From 4efcd0389dbf2ac78028cf4705c72e2d6f396e26 Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Sun, 3 Dec 2023 03:56:07 +0000 Subject: [PATCH] Updated datasets 2023-12-03 UTC --- nasa_cmr_catalog.json | 615 +++++++++++++++++------------------------- nasa_cmr_catalog.tsv | 51 ++-- 2 files changed, 270 insertions(+), 396 deletions(-) diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json index 1a87c51ff..1246d46ad 100644 --- a/nasa_cmr_catalog.json +++ b/nasa_cmr_catalog.json @@ -103,97 +103,6 @@ "description": " This dataset produced by the NASA Harvest team includes crop types labels from ground referencing matched with time-series of Sentinel-2 imagery during the growing season. Ground reference data are collected using an ODK app. Crop types include Maize, Millet, Rice and Sorghum. Labels are vectorized over the Sentinel-2 grid, and provided as raster files. Funding for this dataset is provided by Lutheran World Relief, Bill & Melinda Gates Foundation, and University of Maryland NASA Harvest program.", "license": "not-provided" }, - { - "id": "39480", - "title": "1988 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve", - "catalog": "NOAA_NCEI", - "state_date": "1988-11-24", - "end_date": "1988-11-24", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656753-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656753-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/39480", - "description": "Aerial photographs taken by NOAA's National Geodetic Survey during 1988 were mosaicked and orthorectified by the Biogeography Branch. The resulting image was used to digitize benthic, land cover and mangrove habitat maps of the Salt River Bay National Historic Park and Ecological Preserve (National Park Service), on St. Croix, in the U.S. Virgin Islands.The mosaic is centered on the National Park Service Site, located on the north central coast of St. Croix, and extends beyond the park boundaries approximately 0.5 - 4.0 km.", - "license": "not-provided" - }, - { - "id": "39481", - "title": "1988 Seagrass and Mangrove Habitats of the Salt River Bay National Historical Park and Ecological Preserve", - "catalog": "NOAA_NCEI", - "state_date": "1988-11-24", - "end_date": "1988-11-24", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656462-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656462-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/39481", - "description": "Habitat maps were created as part of a larger ecological assessment conducted by NOAA's National Ocean Service (NOS), Biogeography Branch, for Salt River Bay National Historic Park and Ecological Preserve (National Park Service).Aerial photographs were obtained for 1988 from the National Geodetic Survey, and were orthorectified by the Biogeography Branch. A classification scheme was set up with 20 benthic habitat types, 19 land cover types, and 13 mangrove habitat types. For this map of seagrass and mangrove habitats during 1988 only the 3 seagrass, and 14 mangrove classification categories were used. These were mapped directly into a GIS system through visual interpretation of orthorectified aerial photographs.", - "license": "not-provided" - }, - { - "id": "39482", - "title": "1992 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve", - "catalog": "NOAA_NCEI", - "state_date": "1992-01-31", - "end_date": "1992-01-31", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656472-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656472-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/39482", - "description": "Aerial photographs taken by NOAA's National Geodetic Survey during 1992 were mosaicked and orthorectified by the Biogeography Branch. The resulting image was used to digitize benthic, land cover and mangrove habitat maps of the Salt River Bay National Historic Park and Ecological Preserve (National Park Service), on St. Croix, in the U.S. Virgin Islands.The mosaic is centered on the National Park Service Site, located on the north central coast of St. Croix, and in some areas extends beyond the park boundaries up to 2 km.", - "license": "not-provided" - }, - { - "id": "39483", - "title": "1992 Seagrass and Mangrove Habitats of the Salt River Bay National Historical Park and Ecological Preserve", - "catalog": "NOAA_NCEI", - "state_date": "1992-01-31", - "end_date": "1992-01-31", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656483-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656483-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/39483", - "description": "Habitat maps were created as part of a larger ecological assessment conducted by NOAA's National Ocean Service (NOS), Biogeography Branch, for Salt River Bay National Historic Park and Ecological Preserve (National Park Service).Aerial photographs were obtained for 1992 from the National Geodetic Survey, and were orthorectified by the Biogeography Branch. A classification scheme was set up with 20 benthic habitat types, 19 land cover types, and 13 mangrove habitat types. For this map of seagrass and mangrove habitats during 1992 only the 3 seagrass, and 14 mangrove classification categories were used. These were mapped directly into a GIS system through visual interpretation of orthorectified aerial photographs.", - "license": "not-provided" - }, - { - "id": "39556", - "title": "1993 Average Monthly Sea Surface Temperature for California", - "catalog": "NOAA_NCEI", - "state_date": "1993-01-01", - "end_date": "1993-12-31", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656641-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656641-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/39556", - "description": "The NOAA/NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the NOAA -7, -9, -11, -14, -16 and -17 polar orbiting satellites. Daily, 8-day and monthly averaged data for both the ascending pass (daytime) and descending pass (nighttime) are available on equal-angle grids of 8192 pixels/360 degrees (nominally referred to as the 4km resolution, 4096 pixels/360 degrees (nominally referred to as the 9km resolution), 2048 pixels/360 degrees (nominally referred to as the 18km resolution), and 720 pixels/360 degrees (nominally referred to as the 54km resolution or 0.5 degree resolution).The monthly averaged daytime data was converted to an ESRI GRID format and the 12 monthly grid files were combined into one annual grid with a attribute field for each month.", - "license": "not-provided" - }, - { - "id": "39557", - "title": "1994 Average Monthly Sea Surface Temperature for California", - "catalog": "NOAA_NCEI", - "state_date": "1994-01-01", - "end_date": "1994-12-31", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656671-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656671-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/39557", - "description": "The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the NOAA -7, -9, -11, -14, -16 and -17 polar orbiting satellites. Daily, 8-day and monthly averaged data for both the ascending pass (daytime) and descending pass (nighttime) are available on equal-angle grids of 8192 pixels/360 degrees (nominally referred to as the 4km resolution, 4096 pixels/360 degrees (nominally referred to as the 9km resolution), 2048 pixels/360 degrees (nominally referred to as the 18km resolution), and 720 pixels/360 degrees (nominally referred to as the 54km resolution or 0.5 degree resolution).The monthly averaged daytime data was converted to an ESRI GRID format and the 12 monthly grid files were combined into one annual grid with a attribute field for each month.", - "license": "not-provided" - }, - { - "id": "39558", - "title": "1995 Average Monthly Sea Surface Temperature for California", - "catalog": "NOAA_NCEI", - "state_date": "1995-01-01", - "end_date": "1995-12-31", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656698-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2102656698-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/39558", - "description": "The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the NOAA -7, -9, -11, -14, -16 and -17 polar orbiting satellites. Daily, 8-day and monthly averaged data for both the ascending pass (daytime) and descending pass (nighttime) are available on equal-angle grids of 8192 pixels/360 degrees (nominally referred to as the 4km resolution, 4096 pixels/360 degrees (nominally referred to as the 9km resolution), 2048 pixels/360 degrees (nominally referred to as the 18km resolution), and 720 pixels/360 degrees (nominally referred to as the 54km resolution or 0.5 degree resolution).The monthly averaged daytime data was converted to an ESRI GRID format and the 12 monthly grid files were combined into one annual grid with a attribute field for each month.", - "license": "not-provided" - }, { "id": "3DIMG_L1B_STD", "title": "INSAT-3D Imager Level-1B Full Acquisition Standard Product", @@ -376,19 +285,6 @@ "description": "Land cover is a key variable in the context of climate change. In particular, crop type information is essential to understand the spatial distribution of water usage and anticipate the risk of water scarcity and the consequent danger of food insecurity. This applies to arid regions such as the Aral Sea Basin (ASB), Central Asia, where agriculture relies heavily on irrigation. Here, remote sensing is valuable to map crop types, but its quality depends on consistent ground-truth data. Yet, in the ASB, such data is missing. Addressing this issue, we collected thousands of polygons on crop types, 97.7% of which in Uzbekistan and the remaining in Tajikistan. We collected 8,196 samples between 2015 and 2018, 213 in 2011 and 26 in 2008. Our data compiles samples for 40 crop types and is dominated by \u201ccotton\u201d (40%) and \u201cwheat\u201d, (25%). These data were meticulously validated using expert knowledge and remote sensing data and relied on transferable, open-source workflows that will assure the consistency of future sampling campaigns.", "license": "not-provided" }, - { - "id": "AAOT.v0", - "title": "Acqua Alta Oceanographic Tower (AAOT)", - "catalog": "OB_DAAC", - "state_date": "1999-08-03", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360084-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360084-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/AAOT.v0", - "description": "Measurements made by the Acqua Alta Oceanographic Tower (AAOT), an Italian installation off the coast of Venice in the Adriatic Sea from 1999 to 2002.", - "license": "not-provided" - }, { "id": "AAS_4156_Macquarie_Island_Emerald_Lake.v1", "title": "12,000 year record of sea spray and minerogenic input from Emerald Lake, Macquarie Island", @@ -610,19 +506,6 @@ "description": "ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_CPL_Data) are remotely sensed measurements collected by the Cloud Physics Lidar (CPL) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA\u2019s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.", "license": "not-provided" }, - { - "id": "ACIDD.v0", - "title": "Across the Channel Investigating Diel Dynamics project", - "catalog": "OB_DAAC", - "state_date": "2017-12-16", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360091-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360091-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/ACIDD.v0", - "description": "The ACIDD (Across the Channel Investigating Diel Dynamics) project, in the Santa Barbara Channel, was initially designed to characterize daily variations in phytoplankton populations, but with the Thomas Fire in the Santa Barbara Hills December 2017, this project evolved into a study to characterize the effects of smoke and ash on the mixed layer in the Santa Barbara Channel.", - "license": "not-provided" - }, { "id": "ACOS_L2S.v7.3", "title": "ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V7.3 (ACOS_L2S) at GES DISC", @@ -1858,19 +1741,6 @@ "description": " The Advanced Very High Resolution Radiometer (AVHRR) 1-km Orbital Segments data set is a component of the National Aeronautics and Space Administration (NASA) AVHRR Pathfinder Program and contains global coverage of land masses at 1-kilometer resolution. The data set is the result of an international effort to acquire, process, and distribute AVHRR data of the entire global land surface to meet the needs of the international science community. The orbital segments are comprised of raw AVHRR scenes consisting of 5-channel, 10-bit, AVHRR data at 1.1-km resolution at nadir. The raw data are used to produce vegetation index composites; to support fire detection and cloud screening activities; to support research in atmospheric correction; to develop algorithms; and to support a host of research activities that may require the inclusion of raw AVHRR data. ", "license": "not-provided" }, - { - "id": "Active_Fluorescence_2001.v0", - "title": "Active fluorescence measurements in the Gulf Stream in 2001", - "catalog": "OB_DAAC", - "state_date": "2001-06-01", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360093-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360093-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/Active_Fluorescence_2001.v0", - "description": "Measurements in the Gulf Stream off the East Coast of the US in 2001", - "license": "not-provided" - }, { "id": "AgriFieldNet Competition Dataset.v1", "title": "AgriFieldNet Competition Dataset", @@ -2326,19 +2196,6 @@ "description": "The collection represents browse images and metadata for systematically georeferenced Radarsat-1 Synthetic Aperture Radar(SAR) satellite scenes. The browse scenes are not geometrically enhanced using ground control points, but are systematically corrected using sensor parameters. Full resolution precision geocoded scenes(corrected using ground control points) which correspond to the browse images can be ordered from MacDonald Dettwiler and Associates Ltd., Vancouver, Canada. Metadata discovery is achieved using the online catalog https://neodf.nrcan.gc.ca/neodf_cat3 OR by using the CWIC OGC CSW service URL : http://cwic.csiss.gmu.edu/cwicv1/discovery. Radarsat-1 operates at 5.3 GHz. (C-Band). It is in a sun-synchronous orbit. Image resolution is in the range 8-100 meters.", "license": "not-provided" }, - { - "id": "Catlin_Arctic_Survey.v0", - "title": "2011 R/V Catlin cruise in the Arctic Ocean", - "catalog": "OB_DAAC", - "state_date": "2011-03-17", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360181-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360181-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/Catlin_Arctic_Survey.v0", - "description": "Measurements made in the Arctic Ocean by the RV Catlin in 2011.", - "license": "not-provided" - }, { "id": "Chesapeake Land Cover.v1", "title": "Chesapeake Land Cover", @@ -3002,19 +2859,6 @@ "description": "This database contains information compiled from published studies on gas flux from soil following rewetting or thawing. The resulting database includes 222 field and laboratory observations focused on rewetting of dry soils, and 116 field laboratory observations focused on thawing of frozen soils studies conducted from 1956 to 2010. Fluxes of carbon dioxide, methane, nitrous oxide, nitrogen oxide, and ammonia (CO2, CH4, N2O, NO and NH3) were compiled from the literature and the flux rates were normalized for ease of comparison. Field observations of gas flux following rewetting of dry soils include events caused by natural rainfall, simulated rainfall in natural ecosystems, and irrigation in agricultural lands. Similarly, thawing of frozen soils include field observations of natural thawing, simulated freezing-thawing events (i.e., thawing of simulated frozen soil by snow removal), and thawing of seasonal ice in temperate and high latitude regions (Kim et al., 2012). Reported parameters include experiment type, location, site type, vegetation, climate, soil properties, rainfall, soil moisture, soil gas flux after wetting and thawing, peak soil gas flux properties, and the corresponding study references. There is one comma-delimited data file. ", "license": "not-provided" }, - { - "id": "GreenBay.v0", - "title": "2010 Measurements made in Green Bay, Wisconsin", - "catalog": "OB_DAAC", - "state_date": "2010-09-17", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360352-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360352-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/GreenBay.v0", - "description": "Measurements made in Green Bay, Wisconsin in 2010.", - "license": "not-provided" - }, { "id": "IKONOS_MSI_L1B.v1", "title": "IKONOS Level 1B Multispectral 4-Band Satellite Imagery", @@ -3379,6 +3223,19 @@ "description": "The combined MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product\u2019s short-name. The \u201cCOSP\u201d acronym in its short-name stands for Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. The L3 monthly product is derived by aggregating the daily-produced Aqua+Terra/MODIS D3 Cloud Properties product (MCD06COSP_D3_MODIS). Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters).", "license": "not-provided" }, + { + "id": "MCD14DL_C5_NRT.v005", + "title": "MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT", + "catalog": "LM_FIRMS", + "state_date": "2014-01-28", + "end_date": "", + "bbox": "-180, -80, 180, 80", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LM_FIRMS/collections/MCD14DL_C5_NRT.v005", + "description": "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.", + "license": "not-provided" + }, { "id": "MIANACP.v1", "title": "MISR Aerosol Climatology Product V001", @@ -3457,32 +3314,6 @@ "description": "This is the browse data associated with a particular granule.", "license": "not-provided" }, - { - "id": "MURI_Camouflage.v0", - "title": "A Multi University Research Initiative (MURI) Camouflage Project", - "catalog": "OB_DAAC", - "state_date": "2010-06-14", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360494-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360494-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/MURI_Camouflage.v0", - "description": "A Multi University Research Initiative was funded to study the biological response to the dynamic, polarized light field in distinct water types. During June 2010, a campaign was undertaken in the coastal waters off Port Aransas, Texas to study the angular/temporal distribution of polarization in multiple environment types (eutrophic sediment laden coastal waters, oligotrophic off-shore), as well as the polarization-reflectance responses of several organisms. In addition to radiometric polarization measurements, water column IOPs, Rrs, benthic reflectance, and pigment concentration measurements were collected. Later campaigns expanded this research in the coastal waters off the Florida Keys.", - "license": "not-provided" - }, - { - "id": "MURI_HI.v0", - "title": "A Multi University Research Initiative (MURI) near the Hawaiian Islands", - "catalog": "OB_DAAC", - "state_date": "2012-05-31", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360508-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360508-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/MURI_HI.v0", - "description": "Measurements taken by the RV Kilo Moana in 2012 near the Hawaiian Islands.", - "license": "not-provided" - }, { "id": "MYD021KM.v6.1NRT", "title": "MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 1km - NRT", @@ -4016,6 +3847,123 @@ "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": "not-provided" }, + { + "id": "PACE_HARP2_L0.v1", + "title": "PACE HARP2 Level-0 Instrument Telemetry/Multi-Detector Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798249-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798249-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L0.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L0_D1.v1", + "title": "PACE HARP2 Level-0 Detector 1 (D1) Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798238-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798238-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L0_D1.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L0_D2.v1", + "title": "PACE HARP2 Level-0 Detector 2 (D2) Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798239-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798239-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L0_D2.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L0_D3.v1", + "title": "PACE HARP2 Level-0 Detector 3 (D3) Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798240-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798240-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L0_D3.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L0_REAL.v1", + "title": "PACE HARP2 Level-0 Real-time Direct Transfer Mode Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798243-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798243-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L0_REAL.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L0_SCI.v1", + "title": "PACE HARP2 Level-0 Science Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798245-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798245-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L0_SCI.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L1A_AST0.v1", + "title": "PACE HARP2 Level-1A Acquisition Scheme Type 0 - Full-Resolution Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798253-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798253-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L1A_AST0.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L1A_AST1.v1", + "title": "PACE HARP2 Level-1A Acquisition Scheme Type 1 - Half-Resolution Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798256-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798256-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L1A_AST1.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, + { + "id": "PACE_HARP2_L1A_AST2.v1", + "title": "PACE HARP2 Level-1A Acquisition Scheme Type 2 - Science Mode (no MTDI) Data, version 1", + "catalog": "OB_CLOUD", + "state_date": "2022-03-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798261-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2804798261-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/PACE_HARP2_L1A_AST2.v1", + "description": "The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape.", + "license": "not-provided" + }, { "id": "PM1EPHND_NRT.v6.1NRT", "title": "MODIS/Aqua 24-hour Spacecraft ephemeris/orbit data files to be read via SDP Toolkit Binary Format - NRT", @@ -4094,6 +4042,19 @@ "description": "The Soil Respiration Database (SRDB) is a near-universal compendium of published soil respiration (Rs) data. The database encompasses published studies that report at least one of the following data measured in the field (not laboratory): annual soil respiration, mean seasonal soil respiration, a seasonal or annual partitioning of soil respiration into its source fluxes, soil respiration temperature response (Q10), or soil respiration at 10 degrees C. The SRDB's orientation is to seasonal and annual fluxes, not shorter-term or chamber-specific measurements, and the database is dominated by temperate, well-drained forest measurement locations. Version 5 (V5) is the compilation of 2,266 published studies with measurements taken between 1961-2017. 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. The database is also restructured to have better interoperability with other datasets related to carbon-cycle science.", "license": "not-provided" }, + { + "id": "SeaWiFS_L2_GAC_OC.vR2022.0", + "title": "OrbView-2 SeaWiFS Regional Global Area Coverage (GAC) Ocean Color (OC) Data, version R2022.0", + "catalog": "OB_CLOUD", + "state_date": "1997-09-04", + "end_date": "2010-12-11", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789774382-OB_CLOUD.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789774382-OB_CLOUD.html", + "href": "https://cmr.earthdata.nasa.gov/stac/OB_CLOUD/collections/SeaWiFS_L2_GAC_OC.vR2022.0", + "description": "The SeaWiFS instrument was launched by Orbital Sciences Corporation on the OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from September 1997 until the end of mission in December 2010. SeaWiFS had 8 spectral bands from 412 to 865 nm. It collected global data at 4 km resolution, and local data (limited onboard storage and direct broadcast) at 1 km. The mission and sensor were optimized for ocean color measurements, with a local noon (descending) equator crossing time orbit, fore-and-aft tilt capability, full dynamic range, and low polarization sensitivity.", + "license": "not-provided" + }, { "id": "Survey_1988_89_Mawson_npcms.v1", "title": "1988/89 Summer season, surveying and mapping program, Mawson - North Prince Charles Mountains - Davis", @@ -4107,19 +4068,6 @@ "description": "Field season report of these programs: 1988/89 Summer Season surveying and mapping North Prince Charles Mountains; ...mapping program Northern PCM's - Mawson Doppler Translocation Support; ....mapping program Voyage 6 stopover Davis. Includes maps and mapsheet layouts. See the report for full details on the program. Contents are: Introduction Preparation Voytage to Antarctica 1988/89 Summer Season Surveying and Mapping Program, Northern Prince Charles Mountains 1988/89 Summer Season Surveying and Mapping Program, Voyage 6 Stopover, Davis Performance of Equipment Station Marking Field Camping Climatic Conditions Conclusion Appendices ", "license": "not-provided" }, - { - "id": "Turbid9.v0", - "title": "2004 Measurements made in the Chesapeake Bay", - "catalog": "OB_DAAC", - "state_date": "2004-10-01", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360689-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360689-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/Turbid9.v0", - "description": "Measurements made in the Chesapeake Bay in 2004.", - "license": "not-provided" - }, { "id": "USAP-1543498.v1", "title": "A Full Lifecycle Approach to Understanding Ad\u00e9lie Penguin Response to Changing Pack Ice Conditions in the Ross Sea", @@ -4380,6 +4328,19 @@ "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 2021 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": "not-provided" }, + { + "id": "a-numerical-solver-for-heat-and-mass-transport-in-snow-based-on-fenics.v1.0", + "title": "A numerical solver for heat and mass transport in snow based on FEniCS", + "catalog": "ENVIDAT", + "state_date": "2022-01-01", + "end_date": "2022-01-01", + "bbox": "9.8472494, 46.812044, 9.8472494, 46.812044", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814662-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814662-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/a-numerical-solver-for-heat-and-mass-transport-in-snow-based-on-fenics.v1.0", + "description": "This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format. The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication: _Sch\u00fcrholt, K., Kowalski, J., L\u00f6we, H.; Elements of future snowpack modeling - Part 1: A physical instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_ The code and potential updates can be accessed directly through git via: https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics", + "license": "not-provided" + }, { "id": "a6efcb0868664248b9cb212aba44313d", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from MERIS (ALAMO algorithm), Version 2.2", @@ -4394,133 +4355,68 @@ "license": "not-provided" }, { - "id": "aamhcpex.v1", - "title": "AAMH CPEX V1", - "catalog": "GHRC_DAAC", - "state_date": "2017-05-26", - "end_date": "2017-07-16", - "bbox": "154.716, 0.6408, -19.5629, 44.9689", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2645106424-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2645106424-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/aamhcpex.v1", - "description": "The AAMH CPEX dataset contains products obtained from the MetOp-A, MetOp-B, NOAA-18, and NOAA-19 satellites. These data were collected in support of the NASA Convective Processes Experiment (CPEX) field campaign. The CPEX field campaign took place in the North Atlantic-Gulf of Mexico-Caribbean Sea region from 25 May-25 June 2017. CPEX conducted a total of sixteen DC-8 missions from 27 May-24 June. The CPEX campaign collected data to help explain convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of Mexico-Caribbean Oceanic region during the early summer of 2017. These data are available from May 26, 2017 through July 15, 2017 and are available in netCDF-4 format.", - "license": "not-provided" - }, - { - "id": "aces1am.v1", - "title": "ACES Aircraft and Mechanical Data V1", - "catalog": "GHRC_DAAC", - "state_date": "2002-07-10", - "end_date": "2002-08-30", - "bbox": "-85, 23, -81, 26", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1977826980-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1977826980-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/aces1am.v1", - "description": "The ACES Aircraft and Mechanical Data consist of aircraft (e.g. pitch, roll, yaw) and mechanical (e.g. aircraft engine speed, tail commands, fuel levels) data recorded by the Altus II Unmanned Aerial Vehicle (Altus II UAV) system during the Altus Cumulus Electrification Study (ACES) based at the Naval Air Facility Key West in Florida. ACES aimed to provide extensive observations of the cloud electrification process and its effects by using the Altus II UAV to collect cloud top observations of thunderstorms. The campaign also worked to validate satellite lightning measurements. The Altus II aircraft and mechanical data files are available from July 10 through August 30, 2002 in MATLAB data format (.mat). ", - "license": "not-provided" - }, - { - "id": "aces1cont.v1", - "title": "ACES CONTINUOUS DATA V1", - "catalog": "GHRC_DAAC", - "state_date": "2002-07-10", - "end_date": "2002-08-30", - "bbox": "-85, 23, -81, 26", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1977847043-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1977847043-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/aces1cont.v1", - "description": "The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August, 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloudelectrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from seven instruments: the Slow/Fast antenna, Electric Field Mill, Dual Optical Pulse Sensor, Searchcoil Magnetometer, Accelerometers, Gerdien Conductivity Probe, and the Fluxgate Magnetometer. Data consists of sensor reads at 50HZ throughout the flight from all 64 channels.", + "id": "above-and-below-ground-herbivore-communities-along-elevation.v1.0", + "title": "Above- and below-ground herbivore communities along elevation", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "5.95587, 45.81802, 10.49203, 47.80838", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/above-and-below-ground-herbivore-communities-along-elevation.v1.0", + "description": "Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017. ", "license": "not-provided" }, { - "id": "aces1efm.v1", - "title": "ACES ELECTRIC FIELD MILL V1", - "catalog": "GHRC_DAAC", - "state_date": "2002-07-10", - "end_date": "2002-08-30", - "bbox": "-85, 23, -81, 26", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1977847178-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1977847178-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/aces1efm.v1", - "description": "The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from it's birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data from Electric Field Mills, which yield information about the atmospheric electrical fields above the instruments.", + "id": "aerosol-data-davos-wolfgang.v1.0", + "title": "Aerosol Data Davos Wolfgang", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "9.853594, 46.835577, 9.853594, 46.835577", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/aerosol-data-davos-wolfgang.v1.0", + "description": "Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 \u2013 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle\u2019s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. ", "license": "not-provided" }, { - "id": "aces1log.v1", - "title": "ACES LOG DATA V1", - "catalog": "GHRC_DAAC", - "state_date": "2002-07-10", - "end_date": "2002-08-30", - "bbox": "-85, 23, -81, 26", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1977853903-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1977853903-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/aces1log.v1", - "description": "The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of log data from each flight, and yields instrument and aircraft status throughout the flight.", + "id": "aerosol-data-weissfluhjoch.v1.0", + "title": "Aerosol Data Weissfluhjoch", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "9.806475, 46.832964, 9.806475, 46.832964", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/aerosol-data-weissfluhjoch.v1.0", + "description": "Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 \u2013 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle\u2019s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. ", "license": "not-provided" }, { - "id": "aces1time.v1", - "title": "ACES TIMING DATA V1", - "catalog": "GHRC_DAAC", - "state_date": "2002-07-10", - "end_date": "2002-08-30", - "bbox": "-85, 23, -81, 26", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1977855412-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1977855412-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/aces1time.v1", - "description": "The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August or 2002, ACES researchers overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of timing data used for the experiment. When used it provides: syncclock_time = time found at the syncclock (VSI-SYnCCLOCK-32) in seconds from first file name, syncclock_m_time = time found at the syncclock (VSI-SYnCCLOCK-32) in Matlab dateform format, system_time = system time in seconds from first file name, system_m_time = system time in dateform format, gps_time = time found at the GPS unit in seconds from first file name, gps_m_time = time found at GPS unit in dateform, cmos_time = time found at the computer CMOS in seconds from first file name, cmos_m_time = time found at the computer CMOS in dateform.", + "id": "alnus-glutinosa-orientus-ishidae-flavescence-doree.v1.0", + "title": "Alnus glutinosa (L.) Gaertn. and Orientus ishidae (Matsumura, 1902) share phytoplasma genotypes linked to the \u201cFlavescence dor\u00e9e\u201d epidemics", + "catalog": "ENVIDAT", + "state_date": "2021-01-01", + "end_date": "2021-01-01", + "bbox": "8.4484863, 45.8115721, 9.4372559, 46.4586735", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814963-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814963-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/alnus-glutinosa-orientus-ishidae-flavescence-doree.v1.0", + "description": "Flavescence dor\u00e9e (FD) is a grapevine disease caused by associated phytoplasmas (FDp), which are epidemically spread by their main vector Scaphoideus titanus. The possible roles of alternative and secondary FDp plant hosts and vectors have gained interest to better understand the FDp ecology and epidemiology. A survey conducted in the surroundings of a vineyard in the Swiss Southern Alps aimed at studying the possible epidemiological role of the FDp secondary vector Orientus ishidae and the FDp host plant Alnus glutinosa is reported. Data used for the publication. Insects were captured by using a sweeping net (on common alder trees) and yellow sticky traps (Rebell Giallo, Andermatt Biocontrol AG, Switzerland) placed in the vineyard canopy. Insects were later determined and selected for molecular analyses. Grapevines and common alder samples were collected using the standard techniques. The molecular analyses were conducted in order to identify samples infected by the Flavescence dor\u00e9e phytoplasma (16SrV-p) and the Bois Noir phytoplasma (16SrXII-p). A selection of the infected sampled were further characterized by map genotype and sequenced in order to compare the genotypes in insects, grapevines and common alder trees. ", "license": "not-provided" }, { - "id": "aces1trig.v1", - "title": "ACES TRIGGERED DATA V1", - "catalog": "GHRC_DAAC", - "state_date": "2002-07-10", - "end_date": "2002-08-30", - "bbox": "-85, 23, -81, 26", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1977858342-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1977858342-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/aces1trig.v1", - "description": "The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from the following instruments: Slow/Fast antenna, Electric Field Mill, Optical Pulse Sensors, Searchcoil Magnetometer, Accelerometer, and Gerdien Conductivity Probe. These data were collected at 200KHz from the first 16 telemetry items collected on the aircraft, were initiated by an operator selected trigger (e.g. DOPS), and continued collecting for as long as the trigger continued.", - "license": "not-provided" - }, - { - "id": "amprimpacts.v1", - "title": "Advanced Microwave Precipitation Radiometer (AMPR) IMPACTS V1", - "catalog": "GHRC_DAAC", - "state_date": "2020-01-18", - "end_date": "2022-02-28", - "bbox": "-118.51, 30.6918, -64.3661, 48.2585", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2004708841-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2004708841-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/amprimpacts.v1", - "description": "The Advanced Microwave Precipitation Radiometer (AMPR) IMPACTS dataset consists of brightness temperature measurements collected by the Advanced Microwave Precipitation Radiometer (AMPR) onboard the NASA ER-2 high-altitude research aircraft. AMPR provides multi-frequency microwave imagery, with high spatial and temporal resolution for deriving cloud, precipitation, water vapor and surface properties. These measurements were taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Funded by NASA\u2019s Earth Venture program, IMPACTS is the first comprehensive study of East Coast snowstorms in 30 years. Data files are available from January 18, 2020 through February 28, 2022 in netCDF-4 format. ", - "license": "not-provided" - }, - { - "id": "amsua15sp.v1", - "title": "ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15 V1", - "catalog": "GHRC_DAAC", - "state_date": "1998-08-03", - "end_date": "", - "bbox": "-180, -90, 180, 89.756", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1996541017-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1996541017-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/amsua15sp.v1", - "description": "AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NOAA-15 was the first spacecraft to fly AMSU. Launched on 13 May 1998, NOAA-15 is in a sun synchronous near polar orbit.", - "license": "not-provided" - }, - { - "id": "amsua16sp.v1", - "title": "ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-16 V1", - "catalog": "GHRC_DAAC", - "state_date": "2001-05-27", - "end_date": "2009-07-30", - "bbox": "-180, -89.91, 180, 89.73", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1979956366-GHRC_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1979956366-GHRC_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/GHRC_DAAC/collections/amsua16sp.v1", - "description": "AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). Launched on 21 September 2000, NOAA-16 is in a sun synchronous near polar orbit.", + "id": "alpine3d-simulations-of-future-climate-scenarios-for-graubunden.v1.0", + "title": "Alpine3D simulations of future climate scenarios for Graubunden", + "catalog": "ENVIDAT", + "state_date": "2019-01-01", + "end_date": "2019-01-01", + "bbox": "8.6737061, 46.2216525, 10.6347656, 47.1075228", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814545-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814545-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/alpine3d-simulations-of-future-climate-scenarios-for-graubunden.v1.0", + "description": "This is the simulation dataset from _\"Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland\"_, M. Bavay, T. Gr\u00fcnewald, M. Lehning, Advances in Water Resources __55__, 4-16, 2013 A model study on the impact of climate change on snow cover and runoff has been conducted for the Swiss Canton of Graub\u00fcnden. The model Alpine3D has been forced with the data from 35 Automatic Weather Stations in order to investigate snow and runoff dynamics for the current climate. The data set has then been modified to reflect climate change as predicted for the 2021-2050 and 2070-2095 periods from an ensemble of regional climate models. The predicted changes in snow cover will be moderate for 2021-2050 and become drastic in the second half of the century. Towards the end of the century the snow cover changes will roughly be equivalent to an elevation shift of 800 m. Seasonal snow water equivalents will decrease by one to two thirds and snow seasons will be shortened by five to nine weeks in 2095. Small, higher elevation catchments will show more winter runoff, earlier spring melt peaks and reduced summer runoff. Where glacierized areas exist, the transitional increase in glacier melt will initially offset losses from snow melt. Larger catchments, which reach lower elevations will show much smaller changes since they are already dominated by summer precipitation.", "license": "not-provided" }, { @@ -4576,16 +4472,16 @@ "license": "not-provided" }, { - "id": "chesapeake_val_2013.v0", - "title": "2013 Chesapeake Bay measurements", - "catalog": "OB_DAAC", - "state_date": "2013-04-11", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360188-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360188-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/chesapeake_val_2013.v0", - "description": "2013 Chesapeake Bay measurements.", + "id": "ch2014.v1", + "title": "Alpine3D simulations of future climate scenarios CH2014", + "catalog": "ENVIDAT", + "state_date": "2014-01-01", + "end_date": "2014-01-01", + "bbox": "8.227, 46.79959, 8.227, 46.79959", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814657-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814657-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/ch2014.v1", + "description": "# Overview The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change. # Experimental Setup Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graub\u00fcnden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m \u00d7 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999\u20132012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085). # Data Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5\u20139 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400\u2013800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average. ", "license": "not-provided" }, { @@ -4615,42 +4511,16 @@ "license": "not-provided" }, { - "id": "gov.noaa.nodc:0000029", - "title": "1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029)", - "catalog": "NOAA_NCEI", - "state_date": "1990-09-26", - "end_date": "1995-05-26", - "bbox": "-124.041667, 0.766667, -16.25, 46.263167", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2089372282-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2089372282-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/gov.noaa.nodc:0000029", - "description": "Not provided", - "license": "not-provided" - }, - { - "id": "gov.noaa.nodc:0000035", - "title": "1996 - Early 1998 CRETM/LMER Phytoplankton Data (NCEI Accession 0000035)", - "catalog": "NOAA_NCEI", - "state_date": "1996-07-09", - "end_date": "1998-03-06", - "bbox": "-124.003, 46.179833, -123.183167, 46.261667", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2089372325-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2089372325-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/gov.noaa.nodc:0000035", - "description": "Pump cast sampling, and associated CTD casts took place from a fixed vessel during one 28-35 day cruise per year in 1990, 1991, 1992, 1995, and 1996. In 1997 there were 2 week cruises in May, July, and October.", - "license": "not-provided" - }, - { - "id": "gov.noaa.nodc:0000052", - "title": "1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052)", - "catalog": "NOAA_NCEI", - "state_date": "1988-03-01", - "end_date": "1988-06-28", - "bbox": "-149.4083, 59.9117, -149.3583, 60.02", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2089372461-NOAA_NCEI.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2089372461-NOAA_NCEI.html", - "href": "https://cmr.earthdata.nasa.gov/stac/NOAA_NCEI/collections/gov.noaa.nodc:0000052", - "description": "Zooplantkon and beach tar data were collected using plankton net casts in the Gulf of Alaska from the ALPHA HELIX. Data were collected from 01 March 1988 to 28 June 1988 by University of Alaska in Fairbanks; Institute of Marine Science with support from the Gulf of Alaska - 1 (GAK-1) project.", + "id": "envidat-lwf-34.v2019-03-06", + "title": "10-HS Pfynwald", + "catalog": "ENVIDAT", + "state_date": "2019-01-01", + "end_date": "2019-01-01", + "bbox": "7.61211, 46.30279, 7.61211, 46.30279", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/envidat-lwf-34.v2019-03-06", + "description": "Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) ", "license": "not-provided" }, { @@ -4784,16 +4654,16 @@ "license": "not-provided" }, { - "id": "lake_erie_aug_2014.v0", - "title": "2014 Lake Erie measurements", - "catalog": "OB_DAAC", - "state_date": "2014-08-18", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360418-OB_DAAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633360418-OB_DAAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/OB_DAAC/collections/lake_erie_aug_2014.v0", - "description": "2014 Lake Erie measurements.", + "id": "latent-reserves-in-the-swiss-nfi.v1.0", + "title": "'Latent reserves' within the Swiss NFI", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "5.95587, 45.81802, 10.49203, 47.80838", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/latent-reserves-in-the-swiss-nfi.v1.0", + "description": "The files refer to the data used in Portier et al. \"\u2018Latent reserves\u2019: a hidden treasure in National Forest Inventories\" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered \u2018latent reserves\u2019, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Kl\u00f6tzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement. ", "license": "not-provided" }, { @@ -4822,6 +4692,19 @@ "description": "This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757).", "license": "not-provided" }, + { + "id": "pfynwaldgasexchange.v1.0", + "title": "2013-2020 gas exchange at Pfynwald", + "catalog": "ENVIDAT", + "state_date": "2021-01-01", + "end_date": "2021-01-01", + "bbox": "7.6105556, 46.3001905, 7.6163921, 46.3047564", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789816347-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789816347-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/pfynwaldgasexchange.v1.0", + "description": "Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds. All metadata can be found in the attached documents.", + "license": "not-provided" + }, { "id": "urn:ogc:def:EOP:VITO:VGT_S10.v1", "title": "10 Days Synthesis of SPOT VEGETATION Images (VGT-S10)", diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv index d5f5394d2..13b9319ac 100644 --- a/nasa_cmr_catalog.tsv +++ b/nasa_cmr_catalog.tsv @@ -7,13 +7,6 @@ id title catalog state_date end_date bbox url description license 14c_of_soil_co2_from_ipy_itex_cross_site_comparison 14C of soil CO2 from IPY ITEX Cross Site Comparison SCIOPS 2008-01-16 2008-01-21 -157.4, -36.9, 147.29, 71.3 https://cmr.earthdata.nasa.gov/search/concepts/C1214602443-SCIOPS.json Study sites: Toolik Lake Field Station Alaska, USA 68.63 N, 149.57 W; Atqasuk, Alaska USA 70.45 N, 157.40 W; Barrow, Alaska, USA 71.30 N, 156.67 W; Latnjajaure, Sweden 68.35 N, 18.50 E; Falls Creek, Australia: Site 2-unburned 36.90 S 147.29 E; Site 3-burned 36.89 S 147.28 E. Additional sites will be added summer 2008, but the exact sites are not finalized. Purpose: Collect soil CO2 for analysis of radiocarbon to evaluate the age of the carbon respired in controls and warmed plots from across the ITEX network. Treatments: control and ITEX OTC warming experiment (1994-2007). Design: 5 replicates of each treatment at dry site and moist site. Sampling frequency: Once per peak season. not-provided 200708_CEAMARC_CASO_TRACE_ELEMENT_SAMPLES.v1 2007-08 CEAMARC-CASO VOYAGE TRACE ELEMENT SAMPLING AROUND AN ICEBERG AU_AADC 2008-01-01 2008-03-20 139.01488, -67.07104, 150.06479, -42.88246 https://cmr.earthdata.nasa.gov/search/concepts/C1214305618-AU_AADC.json We collected surface seawater samples using trace clean 1L Nalgene bottles on the end of a long bamboo pole. We will analyse these samples for trace elements. Iron is the element of highest interest to our group. We will determine dissolved iron and total dissolvable iron concentrations. Samples collected from 7 sites: Sites 1, 2, 3, 4 were a transect perpendicular to the edge of the iceberg to try and determine if there is a iron concentration gradient relative to the iceberg. Sites 4, 5, 6 were along the edge of the iceberg to determine if there is any spatial variability along the iceberg edge. Site 7 was away from the iceberg to determine what the iron concentration is in the surrounding waters not influenced by the iceberg. not-provided 2019 Mali CropType Training Data.v1 2019 Mali CropType Training Data MLHUB 2020-01-01 2023-01-01 -6.9444015, 12.8185552, -6.5890481, 13.3734391 https://cmr.earthdata.nasa.gov/search/concepts/C2781412344-MLHUB.json This dataset produced by the NASA Harvest team includes crop types labels from ground referencing matched with time-series of Sentinel-2 imagery during the growing season. Ground reference data are collected using an ODK app. Crop types include Maize, Millet, Rice and Sorghum. Labels are vectorized over the Sentinel-2 grid, and provided as raster files. Funding for this dataset is provided by Lutheran World Relief, Bill & Melinda Gates Foundation, and University of Maryland NASA Harvest program. not-provided -39480 1988 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve NOAA_NCEI 1988-11-24 1988-11-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656753-NOAA_NCEI.json Aerial photographs taken by NOAA's National Geodetic Survey during 1988 were mosaicked and orthorectified by the Biogeography Branch. The resulting image was used to digitize benthic, land cover and mangrove habitat maps of the Salt River Bay National Historic Park and Ecological Preserve (National Park Service), on St. Croix, in the U.S. Virgin Islands.The mosaic is centered on the National Park Service Site, located on the north central coast of St. Croix, and extends beyond the park boundaries approximately 0.5 - 4.0 km. not-provided -39481 1988 Seagrass and Mangrove Habitats of the Salt River Bay National Historical Park and Ecological Preserve NOAA_NCEI 1988-11-24 1988-11-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656462-NOAA_NCEI.json Habitat maps were created as part of a larger ecological assessment conducted by NOAA's National Ocean Service (NOS), Biogeography Branch, for Salt River Bay National Historic Park and Ecological Preserve (National Park Service).Aerial photographs were obtained for 1988 from the National Geodetic Survey, and were orthorectified by the Biogeography Branch. A classification scheme was set up with 20 benthic habitat types, 19 land cover types, and 13 mangrove habitat types. For this map of seagrass and mangrove habitats during 1988 only the 3 seagrass, and 14 mangrove classification categories were used. These were mapped directly into a GIS system through visual interpretation of orthorectified aerial photographs. not-provided -39482 1992 Mosaic of Aerial Photography of the Salt River Bay National Historical Park and Ecological Preserve NOAA_NCEI 1992-01-31 1992-01-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656472-NOAA_NCEI.json Aerial photographs taken by NOAA's National Geodetic Survey during 1992 were mosaicked and orthorectified by the Biogeography Branch. The resulting image was used to digitize benthic, land cover and mangrove habitat maps of the Salt River Bay National Historic Park and Ecological Preserve (National Park Service), on St. Croix, in the U.S. Virgin Islands.The mosaic is centered on the National Park Service Site, located on the north central coast of St. Croix, and in some areas extends beyond the park boundaries up to 2 km. not-provided -39483 1992 Seagrass and Mangrove Habitats of the Salt River Bay National Historical Park and Ecological Preserve NOAA_NCEI 1992-01-31 1992-01-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656483-NOAA_NCEI.json Habitat maps were created as part of a larger ecological assessment conducted by NOAA's National Ocean Service (NOS), Biogeography Branch, for Salt River Bay National Historic Park and Ecological Preserve (National Park Service).Aerial photographs were obtained for 1992 from the National Geodetic Survey, and were orthorectified by the Biogeography Branch. A classification scheme was set up with 20 benthic habitat types, 19 land cover types, and 13 mangrove habitat types. For this map of seagrass and mangrove habitats during 1992 only the 3 seagrass, and 14 mangrove classification categories were used. These were mapped directly into a GIS system through visual interpretation of orthorectified aerial photographs. not-provided -39556 1993 Average Monthly Sea Surface Temperature for California NOAA_NCEI 1993-01-01 1993-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656641-NOAA_NCEI.json The NOAA/NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the NOAA -7, -9, -11, -14, -16 and -17 polar orbiting satellites. Daily, 8-day and monthly averaged data for both the ascending pass (daytime) and descending pass (nighttime) are available on equal-angle grids of 8192 pixels/360 degrees (nominally referred to as the 4km resolution, 4096 pixels/360 degrees (nominally referred to as the 9km resolution), 2048 pixels/360 degrees (nominally referred to as the 18km resolution), and 720 pixels/360 degrees (nominally referred to as the 54km resolution or 0.5 degree resolution).The monthly averaged daytime data was converted to an ESRI GRID format and the 12 monthly grid files were combined into one annual grid with a attribute field for each month. not-provided -39557 1994 Average Monthly Sea Surface Temperature for California NOAA_NCEI 1994-01-01 1994-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656671-NOAA_NCEI.json The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the NOAA -7, -9, -11, -14, -16 and -17 polar orbiting satellites. Daily, 8-day and monthly averaged data for both the ascending pass (daytime) and descending pass (nighttime) are available on equal-angle grids of 8192 pixels/360 degrees (nominally referred to as the 4km resolution, 4096 pixels/360 degrees (nominally referred to as the 9km resolution), 2048 pixels/360 degrees (nominally referred to as the 18km resolution), and 720 pixels/360 degrees (nominally referred to as the 54km resolution or 0.5 degree resolution).The monthly averaged daytime data was converted to an ESRI GRID format and the 12 monthly grid files were combined into one annual grid with a attribute field for each month. not-provided -39558 1995 Average Monthly Sea Surface Temperature for California NOAA_NCEI 1995-01-01 1995-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2102656698-NOAA_NCEI.json The NOAA/ NASA AVHRR Oceans Pathfinder sea surface temperature data are derived from the 5-channel Advanced Very High Resolution Radiometers (AVHRR) on board the NOAA -7, -9, -11, -14, -16 and -17 polar orbiting satellites. Daily, 8-day and monthly averaged data for both the ascending pass (daytime) and descending pass (nighttime) are available on equal-angle grids of 8192 pixels/360 degrees (nominally referred to as the 4km resolution, 4096 pixels/360 degrees (nominally referred to as the 9km resolution), 2048 pixels/360 degrees (nominally referred to as the 18km resolution), and 720 pixels/360 degrees (nominally referred to as the 54km resolution or 0.5 degree resolution).The monthly averaged daytime data was converted to an ESRI GRID format and the 12 monthly grid files were combined into one annual grid with a attribute field for each month. not-provided 3DIMG_L1B_STD INSAT-3D Imager Level-1B Full Acquisition Standard Product ISRO 2013-10-01 0.843296, -81.04153, 163.15671, 81.04153 https://cmr.earthdata.nasa.gov/search/concepts/C1231649308-ISRO.json INSAT-3D Imager Level-1B Standard Product containing 6 channels data in HDF-5 Format not-provided 3DIMG_L1C_SGP INSAT-3D Imager Level-1C Sector Product ISRO 2013-10-01 20, -50, 130, 50 https://cmr.earthdata.nasa.gov/search/concepts/C1214622563-ISRO.json INSAT-3D Imager Level-1C Sector Product (Geocoded, all pixels at same resolution) contains 6 channels data in HDF-5 Format not-provided 3DIMG_L2B_CMK INSAT-3D Imager Level-2B Cloud Map ISRO 2013-10-01 0.843296, -81.04153, 163.15671, 81.04153 https://cmr.earthdata.nasa.gov/search/concepts/C1214622564-ISRO.json INSAT-3D Imager Level-2B Cloud Map Product in HDF-5 Format not-provided @@ -28,7 +21,6 @@ id title catalog state_date end_date bbox url description license A Fusion Dataset for Crop Type Classification in Germany.v1 A Fusion Dataset for Crop Type Classification in Germany MLHUB 2020-01-01 2023-01-01 13.6339485, 52.4179888, 14.3529903, 52.8494418 https://cmr.earthdata.nasa.gov/search/concepts/C2781412484-MLHUB.json This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Brandenburg, Germany. There are nine crop types in this dataset from years 2018 and 2019: Wheat, Rye, Barley, Oats, Corn, Oil Seeds, Root Crops, Meadows, Forage Crops. The 2018 labels from one of the tiles are provided for training, and the 2019 labels from a neighboring tile will be used for scoring in the competition. Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection. The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license. not-provided A Fusion Dataset for Crop Type Classification in Western Cape, South Africa.v1 A Fusion Dataset for Crop Type Classification in Western Cape, South Africa MLHUB 2020-01-01 2023-01-01 20.5212157, -34.413256, 21.043415, -33.9796334 https://cmr.earthdata.nasa.gov/search/concepts/C2781412697-MLHUB.json This dataset contains ground reference crop type labels and multispectral and synthetic aperture radar (SAR) imagery from multiple satellites in an area located in Western Cape, South Africa. There are five crop types from the year 2017: Wheat, Barely, Canola, Lucerne/Medics, Small grain grazing. The AOI is split to three tiles. Two tiles are provided as training labels, and one tile will be used for scoring in the competition. Input imagery consist of time series of Sentinel-2, Sentinel-1 and Planet Fusion (daily and 5-day composite) data. You can access each source from a different collection. The Planet fusion data are made available under a CC-BY-SA license. As an exception to the AI4EO Terms and Conditions published on the competition website, you confirm, by participating in it, that you agree that your results will be made public under the same, open-source license. The Western Cape Department of Agriculture (WCDoA) vector data are supplied via Radiant Earth Foundation with limited distribution rights. Data supplied by the WCDoA may not be distributed further or used for commercial purposes. The vector data supplied are intended strictly for use within the scope of this remote sensing competition - for the purpose of academic research to our mutual benefit. The data is intended for research purposes only and the WCDoA cannot be held responsible for any errors or omissions which may occur in the data. not-provided A crop type dataset for consistent land cover classification in Central Asia.v1 A crop type dataset for consistent land cover classification in Central Asia MLHUB 2020-01-01 2023-01-01 60.2013297, 37.4241018, 72.3539419, 41.8252151 https://cmr.earthdata.nasa.gov/search/concepts/C2781412666-MLHUB.json Land cover is a key variable in the context of climate change. In particular, crop type information is essential to understand the spatial distribution of water usage and anticipate the risk of water scarcity and the consequent danger of food insecurity. This applies to arid regions such as the Aral Sea Basin (ASB), Central Asia, where agriculture relies heavily on irrigation. Here, remote sensing is valuable to map crop types, but its quality depends on consistent ground-truth data. Yet, in the ASB, such data is missing. Addressing this issue, we collected thousands of polygons on crop types, 97.7% of which in Uzbekistan and the remaining in Tajikistan. We collected 8,196 samples between 2015 and 2018, 213 in 2011 and 26 in 2008. Our data compiles samples for 40 crop types and is dominated by “cotton” (40%) and “wheat”, (25%). These data were meticulously validated using expert knowledge and remote sensing data and relied on transferable, open-source workflows that will assure the consistency of future sampling campaigns. not-provided -AAOT.v0 Acqua Alta Oceanographic Tower (AAOT) OB_DAAC 1999-08-03 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360084-OB_DAAC.json Measurements made by the Acqua Alta Oceanographic Tower (AAOT), an Italian installation off the coast of Venice in the Adriatic Sea from 1999 to 2002. not-provided AAS_4156_Macquarie_Island_Emerald_Lake.v1 12,000 year record of sea spray and minerogenic input from Emerald Lake, Macquarie Island AU_AADC 2012-07-01 2019-06-30 158.77441, -54.77772, 158.94951, -54.4828 https://cmr.earthdata.nasa.gov/search/concepts/C2102891784-AU_AADC.json Reconstructed sea spray and minerogenic data for a 12,000 year lake sediment record from Emerald Lake, Macquarie Island. Proxies are based on biological (diatoms) and geochemical (micro x-ray fluorescence and hyperspectral imaging) indicators. Data correspond to the figures in: Saunders et al. 2018 Holocene dynamics of the Southern Hemisphere westerly winds and possible links to CO2 outgassing. Nature Geoscience 11:650-655. doi.org/10.1038/s41561-018-0186-5. Detailed supplementary information: https://static-content.springer.com/esm/art%3A10.1038%2Fs41561-018-0186-5/MediaObjects/41561_2018_186_MOESM1_ESM.pdf Abstract: The Southern Hemisphere westerly winds (SHW) play an important role in regulating the capacity of the Southern Ocean carbon sink. They modulate upwelling of carbon-rich deep water and, with sea ice, determine the ocean surface area available for air–sea gas exchange. Some models indicate that the current strengthening and poleward shift of these winds will weaken the carbon sink. If correct, centennial- to millennial-scale reconstructions of the SHW intensity should be linked with past changes in atmospheric CO2, temperature and sea ice. Here we present a 12,300-year reconstruction of wind strength based on three independent proxies that track inputs of sea-salt aerosols and minerogenic particles accumulating in lake sediments on sub-Antarctic Macquarie Island. Between about 12.1 thousand years ago (ka) and 11.2 ka, and since about 7 ka, the wind intensities were above their long-term mean and corresponded with increasing atmospheric CO2. Conversely, from about 11.2 to 7.2 ka, the wind intensities were below their long-term mean and corresponded with decreasing atmospheric CO2. These observations are consistent with model inferences of enhanced SHW contributing to the long-term outgassing of CO2 from the Southern Ocean. not-provided AAS_4156_Macquarie_Island_unnamed_lake.v1 2000 year record of environmental change from an unnamed lake on Macquarie Island AU_AADC 2012-07-01 2019-06-30 158.74969, -54.78485, 158.96118, -54.47004 https://cmr.earthdata.nasa.gov/search/concepts/C2102891849-AU_AADC.json Age-depth and geochemical data for a 2000 year lake sediment record from an unnamed lake on Macquarie Island. The lake is the small lake to the west of Major Lake, on the edge of the Macquarie Island plateau. The chronology is based on lead-210 (last ca. 100 years) and radiocarbon (extending to ca. 2000 years). Geochemistry is based on micro x-ray fluroescence, and carbon, nitrogen and sulphur contents. Grain size and water content were also measured. Data correspond to the publication: Saunders et al. in prep.Southern Hemisphere westerly wind variability in the sub-Antarctic and relationships to mid-latitude precipitation for the last 2000 years not-provided ABLVIS1B.v1 ABoVE LVIS L1B Geolocated Return Energy Waveforms V001 NSIDC_ECS 2017-06-29 2017-07-17 -158, 48, -104, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1513105920-NSIDC_ECS.json This data set contains return energy waveform data over Alaska and Western Canada measured by the NASA Land, Vegetation, and Ice Sensor (LVIS), an airborne lidar scanning laser altimeter. The data were collected as part of NASA's Terrestrial Ecology Program campaign, the Arctic-Boreal Vulnerability Experiment (ABoVE). not-provided @@ -46,7 +38,6 @@ ACCLIP_TraceGas_AircraftInSitu_WB57_Data.v1 ACCLIP WB-57 Aircraft In-situ Trace ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1 ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data Version 1 LARC_ASDC 2017-10-18 2020-11-20 -130, 25, -100, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1758588261-LARC_ASDC.json ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_AirHARP_Data) are remotely sensed measurements collected by the Airborne Hyper Angular Rainbow Polarimeter (AirHARP) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which is a valuable resource for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. not-provided ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1 ACEPOL Airborne Spectrometer for Planetary Exploration (AirSPEX) Remotely Sensed Data Version 1 LARC_ASDC 2017-10-19 2017-11-09 -130, 25, -100, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.json ACEPOL_AircraftRemoteSensing_AirSPEX_Data are remotely sensed measurements collected by the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. not-provided ACEPOL_AircraftRemoteSensing_CPL_Data.v1 ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data Version 1 LARC_ASDC 2017-10-19 2017-11-09 -130, 25, -100, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1758588308-LARC_ASDC.json ACEPOL Cloud Physics Lidar (CPL) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_CPL_Data) are remotely sensed measurements collected by the Cloud Physics Lidar (CPL) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which make them valuable resources for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. not-provided -ACIDD.v0 Across the Channel Investigating Diel Dynamics project OB_DAAC 2017-12-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360091-OB_DAAC.json The ACIDD (Across the Channel Investigating Diel Dynamics) project, in the Santa Barbara Channel, was initially designed to characterize daily variations in phytoplankton populations, but with the Thomas Fire in the Santa Barbara Hills December 2017, this project evolved into a study to characterize the effects of smoke and ash on the mixed layer in the Santa Barbara Channel. not-provided ACOS_L2S.v7.3 ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V7.3 (ACOS_L2S) at GES DISC GES_DISC 2009-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1339230297-GES_DISC.json "Version 7.3 is the current version of the data set. Version 3.5 is no longer available and has been superseded by Version 7.3. This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch, ""ACOS"" data are still produced and improved, using approaches applied to the OCO-2 spectra. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process. Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings. Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation. An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag. Lastly, users should continue to carefully observe and weigh information from three important flags: ""warn_level"" - Provides a value that summarizes each sounding's acceptability to a larger set of quality filters. A high warn level predicts that the sounding would fail most data filters applied to it. A low warn level suggests that the sounding would pass most quality filters that might be applied. ""sounding_qual_flag"" - quality of input data provided to the retrieval processing ""outcome_flag"" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated) ""master_quality_flag"" - four possible values: ""Good"", ""Caution"" and ""Bad"", and ""Failed"", as determined from other flags in the L2 productThe short name for this data type is ACOS_L2S." not-provided ACOS_L2S.v9r ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V9r (ACOS_L2S) at GES DISC GES_DISC 2009-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633158704-GES_DISC.json "Version 9r is the current version of the data set. Older versions will no longer be available and are superseded by Version 9r. This data set is currently provided by the OCO (Orbiting Carbon Observatory) Project. In expectation of the OCO-2 launch, the algorithm was developed by the Atmospheric CO2 Observations from Space (ACOS) Task as a preparatory project, using GOSAT TANSO-FTS spectra. After the OCO-2 launch, ""ACOS"" data are still produced and improved, using approaches applied to the OCO-2 spectra. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances, and algorithm build version 7.3. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process. Even though the GES DISC is not publicly distributing Level 1B ACOS products, it should be known that changes in this version are affecting both Level 1B and Level 2 data. An important enhancement in Level1B will address the degradation in the number of quality-passed soundings. Elimination of many systematic biases, and better agreement with TCCON (Total Carbon Column Observing Network), is expected in Level 2 retrievals. The key changes to the L2 algorithm include scaling the O2-A band spectroscopy (reducing XCO2 bias by 4 or 5 ppm); using interpolation with the instrument lineshape [ ILS ] (reducing XCO2 bias by 1.5 ppm); and fitting a zero level offset to the A-band. Users have to also carefully familiarize themselves with the disclaimer in the new documentation. An important element to note are the updates on data screening. Although a Master Quality Flag is provided in the data product, further analysis of a larger set of data has allowed the science team to provide an updated set of screening criteria. These are listed in the data user's guide, and are recommended instead of the Master Quality Flag. Lastly, users should continue to carefully observe and weigh information from three important flags: ""sounding_qual_flag"" - quality of input data provided to the retrieval processing ""outcome_flag"" - retrieval quality based upon certain internal thresholds (not thoroughly evaluated) " not-provided ACOS_L2_Lite_FP.v7.3 ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V7.3 (ACOS_L2_Lite_FP) at GES DISC GES_DISC 2009-04-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1339230298-GES_DISC.json "The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process." not-provided @@ -142,7 +133,6 @@ AU_SI25_NRT_R04.v4 NRT AMSR2 Unified L3 Daily 25 km Brightness Temperature & Sea AU_SI6_NRT_R04.v4 NRT AMSR2 Unified L3 Daily 6.25 km Polar Gridded 89 GHz Brightness Temperatures V4 LANCEAMSR2 2020-06-29 -180, -89, 180, 89 https://cmr.earthdata.nasa.gov/search/concepts/C1886605828-LANCEAMSR2.json The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument on the Global Change Observation Mission - Water 1 (GCOM-W1) provides global passive microwave measurements of terrestrial, oceanic, and atmospheric parameters for the investigation of global water and energy cycles. Near real-time (NRT) products are generated within 3 hours of the last observations in the file, by the Land Atmosphere Near real-time Capability for EOS (LANCE) at the AMSR Science Investigator-led Processing System (AMSR SIPS), which is collocated with the Global Hydrology Resource Center (GHRC) DAAC. The NRT AMSR2 Unified L3 Daily 6.25 km Polar Gridded 89 GHz Brightness Temperatures, Version 4 uses as input the resampled brightness temperature (Level-1R) data provided by the Japanese Aerospace Exploration Agency (JAXA). The Version 4 dataset uses the AMSR-U2 product generation algorithm with slight modifications for NRT product generation, same algorithm used to generation the standard, science quality, data that is available at the NSIDC DAAC. This Level-3 gridded product includes brightness temperatures at 89.0 GHz. Data are mapped to a polar stereographic grid at 6.25 km spatial resolution. This product is an intermediate product during processing of LANCE AMSR2 Level-3 sea ice products at 12.5 km and 25 km resolution. Data are stored in HDF-EOS5/netCDF-CF format and are available via HTTP from the EOSDIS LANCE system at https://lance.nsstc.nasa.gov/amsr2-science/data/level3/seaice6. If data latency is not a primary concern, please consider using science quality products. Science products are created using the best available ancillary, calibration and ephemeris information. Science quality products are an internally consistent, well-calibrated record of the Earth's geophysical properties to support science. These standard product, science quality, are available at the NSIDC DAAC: https://nsidc.org/ not-provided AVHRR_GLOBAL_10-DAY_COMPOSITES AVHRR 1-km Global Land 10-Day Composites USGS_LTA 1992-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566288-USGS_LTA.json The Advanced Very High Resolution Radiometer (AVHRR) 1-km Global Land 10-Day Composites data set project is a component of the National Aeronautics and Space Administration (NASA) AVHRR Pathfinder Program. The project is a collaborative effort between the National Oceanic and Atmospheric Administration (NOAA), NASA, the U.S. Geological Survey (USGS), the European Space Agency (ESA), Australia's Commonwealth Scientific and Industrial Research Organization (CSIRO), and 30 international ground receiving stations. The project represents an international effort to archive and distribute the 1-km AVHRR composites of the entire global land surface to scientific researchers and to the general public. The data set is comprised of a time series of global 10-day normalized difference vegetation index composites. The composites are generated from radiometrically calibrated, atmospherically corrected, and geometrically corrected daily AVHRR observations. The time series begins in April 1992 and continues for specific time periods. not-provided AVHRR_ORBITAL_SEGMENTS AVHRR 1-km Orbital Segments USGS_LTA 1992-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566340-USGS_LTA.json The Advanced Very High Resolution Radiometer (AVHRR) 1-km Orbital Segments data set is a component of the National Aeronautics and Space Administration (NASA) AVHRR Pathfinder Program and contains global coverage of land masses at 1-kilometer resolution. The data set is the result of an international effort to acquire, process, and distribute AVHRR data of the entire global land surface to meet the needs of the international science community. The orbital segments are comprised of raw AVHRR scenes consisting of 5-channel, 10-bit, AVHRR data at 1.1-km resolution at nadir. The raw data are used to produce vegetation index composites; to support fire detection and cloud screening activities; to support research in atmospheric correction; to develop algorithms; and to support a host of research activities that may require the inclusion of raw AVHRR data. not-provided -Active_Fluorescence_2001.v0 Active fluorescence measurements in the Gulf Stream in 2001 OB_DAAC 2001-06-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360093-OB_DAAC.json Measurements in the Gulf Stream off the East Coast of the US in 2001 not-provided AgriFieldNet Competition Dataset.v1 AgriFieldNet Competition Dataset MLHUB 2020-01-01 2023-01-01 76.2448319, 18.9414403, 88.0460054, 28.3269976 https://cmr.earthdata.nasa.gov/search/concepts/C2781412563-MLHUB.json This dataset contains crop types of agricultural fields in four states of Uttar Pradesh, Rajasthan, Odisha and Bihar in northern India. There are 13 different classes in the dataset including Fallow land and 12 crop types of Wheat, Mustard, Lentil, Green pea, Sugarcane, Garlic, Maize, Gram, Coriander, Potato, Bersem, and Rice. The dataset is split to train and test collections as part of the AgriFieldNet India Competition. Ground reference data for this dataset is collected by IDinsight’s [Data on Demand](https://www.idinsight.org/services/data-on-demand/) team. Radiant Earth Foundation carried out the training dataset curation and publication. This training dataset is generated through a grant from the Enabling Crop Analytics at Scale ([ECAAS](https://cropanalytics.net/)) Initiative funded by [The Bill & Melinda Gates Foundation](https://www.gatesfoundation.org/) and implemented by [Tetra Tech](https://www.tetratech.com/). not-provided BigEarthNet.v1 BigEarthNet MLHUB 2020-01-01 2023-01-01 -9.0002335, 36.9569567, 31.5984391, 68.021682 https://cmr.earthdata.nasa.gov/search/concepts/C2781412035-MLHUB.json BigEarthNet is a new large-scale Sentinel-2 benchmark archive, consisting of 590,326 Sentinel-2 image patches. To construct BigEarthNet, 125 Sentinel-2 tiles acquired between June 2017 and May 2018 over the 10 countries (Austria, Belgium, Finland, Ireland, Kosovo, Lithuania, Luxembourg, Portugal, Serbia, Switzerland) of Europe were initially selected. All the tiles were atmospherically corrected by the Sentinel-2 Level 2A product generation and formatting tool (sen2cor). Then, they were divided into 590,326 non-overlapping image patches. Each image patch was annotated by the multiple land-cover classes (i.e., multi-labels) that were provided from the CORINE Land Cover database of the year 2018 (CLC 2018). not-provided C1_PANA_STUC00GTD.v1 Cartosat-1 PANA Standard Products ISRO 2005-08-05 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1293271378-ISRO.json This is High resolution satellite carries two PAN sensors with 2.5m resolution and fore-aft stereo capability. The payload is designed to cater to applications in cartography, terrain modeling, cadastral mapping etc. Standard products are full scene (path-row) based geo-referenced as well as geo-orthokit products. not-provided @@ -178,7 +168,6 @@ CV4A Kenya Crop Type Competition.v1 CV4A Kenya Crop Type Competition MLHUB 2020- CWIC_REG.v1.0 Radarsat-2 Scenes, Natural Resources Canada CCMEO 2008-04-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2204659831-CCMEO.json The collection represents browse images and metadata for systematically georeferenced Radarsat-2 Synthetic Aperture Radar(SAR) satellite scenes. The browse scenes are not geometrically enhanced using ground control points, but are systematically corrected using sensor parameters. Full resolution precision geocoded scenes(corrected using ground control points) which correspond to the browse images can be ordered from MacDonald Dettwiler and Associates Ltd., Vancouver, Canada. Metadata discovery is achieved using the online catalog http://neodf.nrcan.gc.ca OR by using the CWIC OGC CSW service URL : http://cwic.csiss.gmu.edu/cwicv1/discovery. The imaging frequency is C Band SAR : 5405.0000 MHz. RADARSAT-2 is in a polar, sun-synchronous orbit with a period of approximately 101 minutes. The RADARSAT-2 orbit will be maintained at +\/- 1 km in across track direction. This orbit maintenance is suitable for InSAR data collection. The geo-location accuracy of RADARSAT-2 products varies with product type. It is currently estimated at +\/- 30 m for Standard beam products. The revisit period for RADARSAT-2 depends on the beam mode, incidence angle and geographic location of the area of interest. In general, revisit is more frequent at the poles than the equator and the wider swath modes have higher revisit than t he narrow swath modes. not-provided CWIC_REG_RCM.v1.0 RCM (Radarsat Constellation Mission ) Products, Natural Resources Canada CCMEO 2019-06-12 2026-06-12 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2204659595-CCMEO.json The collection represents products and metadata for georeferenced Radarsat Constellation Mission ( RCM ) satellite scenes. Metadata discovery and product ordering is achieved using the online catalog https://www.eodms-sgdot.nrcan-rncan.gc.ca/index-en.html OR by using the CWIC OpenSearch OSDD : http://cwic.csiss.gmu.edu/cwicv1/discovery. not-provided CWIC_REG_Radarsat-1.v1.0 Radarsat-1 Scenes, Natural Resources Canada CCMEO 1996-01-11 2013-03-29 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2204658925-CCMEO.json The collection represents browse images and metadata for systematically georeferenced Radarsat-1 Synthetic Aperture Radar(SAR) satellite scenes. The browse scenes are not geometrically enhanced using ground control points, but are systematically corrected using sensor parameters. Full resolution precision geocoded scenes(corrected using ground control points) which correspond to the browse images can be ordered from MacDonald Dettwiler and Associates Ltd., Vancouver, Canada. Metadata discovery is achieved using the online catalog https://neodf.nrcan.gc.ca/neodf_cat3 OR by using the CWIC OGC CSW service URL : http://cwic.csiss.gmu.edu/cwicv1/discovery. Radarsat-1 operates at 5.3 GHz. (C-Band). It is in a sun-synchronous orbit. Image resolution is in the range 8-100 meters. not-provided -Catlin_Arctic_Survey.v0 2011 R/V Catlin cruise in the Arctic Ocean OB_DAAC 2011-03-17 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360181-OB_DAAC.json Measurements made in the Arctic Ocean by the RV Catlin in 2011. not-provided Chesapeake Land Cover.v1 Chesapeake Land Cover MLHUB 2020-01-01 2023-01-01 -80.8092703, 36.5643108, -74.2529408, 43.9973515 https://cmr.earthdata.nasa.gov/search/concepts/C2781412641-MLHUB.json This dataset contains high-resolution aerial imagery from the USDA NAIP program, high-resolution land cover labels from the Chesapeake Conservancy, low-resolution land cover labels from the USGS NLCD 2011 dataset, low-resolution multi-spectral imagery from Landsat 8, and high-resolution building footprint masks from Microsoft Bing, formatted to accelerate machine learning research into land cover mapping. The Chesapeake Conservancy spent over 10 months and $1.3 million creating a consistent six-class land cover dataset covering the Chesapeake Bay watershed. While the purpose of the mapping effort by the Chesapeake Conservancy was to create land cover data to be used in conservation efforts, the same data can be used to train machine learning models that can be applied over even wider areas. not-provided Cloud to Street - Microsoft flood dataset.v1 Cloud to Street - Microsoft flood dataset MLHUB 2020-01-01 2023-01-01 -96.631888, -25.250962, 141.118143, 48.745167 https://cmr.earthdata.nasa.gov/search/concepts/C2781412798-MLHUB.json The C2S-MS Floods Dataset is a dataset of global flood events with labeled Sentinel-1 & Sentinel-2 pairs. There are 900 sets (1800 total) of near-coincident Sentinel-1 and Sentinel-2 chips (512 x 512 pixels) from 18 global flood events. Each chip contains a water label for both Sentinel-1 and Sentinel-2, as well as a cloud/cloud shadow mask for Sentinel-2. The dataset was constructed by Cloud to Street in collaboration with and funded by the Microsoft Planetary Computer team. not-provided DLG100K 1:100,000-scale Digital Line Graphs (DLG) from the U.S. Geological Survey USGS_LTA 1987-06-19 -126, 24, -66, 49 https://cmr.earthdata.nasa.gov/search/concepts/C1220566434-USGS_LTA.json Digital line graph (DLG) data are digital representations of cartographic information. DLG's of map features are converted to digital form from maps and related sources. Intermediate-scale DLG data are derived from USGS 1:100,000-scale 30- by 60-minute quadrangle maps. If these maps are not available, Bureau of Land Management planimetric maps at a scale of 1: 100,000 are used. Intermediate-scale DLG's are sold in five categories: (1) Public Land Survey System; (2) boundaries (3) transportation; (4) hydrography; and (5) hypsography. All DLG data distributed by the USGS are DLG - Level 3 (DLG-3), which means the data contain a full range of attribute codes, have full topological structuring, and have passed certain quality-control checks. not-provided @@ -230,7 +219,6 @@ Global_Litter_Carbon_Nutrients_1244.v1 A Global Database of Litterfall Mass and Global_Microbial_Biomass_C_N_P_1264.v1 A Compilation of Global Soil Microbial Biomass Carbon, Nitrogen, and Phosphorus Data ORNL_CLOUD 1977-11-16 2012-06-01 -180, -90, 177.9, 79 https://cmr.earthdata.nasa.gov/search/concepts/C2216863966-ORNL_CLOUD.json This data set provides the concentrations of soil microbial biomass carbon (C), nitrogen (N) and phosphorus (P), soil organic carbon, total nitrogen, and total phosphorus at biome and global scales. The data were compiled from a comprehensive survey of publications from the late 1970s to 2012 and include 3,422 data points from 315 papers. These data are from soil samples collected primarily at 0-15 cm depth with some from 0-30 cm. In addition, data were compiled for soil microbial biomass concentrations from soil profile samples to depths of 100 cm. Sampling site latitude and longitude were available for the majority of the samples that enabled assembling additional soil properties, site characteristics, vegetation distributions, biomes, and long-term climate data from several global sources of soil, land-cover, and climate data. These site attributes are included with the microbial biomass data. This data set contains two *.csv files of the soil microbial biomass C, N, P data. The first provides all compiled results emphasizing the full spatial extent of the data, while the second is a subset that provides only data from a series of profile samples emphasizing the vertical distribution of microbial biomass concentrations.There is a companion file, also in .csv format, of the references for the surveyed publications. A reference_number relates the data to the respective publication.The concentrations of soil microbial biomass, in combination with other soil databases, were used to estimate the global storage of soil microbial biomass C and N in 0-30 cm and 0-100 cm soil profiles. These storage estimates were combined with a spatial map of 12 major biomes (boreal forest, temperate coniferous forest, temperate broadleaf forest, tropical and subtropical forests, mixed forest, grassland, shrub, tundra, desert, natural wetland, cropland, and pasture) at 0.05-degree by 0.5-degree spatial resolution. The biome map and six estimates of C and N storage and C:N ration in soil microbial biomass are provided in a single netCDF format file. not-provided Global_Phosphorus_Hedley_Fract_1230.v1 A Global Database of Soil Phosphorus Compiled from Studies Using Hedley Fractionation ORNL_CLOUD 1985-01-01 2010-12-31 -117.86, -42.5, 117.6, 63.23 https://cmr.earthdata.nasa.gov/search/concepts/C2216863440-ORNL_CLOUD.json This data set provides concentrations of soil phosphorus (P) compiled from the peer-reviewed literature that cited the Hedley fractionation method (Hedley and Stewart, 1982). This database contains estimates of different forms of naturally occurring soil phosphorus, including labile inorganic P, organic P, occluded P, secondary mineral P, apatite P, and total P, based on the analyses of the various Hedley soil fractions.The recent literature survey (Yang and Post, 2011) was restricted to studies of natural, unfertilized, and uncultivated soils since 1995. Ninety measurements of soil P fractions were identified. These were added to the 88 values from soils in natural ecosystems that Cross and Schlesinger (1995) had compiled. Cross and Schlesinger provided a comprehensive survey on Hedley P data prior to 1995. Measurement data are provided for studies published from 1985 through 2010. In addition to the Hedley P fraction measurement data Yang and Post (2011) also compiled information on soil order, soil pH, organic carbon and nitrogen content, as well as the geographic location (longitude and latitude) of the measurement sites. not-provided Global_RTSG_Flux_1078.v1 A Global Database of Gas Fluxes from Soils after Rewetting or Thawing, Version 1.0 ORNL_CLOUD 1956-01-01 2009-12-31 -149.63, -36.45, 160.52, 74.5 https://cmr.earthdata.nasa.gov/search/concepts/C2216863284-ORNL_CLOUD.json This database contains information compiled from published studies on gas flux from soil following rewetting or thawing. The resulting database includes 222 field and laboratory observations focused on rewetting of dry soils, and 116 field laboratory observations focused on thawing of frozen soils studies conducted from 1956 to 2010. Fluxes of carbon dioxide, methane, nitrous oxide, nitrogen oxide, and ammonia (CO2, CH4, N2O, NO and NH3) were compiled from the literature and the flux rates were normalized for ease of comparison. Field observations of gas flux following rewetting of dry soils include events caused by natural rainfall, simulated rainfall in natural ecosystems, and irrigation in agricultural lands. Similarly, thawing of frozen soils include field observations of natural thawing, simulated freezing-thawing events (i.e., thawing of simulated frozen soil by snow removal), and thawing of seasonal ice in temperate and high latitude regions (Kim et al., 2012). Reported parameters include experiment type, location, site type, vegetation, climate, soil properties, rainfall, soil moisture, soil gas flux after wetting and thawing, peak soil gas flux properties, and the corresponding study references. There is one comma-delimited data file. not-provided -GreenBay.v0 2010 Measurements made in Green Bay, Wisconsin OB_DAAC 2010-09-17 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360352-OB_DAAC.json Measurements made in Green Bay, Wisconsin in 2010. not-provided IKONOS_MSI_L1B.v1 IKONOS Level 1B Multispectral 4-Band Satellite Imagery CSDA 1999-10-14 2015-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497453433-CSDA.json The IKONOS Level 1B Multispectral 4-Band Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This satellite imagery is in the visible and near-infrared waveband range with data in the blue, green, red, and near-infrared wavelengths. The spatial resolution is 3.2m at nadir and the temporal resolution is approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided IKONOS_Pan_L1B.v1 IKONOS Level 1B Panchromatic Satellite Imagery CSDA 1999-10-24 2015-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497468825-CSDA.json The IKONOS Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This data product includes panchromatic imagery with a spatial resolution of 0.82m at nadir and a temporal resolution of approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided IMS1_HYSI_GEO.v1.0 IMS-1 HYSI TOA Radiance and Reflectance Product ISRO 2008-06-22 2012-09-10 -6.0364, -78.8236, 152.6286, 78.6815 https://cmr.earthdata.nasa.gov/search/concepts/C1214622602-ISRO.json The data received from IMS1, HySI which operates in 64 spectral bands in VNIR bands(400-900nm) with 500 meter spatial resolution and swath of 128 kms. not-provided @@ -259,14 +247,13 @@ M1_ AVH09C1.v6 METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily M1_AVH13C1.v6 METOP-B AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05 Deg. CMG LAADS 2013-01-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2751635237-LAADS.json The Long-Term Data Record (LTDR) produces, validates, and distributes a global land surface climate data record (CDR) that uses both mature and well-tested algorithms in concert with the best-available polar-orbiting satellite data from past to the present. The CDR is critically important to studying global climate change. The LTDR project is unique in that it serves as a bridge that connects data derived from the NOAA Advanced Very High Resolution Radiometer (AVHRR), the EOS Moderate resolution Imaging Spectroradiometer (MODIS), the Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Joint Polar Satellite System (JPSS) VIIRS missions. The LTDR draws from the following eight AVHRR missions: NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19, and MetOp-B. Currently, the project generates a daily surface reflectance product as the fundamental climate data record (FCDR) and derives daily Normalized Differential Vegetation Index (NDVI) and Leaf-Area Index/fraction of absorbed Photosynthetically Active Radiation (LAI/fPAR) as two thematic CDRs (TCDR). LAI/fPAR was developed as an experimental product. The METOP-B AVHRR Atmospherically Corrected Normalized Difference Vegetation Index (NDVI) Daily L3 Global 0.05 Deg CMG, short-name M1_AVH13C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (M1_AVH01C1). The M1_AVH13C1 product is available in HDF4 file format. not-provided MCD06COSP_D3_MODIS.v6.1 MODIS (Aqua/Terra) Cloud Properties Level 3 daily, 1x1 degree grid LAADS 2002-07-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1887589686-LAADS.json The combined MODIS (Aqua/Terra) Cloud Properties Level 3 daily, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product’s short-name. The “COSP” acronym in its short-name stands for Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. This product is an aggregation of combined MODIS Level-2 inputs from both the Terra and Aqua incarnations (MOD35/MOD06 and MYD35/MYD06, respectively), and employs an aggregation methodology consistent with the MOD08 and MYD08 products. Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters). not-provided MCD06COSP_M3_MODIS.v6.1 MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid LAADS 2002-07-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1888024429-LAADS.json The combined MODIS (Aqua/Terra) Cloud Properties Level 3 monthly, 1x1 degree grid product represents a new addition that is especially geared to facilitate climate scientists who deal with both models and observations. MCD06COSP_D3_MODIS represents the daily product’s short-name. The “COSP” acronym in its short-name stands for Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package. The L3 monthly product is derived by aggregating the daily-produced Aqua+Terra/MODIS D3 Cloud Properties product (MCD06COSP_D3_MODIS). Provided in netCDF4 format, it contains 23 aggregated science data sets (SDS/parameters). not-provided +MCD14DL_C5_NRT.v005 MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT LM_FIRMS 2014-01-28 -180, -80, 180, 80 https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.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. not-provided MIANACP.v1 MISR Aerosol Climatology Product V001 LARC 1999-11-22 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C185127378-LARC.json MIANACP_1 is the Multi-angle Imaging SpectroRadiometer (MISR) Aerosol Climatology Product version 1. It is 1) the microphysical and scattering characteristics of pure aerosol upon which routine retrievals are based; 2) mixtures of pure aerosol to be compared with MISR observations; and 3) likelihood value assigned to each mode geographically. The ACP describes mixtures of up to three component aerosol types from a list of eight components, in varying proportions. ACP component aerosol particle data quality depends on the ACP input data, which are based on aerosol particles described in the literature, and consider MISR-specific sensitivity to particle size, single-scattering albedo, and shape, and shape - roughly: small, medium and large; dirty and clean; spherical and nonspherical [Kahn et al. , 1998; 2001]. Also reported in the ACP are the mixtures of these components used by the retrieval algorithm. 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. not-provided MIANCAGP.v1 MISR Ancillary Geographic Product V001 LARC 1999-11-07 2005-06-30 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C183897339-LARC.json MIANCAGP_1 is the Multi-angle Imaging SpectroRadiometer (MISR) Ancillary Geographic Product version 1. It is a set of 233 pre-computed files. Each AGP file pertains to a single Terra orbital path. MISR production software relies on information in the AGP, such as digital terrain elevation, as input to the algorithms which generate MISR products. The AGP contains eleven fields of geographical data. This product consists primarily of geolocation data on a Space Oblique Mercator (SOM) Grid. It has 233 parts, corresponding to the 233 repeat orbits of the EOS-AM1 Spacecraft. 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. not-provided MIANCARP.v2 MISR Ancillary Radiometric Product V002 LARC 1999-12-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031521-LARC.json MIANCARP_2 is the Multi-angle Imaging SpectroRadiometer (MISR) Ancillary Radiometric Product version 2. It is composed of 4 files covering instrument characterization data, pre-flight calibration data, in-flight calibration data, and configuration parameters. 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. not-provided MIRCCMF.v001 MISR FIRSTLOOK radiometric camera-by-camera Cloud Mask V001 LARC 2000-12-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C135857530-LARC.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 FIRSTLOOK radiometric camera-by-camera Cloud Mask V001 contains the FIRSTLOOK Radiometric camera-by-camera Cloud Mask (RCCM) dataset produced using ancillary inputs Radiometric Camera-by-camera Cloud mask Threshold (RCCT) from the previous time period. It is used to determine whether a scene is clear, cloudy or dusty (over ocean). not-provided MIRCCMF.v002 MISR FIRSTLOOK radiometric camera-by-camera Cloud Mask V002 LARC 2000-02-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2788936281-LARC.json This is the FIRSTLOOK Radiometric Camera-by-camera Cloud Mask (RCCM) product. It contains initial estimated classifications of pixels/regions as clear or cloudy. It also has masks for the presence of glitter or dust. The FIRSTLOOK RCCM product is superceded by the final RCCM product following seasonal calibration. not-provided MISBR.v005 MISR Browse data V005 LARC 1999-12-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C43677744-LARC.json This is the browse data associated with a particular granule. not-provided -MURI_Camouflage.v0 A Multi University Research Initiative (MURI) Camouflage Project OB_DAAC 2010-06-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360494-OB_DAAC.json A Multi University Research Initiative was funded to study the biological response to the dynamic, polarized light field in distinct water types. During June 2010, a campaign was undertaken in the coastal waters off Port Aransas, Texas to study the angular/temporal distribution of polarization in multiple environment types (eutrophic sediment laden coastal waters, oligotrophic off-shore), as well as the polarization-reflectance responses of several organisms. In addition to radiometric polarization measurements, water column IOPs, Rrs, benthic reflectance, and pigment concentration measurements were collected. Later campaigns expanded this research in the coastal waters off the Florida Keys. not-provided -MURI_HI.v0 A Multi University Research Initiative (MURI) near the Hawaiian Islands OB_DAAC 2012-05-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360508-OB_DAAC.json Measurements taken by the RV Kilo Moana in 2012 near the Hawaiian Islands. not-provided MYD021KM.v6.1NRT MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 1km - NRT LANCEMODIS 2017-10-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1426616847-LANCEMODIS.json The MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated at-aperture radiances for 36 discrete bands located in the 0.4 to 14.4 micron region of electromagentic spectrum. These data are generated from the MODIS Level 1A scans of raw radiance and in the process converted to geophysical units of W/(m^2 um sr). In addition, the Earth Bi-directional Reflectance Distribution Function (BRDF) may be determined for the solar reflective bands (1-19, 26) through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry). Additional data are provided including quality flags, error estimates and calibration data. Visible, shortwave infrared, and near infrared measurements are only made during the daytime, while radiances for the thermal infrared region (bands 20-25, 27-36) are measured continuously. Channel locations for MODIS are as follows: Band Center Wavelength (um) Primary Use---- ---------------------- -----------1 0.620 - 0.670 Land/Cloud Boundaries2 0.841 - 0.876 Land/Cloud Boundaries3 0.459 - 0.479 Land/Cloud Properties4 0.545 - 0.565 Land/Cloud Properties5 1.230 - 1.250 Land/Cloud Properties6 1.628 - 1.652 Land/Cloud Properties7 2.105 - 2.155 Land/Cloud Properties8 0.405 - 0.420 Ocean Color/Phytoplankton9 0.438 - 0.448 Ocean Color/Phytoplankton10 0.483 - 0.493 Ocean Color/Phytoplankton11 0.526 - 0.536 Ocean Color/Phytoplankton12 0.546 - 0.556 Ocean Color/Phytoplankton13 0.662 - 0.672 Ocean Color/Phytoplankton14 0.673 - 0.683 Ocean Color/Phytoplankton15 0.743 - 0.753 Ocean Color/Phytoplankton16 0.862 - 0.877 Ocean Color/Phytoplankton17 0.890 - 0.920 Atmospheric Water Vapor18 0.931 - 0.941 Atmospheric Water Vapor19 0.915 - 0.965 Atmospheric Water Vapor20 3.660 - 3.840 Surface/Cloud Temperature21 3.929 - 3.989 Surface/Cloud Temperature22 3.929 - 3.989 Surface/Cloud Temperature23 4.020 - 4.080 Surface/Cloud Temperature24 4.433 - 4.498 Atmospheric Temperature25 4.482 - 4.549 Atmospheric Temperature26 1.360 - 1.390 Cirrus Clouds27 6.535 - 6.895 Water Vapor Profile28 7.175 - 7.475 Water Vapor Profile29 8.400 - 8.700 Water Vapor Profile30 9.580 - 9.880 Ozone Overburden31 10.780 - 11.280 Surface/Cloud Temperature32 11.770 - 12.270 Surface/Cloud Temperature33 13.185 - 13.485 Cloud Top Altitude34 13.485 - 13.785 Cloud Top Altitude35 13.785 - 14.085 Cloud Top Altitude36 14.085 - 14.385 Cloud Top Altitude Channels 1 and 2 have 250 m resolution, channels 3 through 7 have 500m resolution, and the rest have 1 km resolution. However, for the MODIS L1B 1 km product, the 250 m and 500 m band radiance data and their associated uncertainties have been aggregated to 1km resolution. Thus the entire channel data set is referenced to the same spatial and geolocation scales. Separate L1B products are available for the 250 m channels (MYD02QKM) and 500 m channels (MYD02HKM) that preserve the original resolution of the data. Spatial resolution for pixels at nadir is 1 km, degrading to 4.8 km in the along-scan direction at the scan extremes. However, thanks to the overlapping of consecutive swaths and respectively pixels there, the resulting resolution at the scan extremes is about 2km. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330km orbital swath width and provides global coverage every one to two days. A single MODIS Level 1B granule will nominally contain a scene built from 203 scans (or swaths) sampled 1354 times in the cross-track direction, corresponding to approximately 5 minutes worth of data. Since an individual MODIS scan (or swath) will contain 10 along-track spatial elements, the scene will be composed of (1354 x 2030) pixels, resulting in a spatial coverage of (2330 km x 2030 km). Due to the MODIS scan geometry, there will be increasing overlap occurring beyond about 25 degrees scan angle. To summarize, the MODIS L1B 1 km data product consists of: 1. Calibrated radiances and uncertainties for (2) 250 m reflected solar bands aggregated to 1km resolution 2. Calibrated radiances and uncertainties for (5) 500 m reflected solar bands aggregated to 1 km resolution 3. Calibrated radiances and uncertainties for (13) 1 km reflected solar bands and (16) infrared emissive bands 4. Geolocation subsampled at every 5th pixel across and along track 5. Satellite and solar angles subsampled at the above frequency 6. Comprehensive set of file-level metadata summarizing the spatial, temporal and parameter attributes of the data, as well as auxiliary information pertaining to instrument status and data quality characterization. The MODIS L1B data are stored in the Earth Observing System Hierarchical Data Format (HDF-EOS) which is an extension of HDF as developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois. A typical file size will be approximately 260 MB. Environmental information derived from MODIS L1B measurements will offer a comprehensive and unprecedented look at terrestrial, atmospheric, and ocean phenomenology for a wide and diverse community of users throughout the world. The Shortname for this product is MYD021KM not-provided MYD02HKM.v6.1NRT MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 500m - NRT LANCEMODIS 2017-10-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1426617060-LANCEMODIS.json The 500 meter MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated at-aperture radiances for 7 discrete bands located in the 0.45 to 2.20 micron region of the electromagnetic spectrum. These data are generated from the MODIS Level 1A scans of raw radiance and in the process converted to geophysical units of W/(m^2 um sr). In addition, the Earth Bi-directional Reflectance Distribution Function (BRDF) may be determined for these solar reflective bands through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry). Additional data are provided including quality flags, error estimates and calibration data. Visible, shortwave infrared, and near infrared measurements are only made during the daytime, while radiances for the thermal infrared region (bands 20-25, 27-36) are measured continuously. Channel locations for the MODIS 500 meter data are as follows: Band Center Wavelength (um) Primary Use ---- ---------------------- ----------- 1 0.620 - 0.670 Land/Cloud Boundaries 2 0.841 - 0.876 Land/Cloud Boundaries 3 0.459 - 0.479 Land/Cloud Properties 4 0.545 - 0.565 Land/Cloud Properties 5 1.230 - 1.250 Land/Cloud Properties 6 1.628 - 1.652 Land/Cloud Properties 7 2.105 - 2.155 Land/Cloud Properties Channels 1 and 2 have 250 m resolution, channels 3 through 7 have 500 m resolution. However, for the MODIS L1B 500 m product, the 250 m band radiance data and their associated uncertainties have been aggregated to 500 m resolution. Thus the entire channel data set has been co-registered to the same spatial scale in the 500 m product. Separate L1B products are available for the 250 m resolution channels (MYD02QKM) and 1 km resolution channels (MYD021KM). For the latter product, the 250 m and 500 m channel data (bands 1 through 7) have been aggregated into equivalent 1 km pixel values. Spatial resolution for pixels at nadir is 500 km, degrading to 2.4 km in the along-scan direction at the scan extremes. However, thanks to the overlapping of consecutive swaths and respectively pixels there, the resulting resolution at the scan extremes is about 1 km. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width and provides global coverage every one to two days. A single MODIS Level 1B 500 m granule will contain a scene built from 203 scans sampled 2708 times in the cross-track direction, corresponding to approximately 5 minutes worth of data; thus 288 granules will be produced per day. Since an individual MODIS scan will contain 20 along-track spatial elements for the 500 m channels, the scene will be composed of (2708 x 4060) pixels, resulting in a spatial coverage of (2330 km x 2040 km). Due to the MODIS scan geometry, there will be increasing scan overlap beyond about 20 degrees scan angle. To summarize, the MODIS L1B 500 m data product consists of: 1. Calibrated radiances, uncertainties and number of samples for (2) 250 m reflected solar bands aggregated to 500 m resolution 2. Calibrated radiances and uncertainties for (5) 500 m reflected solar bands 3. Geolocation for 1km pixels, that must be interpolated to get 500 m pixel locations. For the relationship of 1km pixels to 500m pixels, see the Geolocation ATBD http://modis.gsfc.nasa.gov/data/atbd/atbd_mod28_v3.pdf . 4. Calibration data for all channels (scale and offset) 5. Comprehensive set of file-level metadata summarizing the spatial, temporal and parameter attributes of the data, as well as auxiliary information pertaining to instrument status and data quality characterization The MODIS L1B 500 m data are stored in the Earth Observing System Hierarchical Data Format (HDF-EOS) which is an extension of HDF as developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois. A typical file size will be approximately 170 MB. Environmental information derived from MODIS L1B measurements will offer a comprehensive and unprecedented look at terrestrial, atmospheric, and ocean phenomenology for a wide and diverse community of users throughout the world. The Shortname for this product is MYD02HKM not-provided MYD02QKM.v6.1NRT MODIS/Aqua Calibrated Radiances 5-Min L1B Swath 250m - NRT LANCEMODIS 2017-10-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1426621826-LANCEMODIS.json The 250 meter MODIS Level 1B Near Real Time (NRT) data set contains calibrated and geolocated at-aperture radiances for 2 discrete bands located in the 0.62 to 0.88 micron region of the electromagnetic spectrum. These data are generated from the MODIS Level 1A scans of raw radiance and in the process converted to geophysical units of W / (m^2 um sr). In addition, the Earth Bi-directional Reflectance Distribution Function (BRDF) may be determined for these solar reflective bands through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry). Additional data are provided including quality flags, error estimates and calibration data. Channel locations for the MODIS 250 meter data are as follows: Band Center Wavelength (um) Primary Use ---- ---------------------- ----------- 1 0.620 - 0.670 Land/Cloud Boundaries 2 0.841 - 0.876 Land/Cloud Boundaries Separate L1B products are available for the five 500 m resolution channels (MYD02HKM) and the twenty-nine 1 km resolution channels (MYD021KM). For the 500 m product, there are actually seven channels available since the data from the two 250 m channels have been aggregated to 500 m resolution. Similarly, for the 1 km product, all 36 MODIS channels are available since the data from the two 250 m and five 500 m channels have been aggregated into equivalent 1 km pixel values. Spatial resolution for pixels at nadir is 250 m, degrading to 1.2 km in the along-scan direction and 0.5 km in the along-track direction for pixels located at the scan extremes. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width and provides global coverage every one to two days. A single MODIS Level 1B 250 m granule will contain a scene built from 203 scans sampled 5416 times in the cross-track direction, corresponding to approximately 5 minutes worth of data; thus 288 granules will be produced per day. Since an individual MODIS scan will contain 40 along-track spatial elements for the 250 m channels, the scene will be composed of (5416 x 8120) pixels, resulting in a spatial coverage of (2330 km x 2040 km). Due to the MODIS scan geometry, there will be increasing scan overlap beyond about 17 degrees scan angle. To summarize, the MODIS L1B 250 m data product consists of: 1. Calibrated radiances and uncertainties for (2) 250 m reflected solar bands 2. Subsampled geolocation at every 4th 250 m pixel across and along track, i.e., a geolocation point every kilometer 3. Satellite and solar angles subsampled at the above frequency 4. Calibration data for all channels (scale and offset) 5. Comprehensive set of file-level metadata summarizing the spatial, temporal and parameter attributes of the data, as well as auxiliary information pertaining to instrument status and data quality characterization The MODIS L1B 250 m data are stored in the Earth Observing System Hierarchical Data Format (HDF-EOS) which is an extension of HDF as developed by the National Center for Supercomputer Applications (NCSA) at the University of Illinois. A typical file size will be approximately 170 MB. Environmental information derived from MODIS L1B measurements will offer a comprehensive and unprecedented look at terrestrial, atmospheric, and ocean phenomenology for a wide and diverse community of users throughout the world. The Shortname for this product is MYD02QKM not-provided @@ -308,14 +295,23 @@ OMICOL3NRT.v3 Ozone Monitoring Instrument Near Real Time Data for v3 OMINRT 1970 OMSO2.v003 OMI/Aura Sulphur Dioxide (SO2) Total Column 1-orbit L2 Swath 13x24 km V003 NRT OMINRT 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000121-OMINRT.json The Ozone Monitoring Instrument (OMI) was launched aboard the EOS-Aura satellite on July 15, 2004 (1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Space Office (NSO) in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO,NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. The Sulfer Dioxide Product 'OMSO2' from the Aura-OMI is now publicly available from NASA GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMSO2 product contains three values of SO2 Vertical column corresponding to three a-priori vertical profiles used in the retrieval algorithm. It also contains quality flags, geolocation and other ancillary information. The shortname for this Level-2 OMI total column SO2 product is OMSO2 and the algorithm leads for this product are NASA/UMBC OMI scientists Drs. Nikolay Krotkov (nickolay.a.krotkov@nasa.gov),Kai Yang(kai.yang@nasa.gov) and Arlin J. Krueger(krueger@umbc.edu). 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 21 Mbytes. On-line spatial and parameter subset options are available during data download A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMSO2 Readme Document that includes brief algorithm description and documents that provides known data quality related issues are available from the UMBC OMI site ( http://so2.gsfc.nasa.gov/docs.php ) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://so2.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/. For the full set of Aura products and other atmospheric composition data available from the GES DISC, please see the links below. http://disc.sci.gsfc.nasa.gov/Aura/ http://disc.gsfc.nasa.gov/acdisc/ not-provided OMTO3.v003 OMI/Aura Ozone (O3) Total Column 1-Orbit L2 Swath 13x24 km V003 NRT OMINRT 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000140-OMINRT.json The OMI/Aura Level-2 Total Column Ozone Data Product OMTO3 Near Real Time data is made available from the OMI SIPS NASA for the public access. The Ozone Monitoring Instrument (OMI)was launched aboard the EOS-Aura satellite on July 15, 2004(1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Agency for Aerospace Programs (NIVR)in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator's (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO, NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. 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 additional hyper-spectral measurements help in the corrections for the factors that induce uncertainty in ozone retrieval (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 extensive quality flags. The shortname for this Level-2 OMI total column ozone product is OMTO3 and the algorithm lead for this product is NASA OMI scientist Dr. Pawan K. Bhartia ( Pawan.K.Bhartia@nasa.gov). OMTO3 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 OMTO3 data product is about 35 Mbytes. A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/ . Data Category Parameters: The OMTO3 data file contains one swath which consists of two groups: Data fields: OMI Total Ozone,Effective Reflectivity (331 - 360 nm), N-value, Cloud Fraction, Cloud Top Pressure, O3 below Cloud, UV Aerosol Index, SO2 index, Wavelength used in the algorithm, many Auxiliary Algorithm Parameter and Quality Flags Geolocation Fields: Latitude, Longitude, Time, Relative Azimuth, Solar Zenith and Azimuth, Viewing Zenith and Azimuth angles, Spacecraft Altitude, Latitude, Longitude, Terrain Height, Ground Pixel Quality Flags.For the full set of Aura data products available from the GES DISC, please see the link http://disc.sci.gsfc.nasa.gov/Aura/ . not-provided OMTO3e.v003 OMI/Aura Ozone (O3) Total Column Daily L3 Global 0.25deg Lat/Lon Grid NRT OMINRT 2004-07-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1428966163-OMINRT.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) . not-provided +PACE_HARP2_L0.v1 PACE HARP2 Level-0 Instrument Telemetry/Multi-Detector Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798249-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L0_D1.v1 PACE HARP2 Level-0 Detector 1 (D1) Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798238-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L0_D2.v1 PACE HARP2 Level-0 Detector 2 (D2) Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798239-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L0_D3.v1 PACE HARP2 Level-0 Detector 3 (D3) Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798240-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L0_REAL.v1 PACE HARP2 Level-0 Real-time Direct Transfer Mode Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798243-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L0_SCI.v1 PACE HARP2 Level-0 Science Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798245-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L1A_AST0.v1 PACE HARP2 Level-1A Acquisition Scheme Type 0 - Full-Resolution Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798253-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L1A_AST1.v1 PACE HARP2 Level-1A Acquisition Scheme Type 1 - Half-Resolution Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798256-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided +PACE_HARP2_L1A_AST2.v1 PACE HARP2 Level-1A Acquisition Scheme Type 2 - Science Mode (no MTDI) Data, version 1 OB_CLOUD 2022-03-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2804798261-OB_CLOUD.json The Hyper-Angular Rainbow Polarimeter #2 (HARP2) instrument is a wide angle imaging polarimeter designed to measure aerosol particles and clouds, as well as properties of land and water surfaces. HARP2 will combine data from multiple along-track viewing angles (up to 60), four spectral bands in the visible and near infrared ranges, and three angles of linear polarization to measure the microphysical properties of the atmospheric particles including their size distribution, amount, refractive indices and particle shape. not-provided PM1EPHND_NRT.v6.1NRT MODIS/Aqua 24-hour Spacecraft ephemeris/orbit data files to be read via SDP Toolkit Binary Format - NRT LANCEMODIS 2017-10-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1426395235-LANCEMODIS.json PM1EPHND is the Aqua Near Real Time (NRT) daily spacecraft definitive ephemeris data file in native format. This is MODIS Ancillary Data. The data collection consists of PM1 Platform Attitude Data that has been preprocessed by ECS to an internal standard supported by the ECS SDP Toolkit. This data is typically used in determining the geolocation of earth remote sensing observations.The file name format is the following: PM1EPHND_NRT.Ayyyyddd.hhmm.vvv where from left to right: PM1 = PM1 (Aqua); EPH = Spacecraft Ephemeris; N = Native format; D = Definitive; A = Acquisition; yyyy = data year, ddd = Julian data day, hh = data hour, mm = data minute; vvv = Version ID. not-provided PSScene3Band.v1 PlanetScope Satellite Imagery 3 Band Scene CSDA 2014-06-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2112982481-CSDA.json The Planet Scope 3 band collection contains satellite imagery obtained from Planet Labs, Inc by the Commercial Smallsat Data Acquisition (CSDA) Program. This satellite imagery is in the visible waveband range with data in the red, green, and blue wavelengths. These data are collected by Planets Dove, Super Dove, and Blue Super Dove instruments collected from across the global land surface from June 2014 to present. Data have a spatial resolution of 3.7 meters at nadir and provided in GeoTIFF format. Data access are restricted to US Government funded investigators approved by the CSDA Program. not-provided QB02_MSI_L1B.v1 QuickBird Level 1B Multispectral 4-Band Satellite Imagery CSDA 2001-10-18 2015-01-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497489665-CSDA.json The QuickBird Level 1B Multispectral 4-Band Imagery collection contains satellite imagery acquired from Maxar Technologies by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the DigitalGlobe QuickBird-2 satellite using the Ball High Resolution Camera 60 across the global land surface from October 2001 to January 2015. This satellite imagery is in the visible and near-infrared waveband range with data in the blue, green, red, and near-infrared wavelengths. The spatial resolution is 2.16m at nadir and the temporal resolution is 2.5 to 5.6 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided QB02_Pan_L1B.v1 QuickBird Level 1B Panchromatic Satellite Imagery CSDA 2001-10-18 2015-01-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497480059-CSDA.json The QuickBird Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the DigitalGlobe QuickBird-2 satellite using the Ball High Resolution Camera 60 across the global land surface from October 2001 to January 2015. This data product includes panchromatic imagery with a spatial resolution of 0.55m at nadir and a temporal resolution of 2.5 to 5.6 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided SEAGLIDER_GUAM_2019.vV1 Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (Guam 2019-2020) POCLOUD 2019-10-03 2020-01-15 143.63035, 13.39476, 144.613, 14.71229 https://cmr.earthdata.nasa.gov/search/concepts/C2151536874-POCLOUD.json This dataset was produced by the Adaptive Sampling of Rain and Ocean Salinity from Autonomous Seagliders (NASA grant NNX17AK07G) project, an investigation to develop tools and strategies to better measure the structure and variability of upper-ocean salinity in rain-dominated environments. From October 2019 to January 2020, three Seagliders were deployed near Guam (14°N 144°E). The Seaglider is an autonomous profiler measuring salinity and temperature in the upper ocean. The three gliders sampled in an adaptive formation to capture the patchiness of the rain and the corresponding oceanic response in real time. The location was chosen because of the likelihood of intense tropical rain events and the availability of a NEXRAD (S-band) rain radar at the Guam Airport. Spacing between gliders varies from 1 to 60 km. Data samples are gridded by profile and on regular depth bins from 0 to 1000 m. The time interval between profiles was about 3 hours, and they are typically about 1.5 km apart. These profiles are available at Level 2 (basic gridding) and Level 3 (despiked and interpolated). All Seaglider data files are in netCDF format with standards compliant metadata. The project was led by a team from the Applied Physics Laboratory at the University of Washington. not-provided SRDB_V5_1827.v5 A Global Database of Soil Respiration Data, Version 5.0 ORNL_CLOUD 1961-01-01 2017-12-31 -163.71, -78.02, 175.9, 81.8 https://cmr.earthdata.nasa.gov/search/concepts/C2216864433-ORNL_CLOUD.json The Soil Respiration Database (SRDB) is a near-universal compendium of published soil respiration (Rs) data. The database encompasses published studies that report at least one of the following data measured in the field (not laboratory): annual soil respiration, mean seasonal soil respiration, a seasonal or annual partitioning of soil respiration into its source fluxes, soil respiration temperature response (Q10), or soil respiration at 10 degrees C. The SRDB's orientation is to seasonal and annual fluxes, not shorter-term or chamber-specific measurements, and the database is dominated by temperate, well-drained forest measurement locations. Version 5 (V5) is the compilation of 2,266 published studies with measurements taken between 1961-2017. 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. The database is also restructured to have better interoperability with other datasets related to carbon-cycle science. not-provided +SeaWiFS_L2_GAC_OC.vR2022.0 OrbView-2 SeaWiFS Regional Global Area Coverage (GAC) Ocean Color (OC) Data, version R2022.0 OB_CLOUD 1997-09-04 2010-12-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2789774382-OB_CLOUD.json The SeaWiFS instrument was launched by Orbital Sciences Corporation on the OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from September 1997 until the end of mission in December 2010. SeaWiFS had 8 spectral bands from 412 to 865 nm. It collected global data at 4 km resolution, and local data (limited onboard storage and direct broadcast) at 1 km. The mission and sensor were optimized for ocean color measurements, with a local noon (descending) equator crossing time orbit, fore-and-aft tilt capability, full dynamic range, and low polarization sensitivity. not-provided Survey_1988_89_Mawson_npcms.v1 1988/89 Summer season, surveying and mapping program, Mawson - North Prince Charles Mountains - Davis AU_AADC 1988-10-01 1989-02-28 62, -70, 79, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214313847-AU_AADC.json Field season report of these programs: 1988/89 Summer Season surveying and mapping North Prince Charles Mountains; ...mapping program Northern PCM's - Mawson Doppler Translocation Support; ....mapping program Voyage 6 stopover Davis. Includes maps and mapsheet layouts. See the report for full details on the program. Contents are: Introduction Preparation Voytage to Antarctica 1988/89 Summer Season Surveying and Mapping Program, Northern Prince Charles Mountains 1988/89 Summer Season Surveying and Mapping Program, Voyage 6 Stopover, Davis Performance of Equipment Station Marking Field Camping Climatic Conditions Conclusion Appendices not-provided -Turbid9.v0 2004 Measurements made in the Chesapeake Bay OB_DAAC 2004-10-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360689-OB_DAAC.json Measurements made in the Chesapeake Bay in 2004. not-provided USAP-1543498.v1 A Full Lifecycle Approach to Understanding Adélie Penguin Response to Changing Pack Ice Conditions in the Ross Sea AMD_USAPDC 2016-06-01 165, -78, -150, -60 https://cmr.earthdata.nasa.gov/search/concepts/C2532074621-AMD_USAPDC.json "The Ross Sea region of the Southern Ocean is experiencing growing sea ice cover in both extent and duration. These trends contrast those of the well-studied, western Antarctic Peninsula area, where sea ice has been disappearing. Unlike the latter, little is known about how expanding sea ice coverage might affect the regional Antarctic marine ecosystem. This project aims to better understand some of the potential effects of the changing ice conditions on the marine ecosystem using the widely-recognized indicator species - the Adélie Penguin. A four-year effort will build on previous results spanning 19 seasons at Ross Island to explore how successes or failures in each part of the penguin's annual cycle are effected by ice conditions and how these carry over to the next annual recruitment cycle, especially with respect to the penguin's condition upon arrival in the spring. Education and public outreach activities will continually be promoted through the PenguinCam and PenguinScience websites (sites with greater than 1 million hits a month) and ""NestCheck"" (a site that is logged-on by >300 classrooms annually that allows students to follow penguin families in their breeding efforts). To encourage students in pursuing educational and career pathways in the Science Technology Engineering and Math fields, the project will also provide stories from the field in a Penguin Journal, develop classroom-ready activities aligned with New Generation Science Standards, increase the availability of instructional presentations as powerpoint files and short webisodes. The project will provide additional outreach activities through local, state and national speaking engagements about penguins, Antarctic science and climate change. The annual outreach efforts are aimed at reaching over 15,000 students through the website, 300 teachers through presentations and workshops, and 500 persons in the general public. The project also will train four interns (undergraduate and graduate level), two post-doctoral researchers, and a science writer/photographer.

The project will accomplish three major goals, all of which relate to how Adélie Penguins adapt to, or cope with environmental change. Specifically the project seeks to determine 1) how changing winter sea ice conditions in the Ross Sea region affect penguin migration, behavior and survival and alter the carry-over effects (COEs) to subsequent reproduction; 2) the interplay between extrinsic and intrinsic factors influencing COEs over multiple years of an individual's lifetime; and 3) how local environmental change may affect population change via impacts to nesting habitat, interacting with individual quality and COEs. Retrospective analyses will be conducted using 19 years of colony based data and collect additional information on individually marked, known-age and known-history penguins, from new recruits to possibly senescent individuals. Four years of new information will be gained from efforts based at two colonies (Cape Royds and Crozier), using radio frequency identification tags to automatically collect data on breeding and foraging effort of marked, known-history birds to explore penguin response to resource availability within the colony as well as between colonies (mates, nesting material, habitat availability). Additional geolocation/time-depth recorders will be used to investigate travels and foraging during winter of these birds. The combined efforts will allow an assessment of the effects of penguin behavior/success in one season on its behavior in the next (e.g. how does winter behavior affect arrival time and body condition on subsequent breeding). It is at the individual level that penguins are responding successfully, or not, to ongoing marine habitat change in the Ross Sea region." not-provided USAP-1643722.v1 A High Resolution Atmospheric Methane Record from the South Pole Ice Core AMD_USAPDC 2017-02-01 2019-01-31 180, -90, 180, -90 https://cmr.earthdata.nasa.gov/search/concepts/C2534799946-AMD_USAPDC.json This award supports a project to measure the concentration of the gas methane in air trapped in an ice core collected from the South Pole. The data will provide an age scale (age as a function of depth) by matching the South Pole methane changes with similar data from other ice cores for which the age vs. depth relationship is well known. The ages provided will allow all other gas measurements made on the South Pole core (by the PI and other NSF supported investigators) to be interpreted accurately as a function of time. This is critical because a major goal of the South Pole coring project is to understand the history of rare gases in the atmosphere like carbon monoxide, carbon dioxide, ethane, propane, methyl chloride, and methyl bromide. Relatively little is known about what controls these gases in the atmosphere despite their importance to atmospheric chemistry and climate. Undergraduate assistants will work on the project and be introduced to independent research through their work. The PI will continue visits to local middle schools to introduce students to polar science, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) as part of the project. Methane concentrations from a major portion (2 depth intervals, excluding the brittle ice-zone which is being measured at Penn State University) of the new South Pole ice core will be used to create a gas chronology by matching the new South Pole ice core record with that from the well-dated WAIS Divide ice core record. In combination with measurements made at Penn State, this will provide gas dating for the entire 50,000-year record. Correlation will be made using a simple but powerful mid-point method that has been previously demonstrated, and other methods of matching records will be explored. The intellectual merit of this work is that the gas chronology will be a fundamental component of this ice core project, and will be used by the PI and other investigators for dating records of atmospheric composition, and determining the gas age-ice age difference independently of glaciological models, which will constrain processes that affected firn densification in the past. The methane data will also provide direct stratigraphic markers of important perturbations to global biogeochemical cycles (e.g., rapid methane variations synchronous with abrupt warming and cooling in the Northern Hemisphere) that will tie other ice core gas records directly to those perturbations. A record of the total air content will also be produced as a by-product of the methane measurements and will contribute to understanding of this parameter. The broader impacts include that the work will provide a fundamental data set for the South Pole ice core project and the age scale (or variants of it) will be used by all other investigators working on gas records from the core. The project will employ an undergraduate assistant(s) in both years who will conduct an undergraduate research project which will be part of the student's senior thesis or other research paper. The project will also offer at least one research position for the Oregon State University Summer REU site program. Visits to local middle schools, and other outreach activities (e.g. laboratory tours, talks to local civic or professional organizations) will also be part of the project. not-provided USAP-1744755.v1 A mechanistic study of bio-physical interaction and air-sea carbon transfer in the Southern Ocean AMD_USAPDC 2018-05-01 2022-04-30 -80, -70, -30, -45 https://cmr.earthdata.nasa.gov/search/concepts/C2545372297-AMD_USAPDC.json Current generation of coupled climate models, that are used to make climate projections, lack the resolution to adequately resolve ocean mesoscale (10 - 100km) processes, exhibiting significant biases in the ocean carbon uptake. Mesoscale processes include many features including jets, fronts and eddies that are crucial for bio-physical interactions, air-sea CO2 exchange and the supply of iron to the surface ocean. This modeling project will support the eddy resolving regional simulations to understand the mechanisms that drives bio-physical interaction and air-sea exchange of carbon dioxide. not-provided @@ -336,27 +332,21 @@ WV01_Pan_L1B.v1 WorldView-1 Level 1B Panchromatic Satellite Imagery CSDA 2007-10 WV02_MSI_L1B.v1 WorldView-2 Level 1B Multispectral 8-Band Satellite Imagery CSDA 2009-10-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497404794-CSDA.json The WorldView-2 Level 1B Multispectral 8-Band Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery is collected by the DigitalGlobe WorldView-2 satellite using the WorldView-110 camera across the global land surface from October 2009 to the present. This satellite imagery is in the visible and near-infrared waveband range with data in the coastal, blue, green, yellow, red, red edge, and near-infrared (2 bands) wavelengths. It has a spatial resolution of 1.85m at nadir and a temporal resolution of approximately 1.1 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided WV02_Pan_L1B.v1 WorldView-2 Level 1B Panchromatic Satellite Imagery CSDA 2009-10-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497398128-CSDA.json The WorldView-2 Level 1B Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery is collected by the DigitalGlobe WorldView-2 satellite using the WorldView-110 camera across the global land surface from October 2009 to the present. This data product includes panchromatic imagery with a spatial resolution of 0.46m and a temporal resolution of approximately 1.1 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided WaterBalance_Daily_Historical_GRIDMET.v1.5 Daily Historical Water Balance Products for the CONUS LPCLOUD 1980-01-01 2021-12-31 -131.70607, 21.115301, -60.530453, 55.457306 https://cmr.earthdata.nasa.gov/search/concepts/C2674694066-LPCLOUD.json 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 2021 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. not-provided +a-numerical-solver-for-heat-and-mass-transport-in-snow-based-on-fenics.v1.0 A numerical solver for heat and mass transport in snow based on FEniCS ENVIDAT 2022-01-01 2022-01-01 9.8472494, 46.812044, 9.8472494, 46.812044 https://cmr.earthdata.nasa.gov/search/concepts/C2789814662-ENVIDAT.json This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format. The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication: _Schürholt, K., Kowalski, J., Löwe, H.; Elements of future snowpack modeling - Part 1: A physical instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_ The code and potential updates can be accessed directly through git via: https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics not-provided a6efcb0868664248b9cb212aba44313d ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from MERIS (ALAMO algorithm), Version 2.2 FEDEO 2008-01-01 2008-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2548142742-FEDEO.json The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises the Level 2 aerosol products from MERIS for 2008, using the ALAMO algorithm, version 2.2. The data have been provided by Hygeos.For further details about these data products please see the linked documentation. not-provided -aamhcpex.v1 AAMH CPEX V1 GHRC_DAAC 2017-05-26 2017-07-16 154.716, 0.6408, -19.5629, 44.9689 https://cmr.earthdata.nasa.gov/search/concepts/C2645106424-GHRC_DAAC.json The AAMH CPEX dataset contains products obtained from the MetOp-A, MetOp-B, NOAA-18, and NOAA-19 satellites. These data were collected in support of the NASA Convective Processes Experiment (CPEX) field campaign. The CPEX field campaign took place in the North Atlantic-Gulf of Mexico-Caribbean Sea region from 25 May-25 June 2017. CPEX conducted a total of sixteen DC-8 missions from 27 May-24 June. The CPEX campaign collected data to help explain convective storm initiation, organization, growth, and dissipation in the North Atlantic-Gulf of Mexico-Caribbean Oceanic region during the early summer of 2017. These data are available from May 26, 2017 through July 15, 2017 and are available in netCDF-4 format. not-provided -aces1am.v1 ACES Aircraft and Mechanical Data V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977826980-GHRC_DAAC.json The ACES Aircraft and Mechanical Data consist of aircraft (e.g. pitch, roll, yaw) and mechanical (e.g. aircraft engine speed, tail commands, fuel levels) data recorded by the Altus II Unmanned Aerial Vehicle (Altus II UAV) system during the Altus Cumulus Electrification Study (ACES) based at the Naval Air Facility Key West in Florida. ACES aimed to provide extensive observations of the cloud electrification process and its effects by using the Altus II UAV to collect cloud top observations of thunderstorms. The campaign also worked to validate satellite lightning measurements. The Altus II aircraft and mechanical data files are available from July 10 through August 30, 2002 in MATLAB data format (.mat). not-provided -aces1cont.v1 ACES CONTINUOUS DATA V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847043-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August, 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloudelectrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from seven instruments: the Slow/Fast antenna, Electric Field Mill, Dual Optical Pulse Sensor, Searchcoil Magnetometer, Accelerometers, Gerdien Conductivity Probe, and the Fluxgate Magnetometer. Data consists of sensor reads at 50HZ throughout the flight from all 64 channels. not-provided -aces1efm.v1 ACES ELECTRIC FIELD MILL V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847178-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from it's birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data from Electric Field Mills, which yield information about the atmospheric electrical fields above the instruments. not-provided -aces1log.v1 ACES LOG DATA V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977853903-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of log data from each flight, and yields instrument and aircraft status throughout the flight. not-provided -aces1time.v1 ACES TIMING DATA V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977855412-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August or 2002, ACES researchers overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of timing data used for the experiment. When used it provides: syncclock_time = time found at the syncclock (VSI-SYnCCLOCK-32) in seconds from first file name, syncclock_m_time = time found at the syncclock (VSI-SYnCCLOCK-32) in Matlab dateform format, system_time = system time in seconds from first file name, system_m_time = system time in dateform format, gps_time = time found at the GPS unit in seconds from first file name, gps_m_time = time found at GPS unit in dateform, cmos_time = time found at the computer CMOS in seconds from first file name, cmos_m_time = time found at the computer CMOS in dateform. not-provided -aces1trig.v1 ACES TRIGGERED DATA V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977858342-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from the following instruments: Slow/Fast antenna, Electric Field Mill, Optical Pulse Sensors, Searchcoil Magnetometer, Accelerometer, and Gerdien Conductivity Probe. These data were collected at 200KHz from the first 16 telemetry items collected on the aircraft, were initiated by an operator selected trigger (e.g. DOPS), and continued collecting for as long as the trigger continued. not-provided -amprimpacts.v1 Advanced Microwave Precipitation Radiometer (AMPR) IMPACTS V1 GHRC_DAAC 2020-01-18 2022-02-28 -118.51, 30.6918, -64.3661, 48.2585 https://cmr.earthdata.nasa.gov/search/concepts/C2004708841-GHRC_DAAC.json The Advanced Microwave Precipitation Radiometer (AMPR) IMPACTS dataset consists of brightness temperature measurements collected by the Advanced Microwave Precipitation Radiometer (AMPR) onboard the NASA ER-2 high-altitude research aircraft. AMPR provides multi-frequency microwave imagery, with high spatial and temporal resolution for deriving cloud, precipitation, water vapor and surface properties. These measurements were taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Funded by NASA’s Earth Venture program, IMPACTS is the first comprehensive study of East Coast snowstorms in 30 years. Data files are available from January 18, 2020 through February 28, 2022 in netCDF-4 format. not-provided -amsua15sp.v1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15 V1 GHRC_DAAC 1998-08-03 -180, -90, 180, 89.756 https://cmr.earthdata.nasa.gov/search/concepts/C1996541017-GHRC_DAAC.json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NOAA-15 was the first spacecraft to fly AMSU. Launched on 13 May 1998, NOAA-15 is in a sun synchronous near polar orbit. not-provided -amsua16sp.v1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-16 V1 GHRC_DAAC 2001-05-27 2009-07-30 -180, -89.91, 180, 89.73 https://cmr.earthdata.nasa.gov/search/concepts/C1979956366-GHRC_DAAC.json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). Launched on 21 September 2000, NOAA-16 is in a sun synchronous near polar orbit. not-provided +above-and-below-ground-herbivore-communities-along-elevation.v1.0 Above- and below-ground herbivore communities along elevation ENVIDAT 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.json Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017. not-provided +aerosol-data-davos-wolfgang.v1.0 Aerosol Data Davos Wolfgang ENVIDAT 2020-01-01 2020-01-01 9.853594, 46.835577, 9.853594, 46.835577 https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. not-provided +aerosol-data-weissfluhjoch.v1.0 Aerosol Data Weissfluhjoch ENVIDAT 2020-01-01 2020-01-01 9.806475, 46.832964, 9.806475, 46.832964 https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. not-provided +alnus-glutinosa-orientus-ishidae-flavescence-doree.v1.0 Alnus glutinosa (L.) Gaertn. and Orientus ishidae (Matsumura, 1902) share phytoplasma genotypes linked to the “Flavescence dorée” epidemics ENVIDAT 2021-01-01 2021-01-01 8.4484863, 45.8115721, 9.4372559, 46.4586735 https://cmr.earthdata.nasa.gov/search/concepts/C2789814963-ENVIDAT.json Flavescence dorée (FD) is a grapevine disease caused by associated phytoplasmas (FDp), which are epidemically spread by their main vector Scaphoideus titanus. The possible roles of alternative and secondary FDp plant hosts and vectors have gained interest to better understand the FDp ecology and epidemiology. A survey conducted in the surroundings of a vineyard in the Swiss Southern Alps aimed at studying the possible epidemiological role of the FDp secondary vector Orientus ishidae and the FDp host plant Alnus glutinosa is reported. Data used for the publication. Insects were captured by using a sweeping net (on common alder trees) and yellow sticky traps (Rebell Giallo, Andermatt Biocontrol AG, Switzerland) placed in the vineyard canopy. Insects were later determined and selected for molecular analyses. Grapevines and common alder samples were collected using the standard techniques. The molecular analyses were conducted in order to identify samples infected by the Flavescence dorée phytoplasma (16SrV-p) and the Bois Noir phytoplasma (16SrXII-p). A selection of the infected sampled were further characterized by map genotype and sequenced in order to compare the genotypes in insects, grapevines and common alder trees. not-provided +alpine3d-simulations-of-future-climate-scenarios-for-graubunden.v1.0 Alpine3D simulations of future climate scenarios for Graubunden ENVIDAT 2019-01-01 2019-01-01 8.6737061, 46.2216525, 10.6347656, 47.1075228 https://cmr.earthdata.nasa.gov/search/concepts/C2789814545-ENVIDAT.json "This is the simulation dataset from _""Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland""_, M. Bavay, T. Grünewald, M. Lehning, Advances in Water Resources __55__, 4-16, 2013 A model study on the impact of climate change on snow cover and runoff has been conducted for the Swiss Canton of Graubünden. The model Alpine3D has been forced with the data from 35 Automatic Weather Stations in order to investigate snow and runoff dynamics for the current climate. The data set has then been modified to reflect climate change as predicted for the 2021-2050 and 2070-2095 periods from an ensemble of regional climate models. The predicted changes in snow cover will be moderate for 2021-2050 and become drastic in the second half of the century. Towards the end of the century the snow cover changes will roughly be equivalent to an elevation shift of 800 m. Seasonal snow water equivalents will decrease by one to two thirds and snow seasons will be shortened by five to nine weeks in 2095. Small, higher elevation catchments will show more winter runoff, earlier spring melt peaks and reduced summer runoff. Where glacierized areas exist, the transitional increase in glacier melt will initially offset losses from snow melt. Larger catchments, which reach lower elevations will show much smaller changes since they are already dominated by summer precipitation." not-provided asas Advanced Solid-state Array Spectroradiometer (ASAS) USGS_LTA 1988-06-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566261-USGS_LTA.json The Advanced Solid-state Array Spectroradiometer (ASAS) data collection contains data collected by the ASAS sensor flown aboard NASA aircraft. A fundamental use of ASAS data is to characterize and understand the directional variability in solar energy scattered by various land surface cover types (e.g.,crops, forests, prairie grass, snow, or bare soil). The sensor's Bidirectional Reflectance Distribution Function determines the variation in the reflectance of a surface as a function of both the view zenith angle and solar illumination angle. The ASAS sensor is a hyperspectral, multiangle, airborne remote sensing instrument maintained and operated by the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The ASAS instrument is mounted on the underside of either NASA C-130 or NASA P-3 aircraft and is capable of off-nadir pointing from approximately 70 degrees forward to 55 degrees aft along the direction of flight. The aircraft is flown at an altitude of 5000 - 6000 meters (approximately 16,000 - 20,000 ft.). Data in the ASAS collection primarily cover areas over the continental United States, but some ASAS data are also available over areas in Canada and western Africa. The ASAS data were collected between 1988 and 1994. not-provided aster_global_dem ASTER Global DEM USGS_LTA 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220567908-USGS_LTA.json ASTER is capable of collecting in-track stereo using nadir- and aft-looking near infrared cameras. Since 2001, these stereo pairs have been used to produce single-scene (60- x 60-kilomenter (km)) digital elevation models (DEM) having vertical (root-mean-squared-error) accuracies generally between 10- and 25-meters (m). The methodology used by Japan's Sensor Information Laboratory Corporation (SILC) to produce the ASTER GDEM involves automated processing of the entire ASTER Level-1A archive. Stereo-correlation is used to produce over one million individual scene-based ASTER DEMs, to which cloud masking is applied to remove cloudy pixels. All cloud-screened DEMS are stacked and residual bad values and outliers are removed. Selected data are averaged to create final pixel values, and residual anomalies are corrected before partitioning the data into 1 degree (°) x 1° tiles. The ASTER GDEM covers land surfaces between 83°N and 83°S and is comprised of 22,702 tiles. Tiles that contain at least 0.01% land area are included. The ASTER GDEM is distributed as Geographic Tagged Image File Format (GeoTIFF) files with geographic coordinates (latitude, longitude). The data are posted on a 1 arc-second (approximately 30–m at the equator) grid and referenced to the 1984 World Geodetic System (WGS84)/ 1996 Earth Gravitational Model (EGM96) geoid. not-provided b673f41b-d934-49e4-af6b-44bbdf164367 AVHRR - Land Surface Temperature (LST) - Europe, Daytime FEDEO 1998-02-23 -24, 28, 57, 78 https://cmr.earthdata.nasa.gov/search/concepts/C2207458008-FEDEO.json "The ""Land Surface Temperature derived from NOAA-AVHRR data (LST_AVHRR)"" is a fixed grid map (in stereographic projection ) with a spatial resolution of 1.1 km. The total size covering Europe is 4100 samples by 4300 lines. Within 24 hours of acquiring data from the satellite, day-time and night-time LSTs are calculated. In general, the products utilise data from all six of the passes that the satellite makes over Europe in each 24 hour period. For the daily day-time LST maps, the compositing criterion for the three day-time passes is maximum NDVI value and for daily night-time LST maps, the criterion is the maximum night-time LST value of the three night-time passes. Weekly and monthly day-time or night-time LST composite products are also produced by averaging daily day-time or daily night-time LST values, respectively. The range of LST values is scaled between –39.5°C and +87°C with a radiometric resolution of 0.5°C. A value of –40°C is used for water. Clouds are masked out as bad values. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/" not-provided blue_ice_core_DML2004_AS 101.1 m long horizontal blue ice core collected from Scharffenbergbotnen, DML, Antarctica, in 2003/2004 SCIOPS 1970-01-01 -180, -90, 180, -62.83 https://cmr.earthdata.nasa.gov/search/concepts/C1214614210-SCIOPS.json Horizontal blue ice core collected from the surface of a blue ice area in Scharffenbergbotnen, Heimefrontfjella, DML. Samples were collected in austral summer 2003/2004 and transported to Finland for chemical analyses. The blue ice core is estimated to represent a 1000-year period of climate history 20 - 40 kyr B.P.. The results of the analyses will be available in 2005. not-provided -chesapeake_val_2013.v0 2013 Chesapeake Bay measurements OB_DAAC 2013-04-11 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360188-OB_DAAC.json 2013 Chesapeake Bay measurements. not-provided +ch2014.v1 Alpine3D simulations of future climate scenarios CH2014 ENVIDAT 2014-01-01 2014-01-01 8.227, 46.79959, 8.227, 46.79959 https://cmr.earthdata.nasa.gov/search/concepts/C2789814657-ENVIDAT.json # Overview The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change. # Experimental Setup Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graubünden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m × 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999–2012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085). # Data Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5–9 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400–800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average. not-provided darling_sst_82-93 1982-1989 and 1993 Seawater Temperatures at the Darling Marine Center SCIOPS 1982-03-01 1993-12-31 -71.31, 42.85, -66.74, 47.67 https://cmr.earthdata.nasa.gov/search/concepts/C1214621676-SCIOPS.json Seawater Surface Temperature Data Collected between the years 1982-1989 and 1993 off the dock at the Darling Marine Center, Walpole, Maine not-provided ef6a9266-a210-4431-a4af-06cec4274726 Cartosat-1 (IRS-P5) - Panchromatic Images (PAN) - Europe, Monographic FEDEO 2015-02-10 -25, 30, 45, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2207457985-FEDEO.json Indian Remote Sensing satellites (IRS) are a series of Earth Observation satellites, built, launched and maintained by Indian Space Research Organisation. The IRS series provides many remote sensing services to India and international ground stations. The satellite has two panchromatic cameras that were especially designed for in flight stereo viewing. However, this collection contains the monoscopic data. not-provided -gov.noaa.nodc:0000029 1990, 1991, 1992 and 1995 CRETM/LMER Zooplankton Data Sets (NCEI Accession 0000029) NOAA_NCEI 1990-09-26 1995-05-26 -124.041667, 0.766667, -16.25, 46.263167 https://cmr.earthdata.nasa.gov/search/concepts/C2089372282-NOAA_NCEI.json Not provided not-provided -gov.noaa.nodc:0000035 1996 - Early 1998 CRETM/LMER Phytoplankton Data (NCEI Accession 0000035) NOAA_NCEI 1996-07-09 1998-03-06 -124.003, 46.179833, -123.183167, 46.261667 https://cmr.earthdata.nasa.gov/search/concepts/C2089372325-NOAA_NCEI.json Pump cast sampling, and associated CTD casts took place from a fixed vessel during one 28-35 day cruise per year in 1990, 1991, 1992, 1995, and 1996. In 1997 there were 2 week cruises in May, July, and October. not-provided -gov.noaa.nodc:0000052 1988 Resurrection Bay Zooplankton Data Set from 01 March 1988 to 28 June 1988 (NCEI Accession 0000052) NOAA_NCEI 1988-03-01 1988-06-28 -149.4083, 59.9117, -149.3583, 60.02 https://cmr.earthdata.nasa.gov/search/concepts/C2089372461-NOAA_NCEI.json Zooplantkon and beach tar data were collected using plankton net casts in the Gulf of Alaska from the ALPHA HELIX. Data were collected from 01 March 1988 to 28 June 1988 by University of Alaska in Fairbanks; Institute of Marine Science with support from the Gulf of Alaska - 1 (GAK-1) project. not-provided +envidat-lwf-34.v2019-03-06 10-HS Pfynwald ENVIDAT 2019-01-01 2019-01-01 7.61211, 46.30279, 7.61211, 46.30279 https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.json Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) not-provided gov.noaa.nodc:GHRSST-AVHRR_SST_METOP_A_GLB-OSISAF-L3C.v1 GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-A) produced by OSI SAF (GDS version 2) GHRSSTCWIC 2013-07-26 2016-02-23 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2213636900-GHRSSTCWIC.json A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-A (MetOp-A) platform (launched 19 Oct 2006). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. SST is retrieved from the AVHRR infrared channels (3.7, 10.8 and 12.0 micrometer) using a multispectral algorithm. Atmospheric profiles of water vapor and temperature from a numerical weather prediction model, together with a radiative transfer model, are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. This global L3C product is derived from full resolution AVHRR l1b data that are re-mapped onto a 0.05 degree grid twice daily. The product format is compliant with the GHRSST Data Specification (GDS) version 2. not-provided gov.noaa.nodc:GHRSST-AVHRR_SST_METOP_B_GLB-OSISAF-L3C.v1 GHRSST L3C global sub-skin Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on Metop satellites (currently Metop-B) produced by OSI SAF (GDS version 2) GHRSSTCWIC 2016-02-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2213637836-GHRSSTCWIC.json A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset derived from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-B (MetOp-B) platform (launched 17 Sep 2012). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. SST is retrieved from the AVHRR infrared channels (3.7, 10.8 and 12.0 micrometer) using a multispectral algorithm. Atmospheric profiles of water vapor and temperature from a numerical weather prediction model, together with a radiative transfer model, are used to correct the multispectral algorithm for regional and seasonal biases due to changing atmospheric conditions. This global L3C product is derived from full resolution AVHRR l1b data that are re-mapped onto a 0.05 degree grid twice daily. The product format is compliant with the GHRSST Data Specification (GDS) version 2. not-provided gov.noaa.nodc:GHRSST-EUR-L2P-AVHRR16_L.v1.0 GHRSST Level 2P Atlantic Regional Bulk Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 satellite (GDS version 1) GHRSSTCWIC 2004-12-30 2005-10-26 -45, 20, 45, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2213638215-GHRSSTCWIC.json A regional Level 2P Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the Atlantic Ocean and nearby regions based on multi-channel sea surface temperature (SST) retrievals from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-16 platform (launched on 21 Sep 2000). The AVHRR is a space-borne scanning sensor on the National Oceanic and Atmospheric Administration (NOAA) family of Polar Orbiting Environmental Satellites (POES) having a operational legacy that traces back to the Television Infrared Observation Satellite-N (TIROS-N) launched in 1978. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micrometer) and near-infrared (0.9 micrometer) regions, the third one is located around 3.5 micrometer, and the last two sample the emitted thermal radiation, around 11 and 12 micrometers, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micrometer. Typically the 11 and 12 micron channels are used to derive sea surface temperature (SST) sometimes in combination with the 3.5 micron channel. The highest ground resolution that can be obtained from the current AVHRR instruments is 1.1 km at nadir. The NOAA platforms are sun synchronous generally viewing the same earth location twice a day (latitude dependent) due to the relatively large AVHRR swath of approximately 2400 km. This particular dataset is derived from Local Area Coverage (LAC) binary AVHRR SST binary data originally produced by the US Naval Oceanographic Office (NAVO) and downloaded from the NASA Physical Oceanography Distributed Active Archive Center (PO.DAAC). LAC are full resolution AVHRR data whose acquisition is prescheduled and recorded with an on-board tape recorder for subsequent transmission during a station overpass. Finally, L2P data products are derived following the GHRSST-PP Data Processing Specification (GDS) version 1.5 including Single Sensor Error Statistics (SSES). not-provided @@ -367,7 +357,8 @@ gov.noaa.nodc:GHRSST-OISST_HR_NRT-GOS-L4-BLK.v2.0 Black Sea High Resolution SST gov.noaa.nodc:GHRSST-OISST_UHR_NRT-GOS-L4-BLK.v2.0 Black Sea Ultra High Resolution SST L4 Analysis 0.01 deg Resolution (GDS version 2) GHRSSTCWIC 2012-01-31 26.375, 38.75, 42.375, 48.812 https://cmr.earthdata.nasa.gov/search/concepts/C2213642712-GHRSSTCWIC.json CNR MED Sea Surface Temperature provides daily gap-free maps (L4) at 0.01 deg. x 0.01 deg. horizontal resolution over the Black Sea. The data are obtained from infra-red measurements collected by satellite radiometers and statistical interpolation. It is the CMEMS sea surface temperature nominal operational product for the Black sea. not-provided gov.noaa.nodc:GHRSST-REMSS-L2P_GRIDDED_25-TMI.v4.0 GHRSST L2P Gridded Global Subskin Sea Surface Temperature from the Tropical Rainfall Mapping Mission (TRMM) Microwave Imager (TMI) (GDS version 1) GHRSSTCWIC 1998-01-01 2015-04-06 -180, -40, 180, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2213645156-GHRSSTCWIC.json "The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to SSM/I, that contains lower frequency channels required for sea surface temperature (SST) retrievals. The TRMM is a joint venture between NASA and the Japan Aerospace Exploration Agency (JAXA) to measure precipitation, water vapor, SST and wind in the global tropical regions and was launched in November 1997. The TRMM satellite travels west to east in a 402 km altitude semi-equatorial precessing orbit that results in day-to-day changes in the observation time of any given earth location between 38S and 38N. In contrast to infrared SST observations, microwave retrievals can be measured through most clouds, and are also insensitive to water vapor and aerosols. Remote Sensing Systems is the producer of these gridded TMI SST data for the Group for High Resolution Sea Surface Temperature (GHRSST) Project. Although the product designation is ""L2P_GRIDDED"" it is in actuality a Level 3 Collated (L3C) product as defined in the GHRSST Data Processing Specification (GDS) version 2.0. Its ""L2P_GRIDDED"" name derives from a deprecated specification in the early Pilot Project phase of GHRSST (pre 2008) and has remained for file naming continuity. In this dataset, both ascending (daytime) and descending (daytime) gridded orbital passes on packaged into the same daily file." not-provided gov.noaa.nodc:GHRSST-VIIRS_NPP-NAVO-L2P.v3.0 GHRSST Level 2P 1 m Depth Global Sea Surface Temperature version 3.0 from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite (GDS version 2) GHRSSTCWIC 2013-06-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2213644303-GHRSSTCWIC.json A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS). This sensor resides on the Suomi National Polar-orbiting Partnership (Suomi_NPP) satellite launched on 28 October 2011. VIIRS is a whiskbroom scanning radiometer which takes measurements in the cross-track direction within a field of regard of 112.56 degrees using 16 detectors and a double-sided mirror assembly. At a nominal altitude of 829 km, the swath width is 3060 km, providing full daily coverage both on the day and night side of the Earth. The VIIRS instrument is a 22-band, multi-spectral scanning radiometer that builds on the heritage of the MODIS, AVHRR and SeaWiFS sensors for sea surface temperature (SST) and ocean color. For the infrared bands for SST the effective pixel size is 750 meters at nadir and the pixel size variation across the swath is constrained to no more than 1600 meters at the edge of the swath. This L2P SST v3.0 is upgraded from the v2.0 with several significant improvements in processing algorithms, including contamination detection, cloud detection, and data format upgrades. It contains the global near daily-coverage Sea Surface Temperature at 1-meter depth with 750 m (along) x 750 m (cross) spatial resolution in swath coordinates. Each netCDF file has 768 x 3200 pixels in size, in compliance with the GHRSST Data Processing Specification (GDS) version 2 format specifications. not-provided -lake_erie_aug_2014.v0 2014 Lake Erie measurements OB_DAAC 2014-08-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360418-OB_DAAC.json 2014 Lake Erie measurements. not-provided +latent-reserves-in-the-swiss-nfi.v1.0 'Latent reserves' within the Swiss NFI ENVIDAT 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.json "The files refer to the data used in Portier et al. ""‘Latent reserves’: a hidden treasure in National Forest Inventories"" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered ‘latent reserves’, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Klötzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement. " not-provided law_dome_annual_msa.v1 150 year MSA sea ice proxy record from Law Dome, Antarctica AU_AADC 1841-01-01 1995-12-31 112.806946, -66.76972, 112.806946, -66.76972 https://cmr.earthdata.nasa.gov/search/concepts/C1214313532-AU_AADC.json "This MSA record (1841-1995) is from a Law Dome ice core called ""DSS"" in East Antarctica. It was calibrated against satellite sea ice records and used to reconstruct sea ice extent prior to the satellite era. The following is taken from the abstract of the paper (Curran et al., 2003). The instrumental record of Antarctic sea ice in recent decades does not reveal a clear signature of warming despite observational evidence from coastal Antarctica. This work shows a significant correlation (P less than 0.002) between methanesulphonic acid (MSA) concentrations from a Law Dome ice core and 22 years of satellite-derived sea ice extent (SIE) for the 80 degrees E to 140 degrees E sector. Applying this instrumental calibration to longer term MSA data (1841 to 1995 A.D.) suggests that there has been a 20% decline in SIE since about 1950. The decline is not uniform, showing large cyclical variations, with periods of about 11 years, that confuse trend detection over the relatively short satellite era. This work was completed as part of ASAC project 757 (ASAC_757)." not-provided mbs_wilhelm_msa_hooh.v1 15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS) AU_AADC 1984-01-01 1998-12-31 86.082, -69.13, 86.084, -69.12 https://cmr.earthdata.nasa.gov/search/concepts/C1214313640-AU_AADC.json This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757). not-provided +pfynwaldgasexchange.v1.0 2013-2020 gas exchange at Pfynwald ENVIDAT 2021-01-01 2021-01-01 7.6105556, 46.3001905, 7.6163921, 46.3047564 https://cmr.earthdata.nasa.gov/search/concepts/C2789816347-ENVIDAT.json Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds. All metadata can be found in the attached documents. not-provided urn:ogc:def:EOP:VITO:VGT_S10.v1 10 Days Synthesis of SPOT VEGETATION Images (VGT-S10) FEDEO 1998-04-01 2014-05-31 -180, -56, 180, 75 https://cmr.earthdata.nasa.gov/search/concepts/C2207472890-FEDEO.json The VGT-S10 are near-global or continental, 10-daily composite images which are synthesised from the 'best available' observations registered in the course of every 'dekad' by the orbiting earth observation system SPOT-VEGETATION. The products provide data from all spectral bands (SWIR, NIR, RED, BLUE), the NDVI and auxiliary data on image acquisition parameters. The VEGETATION system allows operational and near real-time applications, at global, continental and regional scales, in very broad environmentally and socio-economically critical fields. The VEGETATION instrument is operational since April 1998, first with VGT1, from March 2003 onwards, with VGT2. More information is available on: https://docs.terrascope.be/#/DataProducts/SPOT-VGT/Level3/Level3 not-provided