in latitude and longitude) biophysical parameter data set contains essential variables for the calculation of photosynthesis, and the energy and water exchange between the Earth's surface (in particular of vegetation) and the lower boundary layer of the atmosphere. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is related to the light absorption and the photosynthetic capacity of vegetation. It also serves as an intermediate variable to calculate vegetation cover fraction (Vcover), total Leaf Area Index (LAI_T), green leaf area index (LAI_G), roughness length (z0), zero plane displacement (d), and snow-free albedo. The biophysical parameters were derived assuming one canopy layer. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.",
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         "description": "The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. FASIR-NDVI data are also used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface. There are three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude. FASIR adjustments concentrated on reducing NDVI variations arising from atmospheric, calibration, view and illumination geometries and other effects not related to actual vegetation change.FASIR NDVI was also generated to provide inputs for computing a 17-year time series of associated biophysical parameters, provided as a separate data set in this data collection. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.",
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         "description": "As part of the SAFARI 2000), the University of Montana participated in both ground-based and airborne campaigns during the southern African dry season of 2000 to measure trace gas emissions from biofuel production and use and savanna fires, respectively. During the airborne campaign, stable and reactive trace gases were measured over southern Africa with an airborne Fourier transform infrared spectroscopy (AFTIR) onboard the University of Washington Convair-580 research aircraft in August-September of 2000. The measurements included vertical profiles of CO2, CO, H2O, and CH4 up to 5.5 km on 6 occasions above instrumented ground sites and below the TERRA satellite and ER-2 high-flying research aircraft as well as trace gas emissions from ten African savanna fires. These measurements are the first broad characterization of the most abundant trace gases in nascent smoke from African savanna fires (i.e., including oxygen- and nitrogen-containing species).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2763353619-ORNL_CLOUD.html",
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         "description": "This dataset provides global estimates of monthly burned area, monthly emissions and fractional contributions of different fire types, daily or 3-hourly fields to scale the monthly emissions to higher temporal resolutions, and data for monthly biosphere fluxes. The data are at 0.25-degree latitude by 0.25-degree longitude spatial resolution and are available from June 1995 through 2016, depending on the dataset. Emissions data are available for carbon (C), dry matter (DM), carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), hydrogen (H2), nitrous oxide (N2O), nitrogen oxides (NOx), non-methane hydrocarbons (NMHC), organic carbon (OC), black carbon (BC), particulate matter less than 2.5 microns (PM2.5), total particulate matter (TPM), and sulfur dioxide (SO2) among others. These data are yearly totals by region, globally, and by fire source for each region.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785312311-ORNL_CLOUD.html",
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         "description": "This International Satellite Land Surface Climatology Project (ISLSCP II) data set, ISLSCP II Carbon Dioxide Flux at Harvard Forest and Northern BOREAS Sites, contains gapp-filled flux and meterological data for half-hourly, daily, weekly, monthly, and annual time intervals presented for each site and year. The 1992-1995 Harvard Forest, MA site, and the 1994-95 Old Black Spruce, Alberta, Canada site are members of the FLUXNET global network of micrometeorological towers that use eddy covariance methods to measure the excahanges of carbon dioxide (CO2), water vapor, and energy between terrestrial ecosystem and atmosphere. ",
         "license": "proprietary"
     },
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         "description": "A comprehensive global database has been assembled to quantify CO2 fluxes and pathways across different levels of integration (from photosynthesis up to net ecosystem production) in forest ecosystems. The database fills an important gap for model calibration, model validation, and hypothesis testing at global and regional scales. The database archive includes: a Microsoft Office Access Database; data files for all tables in the database; query outputs from the database; and SQL script file for re-creating the database from the tables. The database is structured by site (i.e., a forest or stand of known geographical location, biome, species composition, and management regime). It contains carbon budget variables (fluxes and stocks), ecosystem traits (standing biomass, leaf area index, age), and ancillary information (management regime, climate, soil characteristics) for 529 sites from eight forest biomes. Data entries originated from peer-reviewed literature and personal communications with researchers involved in Fluxnet. Flux estimates were included in the database when they were based on direct measurements (e.g., tower-based eddy covariance system measurements), derived from single or multiple direct measurements, or modeled. Stand description was based on observed values, and climatic description was based on the CRU data set and ORCHIDEE model output. Uncertainty for each carbon balance component in the database was estimated in a uniformed way by expert judgment. Robustness of CO2 balances was tested, and closure terms were introduced as a numerical way to approach data quality and flux uncertainty at the biome level.",
         "license": "proprietary"
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         "description": "This data set contains global, spatially explicit (1 km2 grid cells) and temporally explicit (semi-monthly) modeled output of fuel loads over southern Africa. The fuel types considered in the data set are litter (dead tree leaves), dead grass, green grass, and small-diameter twigs. The Production Efficiency Model (PEM) was used to produce the estimated fuel loads for southern Africa for the 1999-2000 growing seasons.",
         "license": "proprietary"
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         "description": "Fluxes of carbon dioxide, water vapor, and energy exchange have been measured at 38 forest, grassland, and crop sites as part of the EUROFLUX and AmeriFlux projects. A total of 97 site-years of data were compiled, primarily between 1996 and 1998 but also for 1992-1995 and 1999-2000. Half-hour flux and meteorology measurements are included plus the gap-filled half-hour estimates and aggregations to day and night, weekly, monthly, and annual periods. The FLUXNET 2000 Synthesis Workshop was held at the Marconi Conference Center, Marshall, California, June 11-14, 2000. The Marconi Flux Data Collection was compiled to aid in exploring the interactions between the terrestrial biosphere and the overlying atmosphere through carbon, water, and energy exchanges. The workshop resulted in several studies to synthesize and interpret differences and similarities in long-term measurements of carbon dioxide, water vapor, and energy exchanges between vegetation and the atmosphere for a spectrum of ecosystems. A series of synthesis papers based on these data and studies was published in a special issue of the Agriculture and Forest Meteorology, Volume 113, 2002. The papers are listed in the reference section. This data product is being archived as a record of the data used the AFM special issue. Updates and revisions to the data are available at the FLUXNET web site.The eddy covariance technique is used for long-term continuous measurements of mass and energy fluxes to capture seasonal dynamics and allow for a meaningful scaling with respect to time. The equipment and methodology were standardized among sites by using common software and instrumentation. Comparisons of ecosystem fluxes among sites are usually performed on annual or monthly sums calculated on complete data records; however, the average site data coverage during a year was only 65%. Therefore, development and application of robust and consistent data gap-filling methods was required before fluxes could be calculated. One of the outcomes of the FLUXNET project was computer applications to process the data into complete, consistent, quality assured, and documented data sets (Falge et al. 2001a,b). Gap-filled flux data from four different filling methods are reported. Selected meteorological parameters were also gap filled to support flux estimating methods and are reported along with non-filled meteorological data. Note that the measured/estimated CO2 fluxes and storage fluxes were summed into net ecosystem exchange (NEE), and ONLY NEE data are reported. ",
         "license": "proprietary"
     },
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         "description": "The data sets in this directory were provided by Mr. Gregory Yetman and Drs. Stuart Gaffin and Deborah Balk from the Center for International Earth Science Information Network (CIESIN) at Columbia University. There are three data files at three spatial resolutions of 0.25, 0.5 and 1.0 degree in both latitude and longitude and for the reference year of 1990.Estimates of Gross Domestic Product (GDP) are commonly given for nations as a single aggregated number. This data set generates estimates of GDP density distributed subnationally to facilitate the integration of GDP with other data at a sub-national level and to promote interdisciplinary studies that include socioeconomic aspects.  This is one of two coarse resolution Socioeconomic data sets included in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection, the other being the Gridded Population of the World (GPW), also produced by CIESIN. ",
         "license": "proprietary"
     },
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         "description": "Geographic coordinate and other site information from several sources throughout the experiment period. The final set of information is organized into two data sets that provide geographic coordinate and site characteristic information for single sites and corner coordinates for standard geographic areas.",
         "license": "proprietary"
     },
@@ -215314,7 +215600,7 @@
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         "description": "The Geoecology database is a compilation of environmental data for the period 1941 to 1981. The Geoecology database contains selected data on terrain and soils, water resources, forestry, vegetation, agriculture, land use, wildlife, air quality, climate, natural areas, and endangered species. Data on selected human population characteristics are also included to complement the environmental files. Data represent the conterminous United States at the county level. These historical data are provided as a source of 1970s baseline environmental conditions for the United States.",
         "license": "proprietary"
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         "description": "This data set is a subset of Cogley's 1998 global hydrographic data set (GGHYDRO, Release 2.2). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The subset is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, and annual water runoff for the LBA study area. The data are presented at a spatial resolution of 1-degree latitude by 1-degree longitude in ASCII GRID file format.",
         "license": "proprietary"
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         "description": "This data set consists of a southern African subset of the Global Historical Climatology Network (GHCN) Version 1 database. All stations with the following bounding coordinates are included in this subset: 5W - 60E and 5N - 35S. There are three files available, one each for precipitation, temperature, and pressure data. Within this subset the oldest data date from 1874 and the most recent from 1990.",
         "license": "proprietary"
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         "description": "The Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 22-year satellite record of monthly changes in terrestrial vegetation. This data set contains three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude with data from July 1981 through December 2002. New features include reduced NDVI variations arising from calibration, view geometry, volcanic aerosols, and other effects not related to actual vegetation change. In particular, NOAA-9 descending node data from September 1994 to January 1995, volcanic stratospheric aerosol correction for 1982-1984 and 1991-1994, and improved NDVI using empirical mode decomposition/reconstruction (EMD) to minimize effects of orbital drift. Global NDVI was generated to provide inputs for computing the time series of biophysical parameters contained in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II collection. NDVI is used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface. ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2796830663-ORNL_CLOUD.html",
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         "description": "This database provides information on the distribution and environmental characteristics of natural wetlands. The database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. The original data consists of five global 1-degree latitude by 1-degree longitude arrays. The subset retains all five arrays at the 1-degree resolution but only for the area of interest. The arrays are (1) wetland data source, (2) wetland type, (3) fractional inundation, (4) vegetation type, and (5) soil type.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776893351-ORNL_CLOUD.html",
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         "description": "Nitrogen is a major nutrient in terrestrial ecosystems and an important catalyst in tropospheric photochemistry. Over the last century human activities have dramatically increased inputs of reactive nitrogen (Nr, the combination of oxidized, reduced and organically bound nitrogen) to the Earth system. Nitrogen cycle perturbations have compromised air quality and human health, acidified ecosystems, and degraded and eutrophied  lakes and coastal estuaries [Vitousek et al., 1997a, 1997b; Rabalais, 2002; Howarth et al., 2003; Townsend et al., 2003; Galloway et al., 2004]. To begin to quantify the changes to the global N cycle, we have assembled key flux data and N2O mixing ratios from various sources.  The data assembled from different sources includes fertilizer production from 1920-2004;  manure production from 1860-2004; crop N fixation estimated for three time points, 1860, 1900, 1995; tropospheric N2O mixing ratios from ice core and firn measurements, and tropospheric concentrations to cover the time period from 1756-2004.  The changing N2O concentrations provide an independent index of changes to the global N cycle, in much the same way that changing carbon dioxide concentrations provide an important constraint on the global carbon cycle.  The changes to the global N cycle are driven by industrialization, as indicated by fossil fuel NOx emission, and by the intensification of agriculture, as indicted by fertilizer and manure production and crop N2 fixation. The data set and the science it reflects are by nature interdisciplinary.  Making the data set available through the ORNL DAAC is an attempt to make the data set available to the considerable interdisciplinary community studying the N cycle.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776896954-ORNL_CLOUD.html",
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         "description": "This data set provides global gridded estimates of atmospheric deposition of total inorganic nitrogen (N), NHx (NH3 and NH4+), and NOy (all oxidized forms of nitrogen other than N2O), in mg N/m2/year, for the years 1860 and 1993 and projections for the year 2050. The data set was generated using a global three-dimensional chemistry-transport model (TM3) with a spatial resolution of 5 degrees longitude by 3.75 degrees latitude (Jeuken et al., 2001; Lelieveld and Dentener, 2000). Nitrogen emissions estimates (Van Aardenne et al., 2001) and projection scenario data (IPCC, 1996; 2000) were used as input to the model.",
         "license": "proprietary"
     },
@@ -216094,7 +216380,7 @@
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         "description": "Global Population of the World (GPW) translates census population data to a latitude-longitude grid so that population data may be used in cross-disciplinary studies. There are three data files with this data set for the reference years 1990 and 1995. Over 127,000 administrative units and population counts were collected and integrated from various sources to create the gridded data. In brief, GPW was created using the following steps:    * Population data were estimated for the product reference years, 1990 and 1995, either by the data source or by interpolating or extrapolating the given estimates for other years.    * Additional population estimates were created by adjusting the source population data to match UN national population estimates for the reference years.    * Borders and coastlines of the spatial data were matched to the Digital Chart of the World where appropriate and lakes from the Digital Chart of the World were added.    * The resulting data were then transformed into grids of UN-adjusted and unadjusted population counts for the reference years.    * Grids containing the area of administrative boundary data in each cell (net of lakes) were created and used with the count grids to produce population densities.As with any global data set based on multiple data sources, the spatial and attribute precision of GPW is variable. The level of detail and accuracy, both in time and space, vary among the countries for which data were obtained.",
         "license": "proprietary"
     },
@@ -216120,7 +216406,7 @@
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         "description": "The GlobalView Methane (CH4) data product contains synchronized and smoothed time series of atmospheric CH4 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1984 to 1998 with some sites having shorter or longer temporal coverage. Note that the GlobalView-CH4 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CH4 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 74 files with this data set which includes 71 *.zip data files. The other three files include 2 files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file containing CH4 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.",
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         "description": "The GlobalView Carbon Dioxide (CO2) data product contains synchronized and smoothed time series of atmospheric CO2 concentrations at selected sites that were created using the data extension and integration techniques described by Masarie and Tans, (1995). The information needed to derive this time series is also in this data set, along with extensive documentation. The longest period of coverage is from 1979 to 2001 with some sites having longer or shorter temporal coverage. Note that the GlobalView CO2 data products are derived from measurements but contain no actual data. To facilitate heterogeneous CO2 data use in carbon cycle modeling studies, the measurements have been processed (smoothed, interpolated, and extrapolated) resulting in extended records that are evenly incremented in time. There are 92 files with this data set which includes 89 *.zip data files. The other three files include 2  files with site information, one comma-delimited ASCII file (.csv), and one .dat file, and one .dat file which is a single reference marine boundary layer matrix file which contains CO2 mixing ratios as a function of time and sine of latitude and is a by-product of the data extension procedure.",
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         "license": "proprietary"
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         "description": "The Global Precipitation Climatology Project (GPCP) pentad version 1 precipitation data set includes global precipitation rates for 5-day, or pentad, periods. The data sets are derived from measured rain gauge data and merged with satellite estimates of rainfall. This is a portion of the version 1 GPCP pentad data set and covers the ISLSCP II period from 1986 to 1995. The original precipitation rates at 2.5 degrees were re-gridded to a 1 degree spatial resolution by the ISLSCP II staff. ",
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         "description": "Net Primary Production (NPP) is an important component of the carbon cycle and, among the pools and fluxes that make up the cycle, it is one of the steps that are most accessible to field measurement. Direct measurement of NPP is not practical for large areas and so models are generally used to study the carbon cycle at a global scale.  This data set contains 2 *.zip files for above ground and total NPP data. ",
         "license": "proprietary"
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         "description": "The Global Primary Production Data Initiative (GPPDI) was set up as a Focus 1 activity of the IGBP Data and Information System, a coordinated international program to improve worldwide estimates of terrestrial net primary productivity (NPP) for parameterization, calibration, and validation of NPP models at various scales.The GPPDI data collection contains documented field measurements of NPP for global terrestrial sites compiled from published literature and other extant data sources. The point measurements of NPP were categorized as either Class A, representing intensively studied or well-documented study sites (e.g., with site-specific climate, soils information, etc.), Class B, representing more numerous extensive sites with less documentation and site-specific information available, or Class C, representing regional collections of half-degree latitude-longitude grid cells. This data set in the ISLSCP II collection represents the GPPDI Class B NPP data. The Class B NPP data file contains biomass dynamics, climate, and site-characteristics data georeferenced to each site. There is one ASCII data file with this data set. ",
         "license": "proprietary"
     },
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         "description": "The objective of this work was to construct a long-term data set of daily precipitation on half degree and one degree latitude/longitude grids over the global land areas. The analyses are defined by interpolating station observations from GTS (Global Telecommunications System) gauges using the algorithm of Shepard (1968). The algorithm of Shepard (1968) has been widely used to interpolate gauge observations of monthly, pentad, and daily precipitation (Rudolf 1993, Xie et al. 1996). This algorithm is used to interpolate the irregularly distributed station observations onto grid points. The weighting coefficients are inversely proportional to the gauge-grid point distance and are adjusted by a cosine function taking into account the directional isolation of each gauge relative to all other nearby gauges. There are 6 data files with this data set.",
         "license": "proprietary"
     },
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         "description": "In conjunction with the AERONET (AErosol RObotic NETwork) participation in SAFARI 2000, the USDA Forest Service deployed handheld hazemeters in western Zambia from mid-June to late September 2000. Thirty-eight hazemeters were deployed within a 900 km x 900 km region in western Zambia to verify and study the aerosol properties in MODIS data. The handheld measurements were compared with satellite measurements. The hazemeter data were used to examine the effects of inhomogeneous atmosphere on MODIS aerosol product validation and to investigate the dependency of MODIS aerosol measurements on look angle and ground vegetation.",
         "license": "proprietary"
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         "description": "The Historical Croplands Cover data set was developed to understand the consequences of historical changes in land use and land cover for ecosystem goods and services. In particular, this data set can be used to study how global changes in cultivated area has influenced climate, biogeochemical cycles, biodiversity, etc. This data set can be used directly within spatially-explicit climate and biogeochemical models.This is a gridded data set describing the fraction of each grid cell in the globe that is occupied by cultivated land from 1700 to 1992. Data layers are provided for every 50 years from 1700 to 1850, every 10 years from 1850 to 1980, and every year from 1986 to 1992.There are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical. Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.The data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period. ",
         "license": "proprietary"
     },
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         "description": "The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).Testing against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period. ",
         "license": "proprietary"
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         "description": "This data set is a subset of a global croplands data set (Ramankutty and Foley 1999a). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format at 5-min resolution.Navin Ramankutty and Jonathan Foley, of the Center for Sustainability and the Global Environment (SAGE) at the University of Wisconsin, developed a global, spatially explicit data set of reconstructed historical croplands from 1700 to 1992. The method for historical reconstruction used a simple algorithm that linked contemporary satellite data and historical cropland inventory data. A spatially explicit croplands data set for 1992 was first derived by calibrating a satellite-derived land cover classification data set against cropland inventory data for 1992. This derived data set was then used within a simple land cover change model, along with historical cropland inventory data, to derive spatially explicit maps of historical croplands. The global data set was restricted to a representation of permanent croplands (i.e., excluding shifting cultivation), which follows the Food and Agriculture Organization (FAO) definition of arable lands and permanent crops. Data values represent fraction of grid cell in croplands.Data for the LBA study area are available for the years 1900, 1910, 1920, 1930, 1940, 1950, 1960, 1970, 1980, 1990, and 1992. Although the global croplands data set contains data representing croplands since 1700, essentially no croplands were in the LBA study area until 1900. Data from previous years were excluded at the suggestion of the data originator.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/historical_croplands/comp/uwcrop_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
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         "description": "This data set contains coarse scale elevation and elevation-based parameters at 1.0 and 0.5-degree spatial resolutions that were developed to support a wide variety of global modeling activities through the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data collection. These coarse scale data have sufficient statistical information (up to fourth moment) to allow a good statistical description of the sub-cell distribution of any particular elevation parameter (i.e. elevation, slope and aspect). The database used in the development effort was the HYDRO1k product (http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/HYDRO1K) with a native spatial resolution of 1 km, the highest resolution database of global coverage of standard elevation-based derivatives (slope, aspect, elevation, compound topographic index, etc.). ",
         "license": "proprietary"
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         "description": "This southern African subset of the Global Hydrographic data set (GGHYDRO) Release 2.2 is organized into 19 files containing terrain type, stream frequency counts, major drainage basins, main features of the cryosphere surface, and ice/water runoff per year for the entire Earth's surface at a spatial resolution of 1-degree longitude by 1-degree latitude. The data are provided in both ASCII GRID and binary image file formats.",
         "license": "proprietary"
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         "description": "The Integrated Biosphere Simulator (or IBIS) is designed to be a comprehensive model of the terrestrial biosphere. Tthe model represents a wide range of processes, including land surface physics, canopy physiology, plant phenology, vegetation dynamics and competition, and carbon and nutrient cycling. The model generates global simulations of the surface water balance (e.g., runoff), the terrestrial carbon balance (e.g., net primary production, net ecosystem exchange, soil carbon, aboveground and belowground litter, and soil CO2 fluxes), and vegetation structure (e.g., biomass, leaf area index, and vegetation composition). IBIS was developed by Center for Sustainability and the Global Environment (SAGE) researchers as a first step toward gaining an improved understanding of global biospheric processes and studying their potential response to human activity  [Foley et al. 1996].  IBIS was constructed to explicitly link land surface and hydrological processes, terrestrial biogeochemical cycles, and vegetation dynamics within a single, physically consistent framework. Furthermore, IBIS was one of a new generation of global biosphere models, termed Dynamic Global Vegetation Models (or DGVMs), that consider transient changes in vegetation composition and structure in response to environmental change. Previous global ecosystem models have typically focused on the equilibrium state of vegetation and could not allow vegetation patterns to change over time. Version 2.5 of IBIS includes several major improvements and additions [Kucharik et al. 2000]. SAGE continues to test the performance of the model, assembling a wide range of continental- and global-scale data, including measurements of river discharge, net primary production, vegetation structure, root biomass, soil carbon, litter carbon, and soil CO2 flux. Using these field data and model results for the contemporary biosphere (1965-1994), their evaluation shows that simulated patterns of runoff, NPP, biomass, leaf area index, soil carbon, and total soil CO2 flux agreed reasonably well with measurements that have been compiled from numerous ecosystems. These results also compare favorably to other global model results [Kucharik et al. 2000].",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2785271209-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785271209-ORNL_CLOUD.html",
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         "description": "This data set provides gridded data for selected soil parameters derived from data and methods developed by the Global Soil Data Task, an international collaborative project with the objective of making accurate and appropriate data relating to soil properties accessible to the global change research community. The task was coordinated by the International Geosphere-Biosphere Programme (IGBP-DIS). The data in this data set were produced by the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) staff from data obtained from the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov/). See the related data sets section below. Two-dimensional gridded maps of selected soil parameters, including soil texture, at a 1.0 by 1.0 degree spatial resolution and for two soil depths are provided. All data layers have been adjusted to match the ISLSCP II land/water mask. There are 36 data files with this data set.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804796522-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804796522-ORNL_CLOUD.html",
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         "description": "The objective of this study was to determine the spatial variations in field measurements of broadband albedo as related to the ground cover and under a range of solar conditions during the Prototype Validation Exercise (PROVE) at the Jornada Experimental Range in New Mexico on May 20-30, 1997.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804797176-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804797176-ORNL_CLOUD.html",
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         "description": "Directional reflected radiation was measured over plots representing selected canopy components (shrubs and individual plants, bare sand, and background) at the Jornada Experiment Range site near Las Cruces, New Mexico, during the Prototype Validation Experiment (PROVE) in May 1997.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804794793-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804794793-ORNL_CLOUD.html",
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         "description": "Field measurement of shrubland ecological properties is important for both site monitoring and validation of remote-sensing information. During the PROVE exercise on May 20-30, 1997, we calculated plot-level plant area index, leaf area index, total fractional cover, and green fractional cover.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804795305-ORNL_CLOUD.html",
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         "description": "This study utilized low flying, aircraft-based radiometers for optical characterization of top-of-the-canopy reflectance at Jornada Experimental Range in New Mexico during the Prototype Validation Experiment (PROVE) in May 1997. The objective was to examine the usefulness of low-flying aircraft for Moderate Resolution Imaging Spectroradiometer (MODIS) validation of land products.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2788397022-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788397022-ORNL_CLOUD.html",
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         "description": "The data presented here include the aerosol optical thickness (AOT) and column water vapor measurements taken at sites along the Kalahari Transect using a Microtops sunphotometer. Data were collected every 30 minutes at 4 sites that were visited during the SAFARI 2000 Kalahari Wet Season Campaign between March 3, 2000, and March 18, 2000. AOT values are provided at 340-, 440-, 675-, 870-, and 936-nm wavelengths. An estimate of the Angstrom Coefficient is also provided to allow the estimation of AOT at other wavelengths. The purpose of this data collection was primarily for documentation of the conditions at each site and to aid in the correction of remote sensing data, for validation of Earth Observation System (EOS) products such as MODIS and MISR aerosol products, and for modeling of canopy productivity.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789074715-ORNL_CLOUD.html",
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         "description": "Short-term measurements of carbon dioxide, water, and energy fluxes were collected at four locations along a mean annual precipitation gradient in southern Africa during the SAFARI 2000 wet (growing) season campaign of 2000. The purpose of this research was to determine how observed vegetation-atmosphere exchange properties are functionally related to long-term climatic conditions.",
         "license": "proprietary"
     },
@@ -233852,7 +234138,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789033440-ORNL_CLOUD.html",
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         "description": "Kruger National Park (KNP) was established in 1898 to protect wildlife on nearly 2 million hectares of the South African Lowveld. Savanna fires are common in the South African Lowveld during the dry season. The two primary sources of fire ignition, historically and currently, are human activity and lightning. This data set contains a record of all fires observed in the Kruger National Park for each of the 10 fire years from 1992 to 2001. The data were compiled from various sources, including old fire records in hardcopy and vector form, as well as satellite imagery.",
         "license": "proprietary"
     },
@@ -233865,7 +234151,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789022996-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789022996-ORNL_CLOUD.html",
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         "description": "The goal of this study was to understand the change in reflectance caused by the action of fire and the heterogeneity of fire effects (i.e., the fraction of the observation that burned and the combustion completeness of that observation). A spectral mixture model and field and satellite observations were used to compare changes in Landsat reflectance associated with fire and combustion completeness derived from field measurements at prescribed fire sites in South Africa and to substantiate and illustrate the model findings. The data are stored in a single ASCII file in comma-separate-value format (.csv).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789041646-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789041646-ORNL_CLOUD.html",
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         "description": "An eddy covariance system mounted on a tower near the Skukuza Camp in Kruger National Park, South Africa, has been operating continuously since early 2000. Meteorological measurements started in February 2000, and the first flux measurements were made in April 2000. The site is unique in that the micrometeorological instruments are positioned on a tower located between two distinct savanna types, a broad-leafed Combretum savanna and a fine-leafed Acacia savanna. Measurements on the main eddy covariance tower include net ecosystem exchange of CO2, water, and energy, and measurements of a range of meteorological variables with 30-minute averaging period.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789077526-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789077526-ORNL_CLOUD.html",
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         "description": "This data set contains leaf area index (LAI), leaf inclination angle, and canopy dimension data from study sites along the Kalahari Transect in southwest Botswana. The data were collected during the 2001 wet season field campaign of the SAFARI 2000 at a total of seven plots of 200 x 150 meter dimensions: two plots each at Tshane and Mabuasehube and three plots at Tsabong. The data set consists of measurements of leaf angle for plot dominant woody species, LAI calculated from overstory and understory photosynthetically active radiation (PAR) measurements, and canopy dimension data (i.e., crown height, crown width, and height to crown) for grass and woody vegetation for use in the parameterization of plant canopy reflectance models. The data files are stored as ASCII table files, in comma-separated-value (.csv) format, with column headers. Photographs (.jpg) are provided of each plot to provide an idea of site conditions. The photographs can be viewed on the S2K Photo Gallery pages.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789080946-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789080946-ORNL_CLOUD.html",
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         "description": "This data set contains Global Positioning System (GPS) imprinted landscape photographs at 100-m intervals along the Large Grid Transects at Kalahari Transect sites in Botswana and at measurement sites in Kataba Forest, Mongu, Zambia, and in the vicinity of the Skukuza flux tower site in Kruger National Park, South Africa. The Kalahari sites visited were Pandamatenga, Maun, Okwa Valley, and Tshane. There are about 30 pictures per site.  In a related study, vegetation cover and composition were measured at various locations along the Kalahari Transect and trends in major vegetative cover, including species types and richness, were recorded (Ringrose and Matheson, 2004). The photographs are intended to aid in the interpretation of other data sets, and can be used to suggest canopy height, gap fraction, grass, soil, and sky conditions. The photographs are provided as JPEG images.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789085993-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789085993-ORNL_CLOUD.html",
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         "description": "The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign from March 3rd to March 18th, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance, leaf hemispherical transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. LAI data are provided in this data set. LAI was intensively measured at 4 different sites in Botswana -- Pandamatenga, Maun, Okwa River, and Tshane (from north to south) -- where vegetation types range from moist closed woodlands to arid sparsely-shrub-covered grasslands.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789088751-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789088751-ORNL_CLOUD.html",
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         "description": "Data from the Tracing Radiation and Architecture of Canopies (TRAC) instrument were collected at five sites along the International Geosphere-Biosphere Programme (IGBP) Kalahari Transect, including Mongu in Zambia and Pandamatenga, Maun, Okwa River Crossing, and Tshane in Botswana, during the 2000 wet season field campaign (March-April) of SAFARI 2000. At the Mongu site, TRAC measurements began in August of 1999 and continued beyond the 2000 wet season field campaign, about every month for the rest of 2000. The TRAC instrument contains pyranometers that are sensitive to photosynthetically active radiation (PAR) at 400-700 nm. The TRAC measures the PAR flux transmitted through the overstory canopy continuously at 32 Hz. The parameters derived from the TRAC instrument include estimates of plant or leaf area index (PAI, LAI), overstory gap fraction, and clumping index.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789090604-ORNL_CLOUD.html",
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         "description": "Data presented in this data set were collected during an intensive field campaign in Botswana between February 28 and March 18, 2000 along the Kalahari Transect as part of the SAFARI 2000 wet season field campaign. The sites visited were Pandamatenga, Maun, Okwa River Crossing, and Tshane (north to south). Individual leaf blade measurements were made on replicate samples from selected dominant and subdominant tree species using an optical lens and graticule. Leaves used in the study had recently-matured new growth and were fully exposed to the sun for a significant part of the day. The data set comprises individual leaf blade dimensions along the length and width of each leaf by tree species as well as the mean of the replicate leaf length and width samples. The data are in comma-delimited ASCII format (kt_leaf_dimensions.csv).",
         "license": "proprietary"
     },
@@ -234034,7 +234320,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789093077-ORNL_CLOUD.html",
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         "description": "The Boston University team collected several data sets along the Kalahari Transect during the SAFARI 2000 wet season field campaign between March 3 and March 18, 2000, to support the validation of the MODIS LAI/FPAR algorithm. Ground measurements of LAI, FPAR, leaf hemispherical reflectance and transmittance, and canopy transmittance were made using a LAI-2000 plant canopy analyzer, an AccuPAR ceptometer, a LiCor 1800-12S External Integrating Sphere (LI-1800) portable spectroradiometer, and an ASD handheld spectroradiometer. Leaf spectral data are provided in this data set. Leaf spectral measurements were made on samples from dominant tree, shrub, and grass species at 5 different Kalahari Transect sites - Mongu in Zambia and Pandamatenga, Maun, Okwa River, and Tshane in Botswana (from north to south)- where vegetation ranges from moist closed woodlands to arid sparsely-shrub-covered grasslands.",
         "license": "proprietary"
     },
@@ -234047,7 +234333,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789096153-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789096153-ORNL_CLOUD.html",
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         "description": "This data set was collected during February-March 2000 wet season and September 2000 dry season field campaigns of SAFARI 2000. Mongu in Zambia and Pandematenga (aka Kasane) and Tshane in Botswana were visited during the wet season campaign. Dry season data are for Mongu only. Hemispherical photographs, from which Plant Area Index (PAI) estimates are derived, were obtained at the field sites to characterize vegetation structural changes along the Kalahari Transect. The photographs are classified into sky and vegetation (trunk, green and senescent leaves, and branches) using an unsupervised classification scheme.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789732502-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789732502-ORNL_CLOUD.html",
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         "description": "Ceptometer data from a Decagon AccuPAR (Model PAR-80) were collected at four sites in Botswana during the SAFARI 2000 Kalahari Transect Wet Season Campaign (March, 2000). These sites include Maun, Pandamentanga, Ghanzi/Okwa River Crossing, and Tshane. The measurements were taken near stake flags placed at 25 m intervals along three parallel 750 m transects located 250 m apart. The ceptometer contains 80 photosynthetically active radiation (PAR) sensors fixed at 1 cm intervals along a wand and connected to a control box. The sampling protocol followed in general was to first measure above canopy incident PAR, then canopy reflected PAR, then above canopy incident PAR again, and finally, canopy transmitted PAR. The data can be used to compute fraction of photosynthetically active radiation (FPAR), intercepted PAR, leaf area index (LAI), and gap fraction. These data currently exist in raw format, but can be processed using manufacturer-provided software to estimate the derived products.The data are stored as ASCII files, in csv format, organized by site, with one file per transect. Incident, transmitted, and reflected PAR radiation values for a transect and site are in the same file. The type of measurement for each data point is known due to comments in the data files. For the Maun and Pandamatenga sites, there is an additional file containing above canopy PAR irradiance. The PAR data units are micromols m-2 s-1, and the time is in Local Time. There is also a readme file, in txt format, for each site.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789098245-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789098245-ORNL_CLOUD.html",
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         "description": "This data set provides species distribution, basal area, height, and crown cover of woody stems at 10 sites along the Kalahari Transect where a large gradient in both the mean and variation of annual rainfall results in dramatic changes in vegetation structure. Some of the data were collected during earlier Kalahari Transect projects in 1995 and 1997 at Vastrap, South Africa; Sandveld and Sachinga, Namibia; and Maziba, Senanga, and Lukulu, Zambia. The rest of the data were collected at Mongu, Zambia; and Pandamatenga, Maun, and Tshane, Botswana during the February-March 2000 wet season field campaign of SAFARI 2000. Stem maps were generated at each site using a variable-width belt-transect approach. Tree location, species, diameter, height, and major and minor axis of crown dimensions were measured for each individual taller than 1.5 meters. For multi-stemmed individuals, the diameter of each stem was recorded separately. Canopy area was calculated to be an ellipse defined by the two major axes of measurement. Canopy height was estimated using a clinometer. Biomass was calculated following Goodman (1990) as modified by Dowty (1999).There are two ASCII data files, in comma-delimited format. The stem map file contains records of living, dead, and cut stem allometry, canopy geometry, and biomass at the SAFARI sites. The species list file provides plant family, genus, and species names, numerical codes that correspond to the stem map file, and species common names in English and AFRICAANS.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789099661-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789099661-ORNL_CLOUD.html",
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         "description": "Vegetation cover and composition, including species types and richness assessments, were measured at four locations along the Kalahari Transect in Botswana (Pandamatenga, Maun, Okwa River, and Tshane) during the SAFARI 2000 wet season field campaign. The sites visited showed interesting degrees of variability despite the apparent homogeneity of the Kalahari sands and predominantly semi-arid savanna shrub-woodlands vegetation cover (Ringrose et al., 2003).At each site, twelve individual locations were chosen by random stratified techniques within a 30-km radius at each location, based on differences in topography, soils, and known disturbance, to help determine local variability (Huennecke et al., 2001). Data collection methods were identical at each location (Ringrose et al., 1996; 1998): (1) identification and enumeration of all species along 3 x 90-m transects, spaced 45-m apart; (2) visual estimation (tape measure and pacing) of canopy diameter along each transect; and (3) visual estimation of percent live and dead herbaceous cover, litter, and bare soil using 3 x 50 m2 quadrats spaced at 30-m intervals along each transect. In addition, vegetation components were calculated for each site comprising woody vegetation cover, green herbaceous cover in terms of grass and forbs, dead herbaceous cover, plant litter, and bare soil. Species richness was calculated as the actual number of species per three transects (270 m2) at each site (Kent and Coker, 1996).The data set consists of two data files (ASCII tables) in comma-delimited format (.csv) with descriptive header records. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789101524-ORNL_CLOUD.umm_json",
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         "description": "This data set contains species composition, basal area, height, and crown cover of all woody plants at six sites along the Kalahari Transect visited in February-March of 2000 as part of SAFARI 2000. Similar measurements on woody and herbaceous vegetation at the Skukuza Flux Tower site in Kruger National Park, South Africa, were made in June of 2000. Leaf area index was derived from measurements made using PAR sensors at each site.Sampling protocol was the same at each site, with a slight variation at Skukuza.  A grid of 42 points, 6 rows of 7 columns, each 50 m apart, was laid down in an area 300 m x 350 m for the Kalahari Transect sites. At Skukuza, the grid was 7x7, or 350 m x 350 m, centered on the tower site, yielding 49 points. At each grid point, all woody plants within a circular plot of a fixed radius were identified and measured. Stem circumference was measured on all stems and basal area per stem was derived. Basal area for the circular plots, per species, was calculated and extrapolated to hectares. Tree and stem densities were determined from the number of trees and stems in subplots and extrapolated to hectares. Woody plant height and canopy cover were determined, and aboveground woody biomass and peak leaf area index were estimated. The files are in comma-delimited ASCII format, with the first line listing the data set, author, and date, followed by the data records.",
         "license": "proprietary"
     },
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         "description": "LAI estimates computed from unweighted openness by the CANOPY program from digitized canopy photographs",
         "license": "proprietary"
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         "description": "This data set consists of a southern African subset of the 1-km Global Land Cover Data Set Derived from AVHRR developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Both ASCII data and binary image files are available.",
         "license": "proprietary"
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         "description": "This data set consists of a subset of a 1-degree global land cover product (DeFries and Townshend 1994). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777325367-ORNL_CLOUD.html",
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         "description": "This data set is a subset of Hansen et al. (1999), \"1 km Global Land Cover Data Set Derived from AVHRR,\" which was developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are in ASCII GRID file format.In recent years, researchers have increasingly turned to remotely sensed data to improve the accuracy of data sets that describe the geographic distribution of land cover at regional and global scales. To develop improved methodologies for global land cover classifications as well as to provide global land cover products for immediate use in global change research, LGRSS researchers have employed the NASA/NOAA Pathfinder AVHRR Land (PAL) data set with a spatial resolution of 1 km. The PAL data set has a record length of 14 years (1981-1994), providing the ability to test the stability of classification algorithms. The PAL data set includes red, infrared, and thermal bands in addition to the Normalized Difference Vegetation Index (NDVI). Inclusion of these additional bands improves discrimination between cover types. The LGRSS researchers' aim was to develop and validate global land cover data sets and to develop advanced methodologies for more realistically describing the vegetative land surface based on satellite data.The 1-km global land cover product was created from 1992-1993 local area coverage (LAC) AVHRR data. The global land cover product is available for download from the University of Maryland's Global Land Cover Facility (GLCF) Web site (http://glcf.umiacs.umd.edu/data/landcover/index.shtml). Forty-one metrics were developed to describe global vegetation phenology, and these data were used to make the 1-km land cover map. The final product contains 13 land cover classes.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/land_cover_data_1km/comp/glcf1km_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
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         "description": "This data set is a subset of an 8-km global land cover product (DeFries et al. 1998). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are in ASCII GRID file format.To develop improved methodologies for global land cover classifications as well as to provide global land cover products for immediate use in global change research, researchers at the Laboratory for Global Remote Sensing Studies at the University of Maryland employed the NASA/NOAA Pathfinder AVHRR Land (PAL) data set with a spatial resolution of 8 km. The PAL data set has a length of record of 14 years (1981-1994), providing the ability to test the stability of classification algorithms. Furthermore, the data set includes red, infrared, and thermal bands in addition to the Normalized Difference Vegetation Index (NDVI). Inclusion of these additional bands improves discrimination between cover types. The project's aim was to develop and validate global land cover data sets and to develop advanced methodologies for more realistically describing the vegetative land surface based on satellite data.The global land cover product (Defries et al. 1998) was derived by testing several metrics that describe the temporal dynamics of vegetation over an annual cycle. These metrics were applied to 1984 PAL data at 8-km resolution to derive a global land cover classification product using a decision tree classifier. The final product contains 13 land cover classes. The original 8-km global land cover product is available for download from the University of Maryland's Global Land Cover Facility (GLCF) Web site (http://glcf.umiacs.umd.edu/data/landcover/index.shtml). Additional information and references on this data set can be found at the GLCF Web site, as well as at the LGRSS Web site (http://www.geog.umd.edu/LGRSS/intro.html). More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/comp/land_cover_data_8km/glcf8km_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
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         "description": "Improved vegetation distribution and emission data for Africa south of the equator were developed for the Southern African Regional Science Initiative (SAFARI 2000) and combined with biogenic volatile organic compound (BVOC) emission measurements to estimate BVOC emissions for the southern African region. BVOC emissions were estimated for southern Africa on a monthly basis over a one-year period by combining GIS layers of vegetation, LAI, and climate with a biogenic emissions model, GLOBEIS (Guenther et al, 1993; Guenther, 1999).",
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         "description": "This data set consists of a subset of the Global Historical Climatology Network (GHCN) Version 1 database for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). There are three files available, one each for precipitation, temperature, and pressure data.  Within this subset the oldest data date from 1832 and the most recent from 1990. More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
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         "description": "This data set is a subset of a global database compiled by Matthews and Fung (1987) on the distribution and environmental characteristics of natural wetlands. The global database was developed to evaluate the role of wetlands in the annual emission of methane from terrestrial sources. This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777329835-ORNL_CLOUD.html",
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         "description": "The data set consists of a subset of the ISRIC-WISE global data set of derived soil properties for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 to 30 degrees W, latitude 25 degrees S to 10 degrees N). More information about LBA and links to other LBA project sites can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804819697-ORNL_CLOUD.html",
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         "description": "This data set is a subset of the 1-km global tree cover data set (DeFries et al. 1999) developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America. The data are in ASCII GRID format.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789045395-ORNL_CLOUD.html",
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         "description": "Biogenic volatile organic compounds (VOCs) comprise a significant proportion of trace gases in the atmospheric environment and play an important role in the formation of secondary air pollutants. Emissions of monoterpenes from vegetation were studied at adjacent sites in Botswana as part of the SAFARI 2000 (Southern African Regional Science Initiative). Using a LI-COR leaf cuvette, VOC emissions were measured from the dominant tree species (Colophospermum mopane) and other vegetation near Maun, Botswana.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776830164-ORNL_CLOUD.html",
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         "description": "Carbon and nitrogen concentrations of fresh forest foliage were determined. Results were used to calibrate Visible/NIR reflectance for estimation of canopy carbon and nitrogen.",
         "license": "proprietary"
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         "description": "Visible/NIR reflectance spectra data for both fresh and dry leaf samples were collected to determine the relationship of foliar chemical concentrations with reflectance.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776935499-ORNL_CLOUD.html",
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         "description": "This data set is a subset of Cramer and Leemans' (2001) global database of mean monthly climatology, which contains monthly averages of mean temperature, temperature range, precipitation, rain days, and sunshine hours for terrestrial areas during 1931-1960. This subset was created for the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are presented at 0.5-degree latitude/longitude resolution in ASCII GRID file format. Cramer and Leemans (2001, Version 2.1) constituted a major update of an earlier database, Leemans and Cramer (1991). The new version was generated from a larger database by means of the partial thin-plate splining algorithm developed by Michael F. Hutchinson, Canberra (Hutchinson and Bischof 1983). Version 2.1 has been used widely, notably by all groups participating in the International Geosphere-Biosphere Programme's Net Primary Productivity (NPP) model intercomparison (Olsen et al. 2001).More information about the data can be found at ftp://daac.ornl.gov/data/lba/physical_climate/leemans_cramer/comp/cramer_lmns_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776929056-ORNL_CLOUD.html",
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         "description": " The Legal Amazon of Brazil is defined by law to include the states of Acre, Amapa, Amazonas, Para, Rondonia, Roraima, Mato Grosso, Maranhao, and Tocantins [Fundacao Instituto Brasileiro de Geografia e Estatistica (IBGE) 1991]. This is the definition used in generating the Legal Amazon mask. The 8-km Legal Amazon mask was generated by Christopher Potter at the Ecosystem Science and Technology Branch of the Earth Science Division at NASA Ames Research Center (Potter and Brooks-Genovese 1999). The mask was generated from the Digital Chart of the World available from Environmental Systems Research Institute, Inc. (ESRI). The mask is available in ASCII GRID format. The README file accompanying the mask has more information regarding data format. More information can be found at ftp://daac.ornl.gov/data/lba/human_dimensions/legal_amazon_mask/comp/legamazon_readme.pdf.",
         "license": "proprietary"
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         "description": "The Atmospheric Tracer Transport Model Intercomparison Project (TransCom) was created to quantify and diagnose the uncertainty in inversion calculations of the global carbon budget that results from errors in simulated atmospheric transport, the choice of measured atmospheric carbon dioxide data used, and the inversion methodology employed. Under the third phase of TransCom (TransCom 3), surface-atmosphere CO2 fluxes were estimated from an intercomparison of 16 different atmospheric tracer transport models and model variants in order to assess the contribution of uncertainties in transport to the uncertainties in flux estimates for annual mean, seasonal cycle, and interannual inversions (referred to as Level 1, 2, and 3 experiments, respectively).This data set provides the model output and inversion results for the TransCom 3, Level I annual mean inversion experiments. Annual mean CO2 concentration data (GLOBALVIEW-CO2, 2000) were used to estimate CO2 sources. The annual average fluxes were estimated for the 1992-1996 period using each of the 16 transport models and a common inversion set-up (Gurney et al., 2002). Methodological choices for this control inversion were selected on the basis of knowledge gained from a wide range of sensitivity tests (Law et al., 2003). Gurney et al. (2003) present results from the control inversion for individual models as well as results from a number of sensitivity tests related to the specification of prior flux information. Additional information about the experimental protocol and results is provided in the companion files and the TransCom project web site (http://www.purdue.edu/transcom/index.php).The results of the Level 1 experiments presented here are grouped into two broad categories: forward simulation fields and response functions (model output) and estimated fluxes (inversion results).",
         "license": "proprietary"
     },
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         "description": "This data set provides model outputs and seasonal mean CO2 fluxes from the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3), Level 2 inversion experiment. Inversion methods can be used to estimate surface CO2 fluxes from atmospheric CO2 concentration measurements, given an atmospheric transport model to relate the two. This Level 2 experiment inverted for the spatial and temporal pattern of the residual CO2 sources and sinks. There were 12 atmospheric tracer transport models utilized in this experiment. The data inverted were mean CO2 concentration data from 75 sites from the GLOBALVIEW-CO2 2000 data set for the period 1992-1996. The seasonal inversion consists of a 3 year forward simulation (365 days per year) containing 4 presubtracted tracers, 11 SF6 tracers, and 22 CO2 tracers (11 terrestrial, 11 oceanic) (Gurney et al., 2000). Carbon fluxes were estimated for each month of an average year determined as the mean of the 1990-1996 time period from an intercomparison of 12 different atmospheric tracer transport models. This data set provides input data, model output data,the cyclo inversion code, a basis function map, and estimated fluxes.",
         "license": "proprietary"
     },
@@ -235321,7 +235607,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2761762163-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761762163-ORNL_CLOUD.html",
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         "description": "The results of published and unpublished experiments investigating the impacts of elevated carbon dioxide on the chemistry (nitrogen and lignin concentration) of leaf litter and the decomposition of plant tissues are assembled in a format appropriate for statistical meta-analysis of the effect of carbon dioxide.",
         "license": "proprietary"
     },
@@ -235581,7 +235867,7 @@
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         "description": "The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 20-Aug-1988 was used to derive this classification.  A standard supervised maximum likelihood classification approach was used to produce this classification.",
         "license": "proprietary"
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         "description": "A Landsat-5 TM image from 06-Aug-1990 was used to derive this classification, the objective of which is to provide BOREAS investigators with a data product that characterizes the land cover of the SSA. A standard supervised maximum likelihood classification approach was used to produce this classification.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2928000847-ORNL_CLOUD.html",
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         "description": "The objective of this classification is to provide BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 21-Jun-1995 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used in a way that is similar to training  data to classify the image into the different land cover classes.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2928001982-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2928001982-ORNL_CLOUD.html",
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         "description": "The objective of this classification is to provide BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep-1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789737464-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789737464-ORNL_CLOUD.html",
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         "description": "The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD04_L2 aerosol product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 26, 2000, through December 31, 2001. The process of generating the statistics involves identifying these locations on the MODIS MOD04_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following variables: cloud fraction (land); cloud fraction (ocean); particle effective radius (ocean); optical depth (land and ocean); optical depth (land, corrected); optical depth (ocean, effective average); and optical depth ratio (small ocean). ",
         "license": "proprietary"
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         "description": "The MODIS (Moderate Resolution Imaging Spectroradiometer) Atmosphere Group develops remote sensing algorithms for deriving sets of atmospheric parameters from MODIS radiance data. These parameters can be integrated into conceptual and predictive global models. MODIS Atmosphere Products Subset Statistics (MAPSS) are generated over important locations around the world, as one of the ways to increase the scope of application of the MODIS atmospheric parameters. This MAPSS data set contains daily time series of the MODIS MOD05_L2 water vapor product over seventeen (17) AERONET sunphotometer measurement sites in southern Africa for the period February 24, 2000, through March 4, 2002. The process of generating the statistics involves identifying these locations on the MODIS MOD05_L2 product, extracting the values of the pixel corresponding to each coordinate point as well as surrounding pixels falling within a 50 x 50 km box centered on the coordinate point. The data product consists of column water-vapor amounts. During the daytime, a near-infrared algorithm is applied over clear land areas of the globe and above clouds over both land and ocean. Over clear ocean areas, water-vapor estimates are provided over the extended glint area. An infrared algorithm for deriving atmospheric profiles is also applied both day and night for Level 2. The data files are stored as ASCII tables in comma-separated-value (.csv) format. There is one file per site per year for each of the following two variables: total column precipitable water vapor (infrared retrieved) and total column precipitable water vapor (near-infrared retrieved).",
         "license": "proprietary"
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         "description": "Contains 15 minute surface meteorology data collected during the 1994 field campaigns by the Atmospheric Environment Service Meteorological Automatic Reporting System II autostations.",
         "license": "proprietary"
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         "description": "To investigate potential contributions of savanna ecosystems to the Earth's carbon balance, an eddy covariance system was used to measure the seasonal variation in carbon dioxide, water vapor, and energy flux at the Maun micrometerological tower site in a broadleaf semi-arid savanna in Southern Africa, approximately 20 km east of Maun in northeastern Botswana.",
         "license": "proprietary"
     },
@@ -236829,7 +237115,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789021046-ORNL_CLOUD.html",
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         "description": "The University of Wyoming has a series of balloonborne radiosonde measurements from all around the world, from the surface to 30 km.  This data set contains upper air meteorological profiles from 594 radiosonde launches deployed from sites in South Africa.  These sonde launches were made to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaign of 2000.Vaisala RS80 sondes were launched from nine sites in South Africa between August 1, 2000 and September 30, 2000. The launch sites were Pietersburg (changed to Polokwane after 2000), Pretoria (Irene), Bethlehem, Springbok, De Aar, Durban, Cape Town, Port Elizabeth, and Gough Island. The parameters measured by the radiosonde instruments include: pressure, air temperature, relative humidity, wind speed, and wind direction.",
         "license": "proprietary"
     },
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         "description": "Vaisala RS80 sondes were deployed from Skukuza Airport, South Africa, to collect atmospheric sounding profiles of temperature and moisture data from the surface to 30 km. These sonde launches were coordinated to augment the regional sounding network in the region during the SAFARI 2000 Dry Season Campaigns of 1999 and 2000. The radiosondes were launched from Skukuza Airport between August 14-September 3, 1999, and between August 24-September 23, 2000.  The radiosonde instrument package RS80 measured the following meteorological parameters: pressure in hecto-Pascals (P), ambient temperature in degrees Celsius (T), and relative humidity in percentage (RH). A hydrostatic equation was applied to the recorded data, after error-checking, to calculate the output parameters: height above sea level in meters, dew point temperature in degrees Celsius, and q (g/kg) which is specific humidity in grams per kilogram.",
         "license": "proprietary"
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         "description": "Meteorology data collected on an hourly basis from stations located near the OTTER sites in 1990 and summarized to monthly data--see also: Canopy Chemistry (OTTER)",
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         "description": "Two Micro-Pulse Lidar (MPL) systems were deployed to Africa for the SAFARI 2000 experiment. One MPL was set up in Mongu, Zambia, and the other was set up in Skukuza, South Africa. The primary focus of MPL work during SAFARI was to study the vertical distribution and optical properties of smoke from biomass burning in the region.",
         "license": "proprietary"
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         "description": "Steve Running's Forest-BGC Model (v.1991)",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785306797-ORNL_CLOUD.html",
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         "description": "This data set contains modeled annual net primary production (NPP) for the land biosphere from seventeen different global models. Annual NPP is defined as the net difference of annual carbon uptake (grams CO2/m2/yr) from the atmosphere through photosynthesis by the land vegetation and that lost back to the atmosphere through autotrophic and maintenance respiration. NPP is also related to the Net Ecosystem Exchange (NEE) of carbon accumulated by or lost from the surface by its vegetation and soils. NPP is NEE plus heterotrophic (decomposition) respiration of the vegetation and soils. Only NPP values are included in this data set as some models did not estimate NEE. Data for the mean, standard deviation and coefficient of variation of NPP for the 17 models are provided at spatial resolutions of 1.0 degree and 0.5 degrees. There are two compressed (*.zip) data files with this data set.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789736376-ORNL_CLOUD.html",
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         "description": "The subset of the MODIS MOD04_L2 aerosol product provided in this data set represents the swaths that coincide with known times of the South African Weather Bureau/Service (SAWS) Aerocommanders JRA and JRB research aircraft missions to support aerosol research and validation activities for the SAFARI 2000 region. The MODIS aerosol product monitors the ambient aerosol optical thickness over the oceans globally and over a portion of the continents. Further, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. Daily Level 2 data are produced at the spatial resolution of a 10 x 10 1 km (at nadir) pixel array. The daily data files cover the period August 21, 2000, through September 26, 2000. For some data collection dates, there are two or more data files.The MOD04_L2 swath data files included in this data set are from the GSFC DAAC (V4.1.0, Collection 004). The MODIS Level 2 data files were converted from Hierarchical Data Format (HDF) to granule tables (GRANT) format. The GRANT format provides the extracted Scientific Data Set (SDS) in ASCII table form where each pixel (x,y) is represented as a row of data with georeferencing information and each SDS is provided as a separate column in the table. The ASCII tables are in comma-delimited format.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789735221-ORNL_CLOUD.html",
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         "description": "The MODIS precipitable water product consists of vertical column water-vapor amounts in centimeters (cm) at 1 km spatial resolution. The SAFARI 2000 product, provided in flat binary data files, is a subset of the official MODIS Level 2 MOD05 product in EOS Hierarchical Data Format (HDF) format. Specifically, the SAFARI product contains data from daytime-only MODIS granules over southern Africa for the period August 21, 2000, through September 20, 2000. A granule is the data collected over the full MODIS swath in a five-minute period. Further, the SAFARI product contains values generated by the MODIS near-infrared algorithm applied over clear land areas only (determined via the QA bit field). All values were derived from MODIS on the morning-pass Terra satellite. The product is very sensitive to boundary-layer water vapor since it is derived from attenuation of reflected solar light from the surface. This data product is essential to understanding the hydrological cycle, aerosol properties, aerosol-cloud interactions, energy budget, and climate.The MOD05 water vapor data files were converted from their original HDF format to flat binary files for this SAFARI 2000 data set. The conversion was performed using code developed in the Interactive Data Language (IDL) Version 5.5. The following Scientific Data Sets (SDS) are provided in this data set: Latitude; Longitude; Sensor_Zenith; and Water_Vapor_Near_Infrared.",
         "license": "proprietary"
     },
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         "description": "This data set, ISLSCP II Snow-Free, Spatially Complete, 16 Day Albedo, 2002, contains 9 files for snow-free, spatially complete 16-day global black-sky albedos at local solar noon, white-sky albedos and quality information based on MODerate Resolution Imaging Spectroradiometer (MODIS) Collection 4 Albedo Products (MOD43B3). Data are provided for 7 spectral bands and 3 broad bands for a full year of MODIS data (2002). An ecosystem-dependent temporal interpolation technique was developed to fill any missing or seasonally snow-covered data in the official MOD43B3 albedo product. The resulting data set maintains the original resolution and data of the MOD43B3 product while replacing fill values to provide snow-free spatially complete maps.",
         "license": "proprietary"
     },
@@ -237115,7 +237401,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784882766-ORNL_CLOUD.html",
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         "description": "This International Satellite Land Surface Climatology Project (ISLSCP II)  MODerate resolution Image Spectroradiometer (MODIS) dataset, ISLSCP II MODIS (Collection 4) Albedo 2002, provides albedo data for the period January 2002 through December 2002.The MODIS bidirectional reflectance distribution function (BRDF) albedo product (MOD43B) provides measures of clear sky surface albedo every 16 days. Both white-sky albedo (bihemispherical reflectance) and black-sky albedo (directional hemispherical reflectance) at local solar noon are provided for 7 spectral bands and 3 broadbands. Since black-sky albedo represents the direct beam contribution while white-sky represents the completely diffuse contribution, these measures can be linearly combined as a function of the fraction of diffuse skylight (itself a function of optical depth) to provide an actual or instantaneous albedo at local solar noon.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2788368969-ORNL_CLOUD.html",
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         "description": "These data relate to a paper (Morisette et al., 2005) that describes the use of high spatial resolution ASTER data to determine the accuracy of the moderate resolution MODIS active fire product. Our main objective was to develop a methodology to use ASTER data for quantitative evaluation of the MODIS active fire product and to apply it to fires in Southern Africa during the 2001 burning season. We utilize 18 ASTER scenes distributed throughout Southern Africa covering the time period 5 August 2001 to 6 October 2001. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789734124-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789734124-ORNL_CLOUD.html",
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         "description": "The SAFARI 2000 project was selected as the first regional test for a prototype regional 500 m MODIS burned area product. The MODIS burned area product maps the 500 m location and approximate day of burning using a change detection algorithm based on a bi-directional reflectance model-based expectation method applied to the MODIS near-infrared and shortwave infrared bands (Roy et al., 2002). The algorithm was applied to recently reprocessed 500 m daily MODIS land surface reflectance data to produce burned area data sets for all of southern Africa for 2000 forward. This archived data set contains MODIS 500 m burned area products for two dry season months (July and September 2000).Burned area products are spatially explicit data sets that describe the approximate day of burning at 500 m resolution for all of southern Africa south of the Equator, including Madagascar. The burned area maps are compressed GeoTiff files. Several text files are included in the compressed files to aid ENVI (Research Systems, Inc.) users, including ENVI header files and ENVI density slice files. The data set also includes a projection parameters file.The MODIS burned area data set was validated using a methodology based upon the interpretation of multitemporal Landsat Enhanced Thematic Mapper plus (ETM+) data as described in Roy et al. (in press).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789043651-ORNL_CLOUD.html",
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         "description": "A physically-based model, Energy: Surface Towards Atmosphere (ESTA), was used to model and map the energy and water balances of a heterogeneous land surface in a savanna environment on the southern fringe of the Okavango Delta, near Maun, Botswana. ESTA is governed by remotely sensed values of surface temperature, reflection, and vegetation density. Surface reflectance data from the MODIS sensor aboard the Terra satellite were obtained for the Okavango Delta region for September of 2001.",
         "license": "proprietary"
     },
@@ -237167,7 +237453,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789103516-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789103516-ORNL_CLOUD.html",
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         "description": "The Filled Land Surface Albedo Product for Southern Africa, which is generated from MOD43B3 Product (the official Terra/MODIS-derived Land Surface Albedo - http://geography.bu.edu/brdf/userguide/albedo.html ), is a subset of the global data set of spatially complete albedo maps computed for both white-sky and black-sky at 10 wavelengths (0.47mm, 0.55mm, 0.67mm, 0.86mm, 1.24mm, 1.64mm, 2.1mm, and broadband 0.3-0.7mm, 0.3-5.0mm, and 0.7-5.0mm). An exception is that no 2.1mm data for black-sky is being archived at this time. The data spatial extent is from approximately 5 degrees N to -30 degrees S latitude and 5 minutes E to 60 degrees E longitude and covers 7 sixteen day periods starting on July 11 through October 15, 2000.Map Products, containing spatially complete land surface albedo data, are generated at 1-minute resolution on an equal-angle grid. The maps are stored in separate HDF files for each wavelength, each 16-day period and each albedo type (white- and black-sky). Data belonging to black sky and white sky albedo have been zipped separately. This format allows the user to have flexibility to download and store only the data absolutely needed.The One-Minute Land Ecosystem Classification Product is a global (static map) data set of the International Geosphere-Biosphere Programme (IGBP) classification scheme stored on an equal-angle rectangular grid at 1-minute resolution. The dataset is generated from the official MODIS land ecosystem classification dataset, MOD12Q1 for year 2000, day 289 data (October 15, 2000). This dataset is used in generating the spatially complete albedo maps, but is also a stand-alone product designed for use by the user community. The Land Ecosystem Classification Map File product file is stored in Hierarchical Data Format (HDF).",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784890070-ORNL_CLOUD.html",
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         "description": "This data set, ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000-2001, contains  global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).",
         "license": "proprietary"
     },
@@ -237219,7 +237505,7 @@
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         "description": "This data set contains daily rainfall totals (mm) from Mongu, in the Western Province of Zambia. The data were collected with a British standard 5 inch diameter rain gauge in a yard 30 m away from the Meteorological Department building near the Mongu Airport (north of downtown and approximately 20 km from the Kataba Local Forest where the permanent 30 m Mongu tower site is located). Rainfall readings were taken by ZMD staff each morning at 06:00 GMT. These data form the official government rainfall record for Mongu.The data files consist of 3 files, one for each year (July to Jun). Each files contains monthly columns with totals for each day of the month as well as a monthly total. The data files are stored as ASCII text files in comma-separated-value (csv) format.",
         "license": "proprietary"
     },
@@ -237232,7 +237518,7 @@
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         "description": "Data from the Tracing Architecture and Radiation of Canopies (TRAC) instrument were processed to determine the fraction of intercepted photosynthetically active radiation (FPAR) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 1999 and continued into 2002, with measurements collected about every month. TRAC contains three pyranometers sensitive to PAR wavelengths, with two sensors upward looking and one downward looking. The TRAC instrument was carried along three parallel transects, each 750 m long and spaced 250 m apart, about 0.7 m off the ground on clear days near midday. The sensors measured PAR at 32 Hz, resulting in a horizontal sampling interval of about 1.7 cm (Privette et al., 2002). Each transect was divided into 25 m segments, and Fpar values, with date/time stamp, are reported for each segment. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel.  PAR transmittance values were determined from the upward viewing pyranometers on the TRAC instrument. Due to the large gaps in the canopy, incident PAR was estimated from the TRAC data as 95% of the maximum PAR transmittance value for each transect. The FPAR values of all the observations were averaged to give segment-average FPAR, and segment average FPAR values were averaged to give transect-average FPAR.The data file is stored as an ASCII text file, in comma-separated-value (csv) format, with column headers.",
         "license": "proprietary"
     },
@@ -237245,7 +237531,7 @@
         "bbox": "22.03, -16.87, 24.28, -14.93",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789647857-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789647857-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIiwidW1tIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIn0%3D/mongu_irradiance_782_1",
         "description": "This data set contains the top-of-canopy irradiance in the shortwave (0.3-2.8 micron) and photosynthetically active radiation (PAR; 0.4-0.7 micron) wavebands collected with an Eppley Precision Spectral Pyranometer (PSP) and a Skye SKE510 pyranometer, respectively. The instruments were deployed at the top of the 30-m tower in the Kataba Local Forest approximately 20 km south of Mongu in Western Province, Zambia. The data include the hourly mean and maximum values from 0500-1600 GMT (7 a.m. - 6 p.m. local time) and cover the period from September 4, 2000 to December 31, 2002. The data were obtained primarily for EOS validation and energy budget modeling.The Skye SKE510 uses a blue enhanced planar diffused silicon detector and has a fairly even response from 400 to 700 nm. The Eppley PSP is a World Meteorological Organization First Class Radiometer designed for the measurement of sun and sky radiation, totally or in defined broad wavelength bands. It comprises a circular multi-junction wire-wound thermopile. A data logger sampled the sensors at 60-second intervals and recorded the maximum and mean values every 60 minutes throughout the day.The data are contained within a single ASCII text file, in comma-separated-value format, with associated date, time, and QA information.",
         "license": "proprietary"
     },
@@ -237258,7 +237544,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789643601-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789643601-ORNL_CLOUD.html",
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         "description": "Data from the LAI-2000 instrument were processed to determine the leaf area index (LAI) at the EOS Validation Core Site in Kataba Local Forest, approximately 20 km south of Mongu, Zambia. Measurements began in 2000 and continued into 2002, with measurements collected about every month throughout the growing season to examine the phenology of LAI for the site. The LAI-2000 measures the intensity of blue light in five upward-looking concentric conical rings. Measurements are made under the forest canopy and compared with open-sky measurements to determine transmittance for each of the five viewing angles. The sensor head was placed at ground level while the sensors measured light levels in conical scans. Effective leaf area was calculated from the transmittance in the different view angles based on the assumption of a random distribution of leaves (Welles and Norman, 1991).The LAI-2000 was carried along three parallel transects, each 750 m long and spaced 250 m apart. Each transect was divided into 25 m segments, and measurements were collected at the endpoints of each segment. Data from all transects were combined to provide site-average LAI for each sampling date. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel. Ground observations of LAI from this study compared with MODIS LAI products were found to be in close agreement.The data are stored in an ASCII text file, in comma-separated-value (csv) format, with column headers.",
         "license": "proprietary"
     },
@@ -237271,7 +237557,7 @@
         "bbox": "23.25, -25.02, 31.48, -15.44",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789725867-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789725867-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIiwidW1tIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIn0%3D/mongu_skukuza_albedo_786_1",
         "description": "Top-of-the-canopy broadband albedo and radiation fluxes are calculated from measurements at the Mongu and Skukuza flux tower sites in southern Africa from March 2000 through December 2002. Data were collected by instrumentation deployed at the top of the 30 m tower in the Kataba Local Forest near Mongu, Zambia, and atop the 20 m tower at the Skukuza tower site in Kruger National Park, South Africa.  At the Mongu site, Kipp and Zonen albedometers housing both upward- and downward-looking pyranometers were outfitted with clear and red domes to collect broadband albedo and radiation fluxes in the shortwave (SW) and near-infrared  (NIR) wavebands, respectively. The data are mean values provided at 15-minute intervals for 2000-2002. At the Skukuza tower, Kipp and Zonen albedometers (also outfitted with clear and red domes) collected broadband albedo and radiation fluxes in the SW and NIR wavebands. In addition, a pyrgeometer was used to collect longwave radiation flux in thermal infrared (TIR) wavebands. The data at Skukuza are mean values provided at 30-minute intervals for 2000-2002, except for the TIR data, which are provided for 2001 and 2002 only. For both sites, photosynthetically active radiation can be calculated from measurements.The data are provided in comma-delimited ASCII files, with column headers. The SW and NIR data for both sites are provided in one file per year per site for 2000-2002. The Skukuza longwave data are provided separately, and for years 2001 and 2002 only.",
         "license": "proprietary"
     },
@@ -237284,7 +237570,7 @@
         "bbox": "23.25, -25.02, 31.47, -15.44",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789728240-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789728240-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIiwidW1tIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIn0%3D/mongu_skukuza_soil_prop_789_1",
         "description": "Soil moisture and temperature profile sensors were deployed at flux tower sites in Mongu, Zambia and Skukuza, South Africa. In addition, thermal infrared sensors were deployed to monitor surface temperature at the sites, and soil samples were collected for physical property analysis. A heat-flux plate was also installed at 10 cm depth at the Mongu site. The data cover the period variously from August, 1999 to December, 2001.At the Mongu site, three profiles of soil moisture and temperature were obtained to a maximum depth of 125 cm. These profiles were located approximately 30 meters north of the Mongu flux tower, within the Kataba Local Forest. Surface radiometric temperature was measured by thermal infrared sensors deployed on top of the 30-meter tower and on a tree.  At the Skukuza site, two profiles of soil moisture and temperature were obtained to a maximum depth of 40 cm in a Combretum stand. The radiometric temperature of the tree crown and the background surface were monitored by infrared thermocouple sensors deployed on a pole at 2.5 m and 5 m heights. Soil samples were collected at different depths in the vicinity of the soil profiles at each site and were analyzed at CSIR in Pretoria to determine bulk density, texture, and particle size distribution. The data files are stored as ASCII text files, in comma-separated-value (.csv) format. Associated with each data file is a metadata (.txt ) file. Among other information, the metadata files indicate periods of missing data.",
         "license": "proprietary"
     },
@@ -237297,7 +237583,7 @@
         "bbox": "23.26, -15.45, 23.32, -15.19",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789727146-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789727146-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIiwidW1tIjoiW1wic2FmYXJpIDIwMDAgc2hhZG96IG96b25lc29uZGUgZGF0YSwgemFtYmlhIGFuZCByZWdpb25hbCBzaXRlcywgZHJ5IHNlYXNvbiAyMDAwXCIsXCJPUk5MX0NMT1VEXCIsXCJzaGFkb3pfb3pvbmVzb25kZV83MjZcIixcIjFcIiwyNzg5MDE2NjI5LDJdIn0%3D/mongu_tree_rings_788_1",
         "description": "This data set contains tree ring data from three sites located about 25 km of the meteorological station at Mongu, Zambia. Data from about 50 individual trees are reported. In addition, chronologies (or site mean curves) that better represent common influences (e.g., in this study, the climatic signal) were developed for each site based on the individual data (Trouet, 2004; Trouet et al., 2001). The series covers a maximum of 46 years, although most series do not extend longer than 30 years. The data were collected during the SAFARI 2000 Dry Season Field Campaign of August 2000.Ten to 23 samples were taken at each site. Brachystegia bakeriana was sampled at site 1, and Brachystegia spiciformis at sites 2 and 3. The vegetation at all sites underwent primitive harvesting for subsistence earlier the same year, thus samples could be taken from freshly cut trees and no living trees were cut. At all sites, samples consisted of full stem discs. Where possible, samples were taken at breast height (1.3 m) or slightly lower. Growth ring widths were measured to the nearest 0.01 mm using LINTAB equipment and TSAP software (Rinn and Jakel, 1997). Four radii per sample disc were measured. Cross-dating and response function analyses were performed by routine dendrochronological techniques. There are two files for each site, one containing integer values representing tree ring widths (raw data), and the other containing standardized values (chronologies), for each year. The data are stored as ASCII table files in comma-separated-value (.csv) format, with column headers. ",
         "license": "proprietary"
     },
@@ -237310,7 +237596,7 @@
         "bbox": "23.25, -15.44, 23.25, -15.44",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789733347-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789733347-ORNL_CLOUD.html",
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         "description": "Tree basal area, percent tree canopy cover, and proportional contribution of main species to canopy cover were measured at 60 sampling points at 50 m intervals along six transects in the vicinity of the MODIS validation site tower in Kataba Forest, near Mongu, Zambia, in late February to early March 2000 as part of the SAFARI 2000 Wet Season Campaign. The aim of the study was to provide a broad description of the tree canopy layer around the tower.Tree and shrub species composition was recorded for each grid and measurements of canopy cover (% and rank) and frequency of occurrence (%) were made. Basal area was estimated at each grid site in a single 360 degree sweep using a basal area prism. Four estimates of canopy cover, oriented north, south, east, and west around the sample point, were taken at each grid site using a spherical densiometer and the data were averaged to give a single value for each grid. Only the canopies of trees and shrubs above 1.5 m height were measured.The data are stored in an ASCII file, in csv format. The file lists all tree and shrub species recorded and provides the proportional contribution of these species to canopy cover in each grid. Total tree basal area (m2 ha-1) and overall tree canopy cover (%) in each grid is also provided. The companion file provides additional vegetation data, graphics, long-term meteorological data, a discussion of the study results, and photographs of the study site.",
         "license": "proprietary"
     },
@@ -238168,7 +238454,7 @@
         "bbox": "8, -35, 43, 0",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789726555-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789726555-ORNL_CLOUD.html",
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         "description": "The National Botanical Institute (NBI) has mapped woody plant species distribution to provide estimates of individual species contribution to peak leaf area index for designated vegetation types in southern Africa (Rutherford et al., 2000). The target was to account for 80% of the woody vegetation leaf area in terms of named species, for 80% of the surface area of Africa south of the equator. The data sources include published and unpublished species lists for vegetation types and individual sample plots, with the species contribution estimated by local experts in terms of dominants and subdominants. Source maps include: Low and Rebelo (1998); Giess (1971); Wild and Barbosa (1968); Barbosa (1970); and White (1983). Each source map delineates a wide variety of land cover categories that differ from region to region. Because vegetation discontinuities exist along some of the regional borders and a perfectly continuous regional map could not be achieved within the timeframe and budget of the project, the final map is made up of six independent sub-regional maps. A cross-referenced database of woody plant species, in order of species dominance, associated with all mapped units is provided.The data set contains six GIS shapefile archives, each containing a shape file for a given region in southern Africa on a 5 x 5 degree grid. An accompanying ASCII file contains the species list associated with the map files. The regional NBI Vegetation Map (a compilation of the 6 independent sub-regional coverages) is provided as a JPEG image.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785343626-ORNL_CLOUD.html",
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         "description": "This data set for the ISLSCP Initiative II data collection provides near surface meteorological variables, fluxes of heat, moisture and momentum at the surface, and land surface state variables, all with a spatial resolution of 1 degree in both latitude and longitude. There are four temporal categories of data: time invariant and monthly mean annual cycle fields (together referred to as \"fixed\" fields), monthly mean fields, monthly 3-hourly diurnal, and 3-hourly fields. Two types of variables exist in this data; instantaneous fields (primarily state variables), and average fields (primarily flux fields expressed as a rate). The Center for Ocean-Land Atmosphere Studies (COLA) near-surface data set for ISLSCP II was derived from the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Atmospheric Model Inter-comparison Project (AMIP-II) reanalysis (http://www.cpc.ncep.noaa.gov/products/wesley/reanalysis2/), covering the years from 1979-2003. The data set for ISLSCP II covers the period from 1986 to 1995. The purpose of the reanalysis was to provide an improved version of the original NCEP/National Center for Atmospheric Research (NCAR) reanalysis for General Circulation Model (GCM) validation. To co-register the NCEP/DOE reanalysis on the ISLSCP 1-degree grid, the reanalysis data set was regridded from its native T62 Gaussian grid) resolution (192 x 94 grid boxes globally) to 1-degree ISLSCP II required resolution.There are 136 compressed (.tar.gz) data files with this data set. When extrapolated, the individual data files are in ASCII (.asc) format.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779678769-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779678769-ORNL_CLOUD.html",
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         "description": "The variability of net surface carbon assimilation (Asmax), net ecosystem surface respiration (Rsmax), and net surface evapotranspiration (Etsmax) among and within vegetation types was examined based on a review of studies performed in either a micrometeorological setting or an enclosure setting.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776873201-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776873201-ORNL_CLOUD.html",
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         "description": "This data set contains data for wet and dry nitrogen-species deposition for the United States and Western Europe. Deposition data were acquired directly from monitoring programs in the United States and Europe for time periods from 1978-1994 for wet deposition and from 1989-1994 for dry deposition and evaluated using similar quality assurance criteria to ensure comparability. A standard geostatistical method (kriging) was used to interpolate data onto a 0.5 x 0.5 degree resolution map for wet and dry deposition.",
         "license": "proprietary"
     },
@@ -238415,7 +238701,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784885509-ORNL_CLOUD.html",
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         "description": "The objective of this work was to produce a monthly climatology of broadband surface albedos for use in global numerical weather prediction models at the National Centers for Environmental Prediction (NCEP). Monthly means of clear-sky, surface, broadband, snow-free albedos for overhead sun illumination angle were determined using data from a five-year period from April 1985-December 1987 and January 1989-March 1991. The data set is compatible in temporal coverage and spatial resolution with a monthly climatology of green vegetation fraction (Gutman and Ignatov, 1998) delivered earlier and currently in use at NCEP. Three zip files are provided at three spatial resolutions of quarter, half and on degree, each containing 12 data files in standard ESRI ArcGIS ArcInfo Grid format, and 12 data files in ASCII format denoting defifferences between the original data set and the ISLSCP II Land Sea Mask. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776933680-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776933680-ORNL_CLOUD.html",
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         "description": "This data set is a subset of Olson et al. (1985, 2000) \"Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation.\" This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., latitude 10 N to 25 S, longitude 30 to 85 W). The data are in ASCII GRID format.\"Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation\" is a computerized database used to generate a global vegetation map of 44 different land ecosystem complexes (mosaics of vegetation or landscapes) comprising seven broad groups. The map is derived from patterns of preagricultural vegetation, modern areal surveys, and intensive biomass data from research sites. Work on the database was begun in 1960 and completed in 1980.Ecosystem complexes are defined for each 0.5-degree grid cell, reflecting the major climatic, topographic, and land-use patterns. Numeric codes are assigned to each vegetation type. Classifications include natural as well as human managed/modified complexes such as mainly cropped, residential, commercial, and park. The complexes are ranked by estimated organic carbon in the mass of live plants given in units of kilograms of carbon per square meter. Counting the cells of each type and adding their areas give total area estimates for the ecosystem complexes. Multiplying by carbon estimates gives corresponding estimates of carbon by ecosystem complex with in the LBA study area. The results help define the role of the terrestrial biosphere in the global carbon cycle.Information about the ecosystem classifications, as well as the procedure used to create the LBA subset can be found at ftp://daac.ornl.gov/data/lba/carbon_dynamics/olson/comp/olson_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.Carbon in Live Vegetation is a computerized database, used to generate a global vegetation map of 44 different land ecosystem complexes (mosaics of vegetation or landscapes) comprising seven broad groups.",
         "license": "proprietary"
     },
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         "description": "A new method is used to generate spatial estimates of monthly averaged biomass burned area and spatial and temporal estimates of trace gas and aerosol emissions from open fires in southern Africa. Global burned area data for the year 2000 (GBA2000) supplemented with the Along Track Scanning Radiometer (ATSR) fire count data are employed to quantify the area burned at 1-km resolution by using a fractional vegetation cover map derived from satellite observations.",
         "license": "proprietary"
     },
@@ -238818,7 +239104,7 @@
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         "description": "Leaf Area Index (LAI) data from the scientific literature, covering the period from 1932-2000, have been compiled at the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) to support model development and validation for products from the MODerate Resolution Imaging Spectroradiometer (MODIS) instrument. There is one data file which consists of a spreadsheet table, together with a bibliography of more than 300 original-source references. Although the majority of measurements are from natural or semi-natural ecosystems, some LAI values have been included from crops (limited to a sub-set representing different crops at different stages of development under a range of treatments). Like Net Primary Productivity (NPP), Leaf Area Index (LAI) is a key parameter for global and regional models of biosphere/atmosphere exchange. Modeling and validation of coarse scale satellite measurements both require field measurements to constrain LAI values for different biomes (typical minimum, maximum values, phenology, etc.). Maximum values for point measurements are unlikely to be approached or exceeded by area-weighted LAI, which is what satellites and true spatial models are estimating.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789651811-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789651811-ORNL_CLOUD.html",
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         "description": "This data set contains measurements of the concentration and stable carbon (13C/12C) and nitrogen (15N/14N) isotope ratios of plant (leaves, roots and fungi) and soil samples from southern Africa. The study sites in Zambia, Botswana, Namibia, and South Africa are located along the Kalahari Transect precipitation gradient. Some of the sites were relatively undisturbed while others had different intensities of cultivation, domestic grazing, and fires. The data were collected to detect patterns of N cycling along precipitation and grazing gradients, including N2 fixation by legumes. Data from different multiple projects are included. The plants and soils were sampled mainly in the wet season of years 1995, 1999, and 2000, with most of the data collected during the SAFARI 2000 Kalahari Wet Season Field Campaign in February and March of 2000. Some grass samples were collected in the dry season of year 2000 (from Mongu-dambo and Sua Pan grassland sites). Soil and plant samples were analyzed in a laboratory for %C, %N, d13C, and d15N with an Optima isotope ratio mass spectrometer coupled to an elemental analyzer. The stable isotope ratios are expressed using standard delta notation in units per mil. The isotope ratios are expressed relative to the international standard PDB (Pee Dee Belemnite) for carbon and atmospheric N2 for nitrogen samples. The carbon and nitrogen contents are expressed in percentage weight of the dry sample.The data files contain numerical and character fields of varying length separated by commas (.csv format).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2776829507-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2776829507-ORNL_CLOUD.html",
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         "description": "Study plot canopy chemistry values were calculated from leaf chemistry and litterfall weight values. Average leaf concentrations of nitrogen and carbon were used to investigate how reflectance varies with chemistry.  ",
         "license": "proprietary"
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         "description": "AVIRIS image scenes were acquired in 1992 over ACCP sites. Pixels that coincided with field study plots were extracted and reflectance values were correlated  with estimated canopy carbon and nitrogen content.",
         "license": "proprietary"
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         "description": "PnET (Photosynthetic / EvapoTranspiration model) is a nested series of models of carbon, water, and nitrogen dynamics in forest ecosystems. The models can be used to predict transient responses in net primary production (NPP), carbon and water balances, net nitrogen (N) mineralization and nitrification and N leaching losses, resulting from changes in climate, N deposition, tropospheric ozone and land use as well as variation in species composition. The models have been developed and validated in the Northeastern U.S. at both the site and grid level (to 1-km resolution) at the Complex Systems Research Center, University of New Hampshire, by John Aber and colleagues.",
         "license": "proprietary"
     },
@@ -239312,7 +239598,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2956545421-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2956545421-ORNL_CLOUD.html",
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         "description": "This archived model product contains the directions, executables, and procedures for running PnET-BGC to recreate the results of: Gbondo-Tugbawa, S.S., C.T. Driscoll , J.D. Aber and G.E. Likens. 2001. The evaluation of an integrated biogeochemical model (PnET-BGC) at a northern hardwood forest ecosystem. Water Resources Research 37:1057-1070Gbondo-Tugbawa et al,. 2001 Excerpt from Abstract: An integrated biogeochemical model (PnET-BGC) was formulated to simulate chemical transformations of vegetation, soil, and drainage water in northern forest ecosystems. The model operates on a monthly time step and depicts the major biogeochemical processes, such as forest canopy element transformations, hydrology, soil organic matter dynamics, nitrogen cycling, geochemical weathering, and chemical equilibrium reactions involving solid and solution phases. The model was evaluated against soil and stream data at the Hubbard Brook Experimental Forest, New Hampshire. Model predictions of concentrations and fluxes of major elements generally agreed reasonably well with measured values, as estimated by normalized mean error and normalized mean absolute error. Model output of soil base saturation and stream acid neutralizing capacity were sensitive to parameter values of soil partial pressure of carbon dioxide, soil mass, soil cation exchange capacity, and soil selectivity coefficients of calcium and aluminum. PnET-BGC can be used as a tool to evaluate the response of soil and water chemistry of forest ecosystems to disturbances such as clear-cutting, climatic events, and atmospheric deposition.PnET-BGC, was used to investigate inputs and dynamics of S in a northern hardwood forest at the Hubbard Brook Experimental Forest (HBEF) (Gbondo-Tugbawa et al., 2002). The changes in soil S pools and stream-water were simulated to assess the response 22 SO4 to both atmospheric S deposition and forest clear-cutting disturbances. Watershed studies across the northeastern United States have shown that stream losses of exceed atmospheric sulfur (S) deposition. Understanding the processes responsible for this additional source of S is critical to quantifying ecosystem response to ongoing and potential future controls on SO2 emission.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784887174-ORNL_CLOUD.html",
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         "description": "This data set was developed to describe the state of the global land cover in terms of 15 major vegetation types, plus water, before alteration by humans. It forms a complement to the historical croplands data set developed by Ramankutty and Foley (1999). By overlaying the two, one can determine the extent to which natural vegetation has been cleared for cultivation. This data set can be used directly within spatially-explicit climate and biogeochemical models. There are four total files in this data set. Two files contain the land cover types representing potential natural vegetation before human alteration, and two other files contain those points in the original data set submitted by the Principal Investigator that have been modified in order to match the land/water mask of the ISLSCP Initiative II.The geographic distribution of contemporary land cover types can be derived from remotely-sensed data. However, humans now dominate much of the world and there is little evidence of the pre-human-settlement natural vegetation or Potential Natural Vegetation (PNV). PNV, as defined here, does not necessarily represent the world's natural pre-human-disturbance vegetation. Rather, our definition of PNV represents the world's vegetation cover that would most likely exist now in equilibrium with present-day climate and natural disturbance, in the absence of human activities.",
         "license": "proprietary"
     },
@@ -239390,7 +239676,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777327573-ORNL_CLOUD.html",
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         "description": "The data set consists of a subset for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., longitude 85 deg to 30 deg W, latitude 25 deg S to 10 deg N) of the 5-min resolution Global Potential Vegetation data set developed by Navin Ramankutty and Jon Foley at the University of Wisconsin. Data are available in both ASCII GRID and binary image file formats.The original map was derived at a 5-min resolution and contains natural vegetation classified into 15 types.",
         "license": "proprietary"
     },
@@ -239403,7 +239689,7 @@
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         "description": "The main goal of this study was to analyze the possibility of estimating combustion completeness based on fire-induced spectral reflectance changes of surface features by the development of relationships between combustion completeness and pre-fire to post-fire spectral reflectance changes, in the green, red, and near-infrared spectral domains (equivalent to Landsat ETM+ channels 2, 3, and 4).",
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         "description": "Contains 15 minute surface meteorology data collected during the 1994 field campaigns by the Atmospheric Environment Service Remote Environmental Automatic Data Acquisition Concept (READAC) autostations.",
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         "description": "The River Carbon Flux data set represents estimates for the riverine export of carbon and of sediments. This data set includes the amounts of carbon and of sediments that are discharged to the oceans by rivers for each coastal grid point which receives river inputs. This data set contains three compressed (*.zip) files: the original data at 2.5 x 2.0 degrees, and global maps at spatial resolutions of 0.5 and 1.0 degree which the ISLSCP II staff has created from the original data. ",
         "license": "proprietary"
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         "description": "The Simulated Topological Network (STN-30p) data set provides the large-scale hydrological modeling community an accurate representation of the global river system at 0.5 degree and 1.0 degree spatial resolutions. STN-30p represents the potential connectivity of the continental land mass by assigning one of eight (E, SE, S, SW, W, NW, N, NE) possible flow directions to each continental grid cell (Jenson 1988, Band 1993). The potentiality of STN-30p reflects the fact that flow direction is assigned to every land cell regardless of the existence of actively flowing rivers. STN-30p can be viewed as a river network which would exist if sufficient surface runoff was available to form river channels everywhere. There are two data files with this data set.",
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         "description": "This data set of state and regional boundaries was derived from the 1:3 million scale administrative boundaries (ESRI, 1998) for the land area of the Former Soviet Union. There are 162 administrative regions distinguished in this data set.  The vector map of state and regional boundaries for the FSU is in ArcView shapefile format.",
         "license": "proprietary"
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         "description": "This data set is made up of images of forest fires in Russia from NOAA's Operational Significant Event Imagery (OSEI) archive (http://www.osei.noaa.gov) for the 1998 and 1999 seasons. OSEI fire products include multichannel color composite imagery of wildfire and controlled burn events. Products in this event group show fire, smoke, and hotspots (FSMHS) from the fires.",
         "license": "proprietary"
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@@ -240261,7 +240547,7 @@
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         "description": "This dataset is derived from Russian forest fire imagery from the National Forest Fire Center of Russia archive that was collected by the Center of Remote Sensing, Institute of Solar Terrestrial Physics, Irkutsk, Russia for the 1998 and 1999 fire seasons. The data are vector (point) maps of forest fire locations (1998 and 1999) in ArcView shapefile format.",
         "license": "proprietary"
     },
@@ -240274,7 +240560,7 @@
         "bbox": "19.82, 35.17, 170, 75",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671753-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671753-ORNL_CLOUD.html",
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         "description": "This dataset is a 1:15 million scale map of forest stand carbon for the land area of Russia (Stone et al., 2000). The objective was to create a first approximation of the forest stand carbon reserves of Russia. Data include continuous estimates of forest stand carbon in units of metric tons/ha of carbon (C) and categorized data depicting rages of forest stand carbon. The resulting maps show forest stand C by region in a spatially explicit form. It is the first map of its type for Russia of which we are aware. The mapped C represents 96% of the total of 26.1 Pg forest tree stand C described by Alexeyev and Birdsey (1994) and Alexeyev et al. (1995). Of the remaining 4%, nearly half was due to bushes, which were assumed not to be mapped in the 1973 forest cover map.The source data for the forest stand carbon map were acquired by map digitization from the Atlas of Forests for the Soviet Union (State Committee on Forests, 1973) and spatial application and arithmetic manipulation of carbon storage data from Alexeyev and Birdsey (1998).",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671352-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671352-ORNL_CLOUD.html",
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         "description": "This data set is a 1:15 million scale forest cover map for the land area of the Former Soviet Union. Twenty-two land cover classes are distinguished, of which 20 are forest cover classes. The source data were acquired by map digitization from the Atlas of Forests of the USSR (Anon. 1973) which was likely based on forestry data from the 1940s, 1950s and 1960s.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671301-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671301-ORNL_CLOUD.html",
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         "description": "This data set is a 1:2.5 million scale forest cover map for the land area of the Former Soviet Union that was completed in 1990 (Garsia 1990). There are forty-five classes distinguished in this data set, of which 38 are forest cover classes. The purpose of this map was to create a generalized and up-to-date map of forest cover for the USSR. This map should not be viewed as a detailed forest cover map but more like an economic forestry map. The most important tree species of a region are highlighted rather than the dominant trees species or tree cover. Very few tree species are defined. In many cases, of course, the dominant and the most important trees species are the same. ",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671459-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671459-ORNL_CLOUD.html",
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         "description": "This dataset is a 1:2 million scale forest cover map for the land area of the Krasnoyarsk Region, Russia. Thirty-two land cover classes are distinguished. These data were digitized from maps of the Atlas of Forests of the USSR (Anon. 1973). This map should not be strictly viewed as a map of actual forest cover, but rather as a map of dominant tree species. Very few tree species are defined, and generally, each polygon and color has only one tree species assigned to it.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810670679-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810670679-ORNL_CLOUD.html",
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         "description": "This dataset is a 15-kilometer resolution land cover map for the land area of the Former Soviet Union. There are sixty land cover classes distinguished in this dataset, of which 38 are forest cover classes.  The data set is useful for stratification of the FSU into general sub-regions of land cover for subsequent study using higher resolution satellite data.",
         "license": "proprietary"
     },
@@ -240339,7 +240625,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810670893-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810670893-ORNL_CLOUD.html",
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         "description": "This data set is a 1-kilometer resolution land cover map for the land area of the Primor'ye and Southern Khabarovsk Regions, in the Russian Far East, based on 1990 NOAA AVHRR data. Labeling of land cover classes depended upon the Russian 1990 Forest Cover Map (Garsia, 1990), the analyst's experience with AVHRR data, and Russian data sources. There are eight classes distinguished in this dataset, of which 5 are forest cover classes.The objective of this work was to create a 1-km resolution land cover map of the region of the Far Eastern Siberia based on NOAA AVHRR data which might be used by World Wildlife Fund researchers to aid in the definition of remaining habitats and range for threatened animal species (Stone  and Schlesinger, 1996).",
         "license": "proprietary"
     },
@@ -240352,7 +240638,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810672079-ORNL_CLOUD.html",
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         "description": "This data set consists of roads, drainage, railroads, utilities, and population center information in readily usable vector format for the land area of the Former Soviet Union. The purpose of this dataset was to create a completely intact vector layer which could be readily used to aid in mapping efforts for the area of the FSU. These five vector data layers were assembled from the Digital Chart of the World (DCW), 1993. Individual record attributes were stored for population centers only. Vector maps for the FSU are in ArcView shapefile format.",
         "license": "proprietary"
     },
@@ -240365,7 +240651,7 @@
         "bbox": "19.82, 35.17, 170, 75",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810672200-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810672200-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wicmVtb3RlIHNlbnNpbmcgZGVyaXZlZCB0b3Bzb2lsIGFuZCBhZ3JpY3VsdHVyYWwgZWNvbm9taWMgbG9zc2VzLCBtaWR3ZXN0ZXJuIHVzYVwiLFwiT1JOTF9DTE9VRFwiLFwiVG9wU29pbF9Fcm9zaW9uX01pZFdlc3RfVVNfMTc3NFwiLFwiMVwiLDIyMTY4NjQzNTMsNl0iLCJ1bW0iOiJbXCJyZW1vdGUgc2Vuc2luZyBkZXJpdmVkIHRvcHNvaWwgYW5kIGFncmljdWx0dXJhbCBlY29ub21pYyBsb3NzZXMsIG1pZHdlc3Rlcm4gdXNhXCIsXCJPUk5MX0NMT1VEXCIsXCJUb3BTb2lsX0Vyb3Npb25fTWlkV2VzdF9VU18xNzc0XCIsXCIxXCIsMjIxNjg2NDM1Myw2XSJ9/rlc_vegetation_1990_700_1",
         "description": "This dataset is a 1:4 million scale vegetation map for the land area of the Former Soviet Union. Three hundred seventy-three cover classes are distinguished, of which nearly 145 are forest cover-related classes. Stone and Schlesinger (1993) digitized the map Vegetation of the Soviet Union, 1990 (Institute of Geography, 1990). ",
         "license": "proprietary"
     },
@@ -240378,7 +240664,7 @@
         "bbox": "25, 23.21, 180, 71",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671823-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2810671823-ORNL_CLOUD.html",
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         "description": "This data set is the Former Soviet Union (FSU) portion of the Generalized World Forest Map (WCMC, 1998), a 1-kilometer resolution generalized forest cover map for the land area of the Former Soviet Union. There are five forest classes in the original global generalized map. Only two of those classes were distinguished in the geographical portion comprising the FSU.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808094112-ORNL_CLOUD.html",
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         "description": "A global data set of root biomass, rooting profiles, and concentrations nutrients in roots was compiled from the primary literature and used to study distributions of root properties. This data set consists of estimates of fine root biomass and specific area, site characteristics. This data set provides analysis of rooting patterns for terrestrial biomes and compare distributions for various plant functional groups.",
         "license": "proprietary"
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         "description": "Nutrient measurements for fine roots were compiled from 56 published studies providing information on 372 different combinations of species, root diameter, rooting depths, and soils at a variety of locations. The compilation was used to examine dynamics of 14 nutrients, including translocation properties of roots of varying size and status.",
         "license": "proprietary"
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         "description": "Rooting depths were estimated from a global database of root profiles assembled from the primary literature to study relationships of abiotic and biotic factors associated with belowground vegetation structure. For each root profile, information recorded includes latitude and longitude, elevation, soil texture, depth of organic horizons, type of roots measured (e.g., fine or total, live or dead), sampling methods, units of measurements (root mass, length, number, surface area), and sampling depth.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2761764652-ORNL_CLOUD.html",
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         "description": "Estimates of root turnover rates were calculated from measurements of live root standing crop and belowground net primary production (BNPP) compiled from the primary literature.  Vegetation characteristics, soil properties, and climate conditions were associated with turnover rates to examine patterns and controls for biomes worldwide.",
         "license": "proprietary"
     },
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         "description": "This data set provides two estimates of the geographic distribution of the total plant-available soil water storage capacity of the rooting zone (\"rooting zone water storage size\") on a 1.0 degree global grid. Two inverse modeling methods were used. The first modeling approach (optimization) was based on the assumption that vegetation has adapted to the environment such that it makes optimum use of water (Kleidon and Heimann 1998). The second method (assimilation) was based on the assumption that green vegetation indicates sufficient available water for transpiration (Knorr 1997). The data set was developed to provide alternative means to describe rooting characteristics of the global vegetation cover for land surface and climate models in support of the ISLSCP Initiative II data collection. There are three files in this data set. ",
         "license": "proprietary"
     },
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         "description": "SAFARI Subset - GRIDDED SURFACES of SELECTED SOIL CHARACTERISTICS (IGBP-DIS). The data-surfaces pre-generated by SoilData, at a resolution fo 5x5 arc-minutes, in ASCII GRID format for ARC INFO and for the soil depth interval 0-100 cm.",
         "license": "proprietary"
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@@ -241262,7 +241548,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2796831191-ORNL_CLOUD.html",
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         "description": "The data set consists of a southern African subset of the ISRIC-WISE global data set of derived soil properties. The World Inventory of Soil Emission Potentials (WISE) database currently contains data for over 4300 soil profiles collected mostly between 1950 and 1995.",
         "license": "proprietary"
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@@ -241275,7 +241561,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804825455-ORNL_CLOUD.html",
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         "description": "This is a southern African subset of the ISRIC-WISE International soil profile data set.",
         "license": "proprietary"
     },
@@ -241288,7 +241574,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798127-ORNL_CLOUD.html",
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         "description": "The UMD 1-degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD.  The product is based on Advanced Very High Resolution Radiometer (AVHRR) maximum monthly composites for 1987 of Normalized Difference Vegetation Index (NDVI) values at approximately 8-km resolution, averaged to one-by-one degree resolution. This coarse-resolution data set was used as the basis for a supervised classification of eleven cover types that broadly represent the major biomes of the world.",
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         "description": "This data set consists of a southern African subset of the University of Maryland (UMD) 8-km Global Land Cover product in ASCII GRID and binary image files formats.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804800609-ORNL_CLOUD.html",
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         "description": "This data set is a subset of Olson's Major World Ecosystem Complexes for southern Africa in ASCII GRID and binary image file formats. Olson's Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation is a computerized database, used to generate a global vegetation map of 44 different land ecosystem complexes (mosaics of vegetation or landscapes) comprising seven broad groups.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804802625-ORNL_CLOUD.html",
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         "description": "This data set consists of a southern African subset of the 5-min resolution Global Potential Vegetation data set developed by Navin Ramankutty and Jon Foley at the University of Wisconsin. Data are available in both ASCII GRID and binary image file formats.",
         "license": "proprietary"
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         "description": "The data set provides estimated monthly and annual soil CO2 emissions for southern Africa (the SAFARI 2000 project region). The calculated emissions are from the respiration of both soil organisms and plant roots and are provided on a 0.5-degree grid cell basis. The data are a subset of a global data set (Raich and Potter, CDIAC 1996), reformatted and subsetted to the SAFARI region.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804801359-ORNL_CLOUD.html",
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         "description": "This data set consists of a southern Africa subset of the Global Distribution of Freshwater Wetlands database 1-degree data and is available in ASCII GRID and binary image file formats.",
         "license": "proprietary"
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         "description": "This data set contains a subset of the Worldwide Organic Soil Carbon and Nitrogen (Zinke et al. 1986) data set for southern Africa. The data were obtained from soil surveys by Zinke and soil survey literature. The main samples for laboratory analyses were collected at uniform soil increments and included bulk density determinations.&",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777328159-ORNL_CLOUD.html",
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         "description": "This data set is a subset of a global river discharge data set by Coe and Olejniczak (1999). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W).The global river discharge data set (Coe and Olejniczak 1999), formerly known as the \"Climate, People, and Environment Program (CPEP) Global River Discharge Database,\" is a compilation of monthly mean discharge data for more than 2600 sites worldwide. The data were compiled from RivDIS Version 1.1 (Vorosmarty et al. 1998), the U.S. Geological Survey, and the Brazilian National Department of Water and Electrical Energy. The period of record for the sites varies from 3 years to greater than 100.The purpose of the global compilation is to provide detailed hydrographic information for the climate research community in as general a format as possible. Data are given in units of meters cubed per second (m**3/sec) and are in ASCII format. Data from stations that had less than 3 years of information or that had a basin area less than 5000 square kilometers were excluded from the global data set. Thus, the data sources may include more sites than the data set by Coe and Olejniczak (1999). Users should refer to the data originators for further documentation on the source data.More information, a map of discharge sites, and a clickable site data table can be found at ftp://daac.ornl.gov/data/lba/surf_hydro_and_water_chem/sage/comp/sagedischarge_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. Further information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
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         "description": "Contains the data collected in 1994 by the AMS suite A instrument set operated by SRC and provided to BORIS.",
         "license": "proprietary"
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@@ -241522,7 +241808,7 @@
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         "description": "Contains the data collected in 1995 by the AMS suite A instrument set operated by SRC and provided to BORIS.",
         "license": "proprietary"
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         "description": "Contains the data collected in 1996 by the AMS suite A instrument set operated by SRC and provided to BORIS.  ",
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         "description": "Contains the data collected in 1996 by the AMS suite B instrument set operated by SRC and provided to BORIS.",
         "license": "proprietary"
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         "description": "This data set provides Synthetic Aperture Radar (SAR) images for 42 selected sites from various terrestrial ecology and meteorological monitoring networks including FLUXNET, Ameriflux, Long Term Ecological Research (LTER), and the Greenland Climate Network (GC-Net).The data set contains at least one image for all 42 sites, and six sites have multiple images. See Table 1 for the sites and the temporal range of the available images. The scenes are in GeoTIFF format in Universal Transverse Mercator (UTM), WGS-84 projection, and 15-meter resolution.The SAR images are subset scenes of approximately 60 km x 70 km that include an established site in one of the monitoring networks. The spatial resolution of all scenes is 15 meters. These scenes are distributed as geotif files with appropriate projection information defined within the file.The acquisition mode for all data is the Fine Beam Double Polarization or FBD with the HH/HV polarization. The HH and HV channels are distributed as 3 channels to allow for an intuitive image display. The HH band is displayed in the red and blue channels and the HV band is displayed in the green channel. For some images only single polarization is available; these images are distributed as grayscale images.The source of the data is the PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor flying on the Advanced Land Observing Satellite (ALOS). The PALSAR data are in dual Polarization, HH+HV, mode. Bands HH (red and blue) and Band-HV (green) can be used to visualize land use patterns. The resulting images show vegetation in shades of green and barren land in shades of pink or purple.",
         "license": "proprietary"
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         "description": "A condensed forest cover type digital map of Saskatchewan and is a product of the Saskatchewan Environment and Resource Management, Forestry Branch-Inventory Unit (SERM-FBIU).  Map was generalized from SERM township maps of vegetation cover at an approximate scale of 1:63,000 (1 in. = 1 mile).  The cover information was iteratively generalized until it was compiled on a 1:1,000,000 scale map base.",
         "license": "proprietary"
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         "description": "Series of ARC/INFO export files of the fire history of Saskatchewan by year from 1945 to 1996, with a few missing years.",
         "license": "proprietary"
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         "description": "This International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data set, ISLSCP II Global Sea Ice Concentration, is based on the Goddard Space Flight Center (GSFC) Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellites Program (DMSP) Special Sensor Microwave/Imager (SSM/I) Passive Microwave Data. This data set contains four zip files which includes sea ice concentration (in percentage of ocean area covered by sea ice), table data and map data.  These original data were re-gridded by the National Snow and Ice Data Center (NSIDC) from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter, half and one degree spatial resolutions in latitude/longitude. The ISLSCP II staff have taken the one degree resolution original data provided by the Principal Investigator and created global maps of monthly sea ice concentration on a global one degree grid using the latitude and longitude coordinates that were provided. Individual monthly files were created and written to the ASCII format. The re-gridded one degree original data were also adjusted to match the one degree ISLSCP II land/water mask. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784895830-ORNL_CLOUD.html",
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         "description": "Sea surface temperature (SST) is an important indicator of the state of the earth climate system as well as a key variable in the coupling between the atmosphere and the ocean. Accurate knowledge of SST is essential for climate monitoring, prediction and research. It is also a key surface boundary condition for numerical weather prediction and for other atmospheric simulations using atmospheric general circulation models and regional models. SST also is important in gas exchange between the ocean and atmosphere, including the air-sea flux of carbon. Gridded SST products have been developed to satisfy these needs. There are 3 .zip files provided with this data set.Gridded monthly and weekly sea surface temperature (SST) and long term SST monthly climatology for the period 1971-2000 are provided here. Weekly normalized error variance fields are also provided with the weekly data. The data are derived using the National Oceanic and Atmospheric Administration (NOAA) Optimum Interpolation (OI) global sea surface temperature analyses that use seven days of in situ (ship and buoy) and satellite SST observations and SST values derived from sea ice concentration. These analyses are produced weekly using optimum interpolation (OI) on a 1-degree grid. The data sets included in the ISLSCP II data collection are produced using version 2 of the OI analyses, called OIv2. In this data set, the ISLSCP II staff have masked land areas based on the ISLSCP II land/water mask. A file describing the differences between the ISLSCP II mask and the original mask used is provided.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804816085-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804816085-ORNL_CLOUD.html",
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         "description": "This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the eight core study sites of Mongu, Etosha, Kasangu, Skukuza, Mutoko, Mzola, Nampula, and Ndola. There are two main sets of local area coverage (LAC) data: Level-1 and Level-2 200-km x 200-km image subsets for seven of the sites and 400-km x 400-km image subsets for the Etosha site. The data are provided in HDF format files.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804817543-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804817543-ORNL_CLOUD.html",
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         "description": "This data set contains Sea-viewing Wide Field-of-view Sensor (SeaWiFS) imagery for the southern African region. These images are Level-1a swaths of the southern African region selected from global area coverage (GAC) at 4.5-km resolution. The data are provided in HDF format files.",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789016629-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789016629-ORNL_CLOUD.html",
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         "description": "Ozonesonde launches were made by the Southern Hemisphere ADditional OZonesondes (SHADOZ) group as part of the SAFARI 2000 Dry Season Campaign in September 2000 (Thompson et al., 2002). Ozonesondes are balloon-borne instruments measuring profile ozone, as well as temperature and pressure from an attached radiosonde, up to 35 km in height (around 5 hPa in pressure coordinates) capturing the troposphere and lower stratospheric portion of the atmosphere. During the campaign, ozonesondes were launched daily during the height of the burning season and in a region of active biomass burning activity.",
         "license": "proprietary"
     },
@@ -242445,7 +242731,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789018469-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789018469-ORNL_CLOUD.html",
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         "description": "Surface-sensing Measurements for Radiative Transfer (SMART) and Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) consist of a suite of instruments that measure (both in-situ and by remote sensing) parameters that help to characterize, as completely as possible, constituents of the atmosphere at a given location. SMART and COMMIT are mobile systems that can be deployed to locations that exhibit interesting atmospheric phenomena. This allows investigators to participate in coordinated measurement campaigns, such as SAFARI 2000.The SMART instruments were deployed to the Skukuza Airport from August 15 to September 17, 2000 to take part in the SAFARI 2000 Dry Season Aircraft Campaign. The SMART-COMMIT mission is designed to pursue the following goals: Earth Observing System (EOS) validation; innovative investigations; and long-term atmospheric monitoring. The results reported in this data set are for the following instruments deployed and measurements recorded at the Skukuza Airport site within the Kruger National Park: several broadband radiometers, for global, diffuse, direct downward solar irradiance and global infrared downward irradiance; meteorological sensors, for surface air temperature, pressure, relative humidity, and wind; and a Solar Spectral Flux Radiometer (NASA Ames) for spectral solar downward irradiance.",
         "license": "proprietary"
     },
@@ -242640,7 +242926,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784896919-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784896919-ORNL_CLOUD.html",
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         "description": "This ISLSCP data set is derived from the National Snow and Ice Data Center (NSIDC) Northern Hemisphere EASE-Grid Weekly Snow Cover and Sea Ice Extent product which combines snow cover and sea ice extent at weekly intervals for October 1978 through June 2001, and snow cover alone from 1966 through June 2001. The original data set was the first representation of combined snow and sea ice measurements derived from satellite observations for the period of record. Designed to facilitate study of Northern Hemisphere seasonal fluctuations of snow cover and sea ice extent, the original NSIDC data set also includes monthly climatologies describing average extent, probability of occurrence, and variance.This data set shows the extent of snow on the land at a variety of scales (1.0 degree, 0.5 degree, 0.25 degree). The values represent the percentage of days in each month where snow was present -- 100 means 100% of the month, 80 means 80% of the month, etc. There are 4 .zip files provided. Missing data is represented by -99 for water and -88 for land. The data were originally in a yearly tabular format. The file was converted to multi-scale maps by plotting each point in the tabular data onto a map of -99 (water) and -88 (land) created from the standard ISLSCP II Land/Sea Mask. ",
         "license": "proprietary"
     },
@@ -242653,7 +242939,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2784881406-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784881406-ORNL_CLOUD.html",
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         "description": "This data set contains monthly average snow-free surface shortwave albedo calculated for the period 1982-1998 and estimates of background soil/litter reflectances in the visible (0.4-0.7 mm) and near-infrared (NIR) (0.7-1.0 mm) wavelengths. Biophysical Parameters derived from the FASIR-NDVI (Fourier Adjusted, Solar zenith angle correction, Interpolation, and Reconstruction of Normalized Difference Vegetation Index) data set developed for the ISLSCP Initiative II data collection for the months of January 1982 through December 1998 were used to calculate monthly mean surface albedos at 1 X 1 degree spatial resolution for vegetated land surfaces (Sellers et al, 1996b) for the wavelength interval from 0.4 to 3.0 mm. The instantaneous albedo is a function of the properties of the land surface and the solar zenith angle. The monthly mean albedo is an average weighted over time weighted by the incident radiation. NDVI data are used to generate the biophysical parameters leaf area index (LAI) and green fraction of vegetation (Greenness) used by the canopy radiative transfer model of the Simple Biosphere (SiB2) model (Sellers et al, 1996a), which computes the instantaneous albedo. This is coupled to the Colorado State University (CSU) General Circulation Model (GCM) (Randall et al, 1989) which integrates the SiB2 radiative transfer through time. The incident radiation for weighting the time-averaged albedo was provided by a previous run of the GCM using the atmospheric radiation parameterization of Harshvardhan et al (1987). The Harshvardhan parameterization models radiative transfer through the atmosphere in both the longwave and shortwave bands, including the effects of cloudiness and water vapor, carbon dioxide and ozone. The shortwave radiation distinguishes between the direct and diffuse components of the solar beam.",
         "license": "proprietary"
     },
@@ -242783,7 +243069,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2807648392-ORNL_CLOUD.umm_json",
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         "license": "proprietary"
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         "description": "This data set is a compilation of soil respiration rates (g C m-2 yr-1) from terrestrial and wetland ecosystems reported in the literature prior to 1992 subset for the Safari 2000 project. These rates were measured in a variety of ecosystems to examine rates of microbial activity, nutrient turnover, carbon cycling, root dynamics, and a variety of other soil processes.",
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         "description": "Gridded from vector layers of soil maps received from Dr. Hugo Veldhuis, who did the original mapping in the field during 1994.The vector layers were gridded into raster files that cover the NSA-MSA and tower sites.",
         "license": "proprietary"
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         "description": "Vector layers of soil maps. The vector layers were converted to ARC/INFO EXPORT files.  These data cover 1-km diameters around each of the NSA tower sites and another layer covers the NSA-MSA.",
         "license": "proprietary"
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         "description": "Gridded from vector layers of soil maps that were received from Dr. Darwin Anderson TE-01, who did the original soil mapping in the field during 1994. The vector layers were gridded into raster files that cover approximately 1 square kilometer over each of the SSA tower sites.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777324266-ORNL_CLOUD.html",
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         "description": "This data set consists of a subset of a 1-degree gridded global freshwater wetlands database (Stillwell-Soller et al. 1995). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format.The global freshwater wetlands database was assembled from two data sets: Aselman and Crutzen's (1989) wetlands data set and Klinger's political Alaska data set (pers. comm. to L. M. Stillwell-Soller, 1995). The aim of Stillwell-Soller's global data set was to provide an accurate, comprehensive and uniform set of files for convenient specification of wetlands in global climate models. The main source of data was Aselman and Crutzen's global maps of percent cover for a variety of wetlands categories at 2.5-degree latitude by 5-degree longitude resolution. There was some reorganization for seasonally varying categories. Aselman and Crutzen's data were interpolated to a standard 1-degree by 1-degree grid through bilinear interpolation. Their data were geographically complete except for the Alaskan region, for which Klinger's data set provided values.More information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/soller_wetlands/comp/soller_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
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         "description": "The variability of bi-directional spectral reflectance of cut conifer foliage between age classes, species and sites, measured by LICOR",
         "license": "proprietary"
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         "description": "Absolute (diffuse & specular) reflectance of leaves measured in the lab by Perkin-Elmer spectrophotometer to aid in understanding remotely sensed spectral data",
         "license": "proprietary"
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@@ -243004,7 +243290,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804788870-ORNL_CLOUD.html",
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         "description": "Low altitude (Ultralight) spectral reflectances of OTTER research sites measured by Spectron SE590 spectrophotometer",
         "license": "proprietary"
     },
@@ -243017,7 +243303,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804833090-ORNL_CLOUD.html",
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         "description": "Spectral reflectance measurements made by Spectron SE590 instruments in the context of validation of geometric-optical BRDF models",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804776618-ORNL_CLOUD.html",
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         "description": "Laboratory hemispherical reflectance spectra measurements taken to eliminate the effects of atmosphere, understory, exposed soils, mixed species and canopy architecture",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804776928-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804776928-ORNL_CLOUD.html",
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         "description": "Bidirectional spectal reflectance factors of landscape elements (litter, soil, bark, scrubs & grasses, leaves) measured by Spectron SE590 spectroradiometer",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804772156-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804772156-ORNL_CLOUD.html",
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         "description": "Spectral reflectance measurements of flat field targets as reference points representative of pseudo-invariant targets as measured by Spectron SE590 spectrophotometer",
         "license": "proprietary"
     },
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789728878-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789728878-ORNL_CLOUD.html",
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         "description": "The Global Burned Area 2000 initiative (GBA2000) was launched by the Global Vegetation Mapping Unit of the Joint Research Centre of the European Commission, in partnership with several other institutions, to develop reliable and quantitative information on the global magnitude and spatial distribution of biomass burning. The objective of GBA2000 was to produce a map of the areas burned globally for the year 2000, using the medium resolution satellite imagery provided by the SPOT-VEGETATION (VGT) system and to derive statistics of area burned per type of vegetation cover. A subset of the global GBA20000 map was prepared for SAFARI 2000 to map the area burned in sub-Saharan Africa during 2000 on a monthly basis using VGT imagery at 1 km spatial resolution. Burned areas were identified with a classification tree, relying only on the near-infrared channel of VGT. The data used in this work are in the S1 daily synthesis format, i.e. the data are radiometrically calibrated, precisely geo-located, and corrected for atmospheric effects.The data are binary image files of area burned, BSQ format in geographic projection.  There is one file for each month of 2000 and one file for all of the year 2000. There is also a comma-delimited ASCII text file that provides geographic coordinates (latitude and longitude) of the center of each pixel indicated as a burned area for all of 2000.",
         "license": "proprietary"
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         "description": "This data set contains cloud and meteorology data on a 1.0 degree x 1.0 degree spatial resolution. There are eight data files (*.zip) with this data set for several cloud parameters (monthly only) and meteorological parameters including monthly surface skin temperature, monthly total column ozone, and water vapor burdens for the period 1986-1995. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values. ",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2785335036-ORNL_CLOUD.html",
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         "description": "This data set contains global Surface Radiation Budget (SRB) and a few top-of-atmosphere (TOA) radiation budget parameters on a 1-degree x 1-degree spatial resolution. These parameters are provided as monthly, monthly-3 hourly (i.e. monthly average for a particular 3 hourly period) and 3-hourly averages. All monthly parameters include files with a monthly mean value, a monthly standard deviation, and monthly minimum and maximum values. The surface and TOA Shortwave (SW) radiative parameters were computed with the Pinker and Laszlo (1992) radiation model. The Longwave (LW) SRB parameters were derived with the Gupta et al. (1992) model. Meteorological inputs for all processing were taken from the Goddard Earth Observing System version 1 (GEOS-1) reanalysis data sets (Schubert et al., 1993) from the Data Assimilation Office (DAO), at NASA Goddard Space Flight Center (GSFC). Required cloud parameters were derived at NASA Langley Research Center (LaRC) from International Satellite Cloud Climatology Project (ISCCP) DX data using the algorithms developed at the NASA Goddard Institute for Space Studies (GISS) (Rossow et al., 1996). Surface albedos are derived internally in the Pinker and Laszlo SW model. There are 30 compressed data files (*.zip) with this data set. When the *.zip files are expanded, there are 114,912 3-hourly files, 42,064 diurnal files, and 6,254 monthly files. ",
         "license": "proprietary"
     },
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         "description": "This data set was prepared by the SERM-FBIU.  The data include information on forest parameters and cover the area in and near the BOREAS SSA, excluding the PANP.",
         "license": "proprietary"
     },
@@ -243420,7 +243706,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789103004-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789103004-ORNL_CLOUD.html",
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         "description": "The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to the Sua Pan salt playa in the Magkadigkadi region of Botswana during the SAFARI 2000 Dry Season Aircraft Campaign to collect various data sets for validating the MISR LAI/FPAR algorithm. Ground measurements of leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FPAR) were made using the LAI-2000 plant canopy analyzer and Sunfleck PAR ceptometer, respectively, during focused periods from August 20 to August 28, 2000 at a dry grassland site adjacent to the Sua Pan. The 1 km by 1 km sampling grid was a homogeneous, relatively dense grassland, with a height of 20-100 cm and two prevalent grass types, Odyssea paucinervis and Sporobolus spicatus. Associated reflectance measurements were made with the PARABOLA and ASD instruments (Helmlinger et al., 2004a; 2004b).The data files contain measurements of LAI and PAR reflectance and transmission and a description of sky conditions during the sampling periods. With one exception, all measurements were made under clear sky conditions.  PAR data were measured only on the transect scale while LAI are provided at both pixel and transect scales. PAR readings were performed at 93 transect sample points, and LAI readings were performed at 135 (93 transect and 42 subgrid) sample points. Each file also contains mean LAI and PAR values. The data files are ASCII tables, in comma-separated-value format.",
         "license": "proprietary"
     },
@@ -243433,7 +243719,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789638795-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789638795-ORNL_CLOUD.html",
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         "description": "The Jet Propulsion Laboratory's (JPL) Portable Apparatus for Rapid Acquisition of Bidirectional Observation of the Land and Atmosphere (PARABOLA), version III, instrument collected radiance data covering both the upwelling and downwelling hemispheres at the Sua Pan salt playa in the Magkadigkadi region of Botswana and at the Skukuza tower site in the Kruger National Park, South Africa between August 25 and October 2, 2000 during in the SAFARI 2000 Dry Season Aircraft Campaign. PARABOLA III is a sphere-scanning radiometer that provides multi-angle measurements of sky and ground radiances on a spherical grid of 5 degrees in the zenith-to-nadir and azimuthal planes in eight spectral channels (444, 551, 581, 650, 860, 944, 1028, and 1650 nm). The experiment was designed to collect data necessary for multi-angle top-of-atmosphere radiance predictions for a vicarious calibration of the Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite. Four of the PARABOLA channels (444, 551, 650, and 860 nm) are similar to those of the MISR sensor. Measurements were made on cloud-free days of Terra satellite overpasses.Each data file contains radiance counts (ASCII integer values) for 8 bands for each 3-minute data collection. Zenith and azimuth angles are implied by radiance count positions in file. Additional files contain average dark current readings, empirically determined by covering the detectors. The data can be processed to radiance using a series of second order polynomial fit coefficients, provided in the documentation file, and dark current offset. Site-specific auxiliary information is also provided, for each date of PARABOLA data collection.",
         "license": "proprietary"
     },
@@ -243446,7 +243732,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789642681-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789642681-ORNL_CLOUD.html",
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         "description": "The Multi-angle Imaging SpectroRadiometer (MISR) Validation team was deployed to Sua Pan, a salt playa in the Magkadigkadi region of Botswana, from August 18 to September 4, 2000, during the SAFARI 2000 Dry Season Aircraft Campaign. The experiment was designed to collect data necessary for multi-angle top-of-atmosphere radiance predictions in order to provide a vicarious calibration of the MISR instrument aboard the Terra satellite. Reported here are ground-based reflectance measurements collected using an Analytical Spectral Devices (ASD) spectroradiometer at Sua Pan and adjacent grassland targets. The grasslands provided large homogeneous areas for comparison of scale between ground measurements and remote sensing results.Data files contain numeric values that represent mean reflectance over space (grassland) or wavelength range (pan), stored as ASCII files, one file per site, in comma-separated-value (.csv) format, with column headers. The Sua Pan data, collected over a 1 km x 2 km area, are presented as rows of mean reflectance (every 10 nm) for 20 points, where the mean represents the average local reflectance spectra collected within 150 m of the given latitude and longitude. The grassland data cover a 1 km2 area and are provided every nm from 1 to 2500. Each row of data contains a mean and standard deviation at a given wavelength, where the mean represents the average of 570 measurements taken over the 1 km2 area.Related data sets from Sua Pan provide ground measurements of BRDF, and LAI and FPAR (Helmlinger et al., 2004 and Buermann and Helmlinger, 2004, respectively).",
         "license": "proprietary"
     },
@@ -244005,7 +244291,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093243-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093243-ORNL_CLOUD.html",
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         "description": "This data set provides a set of soil properties for the SSA. The soil samples were collected at sets of soil pits. Major soil properties include soil horizon; dry soil color; pH; bulk density; total, organic, and inorganic carbon; electric conductivity; cation exchange capacity; exchangeable sodium, potassium, calcium, magnesium, and hydrogen; water content at 0.01, 0.033, and 1.5 MPascals; nitrogen; phosphorus; particle size distribution; texture; pH of the mineral soil and of the organic soil; extractable acid; and sulfur.",
         "license": "proprietary"
     },
@@ -244018,7 +244304,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127606-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127606-ORNL_CLOUD.html",
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         "description": "Contains 1996 TE-04 data of branch bag studies of photosynthesis, respiration and stomatal conductance of boreal forest species using the open MPH-1000 system.",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127663-ORNL_CLOUD.html",
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         "description": "Contains TE-04 data on gas exchange studies of photosynthesis, respiration and stomatal conductance of boreal forest species using the MPH-1000 system.  ",
         "license": "proprietary"
     },
@@ -244044,7 +244330,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128840-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128840-ORNL_CLOUD.html",
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         "description": "Contains tree summary information for the TE-07 dendrology data.",
         "license": "proprietary"
     },
@@ -244057,7 +244343,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128933-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128933-ORNL_CLOUD.html",
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         "description": "Contains sap flow data collected by TE-07.",
         "license": "proprietary"
     },
@@ -244070,7 +244356,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128991-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128991-ORNL_CLOUD.html",
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         "description": "Contains bark biochemical data collected by TE-08.",
         "license": "proprietary"
     },
@@ -244083,7 +244369,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129186-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129186-ORNL_CLOUD.html",
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         "description": "Contains bark opical data collected by the TE-08 team during the BOREAS field campaign.",
         "license": "proprietary"
     },
@@ -244096,7 +244382,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129402-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129402-ORNL_CLOUD.html",
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         "description": "Contains foliar chlorophyll measurements collected by the TE-09 team.  ",
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         "description": "Contains in situ diurnal gas exchange and water potential data for forest stand in the Northern Study Area collected by TE-09.  ",
         "license": "proprietary"
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         "description": "Contains TE-09 data on the response of photosynthetic capacity to foliage nitrogen concentration and photosynthetic capacity in the canopies of Norther Study Area sites.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129440-ORNL_CLOUD.html",
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         "description": "This data table contains data collected by TE09 on the relationship between PAR and foliage nitrogen in the canopies of NSA-OBS, NSA-UBS, NSA-YJP, NSA-OJP and NSA-OASP.",
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         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129597-ORNL_CLOUD.html",
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         "description": "Leaf chemistry data collected by TE-10. Contains 3 granules: 1) biochemical data; 2) biochemical data on a per dry weight basis; and 3) biochemical carbon, hydrogen, and nitrogen data given on a per dry weight basis and on a per area basis.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129626-ORNL_CLOUD.html",
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         "description": "Contains gas exchange data collected by TE-10 during the BOREAS project.",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093265-ORNL_CLOUD.html",
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         "description": "Data collected in support of efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, oxygen evolution, and biochemical properties of boreal vegetation. This data set describes the spectral optical properties (reflectance and transmittance) of boreal forest conifers and broadleaf tree leaves as measured with a Spectron Engineering SE590 spectroradiometer at the SSA OBS, OJP, YJP, OA, OA-AUX, YA-AUX, and YA sites.  The data were collected during the growing seasons of 1994 and 1996.",
         "license": "proprietary"
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         "description": "Contains the 1994 oxygen evolution and leaf characteristics data collected by TE-10.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129876-ORNL_CLOUD.html",
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         "description": "Contains data collected by BOREAS TE-11 team on CO2 assimilation and transpiration in the SSA.",
         "license": "proprietary"
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@@ -244226,7 +244512,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129912-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808129912-ORNL_CLOUD.html",
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         "description": "Contains sap flow data collected by TE-11.",
         "license": "proprietary"
     },
@@ -244239,7 +244525,7 @@
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         "description": "Data collected in support of efforts to characterize and interpret information on the sapflow, gas exchange, and lichen photosynthesis.",
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         "description": "The Boreal Ecosystem-Atmosphere Study (BOREAS) Terrestrial Ecology (TE)-13 team collected data on site characteristics, soil profiles, woody debris, overstory vegetation, and understory vegetation from approximately 100 sites in the Southern Study Area (SSA), Northern Study Area (NSA), and Transect Areas in the boreal forest. This data sets provides 3 reports published by the Canadian Forest Service for the BOREAS project in pdf file format.",
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         "description": "A BOREAS version of the Global Production Efficiency Model(www.inform.umd.edu/glopem) was developed by TE-17 to generate maps of gross and net primary production, autotrophic respiration, and light use efficiency for the BOREAS region.",
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         "description": "The BOREAS TE-18 team used a radiometric rectification process to produce standardized DN values for a series of Landsat TM images of the BOREAS SSA and NSA in order to compare images that were collected under different atmospheric conditions. The images for each study area were referenced to an image that had very clear atmospheric qualities. Each of the reference scenes had coincident atmospheric optical thickness measurements made by RSS-11.",
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         "description": "The BOREAS TE-18 team used a radiometric rectification process to produce standardized DN values for a series of Landsat TM images of the BOREAS SSA and NSA in order to compare images that were collected under different atmospheric conditions. The images for each study area were referenced to an image that had very clear atmospheric qualities.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2929487616-ORNL_CLOUD.html",
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         "description": "The Spruce and Moss Model (SPAM) was designed to simulate the daily carbon balance of a black spruce/moss boreal forest ecosystem. It is driven by daily weather conditions and consists of four components: (1) soil climate; (2) tree photosynthesis and respiration; (3) moss photosynthesis and respiration; and (4) litter decomposition and associated heterotrophic respiration. The model can be used to generate predictions of total site net ecosystem exchange of carbon (NEE), total soil dark respiration (live roots + heterotrophs + live moss), spruce and moss net productivity, and net carbon accumulation in the soil.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2807648526-ORNL_CLOUD.html",
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         "description": "Contains the TE-01 CH4 flux data for the southern study area old aspen site.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2807650141-ORNL_CLOUD.html",
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         "description": "Contains TE-01 methane flux and inorganic concentrations at the southern study area fen site.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2807648575-ORNL_CLOUD.html",
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         "description": "Contains the TE-01 CH4 and CO2 flux data for the southern study area OBS site.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091512-ORNL_CLOUD.html",
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         "description": "The BOREAS TE-20 team collected several data sets for use in developing and testing models of forest ecosystem dynamics. This data set contains measurements of site characteristics conducted in the SSA from 18-Jul-1994 to 30-Jul-1994.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130459-ORNL_CLOUD.html",
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         "description": "Contains the soils lab data that were collected by TE-20 in 1994.",
         "license": "proprietary"
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@@ -244460,7 +244746,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091530-ORNL_CLOUD.html",
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         "description": "Data for use in developing and testing models of forest ecosystem dynamics. The data set describes the soils and landscape characteristics of the NSA-MSA and tower sites.",
         "license": "proprietary"
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@@ -244473,7 +244759,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130516-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130516-ORNL_CLOUD.html",
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         "description": "Contains meteorological measurement data collected by TE-21.",
         "license": "proprietary"
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@@ -244486,7 +244772,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091680-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091680-ORNL_CLOUD.html",
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         "description": "The BOREAS TE-22 team collected data sets in support of its efforts to characterize and interpret information on the forest structure of boreal vegetation in the SSA and NSA during the 1994 growing season.",
         "license": "proprietary"
     },
@@ -244499,7 +244785,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091720-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091720-ORNL_CLOUD.html",
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         "description": "Tree core  data from several sites in the SSA and NSA collected in order to perform historical growth studies and relate the information to their modeling activities. The cores were collected during the summer of 1994 in the Northern and Southern Study Areas. A sample of the file types resulting from the analysis of the tree cores is provided. ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091754-ORNL_CLOUD.html",
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         "description": "Hemispherical photographs collected in support of the effort to characterize and interpret information on estimates of canopy architecture and radiative transfer properties for most BOREAS study sites. Various OA, OBS, OJP, YJP, and YA sites in the boreal forest were measured from May to August 1994. The hemispherical photographs were used to derive values of LAI, Leaf angle, Gap fraction, and Clumping index.  ",
         "license": "proprietary"
     },
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130597-ORNL_CLOUD.html",
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         "description": "Describes the mapped plot data and the mapped plot site data taken by TE-23.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2807652682-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2807652682-ORNL_CLOUD.html",
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         "description": "Contains foliage respiration data collected by TE-02.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2807653050-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2807653050-ORNL_CLOUD.html",
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         "description": "Contains fine root respiration data collected by TE-02.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127501-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127501-ORNL_CLOUD.html",
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         "description": "Contains stem growth and sapwood data collected by TE-02.",
         "license": "proprietary"
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@@ -244577,7 +244863,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2807652390-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2807652390-ORNL_CLOUD.html",
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         "description": "Contains wood respiration continuous measurement data collected by TE-02.",
         "license": "proprietary"
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@@ -244590,7 +244876,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127572-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127572-ORNL_CLOUD.html",
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         "description": "Contains wood respiration data collected by TE-02.",
         "license": "proprietary"
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@@ -244603,7 +244889,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127926-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808127926-ORNL_CLOUD.html",
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         "description": "This table contains data collected by TE05  in the NSA and SSA on air stable istope measurements.",
         "license": "proprietary"
     },
@@ -244616,7 +244902,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128013-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128013-ORNL_CLOUD.html",
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         "description": "Contains the CO2 profile concentration measurements made by the TE-05 BOREAS team in the NSA and SSA.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128106-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128106-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHNhc2thdGNoZXdhbiBmb3Jlc3QgZmlyZSBjb250cm9sIGNlbnRyZSBzdXJmYWNlIG1ldGVvcm9sb2dpY2FsIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInNhc2tmZmNjXzMwN1wiLFwiMVwiLDI4MDc2NDU4MDIsMl0iLCJ1bW0iOiJbXCJib3JlYXMgc2Fza2F0Y2hld2FuIGZvcmVzdCBmaXJlIGNvbnRyb2wgY2VudHJlIHN1cmZhY2UgbWV0ZW9yb2xvZ2ljYWwgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwic2Fza2ZmY2NfMzA3XCIsXCIxXCIsMjgwNzY0NTgwMiwyXSJ9/te5lciso_323_1",
         "description": "Contains leaf carbon isotope data collected by TE-05 during 1994.",
         "license": "proprietary"
     },
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         "bbox": "-106.2, 53.63, -98.62, 55.93",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128156-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128156-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te5lgxd_324_1",
         "description": "Contains the leaf gas exchange data collected by TE-05 in the NSA and SSA.",
         "license": "proprietary"
     },
@@ -244655,7 +244941,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128293-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128293-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te5metd_326_1",
         "description": "Contains meteorological data collected during field campaigns by TE-05.",
         "license": "proprietary"
     },
@@ -244668,7 +244954,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128221-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128221-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te5soilr_325_1",
         "description": "Contains data collected by TE-05 on soil gas exchange data in the NSA and SSA in 1994.",
         "license": "proprietary"
     },
@@ -244681,7 +244967,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128380-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128380-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgZ2FzIGV4Y2hhbmdlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxneGRfMzI0XCIsXCIxXCIsMjgwODEyODE1NiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGdhcyBleGNoYW5nZSBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZTVsZ3hkXzMyNFwiLFwiMVwiLDI4MDgxMjgxNTYsMl0ifQ%3D%3D/te5treer_327_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te5treer_327_1",
         "description": "Contains tree ring width and C13 isotope cellulose ratio data collected by TE-05.",
         "license": "proprietary"
     },
@@ -244694,7 +244980,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128623-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128623-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgZ2FzIGV4Y2hhbmdlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxneGRfMzI0XCIsXCIxXCIsMjgwODEyODE1NiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGdhcyBleGNoYW5nZSBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZTVsZ3hkXzMyNFwiLFwiMVwiLDI4MDgxMjgxNTYsMl0ifQ%3D%3D/te6allom_329_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te6allom_329_1",
         "description": "Contains allometry data collected by TE-06.",
         "license": "proprietary"
     },
@@ -244707,7 +244993,7 @@
         "bbox": "-106.2, 53.59, -97.34, 55.97",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128654-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128654-ORNL_CLOUD.html",
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         "description": "Contains biomass data collected by TE-06.",
         "license": "proprietary"
     },
@@ -244720,7 +245006,7 @@
         "bbox": "-106.2, 53.63, -98.29, 55.93",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128749-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128749-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te6h2opd_332_1",
         "description": "Contains data collected by TE-06 on pre-dawn leaf water potential and foliage moisture content.",
         "license": "proprietary"
     },
@@ -244733,7 +245019,7 @@
         "bbox": "-106.12, 53.63, -98.62, 55.84",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128688-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128688-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgZ2FzIGV4Y2hhbmdlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxneGRfMzI0XCIsXCIxXCIsMjgwODEyODE1NiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGdhcyBleGNoYW5nZSBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZTVsZ3hkXzMyNFwiLFwiMVwiLDI4MDgxMjgxNTYsMl0ifQ%3D%3D/te6mltvg_331_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te6mltvg_331_1",
         "description": "Describes the average data values derived from the multi-vegetation imager used by TE-06 during the BOREAS project.Describes the single point data values derived from the multi-vegetation imager used by TE-06 during the BOREAS project.",
         "license": "proprietary"
     },
@@ -244746,7 +245032,7 @@
         "bbox": "-106.2, 53.63, -97.34, 56",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2807606269-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2807606269-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgZ2FzIGV4Y2hhbmdlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxneGRfMzI0XCIsXCIxXCIsMjgwODEyODE1NiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGdhcyBleGNoYW5nZSBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZTVsZ3hkXzMyNFwiLFwiMVwiLDI4MDgxMjgxNTYsMl0ifQ%3D%3D/te6npp_200_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRlLTA1IGxlYWYgY2FyYm9uIGlzb3RvcGUgZGF0YVwiLFwiT1JOTF9DTE9VRFwiLFwidGU1bGNpc29fMzIzXCIsXCIxXCIsMjgwODEyODEwNiwyXSIsInVtbSI6IltcImJvcmVhcyB0ZS0wNSBsZWFmIGNhcmJvbiBpc290b3BlIGRhdGFcIixcIk9STkxfQ0xPVURcIixcInRlNWxjaXNvXzMyM1wiLFwiMVwiLDI4MDgxMjgxMDYsMl0ifQ%3D%3D/te6npp_200_1",
         "description": "Contains Net primary production data gathered by the TE-06 group in the NSA and SSA.",
         "license": "proprietary"
     },
@@ -244759,7 +245045,7 @@
         "bbox": "-98.67, 55.89, -98.67, 55.89",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128479-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808128479-ORNL_CLOUD.html",
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         "license": "proprietary"
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@@ -244915,7 +245201,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093089-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093089-ORNL_CLOUD.html",
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         "description": "Energy, carbon dioxide, and water vapor flux data collected by the BOREAS TF-08 team.",
         "license": "proprietary"
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@@ -244941,7 +245227,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808090635-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808090635-ORNL_CLOUD.html",
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         "description": "The flux and ancillary data collected at the NSA-YJP tower flux site by the TF-10 group.  Measurements of stomatal conductance collected at the NSA-YJP site by the TF-10 team.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130902-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130902-ORNL_CLOUD.html",
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         "description": "The flux and ancillary data collected at the NSA-Fen tower flux site by the TF-10 group.",
         "license": "proprietary"
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         "bbox": "-104.62, 53.8, -104.62, 53.8",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131067-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131067-ORNL_CLOUD.html",
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         "description": "Contains plant coverage, plant biomass, and estimated net primary productivity collected by TF-11.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131091-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131091-ORNL_CLOUD.html",
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         "description": "Contains temperature, pH, and CH4 and CO2 concentration profiles in the surface 50 cm of peat.",
         "license": "proprietary"
     },
@@ -244993,7 +245279,7 @@
         "bbox": "-104.62, 53.8, -104.62, 53.8",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131145-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131145-ORNL_CLOUD.html",
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         "description": "Contains decomposition rates of a standard substrate (wheat straw).",
         "license": "proprietary"
     },
@@ -245006,7 +245292,7 @@
         "bbox": "-104.62, 53.8, -104.62, 53.8",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131130-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131130-ORNL_CLOUD.html",
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         "description": "Contains CH4 and CO2 static chamber fluxes at the SSA-FEN.",
         "license": "proprietary"
     },
@@ -245019,7 +245305,7 @@
         "bbox": "-104.62, 53.8, -104.62, 53.8",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091118-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091118-ORNL_CLOUD.html",
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         "description": "Contains the TF-11 Leaf Area Index (LAI) data collected at the SSA Fen site.",
         "license": "proprietary"
     },
@@ -245032,7 +245318,7 @@
         "bbox": "-104.62, 53.8, -104.62, 53.8",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091049-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091049-ORNL_CLOUD.html",
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         "description": "Contains the TF-11 leaf gas exchange data made with the LI-6200 and LI-6400 systems.",
         "license": "proprietary"
     },
@@ -245045,7 +245331,7 @@
         "bbox": "-104.62, 53.8, -104.62, 53.8",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808090702-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808090702-ORNL_CLOUD.html",
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         "description": "Contains the TF-11 CO2 chamber flux measurements made with the LI-6200 under water surface film conditions and  the TF-11 CO2 chamber concentration measurements made using the Gas Chromatograph-Flame Ionization Detector.",
         "license": "proprietary"
     },
@@ -245058,7 +245344,7 @@
         "bbox": "-104.62, 53.8, -104.62, 53.8",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091100-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091100-ORNL_CLOUD.html",
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         "description": "The flux and ancillary data collected at the SSA-Fen tower flux site by the TF-11 group.",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808092858-ORNL_CLOUD.html",
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         "description": "This data set contains methane (CH4) and nitrous oxide (N2O)fluxes that were measured at the BOREAS SSA-OA site",
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         "description": "Contains fluxes of carbon dioxide and methane across the soil-air interface in four ages of jack pine forest at the Southern Study Area.  Gross and net flux of CO2 and flux of CH4 between soil and air are presented for 24 chamber sites in mature jack pine stands.",
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         "description": "The TF-04 Soil profile CH4 concentration data.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130760-ORNL_CLOUD.html",
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         "description": "The flux and ancillary data collected at the SSA-OJP tower flux site by the TF-05 group.",
         "license": "proprietary"
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@@ -245175,7 +245461,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130804-ORNL_CLOUD.html",
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         "description": "Contains meteorology data collected at the SSA-YA tower flux site by the TF6 group. These data were reported at 10 minute intervals. The flux and ancillary data collected at the SSA-YA tower flux site by the TF6 group.",
         "license": "proprietary"
     },
@@ -245188,7 +245474,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130816-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130816-ORNL_CLOUD.html",
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         "description": "CO2 and H2O vapor exchange and ancillary data collected from enclosures around the black spruce branches.  Data collected by the TF-09 group at the SSA-OBS site.",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808130862-ORNL_CLOUD.html",
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         "description": "Soil temperature and heat flux data from the SSA-OBS site, collected by the TF-09 group; and the flux and ancillary data collected at the SSA-OBS tower flux site by the TF-09 group.",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091208-ORNL_CLOUD.html",
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         "description": "Contains TGB-03 dissolved organic carbon concentration data for northern study area.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132198-ORNL_CLOUD.html",
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         "description": "Contains oxidant (O3, H2O2, ROOH) concentration data collected by TGB-10 for the Southern Study Area.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132223-ORNL_CLOUD.html",
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         "description": "Contains oxidant flux data collected by TGB-10 for sites in the Southern Study Area.",
         "license": "proprietary"
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132327-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132327-ORNL_CLOUD.html",
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         "description": "Contains biogenic VOC data collected by TGB-10 during the summer of 1994.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093149-ORNL_CLOUD.html",
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         "description": "This data set contains (1) estimates of soil carbon stocks by horizon based on soil survey data and analyses of data from individual soil profiles; (2) estimates of soil carbon fluxes based on stocks, fire history, drainage, and soil C inputs and decomposition constants based on field work using radiocarbon analyses; (3) fire history data estimating age ranges of time since last fire; (4) a raster image and an associated soils table file from which area-weighted maps of soil carbon and fluxes and fire history may be generated.",
         "license": "proprietary"
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@@ -245279,7 +245565,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132353-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132353-ORNL_CLOUD.html",
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         "description": "Contains TGB-12 soil CO2 flux data for sites in the northern study area.",
         "license": "proprietary"
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@@ -245292,7 +245578,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808087726-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808087726-ORNL_CLOUD.html",
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         "description": "Contains RADON-222 activity in soil gas collected by TGB-12 at 5 BOREAS auxiliary sites in the northern study area.",
         "license": "proprietary"
     },
@@ -245305,7 +245591,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808089765-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808089765-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb12rfd_401_1",
         "description": "Contains RADON-222 flux data data collected by TGB-12 in the northern study area.",
         "license": "proprietary"
     },
@@ -245318,7 +245604,7 @@
         "bbox": "-98.95, 55.07, -97.7, 55.93",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808089794-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808089794-ORNL_CLOUD.html",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093474-ORNL_CLOUD.html",
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131236-ORNL_CLOUD.html",
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         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131256-ORNL_CLOUD.html",
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         "description": "Contains CH4 tower flux data collected by BOREAS science group TGB01 in the Northern Study Area.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131327-ORNL_CLOUD.html",
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         "license": "proprietary"
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@@ -245396,7 +245682,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131469-ORNL_CLOUD.html",
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         "license": "proprietary"
     },
@@ -245409,7 +245695,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131515-ORNL_CLOUD.html",
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         "description": "Composition of plant species that were within the collars used to measure net ecosystem exchange (NEE).",
         "license": "proprietary"
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@@ -245422,7 +245708,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131454-ORNL_CLOUD.html",
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         "description": "Contains water table and peat temperature data collected by the TGB-03 team for sites in the northern study area.",
         "license": "proprietary"
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@@ -245435,7 +245721,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091300-ORNL_CLOUD.html",
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         "description": "The flux and ancillary data collected at the NSA-BP tower flux site by the TGB-04 group.",
         "license": "proprietary"
     },
@@ -245448,7 +245734,7 @@
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         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091319-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808091319-ORNL_CLOUD.html",
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         "description": "Contains TGB-04  water and sediment temperature data for northern study area (tower beaver pond site).",
         "license": "proprietary"
     },
@@ -245461,7 +245747,7 @@
         "bbox": "-99.87, 55.15, -96.52, 56.17",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131739-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131739-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRmLTExIHNzYSBmZW4gMTk5NiB3YXRlciBzdXJmYWNlIGZpbG0gY2FwcGluZyBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZjExc2ZsbV80NTVcIixcIjFcIiwyODA4MDkwNzAyLDJdIiwidW1tIjoiW1wiYm9yZWFzIHRmLTExIHNzYSBmZW4gMTk5NiB3YXRlciBzdXJmYWNlIGZpbG0gY2FwcGluZyBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZjExc2ZsbV80NTVcIixcIjFcIiwyODA4MDkwNzAyLDJdIn0%3D/tgb5cflx_384_1",
         "description": "Contains the TGB-05 CO, CO2, and CH4 flux data for sites in the Boreas Northern Study Area.",
         "license": "proprietary"
     },
@@ -245474,7 +245760,7 @@
         "bbox": "-98.03, 55.84, -98.03, 55.84",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131800-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131800-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRmLTExIHNzYSBmZW4gMTk5NiB3YXRlciBzdXJmYWNlIGZpbG0gY2FwcGluZyBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZjExc2ZsbV80NTVcIixcIjFcIiwyODA4MDkwNzAyLDJdIiwidW1tIjoiW1wiYm9yZWFzIHRmLTExIHNzYSBmZW4gMTk5NiB3YXRlciBzdXJmYWNlIGZpbG0gY2FwcGluZyBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZjExc2ZsbV80NTVcIixcIjFcIiwyODA4MDkwNzAyLDJdIn0%3D/tgb5docd_385_1",
         "description": "Contains the TGB-05 dissolved organic carbon data for the Northern Study Area beaver pond site.",
         "license": "proprietary"
     },
@@ -245487,7 +245773,7 @@
         "bbox": "-99.87, 55.15, -96.52, 56.17",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131554-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131554-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRmLTExIHNzYSBmZW4gMTk5NiB3YXRlciBzdXJmYWNlIGZpbG0gY2FwcGluZyBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZjExc2ZsbV80NTVcIixcIjFcIiwyODA4MDkwNzAyLDJdIiwidW1tIjoiW1wiYm9yZWFzIHRmLTExIHNzYSBmZW4gMTk5NiB3YXRlciBzdXJmYWNlIGZpbG0gY2FwcGluZyBkYXRhXCIsXCJPUk5MX0NMT1VEXCIsXCJ0ZjExc2ZsbV80NTVcIixcIjFcIiwyODA4MDkwNzAyLDJdIn0%3D/tgb5nnfd_383_1",
         "description": "Contains the TGB-05 NO and N2O flux data for sites in the Northern Study Area.  ",
         "license": "proprietary"
     },
@@ -245500,7 +245786,7 @@
         "bbox": "-104.69, 55.84, -98.03, 55.93",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131966-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131966-ORNL_CLOUD.html",
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+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb6chrc_388_1",
         "description": "Contains 1993, 1994, and 1996 methane concentrations from TGB-06 in the NSA and SSA.",
         "license": "proprietary"
     },
@@ -245513,7 +245799,7 @@
         "bbox": "-106.07, 53.92, -106.07, 53.92",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131993-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131993-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNiBzb2lsIG1ldGhhbmUgb3hpZGF0aW9uIGFuZCBwcm9kdWN0aW9uIGZyb20gbnNhIGJwIGFuZCBmZW4gc2l0ZXNcIixcIk9STkxfQ0xPVURcIixcInRnYjZjaHJjXzM4OFwiLFwiMVwiLDI4MDgxMzE5NjYsMl0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA2IHNvaWwgbWV0aGFuZSBveGlkYXRpb24gYW5kIHByb2R1Y3Rpb24gZnJvbSBuc2EgYnAgYW5kIGZlbiBzaXRlc1wiLFwiT1JOTF9DTE9VRFwiLFwidGdiNmNocmNfMzg4XCIsXCIxXCIsMjgwODEzMTk2NiwyXSJ9/tgb7aaho_389_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb7aaho_389_1",
         "description": "Contains herbicide and organic chlorine concentrations in ambient air samples for TGB-07 in the SSA.",
         "license": "proprietary"
     },
@@ -245526,7 +245812,7 @@
         "bbox": "-106.07, 53.92, -106.07, 53.92",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132025-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132025-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNiBzb2lsIG1ldGhhbmUgb3hpZGF0aW9uIGFuZCBwcm9kdWN0aW9uIGZyb20gbnNhIGJwIGFuZCBmZW4gc2l0ZXNcIixcIk9STkxfQ0xPVURcIixcInRnYjZjaHJjXzM4OFwiLFwiMVwiLDI4MDgxMzE5NjYsMl0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA2IHNvaWwgbWV0aGFuZSBveGlkYXRpb24gYW5kIHByb2R1Y3Rpb24gZnJvbSBuc2EgYnAgYW5kIGZlbiBzaXRlc1wiLFwiT1JOTF9DTE9VRFwiLFwidGdiNmNocmNfMzg4XCIsXCIxXCIsMjgwODEzMTk2NiwyXSJ9/tgb7ddho_390_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb7ddho_390_1",
         "description": "Contains herbicide and organic chlorine fluxes in dry deposition samples for TGB-07 in the SSA.",
         "license": "proprietary"
     },
@@ -245539,7 +245825,7 @@
         "bbox": "-106.07, 53.92, -106.07, 53.92",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132038-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132038-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNiBzb2lsIG1ldGhhbmUgb3hpZGF0aW9uIGFuZCBwcm9kdWN0aW9uIGZyb20gbnNhIGJwIGFuZCBmZW4gc2l0ZXNcIixcIk9STkxfQ0xPVURcIixcInRnYjZjaHJjXzM4OFwiLFwiMVwiLDI4MDgxMzE5NjYsMl0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA2IHNvaWwgbWV0aGFuZSBveGlkYXRpb24gYW5kIHByb2R1Y3Rpb24gZnJvbSBuc2EgYnAgYW5kIGZlbiBzaXRlc1wiLFwiT1JOTF9DTE9VRFwiLFwidGdiNmNocmNfMzg4XCIsXCIxXCIsMjgwODEzMTk2NiwyXSJ9/tgb7rwho_391_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb7rwho_391_1",
         "description": "Contains 1993 and 1994 herbicide concentrations in rain samples for TGB-07 in the SSA.",
         "license": "proprietary"
     },
@@ -245552,7 +245838,7 @@
         "bbox": "-105.12, 53.92, -104.69, 53.99",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132062-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132062-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNiBzb2lsIG1ldGhhbmUgb3hpZGF0aW9uIGFuZCBwcm9kdWN0aW9uIGZyb20gbnNhIGJwIGFuZCBmZW4gc2l0ZXNcIixcIk9STkxfQ0xPVURcIixcInRnYjZjaHJjXzM4OFwiLFwiMVwiLDI4MDgxMzE5NjYsMl0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA2IHNvaWwgbWV0aGFuZSBveGlkYXRpb24gYW5kIHByb2R1Y3Rpb24gZnJvbSBuc2EgYnAgYW5kIGZlbiBzaXRlc1wiLFwiT1JOTF9DTE9VRFwiLFwidGdiNmNocmNfMzg4XCIsXCIxXCIsMjgwODEzMTk2NiwyXSJ9/tgb8mono_392_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb8mono_392_1",
         "description": "Contains monoterpene emission and concentration data collected by the TGB-08 BOREAS science group.",
         "license": "proprietary"
     },
@@ -245565,7 +245851,7 @@
         "bbox": "-105.12, 53.92, -104.69, 53.99",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132108-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132108-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNiBzb2lsIG1ldGhhbmUgb3hpZGF0aW9uIGFuZCBwcm9kdWN0aW9uIGZyb20gbnNhIGJwIGFuZCBmZW4gc2l0ZXNcIixcIk9STkxfQ0xPVURcIixcInRnYjZjaHJjXzM4OFwiLFwiMVwiLDI4MDgxMzE5NjYsMl0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA2IHNvaWwgbWV0aGFuZSBveGlkYXRpb24gYW5kIHByb2R1Y3Rpb24gZnJvbSBuc2EgYnAgYW5kIGZlbiBzaXRlc1wiLFwiT1JOTF9DTE9VRFwiLFwidGdiNmNocmNfMzg4XCIsXCIxXCIsMjgwODEzMTk2NiwyXSJ9/tgb8prds_393_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb8prds_393_1",
         "description": "Contains TGB-08 Photosynthesis data measured at 30C by month.",
         "license": "proprietary"
     },
@@ -245578,7 +245864,7 @@
         "bbox": "-105.12, 53.92, -104.69, 53.99",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132136-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132136-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNiBzb2lsIG1ldGhhbmUgb3hpZGF0aW9uIGFuZCBwcm9kdWN0aW9uIGZyb20gbnNhIGJwIGFuZCBmZW4gc2l0ZXNcIixcIk9STkxfQ0xPVURcIixcInRnYjZjaHJjXzM4OFwiLFwiMVwiLDI4MDgxMzE5NjYsMl0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA2IHNvaWwgbWV0aGFuZSBveGlkYXRpb24gYW5kIHByb2R1Y3Rpb24gZnJvbSBuc2EgYnAgYW5kIGZlbiBzaXRlc1wiLFwiT1JOTF9DTE9VRFwiLFwidGdiNmNocmNfMzg4XCIsXCIxXCIsMjgwODEzMTk2NiwyXSJ9/tgb8scds_394_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wiYm9yZWFzIHRnYi0wNSBmaXJlIGhpc3Rvcnkgb2YgbWFuaXRvYmEgMTk4MCB0byAxOTkxIGluIHZlY3RvciBmb3JtYXRcIixcIk9STkxfQ0xPVURcIixcImZoc3RtYW52XzM4N1wiLFwiMVwiLDI4MTMzOTgzNTUsNV0iLCJ1bW0iOiJbXCJib3JlYXMgdGdiLTA1IGZpcmUgaGlzdG9yeSBvZiBtYW5pdG9iYSAxOTgwIHRvIDE5OTEgaW4gdmVjdG9yIGZvcm1hdFwiLFwiT1JOTF9DTE9VRFwiLFwiZmhzdG1hbnZfMzg3XCIsXCIxXCIsMjgxMzM5ODM1NSw1XSJ9/tgb8scds_394_1",
         "description": "Contains starch concentration data collected by TGB-08 from the SSA-OBS and SSA-OJP BOREAS sites in 1994.",
         "license": "proprietary"
     },
@@ -245591,7 +245877,7 @@
         "bbox": "-106.2, 53.63, -104.69, 53.99",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132169-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808132169-ORNL_CLOUD.html",
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         "description": "Contains the mixing ratio and concentration of Non-Methane HydroCarbons (NMHC) taken by the TGB-09 group.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131382-ORNL_CLOUD.html",
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         "description": "Contains TGB-03 methane flux data for fens in the Northern Study Area.",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808131414-ORNL_CLOUD.html",
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         "description": "Contains TGB-03 NET Ecosystem Exchange data from the combined TGB-01 and TGB-03 teams.",
         "license": "proprietary"
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         "description": "Height, crown width, DBH, and height-to-crown distance collected using variable-radius plot sampling with steel tape and hand-held compass to locate points along transect",
         "license": "proprietary"
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789730089-ORNL_CLOUD.html",
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         "description": "The ETA Forecast Trajectory Model was used to produce forecasts of air-parcel trajectories twice a day at three pressure levels over seven sites in Southern Africa for the period August 14, 2000 to September 23, 2000. These sites are Durban, Middleburg, Pietersburg, and Springbok, South Africa; Maun, Botswana; Mongu, Zambia; and Windhoek, Namibia. The twice daily three-dimensional wind field (at 0000 and 1200 UTC) was used as input to the trajectory model. By integrating the vertical motion of the air parcels over a period of time, the trajectory model was able to forecast the net vertical displacement of air parcels during 12-hour periods. The resulting trajectory plots represent the three-dimensional transport of air in time and can be used to examine what is happening in the low-to-mid troposphere during flight and ground-based observations. These levels are most significant in terms of the thermodynamic structure of the troposphere, especially the stable layers and accumulation of material between and below them, as well containing the major levels of subsidence over the subcontinent. The trajectory model output and  thermodynamic profiles of the troposphere were used to position aircraft for sampling trace gases, aerosols and other species during the SAFARI 2000 field campaign and to predict regions of high aerosol and trace gas concentrations downwind.The model output data are daily forward and backward trajectory plots at 850 hPa, 700 hPa, and 500 hPa pressure levels for each location. The plots are provided as JPEG images with coordinate, date, and time stamps.",
         "license": "proprietary"
     },
@@ -245955,7 +246241,7 @@
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         "description": "This data set consists of a southern African subset of the 1-km Global Tree Cover Data Set developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Data are available in both ASCII GRID and binary image files formats.",
         "license": "proprietary"
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@@ -246163,7 +246449,7 @@
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         "description": "The Met Office C-130 research aircraft was based at Windhoek, Namibia, between September 5-16, 2000, where it conducted a series of flights over Namibia as part of the SAFARI 2000 Dry Season Aircraft Campaign. The aims of the Met Office's research were as follows: (1) In-situ measurements of the physical, chemical and optical properties of the aerosol. The data set includes aerosol samples ranging from near source regions to aged plumes several hundreds of kilometres from source, some of which have been cloud processed. (2) Investigation of the direct radiative impact of aerosol over sea, land and low-level cloud. (3) In-situ measurements of aerosol properties in conjunction with ground-based sites to validate the ground-based retrievals of, for example, aerosol size distributions. (4) In-situ measurements of aerosol properties in conjunction with TERRA overpasses, in order to validate the satellite-based retrievals of aerosol properties. (5) In-situ measurements of stratus/stratocumulus cloud of Namibia/Angola in conjunction with TERRA overpasses, in order to validate satellite-based retrievals of cloud properties.",
         "license": "proprietary"
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         "description": "The objective of the International Satellite Land Surface Climatology Project (ISLSCP II) study that produced this data set, ISLSCP II University of Maryland Global Land Cover Classifications 1992-1993, was to create a land cover map derived from 1 kilometer Advanced Very High Resolution Radiometer (AVHRR) data using all available bands, derived Normalized Difference Vegetation Index (NDVI), and a full year of data (April 1992-March 1993). This thematic map was resampled to 0.25, 0.5 and 1.0 degree grids. During this re-processing, the original University of Maryland (UMD) land cover type and fraction maps were adjusted to match the water/land fraction of the ISLSCP II land/water mask. These maps were generated for use by modelers of global biogeochemical cycles and others in need of an internally consistent, global depiction of land cover. This 1km map was also one of the Moderate resolution Imaging Spectroradiometer (MODIS) at-launch land cover maps. This product describes the geographic distributions of 13 classes of vegetation cover (plus water and unclassified classes) based on a modified International Geosphere-Biosphere Programme (IGBP) legend. The data set also provides the fraction of each of the 15 classes within the coarser resolution cells, at three spatial resolutions of 0.25, 0.5 and 1.0 degrees in latitude and longitude. ",
         "license": "proprietary"
     },
@@ -248204,7 +248490,7 @@
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         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2784863182-ORNL_CLOUD.html",
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         "description": "The objective of this study was to derive continuous fields of vegetation cover from multi-temporal Advanced Very High Resolution Radiometer (AVHRR) data using all available bands and derived Normalized Difference Vegetation Index (NDVI). The continuous fields describe sub-pixel proportions of cover for tree, herbaceous, bare ground and water cover types. For tree cover, additional fields describing leaf longevity (evergreen and deciduous) and leaf morphology (broadleaf and needleleaf) were also generated. The modeling of carbon dynamics and climate require knowing tree characteristics such as these. These products were resampled and aggregated to 0.25, 0.5 and 1.0 degree grids for the International Satellite Land Surface Climatology Project (ISLSCP) data initiative II. The data set describes the geographic distributions of three fundamental vegetation characteristics: tree, herbaceous and bare ground cover, plus a water layer. For tree cover, leaf longevity and morphology layers were produced.This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.",
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         "description": "This data set provides the results of the development of The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) Phase 2 transient climate change scenarios for the state of Alaska, USA. The data include gridded monthly historical and future estimates of maximum and minimum temperature, solar radiation, vapor pressure, irradiance, relative humidity and potential evapotranspiration at 0.5-degree spatial resolution. Historical data are for the period 1922-1996; future estimates cover the period 1997-2100.",
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         "description": "The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) was a multi-institutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetation type distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing.Selected variable output results from the VEMAP Phase I modeling exercise are now available for several combinations of biogeochemistry and biogeography models and climate change scenarios through the ORNL DAAC. For a description of the models and climate scenarios employed in the VEMAP 1 project and a discussion of the results please refer to the following publication: VEMAP Members. 1995. Vegetation/Ecosystem Modeling and Analysis Project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochem. Cycles 9:407-437.",
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         "description": "Various aspects of primary production of a variety of plant species found in natural temperate biomes were compiled from literature and presented for use with process-based ecosystem simulation models or ecosystem studies.  Information was selected according to the input parameter needs of the BIOME-BGC process-based simulation model.",
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     },
@@ -248828,7 +249114,7 @@
         "bbox": "-85, -25, -30, 10",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2777328977-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2777328977-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhIHJlZ2lvbmFsIHBvdGVudGlhbCB2ZWdldGF0aW9uLCA1LW1pbiAocmFtYW5rdXR0eSBhbmQgZm9sZXkpXCIsXCJPUk5MX0NMT1VEXCIsXCJwb3RlbnRpYWxfdmVnZXRhdGlvbl82ODRcIixcIjFcIiwyNzc3MzI3NTczLDJdIiwidW1tIjoiW1wibGJhIHJlZ2lvbmFsIHBvdGVudGlhbCB2ZWdldGF0aW9uLCA1LW1pbiAocmFtYW5rdXR0eSBhbmQgZm9sZXkpXCIsXCJPUk5MX0NMT1VEXCIsXCJwb3RlbnRpYWxfdmVnZXRhdGlvbl82ODRcIixcIjFcIiwyNzc3MzI3NTczLDJdIn0%3D/wilhend_687_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGJhIHJlZ2lvbmFsIG9yZ2FuaWMgc29pbCBjYXJib24gYW5kIG5pdHJvZ2VuIGRhdGEgKHppbmtlIGV0IGFsLilcIixcIk9STkxfQ0xPVURcIixcIlppbmtlX3NvaWxfNjgzXCIsXCIxXCIsMjc3NzMyNjkyNCwyXSIsInVtbSI6IltcImxiYSByZWdpb25hbCBvcmdhbmljIHNvaWwgY2FyYm9uIGFuZCBuaXRyb2dlbiBkYXRhICh6aW5rZSBldCBhbC4pXCIsXCJPUk5MX0NMT1VEXCIsXCJaaW5rZV9zb2lsXzY4M1wiLFwiMVwiLDI3NzczMjY5MjQsMl0ifQ%3D%3D/wilhend_687_1",
         "description": "This data set is a subset of a global vegetation and soils data set by Wilson and Henderson-Sellers (1985a). The subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) in South America (i.e., 10 N to 25 S, 30 to 85 W). The data are in ASCII GRID format.The original global data set (Wilson and Henderson-Sellers 1985a) is an archive of soil type and land cover data derived for use in general circulation models (GCMs). The data were collated from maps depicting natural vegetation, forestry, agriculture, land use, and soil, and they were archived at a resolution of 1 latitude by 1 longitude. The data set indicates soil type, soil data reliability, primary vegetation, secondary vegetation, and land cover data reliability. Approximately 50 land cover classifications are used, including categories for agricultural and urban uses. The inclusion of secondary vegetation type is particularly useful in areas with cover types that may have a fragmented distribution, such as in areas of urban development. The soil type data are classified according to climatically important properties for GCMs, and they indicate color (light, medium, or dark), texture, and drainage quality of the soil. The land cover data are compatible with the soils data, forming a coherent and consistent data set. The reliability of the land cover data is ranked on a scale of 1 to 5 (high to low). The reliability of the soil data is ranked as high, good, moderate, fair, or poor.Recommendations for the use of these data, as well as more detailed information can be found in Wilson and Henderson-Sellers (1985b).Further data set information can be found at ftp://daac.ornl.gov/data/lba/land_use_land_cover_change/wilhend/comp/wilhend_readme.pdf.LBA was a cooperative international research initiative led by Brazil. NASA was a lead sponsor for several experiments. LBA was designed to create the new knowledge needed to understand the climatological, ecological, biogeochemical, and hydrological functioning of Amazonia; the impact of land use change on these functions; and the interactions between Amazonia and the Earth system. More information about LBA can be found at http://www.daac.ornl.gov/LBA/misc_amazon.html.",
         "license": "proprietary"
     },
@@ -248841,7 +249127,7 @@
         "bbox": "-85, -25, -30, 10",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2779732234-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2779732234-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGFuZCBzdXJmYWNlIHBoZW5vbG9neSwgZWRkeSBjb3ZhcmlhbmNlIHRvd2VyIHNpdGVzLCBub3J0aCBhbWVyaWNhLCAyMDE3LTIwMjFcIixcIk9STkxfQ0xPVURcIixcIlBoZW5vbG9neV9BbWVyaUZsdXhfTmVvbl9TaXRlc18yMDMzXCIsXCIxXCIsMjc2NDY5MzIxMCwyXSIsInVtbSI6IltcImxhbmQgc3VyZmFjZSBwaGVub2xvZ3ksIGVkZHkgY292YXJpYW5jZSB0b3dlciBzaXRlcywgbm9ydGggYW1lcmljYSwgMjAxNy0yMDIxXCIsXCJPUk5MX0NMT1VEXCIsXCJQaGVub2xvZ3lfQW1lcmlGbHV4X05lb25fU2l0ZXNfMjAzM1wiLFwiMVwiLDI3NjQ2OTMyMTAsMl0ifQ%3D%3D/willmott_673_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wibGFuZCBzdXJmYWNlIG1vZGVsIChsc20gMS4wKSBmb3IgZWNvbG9naWNhbCwgaHlkcm9sb2dpY2FsLCBhdG1vc3BoZXJpYyBzdHVkaWVzXCIsXCJPUk5MX0NMT1VEXCIsXCJMU01fODA3XCIsXCIxXCIsMjk1NjUzOTI0NCwyXSIsInVtbSI6IltcImxhbmQgc3VyZmFjZSBtb2RlbCAobHNtIDEuMCkgZm9yIGVjb2xvZ2ljYWwsIGh5ZHJvbG9naWNhbCwgYXRtb3NwaGVyaWMgc3R1ZGllc1wiLFwiT1JOTF9DTE9VRFwiLFwiTFNNXzgwN1wiLFwiMVwiLDI5NTY1MzkyNDQsMl0ifQ%3D%3D/willmott_673_1",
         "description": "This data set is a subset of a 0.5-degree gridded temperature and precipitation data set for South America (Willmott and Webber 1998). This subset was created for the study area of the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA), defined as 10 N to 25 S, 30 to 85 W. The data are in ASCII GRID format. The data consist of the following: Monthly mean air temperature time series (1960-1990), in degrees C: monthly mean air temperatures for 1960-1990 cross validation errors associated with time series monthly mean air temperatures for 1960-1990, DEM assisted interpolation cross validation errors associated with DEM assisted interpolation time series Monthly mean air temperature climatology, in degrees C: climatic means of monthly and annual air temperatures cross validation errors associated with climatic means climatic means of monthly and annual mean air temperatures, DEM assisted interpolation cross validation errors associated with DEM assisted interpolation climatic means Monthly total precipitation time series (1960-1990), in millimeters: monthly precipitation totals for 1960-1990 cross validation errors associated with time series monthly precipitation totals for 1960-1990, climatologically aided interpolation cross validation errors associated with climatologically aided interpolation time series Monthly total precipitation climatology, in millimeters: climatic means of monthly and annual precipitation totals cross validation errors associated with climatic means More information about the full data set can be found at \"Willmott, Matsuura, and Collaborators' Global Climate Resource Pages\" (http://climate.geog.udel.edu/~climate) at the University of Delaware. To obtain the original documentation and data, follow the link for \"Available Climate Data,\" register or sign in, and follow the link for \"South American Climate Data.\" Information on the LBA subset can be found at ftp://daac.ornl.gov/data/lba/physical_climate/willmott/comp/willmott_readme.pdf. ",
         "license": "proprietary"
     },
@@ -248958,7 +249244,7 @@
         "bbox": "-100, 25, -60, 50",
         "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093948-ORNL_CLOUD.umm_json",
         "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2808093948-ORNL_CLOUD.html",
-        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wid29vZHkgYW5kIGhlcmJhY2VvdXMgdmVnZXRhdGlvbiBjaGFuZ2UgYWNyb3NzIHRoZSBzYXZhbm5hcyBvZiB3ZXN0IGFmcmljYSwgMTk4Mi0yMDEzXCIsXCJPUk5MX0NMT1VEXCIsXCJXQVZlVHJlbmRzXzE3MzhcIixcIjFcIiwyNzY0NzIyNzIwLDJdIiwidW1tIjoiW1wid29vZHkgYW5kIGhlcmJhY2VvdXMgdmVnZXRhdGlvbiBjaGFuZ2UgYWNyb3NzIHRoZSBzYXZhbm5hcyBvZiB3ZXN0IGFmcmljYSwgMTk4Mi0yMDEzXCIsXCJPUk5MX0NMT1VEXCIsXCJXQVZlVHJlbmRzXzE3MzhcIixcIjFcIiwyNzY0NzIyNzIwLDJdIn0%3D/woody_biomass_657_1",
+        "href": "https://cmr.earthdata.nasa.gov/stac/ORNL_CLOUD/collections?cursor=eyJqc29uIjoiW1wid2luZCBwcm9maWxlIGRhdGE6IGxpZGFyIC0gbm9hYSAoZmlmZSlcIixcIk9STkxfQ0xPVURcIixcImZpZmVfYXRtb3Nfd2luZF9saWRfMTM4XCIsXCIxXCIsMjk4MDcyMTI3MiwyXSIsInVtbSI6IltcIndpbmQgcHJvZmlsZSBkYXRhOiBsaWRhciAtIG5vYWEgKGZpZmUpXCIsXCJPUk5MX0NMT1VEXCIsXCJmaWZlX2F0bW9zX3dpbmRfbGlkXzEzOFwiLFwiMVwiLDI5ODA3MjEyNzIsMl0ifQ%3D%3D/woody_biomass_657_1",
         "description": "Estimates of the woody biomass density and pools were derived at the county scale of resolution of all forests of the eastern United States using new approaches for converting inventoried wood volume to estimates of above and belowground biomass.",
         "license": "proprietary"
     },
diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv
index fcef5ac3c..03fa14546 100644
--- a/nasa_cmr_catalog.tsv
+++ b/nasa_cmr_catalog.tsv
@@ -2423,18 +2423,18 @@ AST_L1B_003	ASTER L1B Registered Radiance at the Sensor V003	LPDAAC_ECS STAC Cat
 AST_L1T_003	ASTER Level 1 precision terrain corrected registered at-sensor radiance V003	LPDAAC_ECS STAC Catalog	2000-03-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1000000320-LPDAAC_ECS.umm_json	The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1 Precision Terrain Corrected Registered At-Sensor Radiance (AST_L1T) data contains calibrated at-sensor radiance, which corresponds with the ASTER Level 1B (AST_L1B) (https://doi.org/10.5067/ASTER/AST_L1B.003), that has been geometrically corrected, and rotated to a north-up UTM projection. The AST_L1T is created from a single resampling of the corresponding ASTER L1A (AST_L1A) (https://doi.org/10.5067/ASTER/AST_L1A.003) product. The bands available in the AST_L1T depend on the bands in the AST_L1A and can include up to three Visible and Near Infrared (VNIR) bands, six Shortwave Infrared (SWIR) bands, and five Thermal Infrared (TIR) bands. The AST_L1T dataset does not include the aft-looking VNIR band 3.    The precision terrain correction process incorporates GLS2000 digital elevation data with derived ground control points (GCPs) to achieve topographic accuracy for all daytime scenes where correlation statistics reach a minimum threshold. Alternate levels of correction are possible (systematic terrain, systematic, or precision) for scenes acquired at night or that otherwise represent a reduced quality ground image (e.g., cloud cover).    For daytime images, if the VNIR or SWIR telescope collected data and precision correction was attempted, each precision terrain corrected image will have an accompanying independent quality assessment. It will include the geometric correction available for distribution in both as a text file and a single band browse images with the valid GCPs overlaid.    This multi-file product also includes georeferenced full resolution browse images. The number of browse images and the band combinations of the images depends on the bands available in the corresponding (AST_L1A) (https://doi.org/10.5067/ASTER/AST_L1A.003) dataset. 	proprietary
 AST_L1T_031	ASTER Level 1 Precision Terrain Corrected Registered At-Sensor Radiance V031	LPDAAC_ECS STAC Catalog	2000-03-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2052604735-LPDAAC_ECS.umm_json	The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1 Precision Terrain Corrected Registered At-Sensor Radiance (AST_L1T) Version 3.1 data contains calibrated at-sensor radiance, which corresponds with the ASTER Level 1B AST_L1B  (https://doi.org/10.5067/ASTER/AST_L1B.003), that has been geometrically corrected and rotated to a north-up UTM projection. The AST_L1T V3.1 is created from a single resampling of the corresponding ASTER L1A AST_L1A (https://doi.org/10.5067/ASTER/AST_L1A.003) product. Radiometric calibration coefficients Version 5 (RCC V5) are applied to this product to improve the degradation curve derived from vicarious and lunar calibrations. The bands available in the AST_L1T V3.1 depend on the bands in the AST_L1A and can include up to three Visible and Near Infrared (VNIR) bands, six Shortwave Infrared (SWIR) bands, and five Thermal Infrared (TIR) bands. The AST_L1T V3.1 dataset does not include the aft-looking VNIR band 3.    The 3.1 version uses a precision terrain correction process that incorporates GLS2000 digital elevation data with derived ground control points (GCPs) to achieve topographic accuracy for all daytime scenes where correlation statistics reach a minimum threshold. Alternate levels of correction are possible (systematic terrain, systematic, or precision) for scenes acquired at night or that otherwise represent a reduced quality ground image (e.g., cloud cover).    For daytime images, if the VNIR or SWIR telescope collected data and precision correction was attempted, each precision terrain corrected image will have an accompanying independent quality assessment. It will include the geometric correction available for distribution in both a text file and a single band browse image with the valid GCPs overlaid.    This multi-file product also includes georeferenced full resolution browse images. The number of browse images and the band combinations of the images depend on the bands available in the corresponding AST_L1A dataset.    The AST_L1T V3.1 data product is only available through NASA’s Earthdata Search. The ASTER L1T V3.1 Order Instructions provide step-by-step directions for ordering this product.  	proprietary
 ATCS_0	The A-Train Cloud Segmentation Dataset	OB_DAAC STAC Catalog	2007-11-27		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2172083412-OB_DAAC.umm_json	ATCS is a dataset designed to train deep learning models to volumetrically segment clouds from multi-angle satellite imagery. The dataset consists of spatiotemporally aligned patches of multi-angle polarimetry from the POLDER sensor aboard the PARASOL mission and vertical cloud profiles from the 2B-CLDCLASS product using the cloud profiling radar (CPR) aboard CloudSat.	proprietary
-ATL02_006	ATLAS/ICESat-2 L1B Converted Telemetry Data V006	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.umm_json	This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.	proprietary
 ATL02_006	ATLAS/ICESat-2 L1B Converted Telemetry Data V006	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.umm_json	This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.	proprietary
+ATL02_006	ATLAS/ICESat-2 L1B Converted Telemetry Data V006	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2541211133-NSIDC_ECS.umm_json	This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations.	proprietary
 ATL03_006	ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2559919423-NSIDC_ECS.umm_json	This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.	proprietary
 ATL03_006	ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.umm_json	This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03.	proprietary
 ATL03_ANC_MASKS_1	ATLAS/ICESat-2 ATL03 Ancillary Masks, Version 1	NSIDCV0 STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2278879612-NSIDCV0.umm_json	This ancillary ICESat-2 data set contains four static surface masks (land ice, sea ice, land, and ocean) provided by ATL03 to reduce the volume of data that each surface-specific along-track data product is required to process. For example, the land ice surface mask directs the ATL06 land ice algorithm to consider data from only those areas of interest to the land ice community. Similarly, the sea ice, land, and ocean masks direct ATL07, ATL08, and ATL12 algorithms, respectively. A detailed description of all four masks can be found in section 4 of the Algorithm Theoretical Basis Document (ATBD) for ATL03 linked under technical references.	proprietary
 ATL04_006	ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2561045326-NSIDC_ECS.umm_json	ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL04_006	ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.umm_json	ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
-ATL06_006	ATLAS/ICESat-2 L3A Land Ice Height V006	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.umm_json	This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL06_006	ATLAS/ICESat-2 L3A Land Ice Height V006	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2564427300-NSIDC_ECS.umm_json	This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
+ATL06_006	ATLAS/ICESat-2 L3A Land Ice Height V006	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2670138092-NSIDC_CPRD.umm_json	This data set (ATL06) provides geolocated, land-ice surface heights (above the WGS 84 ellipsoid, ITRF2014 reference frame), plus ancillary parameters that can be used to interpret and assess the quality of the height estimates. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL07QL_006	ATLAS/ICESat-2 L3A Sea Ice Height Quick Look V006	NSIDC_ECS STAC Catalog	2024-06-21		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2548344839-NSIDC_ECS.umm_json	ATL07QL is the quick look version of ATL07. Once final ATL07 files are available, the corresponding ATL07QL files will be removed. ATL07 contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
-ATL07_006	ATLAS/ICESat-2 L3A Sea Ice Height V006	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.umm_json	The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL07_006	ATLAS/ICESat-2 L3A Sea Ice Height V006	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2564625052-NSIDC_ECS.umm_json	The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
+ATL07_006	ATLAS/ICESat-2 L3A Sea Ice Height V006	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2713030505-NSIDC_CPRD.umm_json	The data set (ATL07) contains along-track heights for sea ice and open water leads (at varying length scales) relative to the WGS84 ellipsoid (ITRF2014 reference frame) after adjustment for geoidal and tidal variations, and inverted barometer effects. Height statistics and apparent reflectance are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL08QL_006	ATLAS/ICESat-2 L3A Land and Vegetation Height Quick Look V006	NSIDC_ECS STAC Catalog	2024-05-10		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2548345108-NSIDC_ECS.umm_json	ATL08QL is the quick look version of ATL08. Once final ATL08 files are available the corresponding ATL08QL files will be removed.  ATL08 contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL08_006	ATLAS/ICESat-2 L3A Land and Vegetation Height V006	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2613553260-NSIDC_CPRD.umm_json	This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL08_006	ATLAS/ICESat-2 L3A Land and Vegetation Height V006	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2565090645-NSIDC_ECS.umm_json	This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
@@ -2442,35 +2442,35 @@ ATL09QL_006	ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric L
 ATL09_006	ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2607017115-NSIDC_ECS.umm_json	This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL09_006	ATLAS/ICESat-2 L3A Calibrated Backscatter Profiles and Atmospheric Layer Characteristics V006	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2649212495-NSIDC_CPRD.umm_json	This data set (ATL09) contains calibrated, attenuated backscatter profiles, layer integrated attenuated backscatter, and other parameters including cloud layer height and atmospheric characteristics obtained from the data. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL10QL_006	ATLAS/ICESat-2 L3A Sea Ice Freeboard Quick Look V006	NSIDC_ECS STAC Catalog	2024-06-21		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2551529078-NSIDC_ECS.umm_json	ATL10QL is the quick look version of ATL10. Once final ATL10 files are available the corresponding ATL10QL files will be removed. ATL10 contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
-ATL10_006	ATLAS/ICESat-2 L3A Sea Ice Freeboard V006	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.umm_json	This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL10_006	ATLAS/ICESat-2 L3A Sea Ice Freeboard V006	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2613553243-NSIDC_CPRD.umm_json	This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
-ATL11_006	ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006	NSIDC_CPRD STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2752556504-NSIDC_CPRD.umm_json	This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations.	proprietary
+ATL10_006	ATLAS/ICESat-2 L3A Sea Ice Freeboard V006	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2567856357-NSIDC_ECS.umm_json	This data set (ATL10) contains estimates of sea ice freeboard, calculated using three different approaches. Sea ice leads used to establish the reference sea surface and descriptive statistics used in the height estimates are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL11_006	ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006	NSIDC_ECS STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2750966856-NSIDC_ECS.umm_json	This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations.	proprietary
-ATL12_006	ATLAS/ICESat-2 L3A Ocean Surface Height V006	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json	This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
+ATL11_006	ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series V006	NSIDC_CPRD STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2752556504-NSIDC_CPRD.umm_json	This data set provides time series of land-ice surface heights derived from the ICESat-2 ATL06 Land Ice Height product. It is intended primarily as an input for higher level gridded products but can also be used on its own as a spatially organized product that allows easy access to height-change information derived from ICESat-2 observations.	proprietary
 ATL12_006	ATLAS/ICESat-2 L3A Ocean Surface Height V006	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2560378689-NSIDC_ECS.umm_json	This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
+ATL12_006	ATLAS/ICESat-2 L3A Ocean Surface Height V006	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2613553216-NSIDC_CPRD.umm_json	This data set (ATL12) contains along-track sea surface height of the global open ocean, including the ice-free seasonal ice zone and near-coast regions. Estimates of height distributions, significant wave height, sea state bias, and 10 m heights are also provided. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.	proprietary
 ATL13QL_006	ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data Quick Look V006	NSIDC_ECS STAC Catalog	2024-06-20		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2650092501-NSIDC_ECS.umm_json	ATL13QL is the quick look version of ATL13. Once final ATL13 files are available the corresponding ATL13QL files will be removed. ATL13 contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7 km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).	proprietary
 ATL13_006	ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2684928243-NSIDC_CPRD.umm_json	This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).	proprietary
 ATL13_006	ATLAS/ICESat-2 L3A Along Track Inland Surface Water Data V006	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2650116584-NSIDC_ECS.umm_json	This data set (ATL13) contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).	proprietary
-ATL14_003	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003	NSIDC_CPRD STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json	ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR).   ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.	proprietary
 ATL14_003	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003	NSIDC_ECS STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2776464127-NSIDC_ECS.umm_json	ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR).   ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.	proprietary
-ATL14_004	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004	NSIDC_ECS STAC Catalog	2019-01-01	2023-12-28	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json	This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).	proprietary
+ATL14_003	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V003	NSIDC_CPRD STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2776895337-NSIDC_CPRD.umm_json	ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR).   ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.	proprietary
 ATL14_004	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004	NSIDC_CPRD STAC Catalog	2019-01-01	2023-12-28	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3162179692-NSIDC_CPRD.umm_json	This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).	proprietary
-ATL15_003	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003	NSIDC_CPRD STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json	ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR).   ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.	proprietary
+ATL14_004	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height V004	NSIDC_ECS STAC Catalog	2019-01-01	2023-12-28	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3159684163-NSIDC_ECS.umm_json	This data set contains a high-resolution (100 m) gridded digital elevation model (DEM) for the Antarctic ice sheet and regions around the Arctic. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).	proprietary
 ATL15_003	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003	NSIDC_ECS STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2776464171-NSIDC_ECS.umm_json	ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR).   ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.	proprietary
-ATL15_004	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004	NSIDC_CPRD STAC Catalog	2019-01-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3162334027-NSIDC_CPRD.umm_json	This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).	proprietary
+ATL15_003	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V003	NSIDC_CPRD STAC Catalog	2019-03-29		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2776895930-NSIDC_CPRD.umm_json	ATL14 and ATL15 bring the time-varying height estimates provided in ATLAS/ICESat-2 L3B Annual Land Ice Height (ATL11) into a gridded format. ATL14 is a high-resolution (100 m) digital elevation model (DEM) that provides spatially continuous gridded data of ice sheet surface height. The data can be used to initialize ice sheet models, as boundary conditions for atmospheric models, or to help with the reduction of other satellite data such as optical imagery or synthetic aperture radar (SAR).   ATL15 provides coarser resolution (1 km, 10 km, 20 km, and 40 km) height-change maps at 3-month intervals, allowing for visualization of height-change patterns and calculation of integrated regional volume change.	proprietary
 ATL15_004	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004	NSIDC_ECS STAC Catalog	2019-01-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3159684532-NSIDC_ECS.umm_json	This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).	proprietary
+ATL15_004	ATLAS/ICESat-2 L3B Gridded Antarctic and Arctic Land Ice Height Change V004	NSIDC_CPRD STAC Catalog	2019-01-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3162334027-NSIDC_CPRD.umm_json	This data set contains land ice height changes and change rates for the Antarctic ice sheet and regions around the Arctic gridded at four spatial resolutions (1 km, 10 km, 20 km, and 40 km). The data are derived from the ATLAS/ICESat-2 L3B Slope-Corrected Land Ice Height Time Series product (ATL11).	proprietary
 ATL16_005	ATLAS/ICESat-2 L3B Weekly Gridded Atmosphere V005	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2769337070-NSIDC_CPRD.umm_json	This product reports weekly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency.	proprietary
 ATL16_005	ATLAS/ICESat-2 L3B Weekly Gridded Atmosphere V005	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2737997243-NSIDC_ECS.umm_json	This product reports weekly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency.	proprietary
 ATL17_005	ATLAS/ICESat-2 L3B Monthly Gridded Atmosphere V005	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2769338020-NSIDC_CPRD.umm_json	This data set contains a gridded summary of monthly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency.	proprietary
 ATL17_005	ATLAS/ICESat-2 L3B Monthly Gridded Atmosphere V005	NSIDC_ECS STAC Catalog	2018-10-13		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2737997483-NSIDC_ECS.umm_json	This data set contains a gridded summary of monthly global cloud fraction, total column optical depth over the oceans, polar cloud fraction, blowing snow frequency, apparent surface reflectivity, and ground detection frequency.	proprietary
 ATL19_003	ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -88, 180, 88	https://cmr.earthdata.nasa.gov/search/concepts/C2754956786-NSIDC_CPRD.umm_json	This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography.	proprietary
 ATL19_003	ATLAS/ICESat-2 L3B Monthly Gridded Dynamic Ocean Topography V003	NSIDC_ECS STAC Catalog	2018-10-13		-180, -88, 180, 88	https://cmr.earthdata.nasa.gov/search/concepts/C2746899536-NSIDC_ECS.umm_json	This data set contains monthly gridded dynamic ocean topography (DOT), derived from along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided in this data set. Both single beam and all-beam gridded averages are available in this data set. Single beam averages are useful to identify biases among the beams and the all-beam averages are advised to use for physical oceanography.	proprietary
-ATL20_004	ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2753295020-NSIDC_CPRD.umm_json	ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection.	proprietary
 ATL20_004	ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2666857908-NSIDC_ECS.umm_json	ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection.	proprietary
-ATL21_003	ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json	ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids.	proprietary
+ATL20_004	ATLAS/ICESat-2 L3B Daily and Monthly Gridded Sea Ice Freeboard V004	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2753295020-NSIDC_CPRD.umm_json	ATL20 contains daily and monthly gridded estimates of sea ice freeboard, derived from along-track freeboard estimates in the ATLAS/ICESat-2 L3A Sea Ice Freeboard product (ATL10). Data are gridded at 25 km using the SSM/I Polar Stereographic Projection.	proprietary
 ATL21_003	ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2753316241-NSIDC_CPRD.umm_json	ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids.	proprietary
-ATL22_003	ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -88, 180, 88	https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json	ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers.	proprietary
+ATL21_003	ATLAS/ICESat-2 L3B Daily and Monthly Gridded Polar Sea Surface Height Anomaly V003	NSIDC_ECS STAC Catalog	2018-10-14		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2737912334-NSIDC_ECS.umm_json	ATL21 contains daily and monthly gridded polar sea surface height (SSH) anomalies, derived from the along-track ATLAS/ICESat-2 L3A Sea Ice Height product (ATL10, V6). The ATL10 product identifies leads in sea ice and establishes a reference sea surface used to estimate SSH in 10 km along-track segments. ATL21 aggregates the ATL10 along-track SSH estimates and computes daily and monthly gridded SSH anomaly in NSIDC Polar Stereographic Northern and Southern Hemisphere 25 km grids.	proprietary
 ATL22_003	ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003	NSIDC_ECS STAC Catalog	2018-10-14		-180, -88, 180, 88	https://cmr.earthdata.nasa.gov/search/concepts/C2738530540-NSIDC_ECS.umm_json	ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers.	proprietary
+ATL22_003	ATLAS/ICESat-2 L3B Mean Inland Surface Water Data V003	NSIDC_CPRD STAC Catalog	2018-10-14		-180, -88, 180, 88	https://cmr.earthdata.nasa.gov/search/concepts/C2761722214-NSIDC_CPRD.umm_json	ATL22 is a derivative of the continuous Level 3A ATL13 Along Track Inland Surface Water Data product. ATL13 contains the high-resolution, along-track inland water surface profiles derived from analysis of the geolocated photon clouds from the ATL03 product. Starting from ATL13, ATL22 computes the mean surface water quantities with no additional photon analysis. The two data products, ATL22 and ATL13, can be used in conjunction as they include the same orbit and water body nomenclature independent from version numbers.	proprietary
 ATL23_001	ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001	NSIDC_ECS STAC Catalog	2018-10-13		-180, -88, 180, 88	https://cmr.earthdata.nasa.gov/search/concepts/C2692731693-NSIDC_ECS.umm_json	This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates.	proprietary
 ATL23_001	ATLAS/ICESat-2 L3B Monthly 3-Month Gridded Dynamic Ocean Topography V001	NSIDC_CPRD STAC Catalog	2018-10-13		-180, -88, 180, 88	https://cmr.earthdata.nasa.gov/search/concepts/C2765424272-NSIDC_CPRD.umm_json	This data set contains 3-month gridded averages of dynamic ocean topography (DOT) over midlatitude, north-polar, and south-polar grids derived from the along-track ATLAS/ICESat-2 L3A Ocean Surface Height product (ATL12). Monthly gridded sea surface height (SSH) can be calculated by adding the mean DOT and the weighted average geoid height also provided. Both single beam and all-beam gridded averages are available. Simple averages, degree-of-freedom averages, and averages interpolated to the center of grid cells are included, as well as uncertainty estimates.	proprietary
 ATLAS_DEALIASED_SASS_L2_1	SEASAT SCATTEROMETER DEALIASED OCEAN WIND VECTORS (Atlas)	POCLOUD STAC Catalog	1978-07-07	1978-10-10	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2617197627-POCLOUD.umm_json	Contains wind speeds and directions derived from the Seasat-A Scatterometer (SASS), presented chronologically by swath for the period between 7 July 1978 and 10 October 1978. Robert Atlas et al. (1987) produced this product using an objective ambiguity removal scheme to dealias the wind vector data binned at 100 km cells, which were calculated by Frank Wentz.	proprietary
@@ -6156,12 +6156,12 @@ GISS-CMIP5_1	GISS ModelE2 contributions to the CMIP5 archive	NCCS STAC Catalog	0
 GIS_EastAngliaClimateMonthly_551_1	Global Monthly Climatology for the Twentieth Century (New et al.)	ORNL_CLOUD STAC Catalog	1900-01-01	1998-12-31	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2780535151-ORNL_CLOUD.umm_json	A 0.5 degree lat/lon data set of monthly surface climate over global land areas, excluding Antarctica. Primary variables are interpolated directly from station time-series: precipitation, mean temperature and diurnal temperature range.	proprietary
 GLAH01_033	GLAS/ICESat L1A Global Altimetry Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153547306-NSIDC_CPRD.umm_json	Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter.  Each data granule has an associated browse product.	proprietary
 GLAH01_033	GLAS/ICESat L1A Global Altimetry Data (HDF5) V033	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1000000400-NSIDC_ECS.umm_json	Level-1A altimetry data (GLAH01) include the transmitted and received waveform from the altimeter.  Each data granule has an associated browse product.	proprietary
-GLAH02_033	GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json	GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.	proprietary
 GLAH02_033	GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C189991862-NSIDC_ECS.umm_json	GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.	proprietary
+GLAH02_033	GLAS/ICESat L1A Global Atmosphere Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153547430-NSIDC_CPRD.umm_json	GLAH02 Level-1A atmospheric data include the normalized relative backscatter for the 532 nm and 1064 nm channels, and low-level instrument corrections such as laser energy (1064 nm and 532 nm), photon coincidence (532 nm), and detector gain correction (1064 nm). Each data granule has an associated browse product.	proprietary
 GLAH03_033	GLAS/ICESat L1A Global Engineering Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153547514-NSIDC_CPRD.umm_json	Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02.	proprietary
 GLAH03_033	GLAS/ICESat L1A Global Engineering Data (HDF5) V033	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C189991863-NSIDC_ECS.umm_json	Level-1A global engineering data (GLAH03) include satellite housekeeping data used to calibrate data values for GLA01 and GLA02.	proprietary
-GLAH04_033	GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json	Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing.	proprietary
 GLAH04_033	GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C189991864-NSIDC_ECS.umm_json	Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing.	proprietary
+GLAH04_033	GLAS/ICESat L1A Global Laser Pointing Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153547635-NSIDC_CPRD.umm_json	Level-1A global laser pointing data (GLAH04) contain two orbits of attitude data from the spacecraft star tracker, instrument star tracker, gyro, and laser reference system, and other spacecraft attitude data required to calculate precise laser pointing.	proprietary
 GLAH05_034	GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549166-NSIDC_CPRD.umm_json	GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization).  Each data granule has an associated browse product.	proprietary
 GLAH05_034	GLAS/ICESat L1B Global Waveform-based Range Corrections Data (HDF5) V034	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1000000460-NSIDC_ECS.umm_json	GLAH05 Level-1B waveform parameterization data include output parameters from the waveform characterization procedure and other parameters required to calculate surface slope and relief characteristics. GLAH05 contains parameterizations of both the transmitted and received pulses and other characteristics from which elevation and footprint-scale roughness and slope are calculated. The received pulse characterization uses two implementations of the retracking algorithms: one tuned for ice sheets, called the standard parameterization, used to calculate surface elevation for ice sheets, oceans, and sea ice; and another for land (the alternative parameterization).  Each data granule has an associated browse product.	proprietary
 GLAH06_034	GLAS/ICESat L1B Global Elevation Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2033638023-NSIDC_CPRD.umm_json	GLAH06 Level-1B Global Elevation is a product that is analogous to the geodetic data records distributed for radar altimetry missions. It contains elevations previously corrected for tides, atmospheric delays, and surface characteristics within the footprint. Elevation is calculated using the ice sheet parameterization. Additional information allows the user to calculate an elevation based on land, sea ice, or ocean algorithms. Each data granule has an associated browse product.	proprietary
@@ -6172,18 +6172,18 @@ GLAH08_033	GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol L
 GLAH08_033	GLAS/ICESat L2 Global Planetary Boundary Layer and Elevated Aerosol Layer Heights (HDF5) V033	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1631093696-NSIDC_ECS.umm_json	GLAH08 Level-2 planetary boundary layer (PBL) and elevated aerosol layer heights data contains PBL heights, ground detection heights, and top and bottom heights of elevated aerosols from -1.5 km to 20.5 km (4 sec sampling rate) and from 20.5 km to 41 km (20 sec sampling rate).  Each data granule has an associated browse product.	proprietary
 GLAH09_033	GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549579-NSIDC_CPRD.umm_json	GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz.  Each data granule has an associated browse product.	proprietary
 GLAH09_033	GLAS/ICESat L2 Global Cloud Heights for Multi-layer Clouds (HDF5) V033	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C189991869-NSIDC_ECS.umm_json	GLAH09 Level-2 cloud heights for multi-layer clouds contain cloud layer top and bottom height data at sampling rates of 4 sec, 1 sec, 5 Hz, and 40 Hz.  Each data granule has an associated browse product.	proprietary
-GLAH10_033	GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-09-25	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json	GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds.  Each data granule has an associated browse product.	proprietary
 GLAH10_033	GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033	NSIDC_ECS STAC Catalog	2003-09-25	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C189991870-NSIDC_ECS.umm_json	GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds.  Each data granule has an associated browse product.	proprietary
-GLAH11_033	GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json	GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.	proprietary
+GLAH10_033	GLAS/ICESat L2 Global Aerosol Vertical Structure Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-09-25	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549654-NSIDC_CPRD.umm_json	GLAH10 Level-2 aerosol vertical structure data contain the attenuation-corrected cloud and aerosol backscatter and extinction profiles at a 4 sec sampling rate for aerosols and a 1 sec rate for clouds.  Each data granule has an associated browse product.	proprietary
 GLAH11_033	GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C189991871-NSIDC_ECS.umm_json	GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.	proprietary
-GLAH12_034	GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
+GLAH11_033	GLAS/ICESat L2 Global Thin Cloud/Aerosol Optical Depths Data (HDF5) V033	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549738-NSIDC_CPRD.umm_json	GLAH11 Level-2 thin cloud/aerosol optical depths data contain thin cloud and aerosol optical depths. A thin cloud is one that does not completely attenuate the lidar signal return, which generally corresponds to clouds with optical depths less than about 2.0. Each data granule has an associated browse product.	proprietary
 GLAH12_034	GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1000000461-NSIDC_ECS.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
-GLAH13_034	GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
+GLAH12_034	GLAS/ICESat L2 Global Antarctic and Greenland Ice Sheet Altimetry Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549818-NSIDC_CPRD.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
 GLAH13_034	GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1000000464-NSIDC_ECS.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
-GLAH14_034	GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
+GLAH13_034	GLAS/ICESat L2 Sea Ice Altimetry Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153549910-NSIDC_CPRD.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
 GLAH14_034	GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1000000443-NSIDC_ECS.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
-GLAH15_034	GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
+GLAH14_034	GLAS/ICESat L2 Global Land Surface Altimetry Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153551318-NSIDC_CPRD.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
 GLAH15_034	GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034	NSIDC_CPRD STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C2153552369-NSIDC_CPRD.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
+GLAH15_034	GLAS/ICESat L2 Ocean Altimetry Data (HDF5) V034	NSIDC_ECS STAC Catalog	2003-02-20	2009-10-11	-180, -86, 180, 86	https://cmr.earthdata.nasa.gov/search/concepts/C1000000420-NSIDC_ECS.umm_json	GLAH06 is used in conjunction with GLAH05 to create the Level-2 altimetry products. Level-2 altimetry data provide surface elevations for ice sheets (GLAH12), sea ice (GLAH13), land (GLAH14), and oceans (GLAH15). Data also include the laser footprint geolocation and reflectance, as well as geodetic, instrument, and atmospheric corrections for range measurements. The Level-2 elevation products, are regional products archived at 14 orbits per granule, starting and stopping at the same demarcation (± 50° latitude) as GLAH05 and GLAH06. Each regional product is processed with algorithms specific to that surface type. Surface type masks define which data are written to each of the products. If any data within a given record fall within a specific mask, the entire record is written to the product. Masks can overlap: for example, non-land data in the sea ice region may be written to the sea ice and ocean products. This means that an algorithm may write the same data to more than one Level-2 product. In this case, different algorithms calculate the elevations in their respective products. The surface type masks are versioned and archived at NSIDC, so users can tell which data to expect in each product.  Each data granule has an associated browse product.	proprietary
 GLCHMK_001	G-LiHT Canopy Height Model KML V001	LPCLOUD STAC Catalog	2011-06-30		-170, 10, -50, 73	https://cmr.earthdata.nasa.gov/search/concepts/C2763264695-LPCLOUD.umm_json	Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT(https://gliht.gsfc.nasa.gov/)) mission utilizes a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico.    The purpose of G-LiHT’s Canopy Height Model Keyhole Markup Language (KML) data product (GLCHMK) is to provide LiDAR-derived maximum canopy height and canopy variability information to aid in the study and analysis of biodiversity and climate change. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed.      GLCHMK data are processed as a Google Earth overlay KML file at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the canopy height with a color map applied in JPEG format. 	proprietary
 GLCHMT_001	G-LiHT Canopy Height Model V001	LPCLOUD STAC Catalog	2011-06-30		-170, 10, -50, 73	https://cmr.earthdata.nasa.gov/search/concepts/C2763264702-LPCLOUD.umm_json	Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT(https://gliht.gsfc.nasa.gov/)) mission utilizes a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico.    The purpose of G-LiHT’s Canopy Height Model data product (GLCHMT) is to provide LiDAR-derived maximum canopy height and canopy variability information to aid in the study and analysis of biodiversity and climate change. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed.    GLCHMT data are processed as a raster data product (GeoTIFF) at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the canopy height with a color map applied in JPEG format.   	proprietary
 GLDAS_CLM10SUBP_3H_001	GLDAS CLM Land Surface Model L4 3 hourly 1.0 x 1.0 degree Subsetted V001 (GLDAS_CLM10SUBP_3H) at GES DISC	GES_DISC STAC Catalog	1979-01-02	2020-03-31	-180, -60, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1279404074-GES_DISC.umm_json	With the upgraded Land Surface Models (LSMs) and updated forcing data sets, the GLDAS version 2.1 (GLDAS-2.1) production stream serves as a replacement for GLDAS-001.  The entire GLDAS-001 collection from January 1979 through March 2020 was decommissioned on June 30, 2020 and removed from the GES DISC system.  However, the replacement for GLDAS-001 monthly and 3-hourly 1.0 x 1.0 degree products from CLM Land Surface Model  currently are not available yet. Once their replacement data products become available, the DOIs of GLDAS-001 CLM data products will direct to the GLDAS-2.1 CLM data products.  This data set contains a series of land surface parameters simulated from the Common Land Model (CLM) V2.0 model in the Global Land Data Assimilation System (GLDAS). The data are in 1.0 degree resolution and range from January 1979 to present. The temporal resolution is 3-hourly.   This simulation was forced by a combination of NOAA/GDAS atmospheric analysis fields, spatially and temporally disaggregated NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) fields, and observation based downward shortwave and longwave radiation fields derived using the method of the Air Force Weather Agency's AGRicultural METeorological modeling system (AGRMET). The simulation was initialized on 1 January 1979 using soil moisture and other state fields from a GLDAS/CLM model climatology for that day of the year.   WGRIB or another GRIB reader is required to read the files. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units.   For more information, please see the README document.	proprietary
@@ -9488,6 +9488,7 @@ MASTER_DFRC_September_2006_2022_1	MASTER: Airborne Science, Western US, Septembe
 MASTER_FIREX_AQ_JulySept_2019_1941_1.2	MASTER: FIREX-AQ Airborne Campaign, Western-Central USA, Summer 2019	ORNL_CLOUD STAC Catalog	2019-07-22	2019-09-03	-121.51, 30.79, -83.16, 48.92	https://cmr.earthdata.nasa.gov/search/concepts/C2731654186-ORNL_CLOUD.umm_json	This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) program during 21 flights aboard a NASA DC-8 aircraft over the central and western U.S. from 2019-07-22 to 2019-09-03. The purpose of these flights was to measure emissions and to characterize the aerosols in the smoke plume above and downwind of the fire, and to determine the overall spatial extent of wildfires and prescribed fires. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 20-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.	proprietary
 MASTER_FireSense_2023_2330_1	MASTER: FireSense, western US, October 2023	ORNL_CLOUD STAC Catalog	2023-10-16	2023-10-26	-120.17, 33.02, -112.05, 39.21	https://cmr.earthdata.nasa.gov/search/concepts/C3140367418-ORNL_CLOUD.umm_json	This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected as part of the FireSense project during 11 flights aboard a NASA B200 aircraft over California, Nevada, Utah, and Arizona, U.S., 2023-10-16 to 2023-10-26. The FireSense project is focused on delivering NASA's unique Earth science and technological capabilities to operational agencies, striving towards measurable improvement in US wildland fire management. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 10-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes flight paths, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.	proprietary
 MASTER_Flightline_Locator_2151_1.0	MASTER: Flight Line Geospatial Polygons and Contextual Data	ORNL_CLOUD STAC Catalog	1998-12-02	2023-05-02	-171.99, -55.38, 179.47, 78.68	https://cmr.earthdata.nasa.gov/search/concepts/C2731799041-ORNL_CLOUD.umm_json	This dataset provides resources for identifying flight lines of interest for the MODIS/ASTER Airborne Simulator (MASTER) instrument based on spatial and temporal criteria. MASTER first flew in 1998 and has ongoing deployments as a Facility Instrument in the NASA Airborne Science Program (ASP). MASTER is a joint project involving the Airborne Sensor Facility (ASF) at the Ames Research Center, the Jet Propulsion Laboratory (JPL), and the Earth Resources Observation and Science Center (EROS).  The primary goal of these airborne campaigns is to demonstrate important science and applications research that is uniquely enabled by the full suite of MASTER thermal infrared bands as well as the contiguous spectroscopic measurements of the AVIRIS (also flown in similar campaigns), or combinations of measurements from both instruments. This dataset includes a table of flight lines with dates, bounding coordinates, site names, investigators involved, flight attributes, and associated campaigns for the MASTER Facility Instrument Collection. A shapefile containing flights for all years, a GeoJSON version of the shapefile, and separate KMZ files for each year allow users to visualize flight line locations using GIS software.	proprietary
+MASTER_GEMx_Spring_2024_2370_1	MASTER: Geological Earth Mapping Experiment (GEMx), Spring 2024	ORNL_CLOUD STAC Catalog	2024-04-02	2024-06-28	-124.26, 31.14, -108.08, 43.2	https://cmr.earthdata.nasa.gov/search/concepts/C3255928163-ORNL_CLOUD.umm_json	This dataset includes Level 1B (L1B) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during 30 flights aboard a NASA ER-2 aircraft over California, Oregon, Nevada, and Arizona, US, from 2024-04-02 to 2024-06-28. The Geological Earth Mapping Experiment (GEMx) research project used NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Hyperspectral Thermal Emission Spectrometer (HyTES), and MODIS/ASTER Airborne Simulator (MASTER) instruments to collect the measurements over the country's arid and semi-arid regions, including parts of California, Nevada, Arizona, and New Mexico, to map portions of southwest US for critical minerals. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. The L1B file format is HDF-4. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file. Level 2 products from these GEMx flights will be added to this dataset when they become available.	proprietary
 MASTER_GEMx_Summer_2023_2319_1	MASTER: Geological Earth Mapping Experiment (GEMx), California-Arizona, Summer 2023	ORNL_CLOUD STAC Catalog	2023-04-25	2023-09-26	-129.38, 31.86, -112.49, 45.09	https://cmr.earthdata.nasa.gov/search/concepts/C2905518711-ORNL_CLOUD.umm_json	This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during 13 flights aboard a NASA ER-2 aircraft over California, Oregon, Nevada, and Arizona, US, from 2023-04-25 to 2023-09-26. The Geological Earth Mapping Experiment (GEMx) research project used NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), Hyperspectral Thermal Emission Spectrometer (HyTES), and MODIS/ASTER Airborne Simulator (MASTER) instruments to collect the measurements over the country's arid and semi-arid regions, including parts of California, Nevada, Arizona, and New Mexico, to map portions of southwest US for critical minerals. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in five bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.	proprietary
 MASTER_Hawaii_October_2001_V2_2142_2	MASTER: Airborne Science, Hawaii-Pacific Ocean-western US, Fall, 2001, V2	ORNL_CLOUD STAC Catalog	2001-10-14	2001-11-15	-166.7, 18.71, -106.88, 40.98	https://cmr.earthdata.nasa.gov/search/concepts/C2731786496-ORNL_CLOUD.umm_json	This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The spectral data were collected during 19 flights aboard a NASA ER-2 aircraft over Hawaii, eastern Pacific Ocean, and western U.S. from 2001-10-14 to 2001-11-14. Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.	proprietary
 MASTER_Houston_2010_2126_1	MASTER: BP Oil Spill Mapping, Louisiana-Gulf of Mexico-Wisconsin, Fall, 2010	ORNL_CLOUD STAC Catalog	2010-07-31	2010-09-01	-115.97, 23.06, -81.47, 48.92	https://cmr.earthdata.nasa.gov/search/concepts/C2731781485-ORNL_CLOUD.umm_json	This dataset includes Level 1B (L1B) and Level 2 (L2) data products from the MODIS/ASTER Airborne Simulator (MASTER) instrument. The raw data were collected during 9 flights aboard a NASA ER-2 aircraft over the Gulf of Mexico and portions of California, Colorado, Arizona, Utah, Idaho, New Mexico, Texas, Arkansas, Illinois, Wisconsin, Michigan, Louisiana, Mississippi, and Florida from 2010-07-31 to 2010-09-01. A primary purpose of this deployment was to collect imagery related to the Deepwater Horizon-BP Oil Spill that occurred in late April 2010 in the Gulf of Mexico.  Data products include L1B georeferenced multispectral imagery of calibrated radiance in 50 bands covering wavelengths of 0.460 to 12.879 micrometers at approximately 50-meter spatial resolution. Derived L2 data products are emissivity in 5 bands in thermal infrared range (8.58 to 12.13 micrometers) and land surface temperature. The L1B file format is HDF-4, and L2 products are provided in ENVI and KMZ formats. In addition, the dataset includes the flight path, spectral band information, instrument configuration, ancillary notes, and summary information for each flight, and browse images derived from each L1B data file.	proprietary
@@ -9570,13 +9571,9 @@ MCD12Q2_061	MODIS/Terra+Aqua Land Cover Dynamics Yearly L3 Global 500m SIN Grid
 MCD14DL_C5_NRT_005	MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT	LM_FIRMS STAC Catalog	2014-01-28		-180, -80, 180, 80	https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.umm_json	Near Real-Time (NRT) MODIS Thermal Anomalies / Fire locations processed by FIRMS (Fire Information for Resource Management System) - Land Atmosphere Near real time Capability for EOS (LANCE), using swath products (MOD14/MYD14) rather than the tiled MOD14A1 and MYD14A1 products. The thermal anomalies / active fire represent the center of a 1km pixel that is flagged by the MODIS MOD14/MYD14 Fire and Thermal Anomalies algorithm (Giglio 2003) as containing one or more fires within the pixel. This is the most basic fire product in which active fires and other thermal anomalies, such as volcanoes, are identified.MCD14DL are available in the following formats: TXT, SHP, KML, WMS. These data are also provided through the FIRMS Fire Email Alerts. Please note only the TXT and SHP files contain all the attributes.	proprietary
 MCD15A2H_061	MODIS/Terra+Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V061	LPCLOUD STAC Catalog	2002-07-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2222147000-LPCLOUD.umm_json	The MCD15A2H Version 6.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Level 4, Combined Fraction of Photosynthetically Active Radiation (FPAR), and Leaf Area Index (LAI) product is an 8-day composite dataset with 500 meter pixel size. The algorithm chooses the best pixel available from all the acquisitions of both MODIS sensors located on NASA’s Terra and Aqua satellites from within the 8-day period.    LAI is defined as the one-sided green leaf area per unit ground area in broadleaf canopies and as one-half the total needle surface area per unit ground area in coniferous canopies. FPAR is defined as the fraction of incident photosynthetically active radiation (400-700 nm) absorbed by the green elements of a vegetation canopy.    The LAI product has attained stage 2 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation and the FPAR product has attained stage 1 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation.    Improvements/Changes from Previous Versions     * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017.  * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).  	proprietary
 MCD15A3H_061	MODIS/Terra+Aqua Leaf Area Index/FPAR 4-Day L4 Global 500m SIN Grid V061	LPCLOUD STAC Catalog	2002-07-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2343110937-LPCLOUD.umm_json	The MCD15A3H Version 6.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Level 4, Combined Fraction of Photosynthetically Active Radiation (FPAR), and Leaf Area Index (LAI) product is a 4-day composite data set with 500 meter pixel size. The algorithm chooses the best pixel available from all the acquisitions of both MODIS sensors located on NASA’s Terra and Aqua satellites from within the 4-day period.  LAI is defined as the one-sided green leaf area per unit ground area in broadleaf canopies and as one-half the total needle surface area per unit ground area in coniferous canopies. FPAR is defined as the fraction of incident photosynthetically active radiation (400-700 nm) absorbed by the green elements of a vegetation canopy.  The LAI product has attained stage 2 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation and the FPAR product has attained stage 1 (https://landweb.modaps.eosdis.nasa.gov/cgi-bin/QA_WWW/newPage.cgi?fileName=maturity) validation.  Improvements/Changes from Previous Versions  * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).	proprietary
-MCD18A1_061	MODIS/Terra+Aqua Surface Radiation Daily/3-Hour L3 Global 1km SIN Grid V061	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2484080427-LPCLOUD.umm_json	The MCD18A1 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18A1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).   * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18A1 Version 6.1 product has an improved 1 km resolution over the 5 km Version 6. * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).   	proprietary
 MCD18A1_062	MODIS/Terra+Aqua Surface Radiation Daily/3-Hour L3 Global 1km SIN Grid V062	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2486249220-LPCLOUD.umm_json	The MCD18A1 Version 6.2 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).    Provided in the MOD18A1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.    Validation at stage 1 (https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site (https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).     The Version 6.2 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: 1) MODIS shortwave infrared bands are included in the retrieval algorithm, which significantly reduces estimation uncertainties in cloud- and snow-covered pixels.   2) An improved climatology of surface reflectance was produced and used in the retrieval algorithm.        	proprietary
-MCD18A2_061	MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 1km SIN Grid V061	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2484080763-LPCLOUD.umm_json	The MCD18A2 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Photosynthetically Active Radiation (PAR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of PAR every 3 hours. PAR is incident solar radiation in the visible spectrum (400-700 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident PAR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global PAR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18A2 product are layers for instantaneous PAR array for each individual MODIS overpass and 3-hour PAR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).    * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18A2 Version 6.1 product has an improved 1 km resolution over the 5 km Version 6. * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).	proprietary
 MCD18A2_062	MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 1km SIN Grid V062	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2486282714-LPCLOUD.umm_json	The MCD18A2 Version 6.2 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Photosynthetically Active Radiation (PAR) gridded Level 3 product produced daily at 1 kilometer pixel resolution with estimates of PAR every 3 hours. PAR is incident solar radiation in the visible spectrum (400-700 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident PAR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global PAR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).    Provided in the MOD18A2 product are layers for instantaneous PAR array for each individual MODIS overpass and 3-hour PAR array along with a View Zenith Angle layer.    Validation at stage 1 (https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site (https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).     The Version 6.2 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: 1) MODIS shortwave infrared bands are included in the retrieval algorithm, which significantly reduces estimation uncertainties in cloud- and snow-covered pixels.   2) An improved climatology of surface reflectance was produced and used in the retrieval algorithm.        	proprietary
-MCD18C1_061	MODIS/Terra+Aqua Downward Shortwave Radiation Daily/3-Hour L3 Global 0.05Deg CMG V061	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2484081120-LPCLOUD.umm_json	The MCD18C1 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG) with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18C1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).    * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).	proprietary
 MCD18C1_062	MODIS/Terra+Aqua Downward Shortwave Radiation Daily/3-Hour L3 Global 0.05Deg CMG V062	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2486287629-LPCLOUD.umm_json	The MCD18C1 Version 6.2 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Downward Shortwave Radiation (DSR) Level 3 product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG) with estimates of DSR every 3 hours. DSR is incident solar radiation over land surfaces in the shortwave spectrum (300-4,000 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident DSR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global DSR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).    Provided in the MOD18C1 product are layers for instantaneous DSR array for each individual MODIS overpass and 3-hour DSR array along with a View Zenith Angle layer.    Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).     The Version 6.2 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: 1) MODIS shortwave infrared bands are included in the retrieval algorithm, which significantly reduces estimation uncertainties in cloud- and snow-covered pixels.   2) An improved climatology of surface reflectance was produced and used in the retrieval algorithm.        	proprietary
-MCD18C2_061	MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 0.05Deg CMG V061	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2484081543-LPCLOUD.umm_json	The MCD18C2 Version 6.1 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Photosynthetically Active Radiation (PAR) gridded Level 3 product produced daily at 0.05 degree (5,600 meters at the equator) resolution with estimates of PAR every 3 hours. PAR is incident solar radiation in the visible spectrum (400-700 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident PAR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global PAR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).  Provided in the MOD18C2 product are layers for instantaneous PAR array for each individual MODIS overpass and 3-hour PAR array along with a View Zenith Angle layer.  Validation at stage 1 ( https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site ( https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).    * The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017. * A polarization correction has been applied to the L1B Reflective Solar Bands (RSB). * The MCD18 suite has added CMG products (MCD18C1/MCD18C2).	proprietary
 MCD18C2_062	MODIS/Terra+Aqua Photosynthetically Active Radiation Daily/3-Hour L3 Global 0.05Deg CMG V062	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2486294617-LPCLOUD.umm_json	The MCD18C2 Version 6.2 is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Photosynthetically Active Radiation (PAR) gridded Level 3 product produced daily at 0.05 degree (5,600 meters at the equator) resolution with estimates of PAR every 3 hours. PAR is incident solar radiation in the visible spectrum (400-700 nanometers) and is an important variable in land-surface models that address a variety of scientific and application issues. The MCD18 products are based on a prototyping algorithm that uses multi-temporal signatures of MODIS data to derive surface reflectance and then calculate incident PAR using the look-up table (LUT) approach. The LUTs consider different types of loadings of aerosols and clouds at a variety of illumination/viewing geometry. Global PAR products are generated from MODIS and geostationary satellite data. Additional details regarding the methodology used to create the data are available in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/106/MCD18_ATBD.pdf)).    Provided in the MOD18C2 product are layers for instantaneous PAR array for each individual MODIS overpass and 3-hour PAR array along with a View Zenith Angle layer.    Validation at stage 1 (https://modis-land.gsfc.nasa.gov/MODLAND_val.html) has been achieved for the MODIS Surface Radiation products. Further details regarding MODIS land product validation for the MCD18 data products are available from the MODIS Land Team Validation site (https://modis-land.gsfc.nasa.gov/ValStatus.php?ProductID=MCD18).     The Version 6.2 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: 1) MODIS shortwave infrared bands are included in the retrieval algorithm, which significantly reduces estimation uncertainties in cloud- and snow-covered pixels.   2) An improved climatology of surface reflectance was produced and used in the retrieval algorithm.        	proprietary
 MCD19A1CMGL_061	MODIS/Terra+Aqua Surface Reflectance (Bands 1-7) from MAIAC, Daily L3 Global 0.05Deg CMG V061	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2565807727-LPCLOUD.umm_json	The MCD19A1CMGL Version 6.1 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-Angle Implementation of Atmospheric Correction (MAIAC) Surface Reflectance Level 3 (Bands 1-7) product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The MCD19A1CMGL product is corrected for atmospheric gases and aerosols using a new MAIAC algorithm that is based on a time series analysis and a combination of pixel- and image-based processing. The MODIS MAIAC products provide an estimate of the surface spectral reflectance, also referred to as Bidirectional Reflectance Factor (BRF), as it would be measured at ground-level in the absence of atmospheric scattering or absorption. The Surface Reflectance dataset includes BRF, BRF normalized to a fixed geometry of solar zenith angle at 45° and nadir view, and Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) normalized to the nadir view and local sun angle at 1:30 pm.    The MCD19A1CMGL MAIAC Surface Reflectance product for land bands includes 25 Science Dataset (SDS) layers: BRF for bands 1-7, BRF normalized to a fixed geometry for bands 1-7, NBAR for bands 1-7, Quality Assessment (QA) bits, cosine of solar zenith angle, cosine of view zenith angle, and relative azimuth angle. A low-resolution browse is also included.  	proprietary
 MCD19A1CMGO_061	MODIS/Terra+Aqua Surface Reflectance (Bands 8-12) from MAIAC, Daily L3 Global 0.05Deg CMG V061	LPCLOUD STAC Catalog	2000-02-24		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2565807729-LPCLOUD.umm_json	The MCD19A1CMGO Version 6.1 data product is a Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua combined Multi-Angle Implementation of Atmospheric Correction (MAIAC) Surface Reflectance Level 3 (Bands 8-12) product produced daily in a 0.05 degree (5,600 meters at the equator) Climate Modeling Grid (CMG). The MCD19A1CMGO product is corrected for atmospheric gases and aerosols using a new MAIAC algorithm that is based on a time series analysis and a combination of pixel- and image-based processing. The MODIS MAIAC products provide an estimate of the surface spectral reflectance, also referred to as Bidirectional Reflectance Factor (BRF), as it would be measured at ground-level in the absence of atmospheric scattering or absorption. The Surface Reflectance dataset includes BRF, BRF normalized to a fixed geometry of solar zenith angle at 45° and nadir view, and Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) normalized to the nadir view and local sun angle at 1:30 pm.    The MCD19A1CMGO MAIAC Surface Reflectance product for ocean bands includes 19 Science Dataset (SDS) layers: BRF for bands 8-12, BRF normalized to a fixed geometry for bands 8-12, NBAR for bands 8-12, Quality Assessment (QA) bits, cosine of solar zenith angle, cosine of view zenith angle, and relative azimuth angle. A low-resolution browse is also included.	proprietary
@@ -9789,8 +9786,8 @@ MICRONESIAN_0	Measurements stretching across the Pacific Ocean to the Hawaiian I
 MIL1A_2	MISR Level 1A CCD Science data, all cameras V002	LARC STAC Catalog	2018-05-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C179031533-LARC.umm_json	MIL1A_2 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 1A CCD Science data, all cameras version 2. It is the Reformatted Annotated Level 1A product for the CCD science data. The data numbers (DN) have been commuted from 12-bit numbers to 16-bit byte aligned half-words. The MISR CCD Science Instrument Data acquired from all nine of the MISR cameras for each of the four bands represent the raw MISR input data staged for MISR Science Instrument Data processing. There are nine file granules of this type, one corresponding to each of the nine MISR cameras. Each file granule contains four entire swaths of data, one swath for each of the four MISR bands associated with each MISR camera. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm.	proprietary
 MIL2ASAE_002	MISR Level 2 Aerosol parameters V002	LARC STAC Catalog	2000-02-24	2017-06-01	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C43677706-LARC.umm_json	Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Level 2 Aerosol parameters V002 contains Aerosol optical depth and particle type, with associated atmospheric data.	proprietary
 MIL2ASAE_3	MISR Level 2 Aerosol parameters V003	LARC STAC Catalog	2000-03-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542385141-LARC.umm_json	MIL2ASAE_3 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 Aerosol parameters Version 3 product. It contains information on retrieved aerosol column amount, aerosol particle properties, and ancillary information based on Level 1B2 geolocated radiances observed by MISR. Data collection for this product is ongoing.     As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.	proprietary
-MIL2ASAF_002	MISR Level 2 FIRSTLOOK Aerosol parameters V002	LARC STAC Catalog	1999-12-18		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542382556-LARC.umm_json	This is the Level 2 FIRSTLOOK Aerosol Product. It contains Aerosol optical depth and particle type, with associated atmospheric data, produced using ancillary inputs from the previous time period.	proprietary
-MIL2ASLF_002	MISR Level 2 FIRSTLOOK Surface parameters V002	LARC STAC Catalog	1999-12-18		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542382559-LARC.umm_json	This Level 2 FIRSTLOOK Land Surface product contains directional reflectance properties,albedo(spectral & PAR integrated),FPAR,radiation parameters & terrain-referenced geometric parameters, produced using ancillary input from the previous time period.	proprietary
+MIL2ASAF_002	MISR Level 2 FIRSTLOOK Aerosol parameters V002	LARC STAC Catalog	2017-11-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542382556-LARC.umm_json	This is the Level 2 FIRSTLOOK Aerosol Product. It contains Aerosol optical depth and particle type, with associated atmospheric data, produced using ancillary inputs from the previous time period.	proprietary
+MIL2ASLF_002	MISR Level 2 FIRSTLOOK Surface parameters V002	LARC STAC Catalog	2017-11-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542382559-LARC.umm_json	This Level 2 FIRSTLOOK Land Surface product contains directional reflectance properties, albedo(spectral and PAR integrated), FPAR, radiation parameters, and terrain-referenced geometric parameters produced using ancillary input from the previous time period. MIL2ASLF_002 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 FIRSTLOOK Surface parameters version 2. It contains directional reflectance properties, albedo (spectral and photosynthetically active radiation (PAR) integrated), a fraction of photosynthetically active radiation absorbed by vegetation (FPAR), radiation parameters, and terrain-referenced geometric parameters produced using ancillary input from the previous time period. Data collection for this product is ongoing. This collection contains the Leaf Area Index (LAI).\r\n\r\nMulti-angle Imaging SpectroRadiometer (MISR) Level 2 Aerosol data products contain various information on the Earth's atmosphere. The aerosol data include tropospheric aerosol optical depth on 17. 6-km centers archived with a compositional model identifier and retrieval residuals, ancillary data including relative humidity, ozone optical depth, stratospheric aerosol optical depth, and retrieval flags. MISR multi-angle imagery will be used to monitor global and regional trends radiatively significant to optical properties (optical depth, single scattering albedo, and size distribution) and amounts (mass loading) of natural and anthropogenic aerosols, including those arising from industrial and volcanic emissions, slash-and-burn agriculture, and desertification. Coupled with MISR's determinations of top-of-atmosphere and surface albedos, these data will measure the global aerosol forcing of the shortwave planetary radiation budget. \r\n\r\nThe MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four forward, and four aftward. It takes seven minutes for all nine cameras to view the exact surface location. The view angles relative to the surface reference ellipsoid are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. MISR is designed to view Earth with cameras in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successfully imaged by all nine cameras in 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the effects of sunlight on Earth and distinguish different types of clouds, particles, and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.	proprietary
 MIL2ASLS_2	MISR Level 2 Surface parameters V002	LARC STAC Catalog	2000-02-24	2017-06-01	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C43677707-LARC.umm_json	MIL2ASLS_2 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 Land Surface parameters version 2 data product. It contains a variety of information on the Earth's surface; such ashemispherical directional reflectance factor (HDRF), bihemispherical reflectance (BHR) (i.e., albedo), bidirectional reflectance factor (BRF), directional hemispherical reflectance (DHR), BRF model parameters, Fractional absorbed Photosysenthetically Active Radiation (FPAR), and terrain-referenced view and illumination angles. A surface retrieval is conducted on regions for which valid land aerosol retrieval exists. The retrieval is performed using the corrected equivalent reflectances, retrieved aerosol parameters, and auxiliary information from the Simulated MISR Ancillary Radiative Transfer (SMART) dataset. The spectral and Photosynthetically Active spectral Region (PAR)-integrated BHR and DHR are retrieved, along with the spectral land HDRF and BRF and BRF model parameters, for all valid land and inland water subregions. Subregion surface classification and leaf area index (LAI) and regional FPAR are also determined. Subregion variability is also calculated for land regions. Data collection for this product was completed in June 2017.  The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm.  MISR itself is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the affects of sunlight on Earth, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.	proprietary
 MIL2ASLS_3	MISR Level 2 Surface parameters V003	LARC STAC Catalog	2000-03-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1542384334-LARC.umm_json	MIL2ASLS_3 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 2 Land Surface parameters version 3 data product. It contains a variety of information on the Earth's surface; such ashemispherical directional reflectance factor (HDRF), bihemispherical reflectance (BHR) (i.e., albedo), bidirectional reflectance factor (BRF), directional hemispherical reflectance (DHR), BRF model parameters, Fractional absorbed Photosysenthetically Active Radiation (FPAR), and terrain-referenced view and illumination angles. A surface retrieval is conducted on regions for which valid land aerosol retrieval exists. The retrieval is performed using the corrected equivalent reflectances, retrieved aerosol parameters, and auxiliary information from the Simulated MISR Ancillary Radiative Transfer (SMART) dataset. The spectral and Photosynthetically Active spectral Region (PAR)-integrated BHR and DHR are retrieved, along with the spectral land HDRF and BRF and BRF model parameters, for all valid land and inland water subregions. Subregion surface classification and leaf area index (LAI) and regional FPAR are also determined. Subregion variability is also calculated for land regions. Data collection for this product is ongoing. This collection contains Leaf Area Index (LAI).    The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm.    MISR itself is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the affects of sunlight on Earth, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.	proprietary
 MIL2TCAF_001	MISR Level 2 FIRSTLOOK TOA/Cloud Albedo parameters V001	LARC STAC Catalog	2007-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C135857533-LARC.umm_json	Multi-angle Imaging SpectroRadiometer (MISR) is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared). The goal of MISR is to improve our understanding of the fate of sunlight in Earth environment, as well as distinguish different types of clouds, particles and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure. MISR Level 2 FIRSTLOOK TOA/Cloud Albedo parameters V001 contains local, restrictive, and expansive albedo, with associated data, produced using ancillary inputs from the previous time period.	proprietary
@@ -11367,9 +11364,11 @@ OCO2_GEOS_L3CO2_DAY_10r	OCO-2 GEOS Level 3 daily, 0.5x0.625 assimilated CO2 V10r
 OCO2_GEOS_L3CO2_MONTH_10r	OCO-2 GEOS Level 3 monthly, 0.5x0.625 assimilated CO2 V10r (OCO2_GEOS_L3CO2_MONTH) at GES DISC	GES_DISC STAC Catalog	2014-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2240248790-GES_DISC.umm_json	This is the Gridded Monthly OCO-2 Carbon Dioxide assimilated dataset.    The OCO-2 mission provides the highest quality space-based XCO2 retrievals to date. However, the instrument data are characterized by large gaps in coverage due to OCO-2’s narrow 10-km ground track and an inability to see through clouds and thick aerosols. This global gridded dataset is produced using a data assimilation technique commonly referred to as state estimation within the geophysical literature. Data assimilation synthesizes simulations and observations, adjusting the state of atmospheric constituents like CO2 to reflect observed values, thus gap-filling observations when and where they are unavailable based on previous observations and short transport simulations by GEOS. Compared to other methods, data assimilation has the advantage that it makes estimates based on our collective scientific understanding, notably of the Earth’s carbon cycle and atmospheric transport.    OCO-2 GEOS (Goddard Earth Observing System) Level 3 data are produced by ingesting OCO-2 L2 retrievals every 6 hours with GEOS CoDAS, a modeling and data assimilation system maintained by NASA’s Global Modeling and Assimilation Office (GMAO). GEOS CoDAS uses a high-performance computing implementation of the Gridpoint Statistical Interpolation approach for solving the state estimation problem. GSI finds the analyzed state that minimizes the three-dimensional variational (3D-Var) cost function formulation of the state estimation problem.	proprietary
 OCO2_L1B_Calibration_10r	OCO-2 Level 1B calibrated, geolocated calibration spectra, Retrospective Processing V10r (OCO2_L1B_Calibration) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783883-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  Version 8r is the current version of the data set. Version 7r has been superseded by Version 8r. The Orbiting Carbon Observatory is the first NASA missiondesigned to collect space-based measurements of atmospheric carbon dioxidewith the precision, resolution, and coverage needed to characterize theprocesses controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and inmolecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time tothe Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO2_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L1B_Calibration_11.2	OCO-2 Level 1B calibrated, geolocated calibration spectra V11.2 (OCO2_L1B_Calibration) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913031060-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA missiondesigned to collect space-based measurements of atmospheric carbon dioxidewith the precision, resolution, and coverage needed to characterize theprocesses controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and inmolecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time tothe Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO2_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.	proprietary
+OCO2_L1B_Calibration_11.2r	OCO-2 Level 1B calibrated, geolocated calibration spectra Retrospective Processing V11.2r (OCO2_L1B_Calibration) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3090453484-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA missiondesigned to collect space-based measurements of atmospheric carbon dioxidewith the precision, resolution, and coverage needed to characterize theprocesses controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and inmolecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time tothe Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO2_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.	proprietary
 OCO2_L1B_Calibration_11r	OCO-2 Level 1B calibrated, geolocated calibration spectra, Retrospective Processing V11r (OCO2_L1B_Calibration) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248663235-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA missiondesigned to collect space-based measurements of atmospheric carbon dioxidewith the precision, resolution, and coverage needed to characterize theprocesses controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and inmolecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time tothe Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO2_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L1B_Science_10r	OCO-2 Level 1B calibrated, geolocated science spectra, Retrospective Processing V10r (OCO2_L1B_Science) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783889-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the output from the Level 1B process. It converts the raw instrument data numbers into calibrated radiances. This conversion is based upon files of instrument characteristics and algorithm parameters that may vary over time. In addition to calibrated radiances, the Level 1B output products have geolocation information recorded for each measurement for use in higher-level processes.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L1B_Science_11.2	OCO-2 Level 1B calibrated, geolocated science spectra V11.2 (OCO2_L1B_Science) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913032028-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the output from the Level 1B process. It converts the raw instrument data numbers into calibrated radiances. This conversion is based upon files of instrument characteristics and algorithm parameters that may vary over time. In addition to calibrated radiances, the Level 1B output products have geolocation information recorded for each measurement for use in higher-level processes.	proprietary
+OCO2_L1B_Science_11.2r	OCO-2 Level 1B calibrated, geolocated science spectra Retrospective Processing V11.2r (OCO2_L1B_Science) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3090438902-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the output from the Level 1B process. It converts the raw instrument data numbers into calibrated radiances. This conversion is based upon files of instrument characteristics and algorithm parameters that may vary over time. In addition to calibrated radiances, the Level 1B output products have geolocation information recorded for each measurement for use in higher-level processes.	proprietary
 OCO2_L1B_Science_11r	OCO-2 Level 1B calibrated, geolocated science spectra, Retrospective Processing V11r (OCO2_L1B_Science) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652600-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the output from the Level 1B process. It converts the raw instrument data numbers into calibrated radiances. This conversion is based upon files of instrument characteristics and algorithm parameters that may vary over time. In addition to calibrated radiances, the Level 1B output products have geolocation information recorded for each measurement for use in higher-level processes.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L1aIn_Pixel_10	OCO-2 Level 1A collated, parsed, calibration data V10 (OCO2_L1aIn_Pixel) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783974-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the input to the Level 1B process. It is depacketized raw data formatted into a standard granularity with calibrated engineering data (for both science and calibration observations), in the Single-pixel Mode of operation.	proprietary
 OCO2_L1aIn_Pixel_10r	OCO-2 Level 1A collated, parsed, calibration data, Retrospective Processing V10r (OCO2_L1aIn_Pixel) at GES DISC	GES_DISC STAC Catalog	2014-07-21		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783865-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  Version 8r is the current version of the data set. Version 7r has been superseded by Version 8r. The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the input to the Level 1B process. It is depacketized raw data formatted into a standard granularity with calibrated engineering data (for both science and calibration observations), in the Single-pixel Mode of operation.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
@@ -11383,45 +11382,62 @@ OCO2_L1aIn_Sample_11.2	OCO-2 Level 1A collated, parsed, science or calibration d
 OCO2_L1aIn_Sample_11r	OCO-2 Level 1A collated, parsed, science or calibration data, Retrospective Processing V11r (OCO2_L1aIn_Sample) at GES DISC	GES_DISC STAC Catalog	2014-07-03		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248663267-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectral elements, although some are masked out in the L2 retrieval.This product is the input to the Level 1B process. It is depacketized raw data formatted into a standard granularity with calibrated engineering data (for both science and calibration observations), in the Sample Mode of operation.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L2_ABand_10r	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Retrospective Processing V10r (OCO2_L2_ABand) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783936-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
 OCO2_L2_ABand_11.2	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor V11.2 (OCO2_L2_ABand) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913024412-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
+OCO2_L2_ABand_11.2r	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor Retrospective Processing V11.2r (OCO2_L2_ABand) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3133987494-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
 OCO2_L2_ABand_11r	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Retrospective Processing V11r (OCO2_L2_ABand) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652681-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
 OCO2_L2_CO2Prior_10r	OCO-2 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air, Retrospective Processing V10r (OCO2_L2_CO2Prior) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783897-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
 OCO2_L2_CO2Prior_11.2	OCO-2 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air V11.2 (OCO2_L2_CO2Prior) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913025334-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
+OCO2_L2_CO2Prior_11.2r	OCO-2 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air Retrospective Processing V11.2r (OCO2_L2_CO2Prior) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3090475443-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
 OCO2_L2_CO2Prior_11r	OCO-2 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air, Retrospective Processing V11r (OCO2_L2_CO2Prior) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652595-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   	proprietary
 OCO2_L2_Diagnostic_10r	OCO-2 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information, Retrospective Processing V10r (OCO2_L2_Diagnostic) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783941-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass various data fields used for diagnostic and pre-processing, including aerosol optical depth, albedo, absorption coefficients, fluorescence, XCO2 uncertainties, averaging kernel, surface type, etc.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L2_Diagnostic_11.2	OCO-2 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information V11.2 (OCO2_L2_Diagnostic) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913027533-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass various data fields used for diagnostic and pre-processing, including aerosol optical depth, albedo, absorption coefficients, fluorescence, XCO2 uncertainties, averaging kernel, surface type, etc.	proprietary
+OCO2_L2_Diagnostic_11.2r	OCO-2 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information Retrospective Processing V11.2r (OCO2_L2_Diagnostic) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3090472506-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass various data fields used for diagnostic and pre-processing, including aerosol optical depth, albedo, absorption coefficients, fluorescence, XCO2 uncertainties, averaging kernel, surface type, etc.	proprietary
 OCO2_L2_Diagnostic_11r	OCO-2 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information, Retrospective Processing V11r (OCO2_L2_Diagnostic) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652598-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass various data fields used for diagnostic and pre-processing, including aerosol optical depth, albedo, absorption coefficients, fluorescence, XCO2 uncertainties, averaging kernel, surface type, etc.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L2_IMAPDOAS_10r	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V10r (OCO2_L2_IMAPDOAS) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783895-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L2_IMAPDOAS_11.2	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP) V11.2 (OCO2_L2_IMAPDOAS) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913029029-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.	proprietary
+OCO2_L2_IMAPDOAS_11.2r	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP) Retrospective Processing V11.2r (OCO2_L2_IMAPDOAS) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3090466573-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.	proprietary
 OCO2_L2_IMAPDOAS_11r	OCO-2 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V11r (OCO2_L2_IMAPDOAS) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652608-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L2_Lite_FP_10r	OCO-2 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V10r (OCO2_L2_Lite_FP) at GES DISC	GES_DISC STAC Catalog	2014-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783927-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The OCO-2 Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.	proprietary
 OCO2_L2_Lite_FP_11.1r	OCO-2 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V11.1r (OCO2_L2_Lite_FP) at GES DISC	GES_DISC STAC Catalog	2014-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2716248872-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The OCO-2 Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.	proprietary
+OCO2_L2_Lite_FP_11.2r	OCO-2 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V11.2r (OCO2_L2_Lite_FP) at GES DISC	GES_DISC STAC Catalog	2014-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2912085112-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The OCO-2 Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.	proprietary
 OCO2_L2_Lite_SIF_10r	OCO-2 Level 2 bias-corrected solar-induced fluorescence and other select fields from the IMAP-DOAS algorithm aggregated as daily files, Retrospective processing V10r (OCO2_L2_Lite_SIF) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783920-GES_DISC.umm_json	 Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The OCO-2 SIF Lite files contain bias-corrected solar induced chlorophyll fluorescence along with other select fields aggregated as daily files.   In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.  This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.  	proprietary
+OCO2_L2_Lite_SIF_11.2r	OCO-2 Level 2 bias-corrected solar-induced fluorescence and other select fields from the IMAP-DOAS algorithm aggregated as daily files, Retrospective processing V11.2r (OCO2_L2_Lite_SIF) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2912084771-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The OCO-2 SIF Lite files contain bias-corrected solar induced chlorophyll fluorescence along with other select fields aggregated as daily files.   The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.  	proprietary
 OCO2_L2_Lite_SIF_11r	OCO-2 Level 2 bias-corrected solar-induced fluorescence and other select fields from the IMAP-DOAS algorithm aggregated as daily files, Retrospective processing V11r (OCO2_L2_Lite_SIF) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652649-GES_DISC.umm_json	 Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.   The OCO-2 SIF Lite files contain bias-corrected solar induced chlorophyll fluorescence along with other select fields aggregated as daily files.   The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection encompass the output from the IMAP-DOAS preprocessor, which is used for both screening of the official XCO2 product as well as for the retrieval of Solar-Induced Fluorescence from the 0.76 micrometer O2 A-band. The IMAP-DOAS preprocessor, just as the ABO2 cloud screen, is implemented in the operational OCO-2 processing pipeline.  	proprietary
 OCO2_L2_Met_10r	OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V10r (OCO2_L2_Met) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783912-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.  	proprietary
 OCO2_L2_Met_11.2	OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding V11.2 (OCO2_L2_Met) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913029880-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.  	proprietary
+OCO2_L2_Met_11.2r	OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding Retrospective Processing V11.2r (OCO2_L2_Met) at GES DISC	GES_DISC STAC Catalog	2014-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3090460016-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.  	proprietary
 OCO2_L2_Met_11r	OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO2_L2_Met) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652634-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.  	proprietary
 OCO2_L2_Met_9r	OCO-2 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V9r (OCO2_L2_Met) at GES DISC	GES_DISC STAC Catalog	2014-06-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1537466735-GES_DISC.umm_json	Version 9r is the current version of the data set. Previous versions have been superseded by Version 9r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers.   This collection encompass meteorological parameters interpolated from global assimilation model for each sounding.  	proprietary
 OCO2_L2_Standard_10r	OCO-2 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V10r (OCO2_L2_Standard) at GES DISC	GES_DISC STAC Catalog	2014-09-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1685783910-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  In early 2021, the OCO Team identified an issue with OCO-2 level 2 products processed since January 28, 2020. The Ancillary Geometric Product (AGAP) file, a static file used in OCO-2 Geolocation processing, was inadvertently replaced with an obsolete version. This AGAP file included a ~300 m pointing error. As a result, all OCO-2 Level 2, version 10r, data files for the period January 28 - December 31, 2020, were corrected and replaced. The replacement process was completed by the end of June, 2021. The significance of this error has been described in Kiel et al. (2019; doi:10.5194/amt-12-2241-2019).  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO2_L2_Standard_11.2	OCO-2 Level 2 geolocated XCO2 retrievals results, physical model V11.2 (OCO2_L2_Standard) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2913033111-GES_DISC.umm_json	Version 11.2 is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).	proprietary
+OCO2_L2_Standard_11.2r	OCO-2 Level 2 geolocated XCO2 retrievals results, physical model Retrospective Processing V11.2r (OCO2_L2_Standard) at GES DISC	GES_DISC STAC Catalog	2019-11-30		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3090432546-GES_DISC.umm_json	Version 11.2r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11.2r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).	proprietary
 OCO2_L2_Standard_11r	OCO-2 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V11r (OCO2_L2_Standard) at GES DISC	GES_DISC STAC Catalog	2014-09-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2248652620-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The OCO-2 project uses the LEOStar-2 spacecraft that carries a single instrument. It incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. This collection is the output from the algorithm retrieving the column-averaged CO2 dry air mole fraction XCO2 and other quantities from the spectra collected by the Orbiting Carbon Observatory-2 (OCO-2).  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.	proprietary
 OCO3_L1B_Calibration_10	OCO-3 Level 1B calibrated, geolocated calibration spectra,  V10 (OCO3_L1B_Calibration) at GES DISC	GES_DISC STAC Catalog	2019-12-17		-180, -53, 180, 53	https://cmr.earthdata.nasa.gov/search/concepts/C2074239073-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.   The OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.  This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO3_L1B_Science (L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the direction of the boresight vector.   	proprietary
 OCO3_L1B_Calibration_10r	OCO-3 Level 1B calibrated, geolocated calibration spectra, Retrospective Processing V10r (OCO3_L1B_Calibration) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -53, 180, 53	https://cmr.earthdata.nasa.gov/search/concepts/C2074239090-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.   The OCO-3 incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.  This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO3_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality. 	proprietary
+OCO3_L1B_Calibration_11r	OCO-3 Level 1B calibrated, geolocated calibration spectra, Retrospective Processing V11r (OCO3_L1B_Calibration) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -53, 180, 53	https://cmr.earthdata.nasa.gov/search/concepts/C2916548539-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.   The OCO-3 incorporates three high-resolution spectrometers that make coincident measurements ofreflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently. Their raw data numbers (DN) are delivered correlated in time to the Level 1B process as Level 1A products. Each band has 1016 spectralelements, although some are masked out in the L2 retrieval.  This L1B product results from calibration mode measurements (e.g., Lunar,Solar, Dark observations), and thus it differs from the OCO3_L1B_Science(L1bSc) product. The differences in the product formats are only in the geolocation information provided. Whereas the L1bSc products report geolocation data for each sounding, calibration products report the directionof the boresight vector.This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality.  This is the retrospective processing where the calibration data is estimated from the full timeseries of data (before, during, and after the measurements), and is expected to be of slightly higher quality. 	proprietary
 OCO3_L1B_Science_10	OCO-3 Level 1B calibrated, geolocated science spectra, Forward Processing V10 (OCO3_L1B_Science) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387275-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L1B_Science_10r	OCO-3 Level 1B calibrated, geolocated science spectra, Retrospective Processing V10r (OCO3_L1B_Science) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387227-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L1B_Science_11r	OCO-3 Level 1B calibrated, geolocated science spectra, Retrospective Processing V11r (OCO3_L1B_Science) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910091100-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_ABand_10	OCO-3 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Forward Processing V10 (OCO3_L2_ABand) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387278-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_ABand_10r	OCO-3 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Retrospective Processing V10r (OCO3_L2_ABand) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387228-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L2_ABand_11r	OCO-3 Level 2 spatially ordered geolocated retrievals screened using the A-band Preprocessor, Retrospective Processing V11r (OCO3_L2_ABand) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910090703-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_CO2Prior_10	OCO-3 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air, Forward Processing V10 (OCO3_L2_CO2Prior) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387288-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_CO2Prior_10r	OCO-3 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air, Retrospective Processing V10r (OCO3_L2_CO2Prior) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387253-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L2_CO2Prior_11r	OCO-3 Level 2 CO2 prior based on CO2 monthly flask record, global meteorology, and age of air, Retrospective Processing V11r (OCO3_L2_CO2Prior) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910091433-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Diagnostic_10	OCO-3 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information, Forward Processing V10 (OCO3_L2_Diagnostic) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387279-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Diagnostic_10r	OCO-3 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information, Retrospective Processing V10r (OCO3_L2_Diagnostic) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387247-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L2_Diagnostic_11r	OCO-3 Level 2 geolocated XCO2 retrieval results and algorithm diagnostic information, Retrospective Processing V11r (OCO3_L2_Diagnostic) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910090458-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_IMAPDOAS_10	OCO-3 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Forward Processing V10 (OCO3_L2_IMAPDOAS) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387286-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_IMAPDOAS_10r	OCO-3 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V10r (OCO3_L2_IMAPDOAS) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387270-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L2_IMAPDOAS_11r	OCO-3 Level 2 spatially ordered geolocated retrievals screened using the IMAP-DOAS Preprocessor (IDP), Retrospective Processing V11r (OCO3_L2_IMAPDOAS) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910089793-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Lite_FP_10.4r	OCO-3 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing v10.4r (OCO3_L2_Lite_FP) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2237732007-GES_DISC.umm_json	Version 10.4r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.4r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L2_Lite_FP_11r	OCO-3 Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files, Retrospective processing V11r (OCO3_L2_Lite_FP) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910086168-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Lite_SIF_10r	OCO-3 Level 2 bias-corrected solar-induced fluorescence and other select fields from the IMAP-DOAS algorithm aggregated as daily files, Retrospective processing V10r (OCO3_L2_Lite_SIF) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387249-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Met_10	OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Forward Processing V10 (OCO3_L2_Met) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387287-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Met_10r	OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V10r (OCO3_L2_Met) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387254-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L2_Met_11r	OCO-3 Level 2 meteorological parameters interpolated from global assimilation model for each sounding, Retrospective Processing V11r (OCO3_L2_Met) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910089375-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Standard_10	OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Forward Processing V10 (OCO3_L2_Standard) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387276-GES_DISC.umm_json	Version 10 is the current version of the data set. Older versions will no longer be available and are superseded by Version 10.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCO3_L2_Standard_10r	OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V10r (OCO3_L2_Standard) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2082387252-GES_DISC.umm_json	Version 10r is the current version of the data set. Older versions will no longer be available and are superseded by Version 10r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
+OCO3_L2_Standard_11r	OCO-3 Level 2 geolocated XCO2 retrievals results, physical model, Retrospective Processing V11r (OCO3_L2_Standard) at GES DISC	GES_DISC STAC Catalog	2019-08-06		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2910086890-GES_DISC.umm_json	Version 11r is the current version of the data set. Older versions will no longer be available and are superseded by Version 11r.  The Orbiting Carbon Observatory -3 (OCO-3) was deployed to the International Space Station in May, 2019. It is technically a single instrument, almost identical to OCO-2.  The Orbiting Carbon Observatory is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere.  OCO-3 incorporates three high-resolution spectrometers that make coincident measurements of reflected sunlight in the near-infrared CO2 near 1.61 and 2.06 micrometers and in molecular oxygen (O2) A-Band at 0.76 micrometers. The three spectrometers have different characteristics and are calibrated independently.   Oxygen-A Band cloud screening algorithm is one of the primary cloud screening tools implemented in the operational OCO processing pipeline. The algorithm was introduced and applied to early GOSAT data  with further analysis performed on OCO-2 simulations.  The OCO ABO2 algorithm employs a fast Bayesian retrieval to estimate surface pressure and surface albedo from high resolution spectra of the molecular oxygen (O2) A-band, near 0.765 µm. The radiative transfer forward model (FM) assumes a clear-sky condition, i.e. Rayleigh scattering only, such that differences between the modeled and measured radiances are apparent when the measurement scene contains cloud or aerosol.   	proprietary
 OCTS_L1_1	ADEOS-I Ocean Color and Temperature Scanner (OCTS) Data Regional Data	OB_DAAC STAC Catalog	1996-11-01	1997-06-30	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1200034340-OB_DAAC.umm_json	On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS.	proprietary
 OCTS_L2_IOP_2014	ADEOS-I Ocean Color and Temperature Scanner (OCTS) Inherent Optical Properties (IOP) Regional Data	OB_DAAC STAC Catalog	1996-11-01	1997-06-30	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1200034360-OB_DAAC.umm_json	On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS.	proprietary
 OCTS_L2_OC_2014	ADEOS-I Ocean Color and Temperature Scanner (OCTS) Ocean Color (OC) Regional Data	OB_DAAC STAC Catalog	1996-11-01	1997-06-30	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1200034380-OB_DAAC.umm_json	On August 17, 1996, the Japanese Space Agency (NASDA - National Space Development Agency) launched the Advanced Earth Observing Satellite (ADEOS). ADEOS was in a descending, Sun synchronous orbit with a nominal equatorial crossing time of 10:30 a.m. Amoung the instruments carried aboard the ADEOS spacecraft was the Ocean Color and Temperature Scanner (OCTS). OCTS is an optical radiometer with 12 bands covering the visible, near infrared and thermal infrared regions. (Eight of the bands are in the VIS/NIR. These are the only bands calibrated and processed by the OBPG) OCTS has a swath width of approximately 1400 km, and a nominal nadir resolution of 700 m. The instrument operated at three tilt states (20 degrees aft, nadir and 20 degrees fore), similar to SeaWiFS.	proprietary
@@ -11593,6 +11609,8 @@ OMPIXCOR_003	OMI/Aura Global Ground Pixel Corners 1-Orbit L2 Swath 13x24km V003
 OMPS_N20_NMHCHO_L2_1	OMPS-N20 L2 NM Formaldehyde (HCHO) Total Column swath orbital	GES_DISC STAC Catalog	2018-01-16		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2477751536-GES_DISC.umm_json	The OMPS-N20 L2 NM Formaldehyde (HCHO) Total Column swath orbital product provides formaldehyde measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the NOAA-20 (JPSS-1) satellite. The total column HCHO amount is derived from radiances at wavelengths between 328.5 and 356.5 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day. Each has typically 1201 swaths. The swath width of the NM is about 2800 km. Prior to orbit 6419 on 13 February 2019, each swath has 104 scenes, or pixels, with a footprint size of 17 km x 17 km at nadir. Orbits 6419 and later have 140 scenes across the swath, with a footprint size of 12 km x 17 km. The files are written in the new netCDF version 4 format.	proprietary
 OMPS_N20_NMSO2_PCA_L2_Step1_1	OMPS-N20 NM PCA SO2 Step 1 Total Column 1-Orbit L2 Swath 17x13km	GES_DISC STAC Catalog	2018-01-16		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2808692512-GES_DISC.umm_json	The OMPS-N20 NM PCA SO2 Step1 Total Column 1-Orbit L2 Swath 17x13km collection 1 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the NOAA-20 (JPSS-1) satellite. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017) used to retrieve the SO2 total column amounts assuming different SO2 plume heights, including the boundary layer (lowest 1 km of the atmosphere), the lower (centered at 3 km), middle (centered at 8 km) and upper (centered at 13 km) troposphere, as well as the lower stratosphere (centered at 18 km).  Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 104 pixels in the cross-track direction before February 13, 2019 with a pixel resolution of about 17 km x 17 km at nadir. Since then, the pixel resolution has been enhanced to 17 km x 13 km at nadir, with 140 pixels in the cross-track direction. The files are written using netCDF version 4.	proprietary
 OMPS_N20_NMSO2_PCA_L2_Step1_NRT_1	OMPS-N20 NM PCA SO2 Step 1 Total Column 1-Orbit L2 Swath 17x13km NRT	OMINRT STAC Catalog	2018-01-16		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3186057121-OMINRT.umm_json	The OMPS-N20 NM PCA SO2 Step1 Total Column 1-Orbit L2 Swath 17x13km collection 1 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the NOAA-20 (JPSS-1) satellite. The product is based on the NASA Goddard Space Flight Center principal component analysis (PCA) spectral fitting algorithm (Li et al., 2013, 2017) used to retrieve the SO2 total column amounts assuming different SO2 plume heights, including the boundary layer (lowest 1 km of the atmosphere), the lower (centered at 3 km), middle (centered at 8 km) and upper (centered at 13 km) troposphere, as well as the lower stratosphere (centered at 18 km).  Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 104 pixels in the cross-track direction before February 13, 2019 with a pixel resolution of about 17 km x 17 km at nadir. Since then, the pixel resolution has been enhanced to 17 km x 13 km at nadir, with 140 pixels in the cross-track direction. The files are written using netCDF version 4.  	proprietary
+OMPS_N21_LP_L1G_EV_1.0	OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V1.0 (OMPS_N21_LP_L1G_EV) at GES DISC	GES_DISC STAC Catalog	2022-11-10		-180, -84, 180, 84	https://cmr.earthdata.nasa.gov/search/concepts/C3117300814-GES_DISC.umm_json	The OMPS-N21 L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA 21 (JPSS-2) satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.	proprietary
+OMPS_N21_LP_L2_O3_DAILY_1.0	OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit V1.0 (OMPS_N21_LP_L2_O3_DAILY) at GES DISC	GES_DISC STAC Catalog	2022-11-10		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3237592774-GES_DISC.umm_json	The OMPS-N21 L2 LP Ozone (O3) Vertical Profile swath daily 3slit collection contains ozone measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the NOAA-21 satellite. The LP ozone product measures the vertical distribution of ozone in the stratosphere and lower mesosphere. The algorithm derives ozone profile values along with errors in the UV from 29.5 km and 52.5 km, and in the visible from cloud top to 37.5 km (when there are no clouds the lower limit is 12.5 km).   Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day, the data from the center of the LP three slits are used to make a vertical profile. The profile is measured from the ground up to about 60 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.	proprietary
 OMPS_NPP_LP_L1G_EV_2	OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V2 (OMPS_NPP_LP_L1G_EV) at GES DISC	GES_DISC STAC Catalog	2011-11-07		-180, -84, 180, 84	https://cmr.earthdata.nasa.gov/search/concepts/C1412974463-GES_DISC.umm_json	The OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.	proprietary
 OMPS_NPP_LP_L1G_EV_2.6	OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit V2.6 (OMPS_NPP_LP_L1G_EV) at GES DISC	GES_DISC STAC Catalog	2011-11-07		-180, -84, 180, 84	https://cmr.earthdata.nasa.gov/search/concepts/C2469227759-GES_DISC.umm_json	The OMPS-NPP L1G LP Radiance EV Wavelength-Altitude Grid swath orbital 3slit product contains the calibrated earth-viewing radiances measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The LP L1G product measures radiances in the wavelength region from 280 nm to 1000 nm.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1-2 km.  The data are written using the Hierarchical Data Format Version 5 or HDF5.	proprietary
 OMPS_NPP_LP_L2_AER_DAILY_2	OMPS-NPP L2 LP Aerosol Extinction Vertical Profile swath daily 3slit V2 (OMPS_NPP_LP_L2_AER_DAILY) at GES DISC	GES_DISC STAC Catalog	2012-02-07		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1898401389-GES_DISC.umm_json	The OMPS-NPP L2 LP Aerosol Extinction Vertical Profile swath daily 3slit (AER) product contains the retrieved aerosol extinction coefficients measured by the Ozone Mapping and Profiling Suite (OMPS) Limb-Profiler (LP) sensor on the Suomi-NPP satellite. The AER product measures stratospheric aerosol abundance and evolution at 6 wavelengths (510, 600, 675, 745, 869 and 997 nm) to complement the OMPS LP measurements of stratospheric and mesospheric profile ozone. This product replaces the previous single wavelength 675 nm (AER675) product.  Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to  90 degrees latitude), and there are about 14.5 orbits per day each measuring three limb profiles spaced approximately 250 km in the cross-track direction. The profiles are measured from the ground up to about 80 km with a vertical resolution of the retrieved profiles of approximately 1.8 km.  The files are written using the Hierarchical Data Format Version 5 or HDF5.	proprietary
@@ -11625,8 +11643,8 @@ OMTO3_003	OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT	OM
 OMTO3_003	OMI/Aura Ozone(O3) Total Column 1-Orbit L2 Swath 13x24 km V003 (OMTO3) at GES DISC	GES_DISC STAC Catalog	2004-10-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1239966818-GES_DISC.umm_json	The Aura Ozone Monitoring Instrument (OMI) Level-2 Total Column Ozone Data Product OMTO3 (Version 003) is available from the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for the public access. OMI provides two Level-2 (OMTO3 and OMDOAO3) total column ozone products at pixel resolution (13 x 24 km at nadir) that are based on two different algorithms. This level-2 global total column ozone product (OMTO3) is based on the enhanced TOMS version-8 algorithm that essentially uses the ultraviolet radiance data at 317.5 and 331.2 nm. OMI hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrievals (e.g., cloud and aerosol, sea-glint effects, profile shape sensitivity, SO2 and other trace gas contamination). In addition to the total ozone values this product also contains some auxiliary derived and ancillary input parameters including N-values, effective Lambertian scene-reflectivity, UV aerosol index, SO2 index, cloud fraction, cloud pressure, ozone below clouds, terrain height, geolocation, solar and satellite viewing angles, and quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3. The algorithm lead for this product is NASA OMI scientist  Dr. Pawan K. Bhartia.  The OMTO3 files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMTO3 data product is approximately 35 MB.	proprietary
 OMTO3_CPR_003	OMI/Aura Level 2 Ozone (O3) Total Column 1-Orbit Subset and Collocated Swath along CloudSat track 200-km wide at 13x24 km2 resolution	GES_DISC STAC Catalog	2006-06-01	2018-03-02	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1236350982-GES_DISC.umm_json	This is a CloudSat-collocated subset of the original product OMTO3, for the purposes of the A-Train mission. The goal of the subset is to select and return OMI data that are within +/-100 km across the CloudSat track. The resultant OMI subset swath is sought to be about 200 km cross-track of CloudSat. This product also contains many ancillary and derived parameters, terrain and geolocation information, solar and satellite viewing angles, and quality flags. Even though collocated with CloudSat, this subset can serve many other A-Train applications.             (The shortname for this CloudSat-collocated OMI Level 2 Total Ozone Column subset is OMTO3_CPR_V003)	proprietary
 OMTO3d_003	OMI/Aura TOMS-Like Ozone, Aerosol Index, Cloud Radiance Fraction L3 1 day 1 degree x 1 degree V3 (OMTO3d) at GES DISC	GES_DISC STAC Catalog	2004-10-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1266136070-GES_DISC.umm_json	The OMI science team produces this Level-3 daily global TOMS-Like Total Column Ozone gridded product OMTO3d (1 deg Lat/Lon grids). The OMTO3d product is produced by gridding and averaging only good quality level-2 total column ozone orbital swath data (OMTO3, based on the enhanced TOMS version-8 algorithm) on the 1x1 degree global grids.  The OMTO3d files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3d data product is about 0.65 Mbytes.	proprietary
-OMTO3e_003	OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT	OMINRT STAC Catalog	2004-07-15		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json	The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) .	proprietary
 OMTO3e_003	OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction L3 1 day 0.25 degree x 0.25 degree V3 (OMTO3e) at GES DISC	GES_DISC STAC Catalog	2004-10-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1266136071-GES_DISC.umm_json	The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles.  The OMTO3e files are stored in the version 5 EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes.	proprietary
+OMTO3e_003	OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT	OMINRT STAC Catalog	2004-07-15		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.umm_json	The OMI science team produces this Level-3 Aura/OMI Global TOMS-Like Total Column Ozone gridded product OMTO3e (0.25deg Lat/Lon grids). The OMTO3e product selects the best pixel (shortest path length) data from the good quality filtered level-2 total column ozone data (OMTO3) that fall in the 0.25 x 0.25 degree global grids. Each file contains total column ozone, radiative cloud fraction and solar and viewing zenith angles. OMTO3e files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains daily data from approximately 15 orbits. The maximum file size for the OMTO3e data product is about 2.8 Mbytes. (The shortname for this Level-3 TOMS-Like Total Column Ozone gridded product is OMTO3e) .	proprietary
 OMUANC_004	Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUANC) at GES DISC	GES_DISC STAC Catalog	2004-10-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2556143653-GES_DISC.umm_json	The Primary Ancillary Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km (OMUANC) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath.  The fields in this product include snow cover, sea ice cover, land cover, terrain height, row anomaly flag, and pixel area. The OMI team also provides a corresponding product for the OMI VIS swath, OMVANC. This product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir.  The OMUANC files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools.  Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official.	proprietary
 OMUFPITMET_003	GEOS-5 FP-IT Assimilation Geo-colocated to OMI/Aura UV-2 1-Orbit L2 Support Swath 13x24km V3 (OMUFPITMET) at GES DISC	GES_DISC STAC Catalog	2004-10-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1561222825-GES_DISC.umm_json	The GEOS-5 FP-IT Assimilation Geo-colocated to OMI/Aura UV-2 1-Orbit L2 Support Swath 13x24km (OMUFPITMET) provides selected parameters from GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath.    The fields in this product include surface pressure, vertical temperature profiles, surface and vertical wind profiles, tropopause pressure, boundary layer top pressure, and surface geopotenial. The OMI team also provides a corresponding product for the OMI VIS swath, OMVFPITMET.  The product has been generated for convenient use by the OMI/Aura team in their L2 algorithms, and for research where those L2 products are used.  The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir.  To reduce the size of each orbital file, FP-IT data fields with a vertical dimension of 72 layers have been reduced to 47 layers in OMUFPITMET by combining layers above the troposphere.   The OMUFPITMET files are in netCDF4 format which is compatible with most HDF5 readers and tools.  Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official.	proprietary
 OMUFPMET_004	GEOS-5 FP-IT 3D Time-Averaged Model-Layer Assimilated Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km V4 (OMUFPMET) at GES DISC	GES_DISC STAC Catalog	2004-10-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2556146042-GES_DISC.umm_json	The GEOS-5 FP-IT 3D Time-Averaged Model-Layer Assimilated Data Geo-Colocated to OMI/Aura UV2 1-Orbit L2 Swath 13x24km (OMUFPMET) product provides selected meteorlogical fields from the GEOS-5 Forward Processing for Instrument Teams (FP-IT) assimilated product produced by the Global Modeling and Assimilation Office (GMAO) co-located in space and time with the OMI UV-2 swath.  The fields in this product include layer pressure thickness, surface pressure, vertical temperature profiles, surface potential, and mid-layer pressure along with geolocation info. The OMI team also provides a corresponding product for the OMI VIS swath, OMVFPMET. The OMI ancillary products were developed to provide supplementary information for use with the OMI collection 4 L1B data sets. The original GEOS-5 FP-IT data are reported on a 0.625 deg longitude by 0.5 deg latitude grid, whereas the OMI UV-2 spatial resolution is 13km x 24km at nadir.  The OMUFPMET files are in netCDF4 format which is compatible with most netCDF and HDF5 readers and tools.  Each file is approximately 45mb in size. The lead for this product is Zachary Fasnacht of SSAI. Joanna Joiner is the responsible NASA official.	proprietary
@@ -11643,10 +11661,8 @@ ONICE_Chlorophyll_1	Aurora Australis Voyage 2 (ONICE) 1997-98 Chlorophyll a Data
 ONR-MAB_0	Office of Naval Research (ONR) - Mid-Atlantic Bight (MAB) measurements	OB_DAAC STAC Catalog	1996-08-08		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360572-OB_DAAC.umm_json	Mid-Atlantic Bight measurements taken between 1996 and 1999.	proprietary
 ONR_PenobscotRiverSystem_0	Office of Naval Research (ONR) measurements in the Penobscot River System	OB_DAAC STAC Catalog	2006-01-09		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360573-OB_DAAC.umm_json	Measurements from the Penobscot River System in Maine taken between 2006 and 2009.	proprietary
 OPERA_L2_CSLC-S1-STATIC_V1_1	OPERA Coregistered Single-Look Complex from Sentinel-1 Static Layers validated product (Version 1)	ASF STAC Catalog	2014-04-03		-180, 4.9744342, -64.4225561, 71.2183663	https://cmr.earthdata.nasa.gov/search/concepts/C2795135668-ASF.umm_json	The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Coregistered Single-Look Complex (CSLC) from Sentinel-1 (S1) Static Layers (CSLC-S1-STATIC) validated product contains static radar geometry layers associated with the OPERA Coregistered Single-Look Complex (CSLC) from Sentinel-1 (S1) validated product. Due to the S1 mission’s narrow orbital tube, radar-geometry layers vary slightly over time for each position on the ground, and therefore are considered static. These static layers are provided separately from the OPERA CSLC-S1 product, as they are produced only once or a limited number of times, to account for changes in the DEM, in the S1 orbit, or in the static layers generation algorithm. Each OPERA CSLC-S1-STATIC product is distributed as a Hierarchical Data Format version 5 (HDF5) file following the CF-1.8 convention containing both data raster layers and product metadata and corresponds to matching CSLC-S1 products with the same burst ID. OPERA CSLC-S1 products are available over North America which includes the USA and U.S. Territories, Canada within 200 km of the U.S. border, and all mainland countries from the southern U.S. border down to and including Panama. The CSLC-S1 products are available in the associated OPERA Coregistered Single-Look Complex from Sentinel-1 validated product (Version 1) dataset.	proprietary
-OPERA_L2_CSLC-S1_CALVAL_V1_1	OPERA Coregistered Single-Look Complex from Sentinel-1 product for Calibration & Validation (Version 1)	ASF STAC Catalog	2014-10-14	2023-07-29	-180, 4.9744342, -64.4225561, 71.2183663	https://cmr.earthdata.nasa.gov/search/concepts/C2803501758-ASF.umm_json	This dataset contains the products used for calibration and validation of the Observational Products for End-Users from Remote Sensing Analysis (OPERA) Coregistered Single-Look Complex (CSLC) from Sentinel-1 validated product. The CSLC-S1 product is derived from Copernicus Sentinel-1A and Sentinel-1B Interferometric Wide (IW) SLC data, provided by the European Space Agency.  OPERA CSLC-S1 products are available over North America which includes USA and US Territories within 200 km from the US border, Canada, and all mainland countries from the southern US border down to and including Panama. 	proprietary
 OPERA_L2_CSLC-S1_V1_1	OPERA Coregistered Single-Look Complex from Sentinel-1 validated product (Version 1)	ASF STAC Catalog	2014-06-15		-180, 4.9744342, -64.4225561, 71.2183663	https://cmr.earthdata.nasa.gov/search/concepts/C2777443834-ASF.umm_json	The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Coregistered Single-Look Complex (CSLC) from Sentinel-1 validated product consists of Single Look Complex (SLC) images which contain both amplitude and phase information of the complex radar return. The amplitude is primarily determined by ground surface properties (e.g., terrain slope, surface roughness, and physical properties), and phase primarily represents the distance between the radar and ground targets corrected for the geometrical distance between the two based on the knowledge from Digital Elevation Model and platform’s position, i.e., the CSLC phase represents residual geometrical distance between the sensor and target, the atmospheric propagation delay and the target movements. The CSLC-S1 product is derived from Copernicus Sentinel-1A and Sentinel-1B Interferometric Wide (IW) SLC data, provided by the European Space Agency.  The CSLC images are precisely aligned or “coregistered” to a pre-defined UTM/Polar stereographic map projection systems and posted at 5x10 m spacing in east and north direction, respectively.  Each CSLC-S1 product corresponds to a single S1 burst and is distributed as a Hierarchical Data Format version 5 (HDF5) file following the CF-1.8 convention containing both data raster layers (e.g., geocoded complex backscatter, low-resolution correction look-up tables) and product metadata. OPERA CSLC-S1 products are available over North America which includes the USA and U.S. Territories, Canada within 200 km of the U.S. border, and all mainland countries from the southern U.S. border down to and including Panama. Due to the S1 mission’s narrow orbital tube, radar-geometry layers vary slightly over time for each position on the ground, and therefore are considered static. These static layers are provided separately from the OPERA CLSLC-S1 product, as they are produced only once or a limited number of times. The static layers are available in the associated OPERA Coregistered Single-Look Complex from Sentinel-1 Static Layers validated product (Version 1).	proprietary
 OPERA_L2_RTC-S1-STATIC_V1_1	OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 Static Layers validated product (Version 1)	ASF STAC Catalog	2014-04-03		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2795135174-ASF.umm_json	The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) Static Layers (RTC-S1-STATIC) validated product contains static radar geometry layers associated with the OPERA Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) (RTC-S1) validated product.  Due to the S1 mission’s narrow orbital tube, radar-geometry layers such as incidence angle, local incidence angle, number of looks, and RTC Area Normalization Factor (ANF) vary slightly over time for each position on the ground, and therefore are considered static. These static layers are provided separately from the OPERA RTC-S1 product, as they are produced only once or a limited number of times, to account for changes in the DEM, in the S1 orbit, or in the static-layers generation algorithm.  Static layers are provided as single-band cloud-optimized GeoTIFF (COG) files, with map grid matching RTC-S1 products with the same burst ID.  The standard OPERA RTC-S1 product is derived from the original Copernicus Sentinel-1 (S1) interferometric wide (IW) single-look complex (SLC) data, provided by the European Space Agency, with a temporal sampling coincident with the availability of Sentinel-1A and Sentinel-1B SLC data. The OPERA RTC-S1-STATIC and RTC-S1 products are provided at a near global scope (land masses excluding Antarctica).  The RTC-S1 products are available in the associated OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 validated product (Version 1) dataset.	proprietary
-OPERA_L2_RTC-S1_CALVAL_V1_1	OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 product for Calibration & Validation (Version 1)	ASF STAC Catalog	2014-10-28	2023-07-13	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2803501097-ASF.umm_json	This dataset contains the products used for calibration and validation of the Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) validated product.  The OPERA RTC-S1 product is derived from the original Copernicus Sentinel-1 Interferometric Wide (IW) Single Look Complex (SLC) data, provided by the European Space Agency, with a near global scope and temporal sampling coincident with the availability of S1 SLC data.      	proprietary
 OPERA_L2_RTC-S1_V1_1	OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 validated product (Version 1)	ASF STAC Catalog	2023-10-04		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2777436413-ASF.umm_json	The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Radiometric Terrain Corrected (RTC) SAR Backscatter from Sentinel-1 (S1) validated product consists of radar backscatter normalized with respect to the topography. The product maps signals related to the physical properties of ground scattering objects, such as surface roughness and soil moisture and/or vegetation. The OPERA RTC-S1 product is derived from the original Copernicus Sentinel-1 Interferometric Wide (IW) Single Look Complex (SLC) data, provided by the European Space Agency, with a near global scope and temporal sampling coincident with the availability of S1 SLC data. Each OPERA RTC-S1 product corresponds to a single S1 burst projected onto a pre-defined UTM/Polar stereographic map projection system map grid with a 30-meter spacing. The Copernicus global 30 m (GLO-30) Digital Elevation Model (DEM) is the reference DEM used to correct for the impacts of topography and to geocode the product.  The OPERA RTC-S1 product is normalized to the backscatter coefficient gamma-naught, ɣ0,  obtained from the original radar brightness beta-naught, β0,  through radiometric terrain correction.  The RTC-S1 product is distributed as cloud optimized GeoTIFFs with one GeoTIFF file per processed polarization. The RTC-S1 product metadata is provided in the Hierarchical Data Format version 5 (HDF5) format. Due to the S1 mission’s narrow orbital tube, radar-geometry layers such as incidence angle, local incidence angle, number of looks, and RTC Area Normalization Factor (ANF) vary slightly over time for each position on the ground, and therefore are considered static. These static layers are provided separately from the OPERA RTC-S1 product, as they are produced only once or a limited number of times, to account for changes in the DEM, in the S1 orbit, or in the static-layers generation algorithm. The static layers are available in the associated OPERA Radiometric Terrain Corrected SAR Backscatter from Sentinel-1 Static Layers validated product (Version 1) dataset.	proprietary
 OPERA_L3_DIST-ALERT-HLS_V1_1	OPERA Land Surface Disturbance Alert from Harmonized Landsat Sentinel-2 product (Version 1)	LPCLOUD STAC Catalog	2022-01-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2746980408-LPCLOUD.umm_json	The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Land Surface Disturbance Alert from Harmonized Landsat Sentinel-2 (HLS) product Version 1 maps vegetation disturbance alerts that are derived from data collected by Landsat 8 and Landsat 9 Operational Land Imager (OLI) and Sentinel-2A and Sentinel-2B Multi-Spectral Instrument (MSI). A vegetation disturbance alert is detected at 30 meter (m) spatial resolution when there is an indicated decrease in vegetation cover within an HLS pixel. The Level-3 data product also provides additional information about more general disturbance trends and auxiliary generic disturbance information as determined from the variations of the reflectance through the HLS scenes. HLS data represent the highest temporal frequency data available at medium spatial resolution. The combined observations will provide greater sensitivity to land changes, whether of large magnitude/short duration or small magnitude/long duration.  The OPERA_L3_DIST-ALERT-HLS (or DIST-ALERT) data product is provided in Cloud Optimized GeoTIFF (COG) format, and each layer is distributed as a separate file. There are 19 layers contained within the DIST-ALERT product. The layers for both vegetation and generic disturbance include disturbance status, loss or anomaly, maximum loss anomaly, disturbance confidence layer, date of disturbance, count of observations with loss anomalies, days of ongoing anomalies, and day of last disturbance detection. Additional layers are vegetation cover percent, historical percent vegetation cover, and data mask. See the Product Specification Document  for a more detailed description of the individual layers provided in the DIST-ALERT product.  	proprietary
 OPERA_L3_DIST-ANN-HLS_V1_1	OPERA Land Surface Disturbance Annual from Harmonized Landsat Sentinel-2 product (Version 1)	LPCLOUD STAC Catalog	2022-01-01		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2519119034-LPCLOUD.umm_json	The Observational Products for End-Users from Remote Sensing Analysis (OPERA) Land Surface Disturbance Annual from Harmonized Landsat Sentinel-2 (HLS)  product Version 1 summarizes the DIST-ALERT data product into an annual vegetation disturbance data product. Vegetation disturbance is mapped when there is an indicated decrease in vegetation cover within an HLS Version 2 pixel. The product also provides auxiliary generic disturbance information as determined from the variations of the reflectance through the DIST-ALERT scenes to provide information about more general disturbance trends. The DIST-ANN product tracks changes at the annual scale, aggregating changes identified in the DIST-ALERT product. Only confirmed disturbances from the associated year are reported together with the date of initial disturbance. As confirmed disturbances are determined using subsequent cloud-free observations to determine if the loss detections persist, the required number of HLS scenes depends on visibility of the target. Due to this dependency, summarizing the DIST-ALERT in the DIST-ANN product will have some latency contingent on the algorithmic calibration and is detailed in the Algorithm Theoretical Basis Document (ATBD).  The OPERA_L3_DIST-ANN-HLS (or DIST-ANN) data product is provided in Cloud Optimized GeoTIFF (COG) format, and each layer is distributed as a separate COG. There are 21 layers contained within the DIST-ANN product: vegetation disturbance status, historical vegetation cover indicator, maximum vegetation cover indicator, maximum vegetation anomaly value, vegetation disturbance confidence layer, date of initial vegetation disturbance, number of detected vegetation loss anomalies, vegetation disturbance duration, date of last observation assessed for vegetation disturbance, and several generic disturbance layers. Each product layer is gridded to the same resolution and tiling system as HLS V2: 30 meter (m) and Military Grid Reference System (MGRS).  See the Product Specification Document (PSD) for a more detailed description of the individual layers provided in the DIST-ANN product.   	proprietary
@@ -11910,6 +11926,9 @@ PRECIP_SSMI_F13_1	NASA MEASURES Precipitation Ensemble based on SSM/I DMSP F13 N
 PRECIP_SSMI_F14_1	NASA MEASURES Precipitation Ensemble based on SSM/I DMSP F14 NASA PPS L1C V06 Tbs 1-orbit L2 Swath 12x12km V1 (PRECIP_SSMI_F14) at GES DISC	GES_DISC STAC Catalog	1997-05-07	2008-08-24	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2368309429-GES_DISC.umm_json	The data presented in this level 2 orbital product are rain rate estimates expressed as mm/hour determined from brightness temperatures (Tbs) obtained from the Special Sensor Microwave/Imager (SSM/I) flown on the US Defense Meteorological Satellite Program (DMSP) F14 mission. Most of the products generated in this data set are based upon the algorithms developed for the 3rd Algorithm Intercomparison Project (AIP-3) of the Global Precipitation Climatology Project (GPCP).  Details of these 15 algorithms and development of a quality score which is a measure of confidence in the estimate, along with processing and algorithmic flags, can be found in the Algorithm Theoretical Basis Document  (ATBD).  The data in this product cover the period from 1997 to 2008 with one file per orbit.	proprietary
 PRECIP_SSMI_F15_1	NASA MEASURES Precipitation Ensemble based on SSM/I DMSP F15 NASA PPS L1C V06 Tbs 1-orbit L2 Swath 12x12km V1 (PRECIP_SSMI_F15) at GES DISC	GES_DISC STAC Catalog	2000-02-03	2006-08-14	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2368309823-GES_DISC.umm_json	The data presented in this level 2 orbital product are rain rate estimates expressed as mm/hour determined from brightness temperatures (Tbs) obtained from the Special Sensor Microwave/Imager (SSM/I) flown on the US Defense Meteorological Satellite Program (DMSP) F15 mission. Most of the products generated in this data set are based upon the algorithms developed for the 3rd Algorithm Intercomparison Project (AIP-3) of the Global Precipitation Climatology Project (GPCP).  Details of these 15 algorithms and development of a quality score which is a measure of confidence in the estimate, along with processing and algorithmic flags, can be found in the Algorithm Theoretical Basis Document  (ATBD).  The data in this product cover the period from 2000 to 2006 with one file per orbit.	proprietary
 PRECIP_TMI_TRMM_1	NASA MEASURES Precipitation Ensemble based on TMI TRMM NASA PPS L1C V05 Tbs 1-orbit L2 Swath 5x5km V1 (PRECIP_TMI_TRMM) at GES DISC	GES_DISC STAC Catalog	1997-12-07	2015-04-08	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2368307239-GES_DISC.umm_json	The data presented in this level 2 orbital product are rain rate estimates expressed as mm/hour determined from brightness temperatures (Tbs) obtained from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) flown on the TRMM satellite. Most of the products generated in this data set are based upon the algorithms developed for the 3rd Algorithm Intercomparison Project (AIP-3) of the Global Precipitation Climatology Project (GPCP).  Details of these 15 algorithms and development of a quality score which is a measure of confidence in the estimate, along with processing and algorithmic flags, can be found in the Algorithm Theoretical Basis Document  (ATBD).  The data in this product cover the period from 1997 to 2015 with one file per orbit.	proprietary
+PREFIRE_SAT2_0-BUS-TLM_R01	Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 telemetry R01	LARC_CLOUD STAC Catalog	2024-05-01		-180, -84, 180, 84	https://cmr.earthdata.nasa.gov/search/concepts/C3246712895-LARC_CLOUD.umm_json	Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Telemetry (PREFIRE_SAT2_0-BUS-TLM) contains positioning and pointing information for one of two PREFIRE polar orbiting CubeSats. Both CubeSats carry a PREFIRE Thermal Infrared Spectrometer (TIRS-PREFIRE), a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale.  PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions.  This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.    This collection contains the time, beta angle, orbit position and velocity, and the quaternion of PREFIRE Satellite 2 (PREFIRE-SAT2).  Combined with a Digital Elevation Map, these telemeters geolocate PREFIRE data on the Earth’s surface.      Data retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions.  This data is retrieved at a frequency of 1Hz and is available in CSV format.    Positioning and pointing information for the sister satellite, PREFIRE-SAT1, can be found in the PREFIRE_SAT1_0-BUS-TLM collection.    	proprietary
+PREFIRE_SAT2_0-PAYLOAD-TLM_R01	Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Curated Radiance R01	LARC_CLOUD STAC Catalog	2024-05-01		-180, -84, 180, 84	https://cmr.earthdata.nasa.gov/search/concepts/C3246712936-LARC_CLOUD.umm_json	Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Curated Radiance (PREFIRE_SAT2_0-PAYLOAD-TLM) contains the curated raw measurements from one of two PREFIRE Thermal Infrared Spectrometers (TIRS-PREFIRE), which is a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale. PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions. This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.    This collection contains the raw, curated digital number counts for TIRS-PREFIRE aboard PREFIRE Satellite 2 (PREFIRE-SAT2). Data retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions. This data has a temporal resolution of 0.707 seconds and is available in binary format.    Raw, curated digital number counts for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_0-PAYLOAD-TLM collection.  	proprietary
+PREFIRE_SAT2_0-PAYLOAD_R01	Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Payload R01	LARC_CLOUD STAC Catalog	2024-05-01		-180, -84, 180, 84	https://cmr.earthdata.nasa.gov/search/concepts/C3246712916-LARC_CLOUD.umm_json	Polar Radiant Energy in the Far InfraRed Experiment (PREFIRE) Satellite 2 Raw Payload (PREFIRE_SAT2_0-PAYLOAD) contains the uncurated raw measurements from one of two PREFIRE Thermal Infrared Spectrometers (TIRS-PREFIRE), which is a push broom spectrometer with 63 channels measuring mid- and far-infrared (FIR) radiation from approximately 5 to 53 µm. Most polar emissions are in the FIR but have not been measured on a large scale.  PREFIRE aims to fill knowledge gaps in the global energy budget by more accurately characterizing polar emissions.  This information will then be assimilated into global circulation and other climate models to predict future climates more accurately.    This collection contains the raw and uncurated digital number counts for TIRS-PREFIRE aboard PREFIRE Satellite 2 (PREFIRE-SAT2).  Data retrieval started in May TBD, 2024, and is ongoing. Geographic coverage is global, with the greatest concentration of data in the polar regions.  This data has a temporal resolution of 0.707 seconds and is available in binary format.    Raw, uncurated digital number counts for the sister instrument aboard PREFIRE-SAT1 can be found in the PREFIRE_SAT1_0-PAYLOAD collection.	proprietary
 PREPP_0	Pearl River Estuary Pollution Project (PREPP)	OB_DAAC STAC Catalog	2001-02-08		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C1633360621-OB_DAAC.umm_json	Measurements made under the Pearl River Estuary Pollution Project (PREPP) near Hong Kong in 2001.	proprietary
 PRESWOT_HYDRO_GRRATS_L2_DAILY_VIRTUAL_STATION_HEIGHTS_V2_2	Pre SWOT Hydrology GRRATS Daily River Heights and Storage Version 2	POCLOUD STAC Catalog	1992-04-06	2018-04-20	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2036882359-POCLOUD.umm_json	The Global River Radar Altimeter Time Series (GRRATS) 1km/daily interpolations are river heights from ERS-1, ERS-2, TOPEX/Poseidon OSTM/Jason-2 and Envisat that are interpolated and processed to create a continuous heights for the study over the temporal range of the altimeters used. The purpose of these heights are to provide satellite altimetric river height data in a form that is more recognizable to the observational community and as a way to get users use to using satellite data for river hydrology. These pre SWOT data are derived from satellites to provide hydrological measurements. The Surface Water and Ocean Topography (SWOT) mission will have hydrology as one of its objectives. This dataset does not have the same variables as SWOT, but does provide hydrological measurements with typical quality flagging typical of satellite data. Not only does it provide science information, it can also assist hydrological users new to satellite data with the satellite data formats and variables before SWOT launches.	proprietary
 PRESWOT_HYDRO_GRRATS_L2_VIRTUAL_STATION_HEIGHTS_V2_2	Pre SWOT Hydrology GRRATS Virtual Station River Heights Version 2	POCLOUD STAC Catalog	1992-04-06	2018-04-20	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2036882009-POCLOUD.umm_json	The Global River Radar Altimeter Time Series (GRRATS) are simulated river gauge data that are derived from ERS-1, ERS-2, TOPEX/Poseidon OSTM/Jason-2, Jason-3 and Envisat altimetric measurements. The purpose of these heights are to provide satellite altimetric river height data in a form that is more recognizable to the observational community and as a way to get users use to using satellite data for river hydrology. These pre SWOT data are derived from satellites to provide hydrological measurements. The Surface Water and Ocean Topography (SWOT) mission will have hydrology as one of its objectives. This dataset does not have the same variables as SWOT, but does provide hydrological measurements with typical quality flagging typical of satellite data. Not only does it provide science information, it can also assist hydrological users new to satellite data with the satellite data formats and variables before SWOT launches.If you are looking for version 1 it can be found at https://podaac.jpl.nasa.gov/dataset/PRESWOT_HYDRO_GRRATS_L2_VIRTUAL_STATION_HEIGHTS_V1 however this version should be used with caution. Version 2, this page, is the most recent version with the most accurate algorithms used for producing river heights.	proprietary
@@ -12057,6 +12076,7 @@ RSCAT_LEVEL_2B_OWV_COMP_12_V1.3_1.3	RapidScat Level 2B Ocean Wind Vectors in 12.
 RSES_PCM_1	Cosmogenic dating	AU_AADC STAC Catalog	2001-12-20		63.6203, -75.2756, 73.7101, -69.7425	https://cmr.earthdata.nasa.gov/search/concepts/C1214313722-AU_AADC.umm_json	The data set consists of cosmogenic exposure ages for samples collected by Research School of Earth Sciences in the Prince Charles Mountains and vicinity.  Thus far work has been carried out in the 2001/2002, 2002/2003, 2003/2004 and 2004/2005 field seasons.  Currently, the only data publicly available is an excel spreadsheet detailing sampling locations.  The objectives of this project were:  To develop a comprehensive understanding of the Lambert Glacier of East Antarctica, from the time of the last maximum glaciation to the present, through an integrated and interdisciplinary study combining new field evidence - ice retreat history from cosmogenic exposure dating, geodetic measurements of crustal rebound, satellite measurements of present ice heights and changes therein - with other geological and glaciological data and numerical geophysical modelling advances.  The project contributes to the quantitative characterisation of the complex interactions between ice-sheets, oceans and solid earth within the climate system. Outcomes have implications for geophysics, glaciology, geomorphology, climate, and past and future sea-level change.  This work was completed as part of ASAC projects 2502 and 2516 (ASAC_2502 and ASAC_2516).  The fields in this dataset are:  Sample Date Collector Type Lithology Location Elevation Latitude Longitude	proprietary
 RSFDCE_KLIM4_Not provided	Absolute Minimum of Air Temperature. Year By Year Data	SCIOPS STAC Catalog	1881-01-01	1965-12-31	25, 23.21, -175, 71	https://cmr.earthdata.nasa.gov/search/concepts/C1214608674-SCIOPS.umm_json	Hydrometeorological data on the conditions of the environment are held       by the Russian State Fund of data. This dataset was created by West       Sybiria Computer Centre in 1977 and containes data from 1078 stations       of the USSR. Data is currently stored on magnetic tape (800 bit/inch).	proprietary
 RSFDCE_KLIM5_Not provided	Air Temperature 01.00 P.M. Year By Year Date	SCIOPS STAC Catalog	1881-01-01	1965-12-31	25, 23.21, -175, 71	https://cmr.earthdata.nasa.gov/search/concepts/C1214608673-SCIOPS.umm_json	Hydrometeorological data on the conditions of the environment are held       by the Russian State Fund of data. This dataset was created by West       Subiria Computer Centre in 1977 and containes data from 1078 stations       of the USSR. Data is currently stored on magnetic tape (800 bit/inch).	proprietary
+RSS18_AVIRIS_L1B_449_1	BOREAS RSS-18 Level 1B AVIRIS At-Sensor Radiance Imagery	ORNL_CLOUD STAC Catalog	1996-08-14	1996-08-14	-106.49, 53.45, -105.03, 54.32	https://cmr.earthdata.nasa.gov/search/concepts/C2929128157-ORNL_CLOUD.umm_json	This dataset holds Level 1B (L1B) radiance data collected by the AVIRIS-Classic instrument near Prince Albert, Saskatchewan, Canada, on August 14, 1996.  This imagery was acquired for the Boreal Ecosystem-Atmosphere Study (BOREAS) project in the boreal forests of central Canada. BOREAS focused on improving the understanding of exchanges of radiative energy, sensible heat, water, CO2 and trace gases between the boreal forest and the lower atmosphere. NASA's AVIRIS-Classic is a pushbroom spectral mapping system with high signal-to-noise ratio (SNR), designed and toleranced for high performance spectroscopy. AVIRIS-Classic measures reflected radiance in 224 contiguous bands at approximately 10-nm intervals in the Visible to Shortwave Infrared (VSWIR) spectral range from 400-2500 nm. The AVIRIS-Classic sensor has a 1 milliradian instantaneous field of view, providing altitude dependent ground sampling distances from 20 m to sub meter range. For these data, AVIRIS-Classic was deployed on NASA's ER-2 high altitude aircraft.  These spectra are acquired as images with 20-meter spatial resolution, 11 km swath width, and flight lines up to 800 km in length. The measurements are spectrally, radiometrically, and geometrically calibrated. There are seven flight lines subdivided into 66 scenes. The dataset includes the radiance imagery cube for each scene along with calibration and navigation information. The radiance data are in instrument coordinates, georeferenced by center of each scan line, and provided in a binary file. Metadata are included in a mixture of binary and text file formats.	proprietary
 RSS_WindSat_L1C_TB_V08.0_8.0	RSS WindSat L1C Calibrated TB Version 8	POCLOUD STAC Catalog	2003-02-01	2020-10-19	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2559430954-POCLOUD.umm_json	The WindSat Polarimetric Radiometer, launched on January 6, 2003 aboard the Department of Defense Coriolis satellite, was designed to measure the ocean surface wind vector from space. It developed by the Naval Research Laboratory (NRL) Remote Sensing Division and the Naval Center for Space Technology for the U.S. Navy and the National Polar-orbiting Operational Environmental Satellite System (NPOESS) Integrated Program Office (IPO). The dataset contains the Level 1C WindSat Top of the Atmosphere (TOA) TB processed by RSS. The WindSat radiances are turned into TOA TB after correction for hot and cold calibration anomalies, receiver non-linearities, sensor pointing errors, antenna cross-polarization contamination, spillover, Faraday rotation and polarization alignment. The data are resampled on a fixed regular 0.125 deg Earth grid using Backus-Gilbert Optimum Interpolation. The sampling is done separately for fore and aft looks. The 10.7, 18.7, 23.8, 37.0 GHz channels are resampled to the 10.7 GHz spatial resolution. The 6.8 GHz channels are given at their native spatial resolution. The 10.7, 18.7, 23.8, 37.0 GHz channels are absolutely calibrated using the GMI sensor as calibration reference. The 6.8 GHz channels are calibrated using the open ocean with the RSS ocean emission model and the Amazon rain forest as calibration targets. The Faraday rotation angle (FRA) and geometric polarization basis rotation angle (PRA) were added in the last run.	proprietary
 Radarsat-2_NA	RADARSAT-2 ESA Archive	ESA STAC Catalog	2008-07-27	2021-04-11	-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2119689631-ESA.umm_json	The RADARSAT-2 ESA archive collection consists of RADARSAT-2 products requested by ESA supported projects over their areas of interest around the world. The dataset regularly grows as ESA collects new products over the years. Following Beam modes are available: Standard, Wide Swath, Fine Resolution, Extended Low Incidence, Extended High Incidence, ScanSAR Narrow and ScanSAR Wide. Standard Beam Mode allows imaging over a wide range of incidence angles with a set of image quality characteristics which provides a balance between fine resolution and wide coverage, and between spatial and radiometric resolutions. Standard Beam Mode operates with any one of eight beams, referred to as S1 to S8, in single and dual polarisation . The nominal incidence angle range covered by the full set of beams is 20 degrees (at the inner edge of S1) to 52 degrees (at the outer edge of S8). Each individual beam covers a nominal ground swath of 100 km within the total standard beam accessibility swath of more than 500 km.  BEAM MODE: Standard PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 8.0 or 11.8 x 5.1  (SLC), 8.0 x 8.0 (SGX), 12.5 x 12.5 (SSG, SPG) Resolution - Range x Azimuth (m): 9.0 or 13.5 x 7.7  (SLC), 26.8 - 17.3 x 24.7  (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 100 x 100 Range of Angle of Incidence (deg): 20 - 52 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: • Single: HH or VV or HV or VH • Dual: HH + HV or VV + VH   Wide Swath Beam Mode allows imaging of wider swaths than Standard Beam Mode, but at the expense of slightly coarser spatial resolution. The three Wide Swath beams, W1, W2 and W3, provide coverage of swaths of approximately 170 km, 150 km and 130 km in width respectively, and collectively span a total incidence angle range from 20 degrees to 45 degrees. Polarisation can be single and dual.  BEAM MODE: Wide PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 11.8 x 5.1  (SLC), 10 x 10 (SGX), 12.5 x 12.5 (SSG, SPG) Resolution - Range x Azimuth (m): 13.5 x 7.7  (SLC), 40.0 - 19.2 x 24.7  (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 150 x 150 Range of Angle of Incidence (deg): 20 - 45 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: • Single: HH or VV or HV or VH • Dual: HH + HV or VV + VH  Fine Resolution Beam Mode is intended for applications which require finer spatial resolution. Products from this beam mode have a nominal ground swath of 50 km. Nine Fine Resolution physical beams, F23 to F21, and F1 to F6 are available to cover the incidence angle range from 30 to 50 degrees. For each of these beams, the swath can optionally be centred with respect to the physical beam or it can be shifted slightly to the near or far range side. Thanks to these additional swath positioning choices, overlaps of more than 50% are provided between adjacent swaths. RADARSAT-2 can operate in single and dual polarisation for this beam mode.  BEAM MODE: Fine PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 4.7 x 5.1   (SLC), 3.13 x 3.13 (SGX), 6.25 x 6.25 (SSG, SPG) Resolution - Range x Azimuth (m): 5.2 x 7.7  (SLC), 10.4 - 6.8 x 7.7  (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 50 x 50 Range of Angle of Incidence (deg): 30 - 50 No. of Looks - Range x Azimuth: 1 x 1 (SLC,SGX, SGF, SSG, SPG) Polarisations - Options: • Single: HH or VV or HV or VH • Dual: HH + HV or VV + VH  In the Extended Low Incidence Beam Mode, a single Extended Low Incidence Beam, EL1, is provided for imaging in the incidence angle range from 10 to 23 degrees with a nominal ground swath coverage of 170 km. Some minor degradation of image quality can be expected due to operation of the antenna beyond its optimum scan angle range. Only single polarisation is available.  BEAM MODE: Extended Low PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 8.0 x 5.1  (SLC), 10.0 x 10.0 (SGX), 12.5 x 12.5 (SSG, SPG) Nominal Resolution - Range x Azimuth (m): 9.0 x 7.7  (SLC), 52.7 - 23.3 x 24.7 (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 170 x 170 Range of Angle of Incidence (deg): 10 - 23 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: Single Pol HH  In the Extended High Incidence Beam Mode, six Extended High Incidence Beams, EH1 to EH6, are available for imaging in the 49 to 60 degree incidence angle range. Since these beams operate outside the optimum scan angle range of the SAR antenna, some degradation of image quality, becoming progressively more severe with increasing incidence angle, can be expected when compared with the Standard Beams. Swath widths are restricted to a nominal 80 km for the inner three beams, and 70 km for the outer beams. Only single polarisation available.  BEAM MODE: Extended High PRODUCT: SLC, SGX, SGF, SSG, SPG Nominal Pixel Spacing - Range x Azimuth (m) : 11.8 x 5.1  (SLC), 8.0 x 8.0 (SGX), 12.5 x 12.5 (SSG, SPG) Resolution - Range x Azimuth (m): 13.5 x 7.7  (SLC), 18.2 - 15.9 x 24.7 (SGX, SGF, SSG, SPG) Nominal Scene Size - Range x Azimuth (km): 75 x 75 Range of Angle of Incidence (deg): 49 - 60 No. of Looks - Range x Azimuth: 1 x 1 (SLC), 1 x 4 (SGX, SGF, SSG, SPG) Polarisations - Options: Single Pol HH  ScanSAR Narrow Beam Mode provides coverage of a ground swath approximately double the width of the Wide Swath Beam Mode swaths. Two swath positions with different combinations of physical beams can be used: SCNA, which uses physical beams W1 and W2, and SCNB, which uses physical beams W2, S5, and S6. Both options provide coverage of swath widths of about 300 km. The SCNA combination provides coverage over the incidence angle range from 20 to 39 degrees. The SCNB combination provides coverage over the incidence angle range 31 to 47 degrees. RADARSAT-2 can operate in single and dual polarisation for this beam mode.  BEAM MODE: ScanSAR Narrow PRODUCT: SCN, SCF, SCS Nominal Pixel Spacing - Range x Azimuth (m) : 25 x 25 Nominal Resolution - Range x Azimuth (m):81-38 x 40-70 Nominal Scene Size - Range x Azimuth (km): 300 x 300 Range of Angle of Incidence (deg): 20 - 46 No. of Looks - Range x Azimuth: 2 x 2 Polarisations - Options: • Single Co or Cross: HH or VV or HV or VH • Dual: HH + HV or VV + VH  ScanSAR Wide Beam Mode provides coverage of a ground swath approximately triple the width of the Wide Swath Beam Mode swaths. Two swath positions with different combinations of physical beams can be used: SCWA, which uses physical beams W1, W2, W3, and S7, and SCWB, which uses physical beams W1, W2, S5 and S6. The SCWA combination allows imaging of a swath of more than 500 km covering an incidence angle range of 20 to 49 degrees. The SCWB combination allows imaging of a swath of more than 450 km covering the incidence angle. Polarisation can be single and dual.  BEAM MODE: ScanSAR Wide PRODUCT: SCW, SCF, SCS Nominal Pixel Spacing - Range x Azimuth (m) : 50 x 50 Resolution - Range x Azimuth (m): 163.0 - 73 x 78-106 Nominal Scene Size - Range x Azimuth (km): 500 x 500 Range of Angle of Incidence (deg): 20 - 49 No. of Looks - Range x Azimuth: 4 x 2 Polarisations - Options: • Single Co or Cross: HH or VV or HV or VH • Dual: HH + HV or VV + VH  These are the different products :  SLC (Single Look Complex): Amplitude and phase information is preserved. Data is in slant range. Georeferenced and aligned with the satellite track SGF (Path Image): Data is converted to ground range and may be multi-look processed. Scene is oriented in direction of orbit path. Georeferenced and aligned with the satellite track. SGX (Path Image Plus): Same as SGF except processed with refined pixel spacing as needed to fully encompass the image data bandwidths. Georeferenced and aligned with the satellite track SSG(Map Image): Image is geocorrected to a map projection. SPG (Precision Map Image): Image is geocorrected to a map projection. Ground control points (GCP) are used to improve positional accuracy. SCN(ScanSAR Narrow)/SCF(ScanSAR Wide) : ScanSAR Narrow/Wide beam mode product with original processing options and metadata fields (for backwards compatibility only). Georeferenced and aligned with the satellite track SCF (ScanSAR Fine): ScanSAR product equivalent to SGF with additional processing options and metadata fields. Georeferenced and aligned with the satellite track SCS(ScanSAR Sampled) : Same as SCF except with finer sampling. Georeferenced and aligned with the satellite track	proprietary
 Radial_Growth_PRI_1781_1	ABoVE: Photochemical Reflectance and Tree Growth, Brooks Range, Alaska, 2018-2019	ORNL_CLOUD STAC Catalog	2018-05-01	2019-09-13	-149.76, 67.97, -149.72, 68.02	https://cmr.earthdata.nasa.gov/search/concepts/C2143401854-ORNL_CLOUD.umm_json	This dataset provides simultaneous in-situ measurements of the photochemical reflectance index (PRI) and radial tree growth of selected white spruce trees (Picea glauca (Moench) Voss) at the northern treeline in the Brooks Range of Alaska, south of Chandalar Shelf and Atigun Pass on the east side of the Dalton Highway. PRI and dendrometer measurements were simultaneously collected on 29 trees from six plots spaced along a 5.5 km transect from south to north where tree density becomes increasingly sparse. Measurements were made throughout the 2018 and 2019 growing seasons (May 1 to September 15) with a sampling interval of 5 minutes. The data were collected to better understand the suitability of the PRI to remotely track radial tree growth dynamics.	proprietary
@@ -12633,6 +12653,8 @@ SNEX20_VPTS_Raw_1	SnowEx20 Raw Near Surface Snow Temperature Profile Time Series
 SNEX21_COCP_GPR_1	SnowEx21 Cameron Pass Ground Penetrating Radar V001	NSIDC_ECS STAC Catalog	2021-01-13	2021-05-27	-105.893, 40.517, -105.867, 40.566	https://cmr.earthdata.nasa.gov/search/concepts/C2439238393-NSIDC_ECS.umm_json	This data set contains the results of 1 GHz ground-penetrating radar surveys conducted at Cameron Pass, Colorado during the SnowEx21 campaign. Data include two-way travel time, pit-measured snow density, calculated snow depth, and calculated snow water equivalent. Data were collected between 13 January 2021 and 27 May 2021.	proprietary
 SNEX21_COCP_GPR_Raw_1	SnowEx21 Cameron Pass Ground Penetrating Radar Raw V001	NSIDC_ECS STAC Catalog	2021-01-13	2021-05-27	-105.893, 40.517, -105.867, 40.566	https://cmr.earthdata.nasa.gov/search/concepts/C2551380225-NSIDC_ECS.umm_json	This data set contains the raw files from ground-penetrating radar surveys conducted at Cameron Pass, Colorado during the SnowEx21 campaign. Data were collected between 13 January 2021 and 27 May 2021.	proprietary
 SNEX21_DSM_1	SnowEx21 Prairie Station In Situ Dielectric Soil Moisture and Soil Temperature V001	NSIDC_ECS STAC Catalog	2020-11-05	2021-04-02	-109.959, 47.055, -109.946, 47.065	https://cmr.earthdata.nasa.gov/search/concepts/C2215574184-NSIDC_ECS.umm_json	This data set consists of soil moisture and soil temperature measurements taken during the SnowEx 2021 field campaign. Soil moisture probes were deployed at 9 locations within the Montana Prairie Station study area and monitored soil properties at four different depths (5, 10, 20 and 50 cm).	proprietary
+SNEX21_PS_DSM_1	SnowEx21 Prairie Station Digital Surface Models from UAV-LiDAR V001	NSIDC_ECS STAC Catalog	2021-01-15	2021-03-04	-109.9595558, 47.0562694, -109.945955, 47.0655368	https://cmr.earthdata.nasa.gov/search/concepts/C3241729770-NSIDC_ECS.umm_json	This dataset consists of Digital Surface Models (DSMs) derived from UAV-LiDAR acquired during the SnowEx 2021 field campaign at the Central Agricultural Research Center in central Montana (USA). The DSMs are at 0.3 m resolution and consist of one snow-off and seven snow-on flights.	proprietary
+SNEX21_PS_MET_1	SnowEx21 Prairie Station Hourly Meteorological Data V001	NSIDC_ECS STAC Catalog	2020-11-12	2021-04-02	-109.956783, 47.060545, -109.956783, 47.060545	https://cmr.earthdata.nasa.gov/search/concepts/C3241728800-NSIDC_ECS.umm_json	This data set contains observations from a meteorological station installed at the Central Agricultural Research Center in Moccasin Montana as part of the NASA SnowEx 2021 Prairie Snow field campaign. Parameters include: air temperature, wind speed and direction, and barometric pressure. Data are available from 12 November 2020 through 2 March 2021.	proprietary
 SNEX21_SSR_1	SnowEx21 Senator Beck Basin and Grand Mesa, CO AVIRIS-NG Surface Spectral Reflectance V001	NSIDC_ECS STAC Catalog	2021-03-19	2021-04-29	-109, 37, -107, 40	https://cmr.earthdata.nasa.gov/search/concepts/C2560987849-NSIDC_ECS.umm_json	This data set provides apparent surface spectral reflectance imagery which demonstrates snow albedo and snow optical property evolution across two distinct snow-covered environments in Colorado. Data collection occurred in the spring of 2021 as part of the NASA SnowEx mission. The two study sites (Senator Beck Basin and Grand Mesa) were chosen for their contrasting terrain and vegetation characteristics. Data collection occurred over three days (19 March, 1 April, and 29 April) to produce a time series data set across varying snow conditions.	proprietary
 SNEX21_TS_SP_1	SnowEx21 Time Series Snow Pits V001	NSIDC_ECS STAC Catalog	2020-11-16	2021-05-27	-116.12351, 37.9071, -105.86093, 47.0607	https://cmr.earthdata.nasa.gov/search/concepts/C3046987606-NSIDC_ECS.umm_json	The data set is a time-series of snow pit measurements obtained by the SnowEx community during the 2021 field campaign. Between November 2020 and May 2021 data from 247 snow pits were collected at 24 unique sites distributed over 4 states (CO, ID, MT, UT) throughout the Western United States. Five of the unique sites had a single visit to establish baseline conditions, while the remaining 19 sites had 3 or more repeat visits throughout the season, with a median visit count of 11.5. On a weekly interval, a snow pit was dug approximately 1 m away from the previous week’s snow pit. Available measured parameters are: snow depth, snow temperature, snow density, stratigraphy, grain size, manual wetness, liquid water content (LWC), and snow water equivalent (SWE). Also available are photos of the field notes and snow pit sites.	proprietary
 SNEX23_BCEF_TLS_1	SnowEx23 Bonanza Creek Experimental Forest Terrestrial Lidar Scans V001	NSIDC_ECS STAC Catalog	2022-10-22	2023-03-26	-148.325, 64.697, -148.278, 64.714	https://cmr.earthdata.nasa.gov/search/concepts/C2854618795-NSIDC_ECS.umm_json	"This data set contains digital terrain models (DTMs) derived from terrestrial lidar scans (TLS) collected as part of the SnowEx 2023 campaign. Data were collected at the Bonanza Creek Experimental Forest near Fairbanks, Alaska in October 2022 (snow-off conditions) and March 2023 (snow-on conditions). The DTMs are provided as Geographic Tagged Image (GeoTIFF) files, where each file corresponds to a unique survey site. Unprocessed point cloud data from which these DTMs were derived are available as the <a href=""https://doi.org/10.5067/OIBBFR49P0Q6"">SnowEx23 Bonanza Creek Experimental Forest Terrestrial Lidar Scans Raw, Version 1 (SNEX23_BCEF_TLS_Raw) data set</a>"	proprietary
@@ -13685,7 +13707,7 @@ TROPICS01URADL2A_1.0	TROPICS01 Pathfinder L2A Unified Resolution Brightness Te
 TROPICS03ANTTL1A_1.0	TROPICS03 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3171499152-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary
 TROPICS03BRTTL1B_1.0	TROPICS03 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3171499529-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary
 TROPICS03MIRSL2B_0.2	TROPICS03 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2857802936-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.   Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.   This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details."	proprietary
-TROPICS03PRPSL2B_0.2	TROPICS03 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2984907462-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.   Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS03 satellite and is the Provisional version of the Level 2B retrievals of instantaneous surface rain rate in units of mm/hr at G-band spatial resolution. The algorithm was adapted from the NASA Goddard Precipitation Retrieval and Profiling Scheme (PRPS). Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.  The provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details."	proprietary
+TROPICS03PRPSL2B_1.0	TROPICS03 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3254839500-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.   Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.   This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details."	proprietary
 TROPICS03URADL2A_1.0	TROPICS03 L2A Unified Resolution Brightness Temperatures V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3179859133-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS03 satellite, as the Validated Stage-1 version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary
 TROPICS05ANTTL1A_0.2	TROPICS05 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2985158466-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. "	proprietary
 TROPICS05BRTTL1B_0.2	TROPICS05 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2985145021-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data. "	proprietary
@@ -13693,7 +13715,7 @@ TROPICS05URADL2A_0.2	TROPICS05 L2A Unified Resolution Brightness Temperatures V
 TROPICS06ANTTL1A_1.0	TROPICS06 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3171499640-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary
 TROPICS06BRTTL1B_1.0	TROPICS06 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3171499970-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of six identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  This dataset is produced from the Pathfinder satellite, a single 3U small satellite, which has launched previous to the constellation, on a sun-synchronous orbital plane.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary
 TROPICS06MIRSL2B_0.2	TROPICS06 L2B Atmospheric Vertical Temperature and Moisture Profiles (AVTP, AVMP) V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2857801590-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.   Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS06 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.   This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details."	proprietary
-TROPICS06PRPSL2B_0.2	TROPICS06 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C2984933031-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.   Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS06 satellite and is the Provisional version of the Level 2B retrievals of instantaneous surface rain rate in units of mm/hr at G-band spatial resolution. The algorithm was adapted from the NASA Goddard Precipitation Retrieval and Profiling Scheme (PRPS). Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.   The provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details."	proprietary
+TROPICS06PRPSL2B_1.0	TROPICS06 Pathfinder L2B Instantaneous Surface Rain Rate (ISRR) V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3254839721-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones.  The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.   Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS03 satellite, as the Beta version of the Level 2B geophysical retrieval of atmospheric vertical temperature (kelvins) at the larger unified F-band resolution, retrieval of vertical moisture (g/kg) at the finer G-band spatial resolution, and total Precipitable Water (mm) at the finer G-band spatial resolution. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data.   This provisional TROPICS03 data release starts in the middle of June 2023 and TROPICS06 starts at the beginning of June 2023. Both data sets are updated nightly. There are some blackout periods where data is unavailable while the TROPICS team addresses a calibration issue that occurs during the warmest instrument temperatures. The warmest temperatures happen at extreme CubeSat solar beta angles. See README for this and other calibration observations and the Data Product Users Guide for orbit details."	proprietary
 TROPICS06URADL2A_1.0	TROPICS06 L2A Unified Resolution Brightness Temperatures V1.0	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3179860505-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  This dataset is from the TROPICS06 satellite, as the Validated Stage-1 version of the Level 2A geolocated brightness temperature with the water vapor sounding channels (Ch. 9 to 12) converted from their native G-band resolution to the temperature sounding channel (F-band) native resolution (i.e., all measurements at the same unified larger resolution). This product is used in the Atmospheric Vertical Temperature Profile (AVTP) retrievals to gain the benefit of averaging the G-band channels (i.e., noise reduction) while maintain the F-band (AVTP) spatial resolution. The conversion uses the Backus-Gilbert technique. Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary
 TROPICS07ANTTL1A_0.2	TROPICS07 L1A Orbital Geolocated Native-Resolution Antenna Temperatures V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3104586410-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary
 TROPICS07BRTTL1B_0.2	TROPICS07 L1B Orbital Geolocated Native-Resolution Brightness Temperatures V0.2	GES_DISC STAC Catalog	2021-07-19		-180, -90, 180, 90	https://cmr.earthdata.nasa.gov/search/concepts/C3104588185-GES_DISC.umm_json	"The ""Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats"" (TROPICS) mission has a goal of providing nearly all-weather observations of three-dimensional temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. The mission comprises a constellation of five identical Space Vehicles (SVs) conforming to the 3U form factor and hosting a passive microwave spectrometer payload.  Each SV hosts an identical high-performance spectrometer named the TROPICS Millimeter-wave Sounder (TMS) that will provide temperature profiles using seven channels near the 118.75-GHz oxygen absorption line, water vapor profiles using three channels near the 183-GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to cloud-sized ice particles.  Each TROPICS netCDF file contains a granule of data with 81 spots and approximately 2880 scans, where a granule is defined as an orbit's worth of data."	proprietary