From 8307276979a6d495de6250a676f07623fc6b6e7e Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Sat, 24 Aug 2024 03:48:26 +0000 Subject: [PATCH] Updated datasets 2024-08-24 UTC --- nasa_cmr_catalog.json | 611 +++++++++++++++++++++++++++++++++--------- nasa_cmr_catalog.tsv | 47 +++- 2 files changed, 518 insertions(+), 140 deletions(-) diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json index d366dca31..13cc88058 100644 --- a/nasa_cmr_catalog.json +++ b/nasa_cmr_catalog.json @@ -103,6 +103,97 @@ "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", @@ -350,6 +441,136 @@ "description": "This document presents the Concise Experiment Plan for NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) to serve as a guide to the Program as it identifies the research to be conducted under this study. Research for ABoVE will link field-based, process-level studies with geospatial data products derived from airborne and satellite remote sensing, providing a foundation for improving the analysis and modeling capabilities needed to understand and predict ecosystem responses and societal implications. The ABoVE Concise Experiment Plan (ACEP) outlines the conceptual basis for the Field Campaign and expresses the compelling rationale explaining the scientific and societal importance of the study. It presents both the science questions driving ABoVE research as well as the top-level requirements for a study design to address them.", "license": "not-provided" }, + { + "id": "ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data.v1", + "title": "ACCLIP WB-57 Aerosol and Cloud Remotely Sensed Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-14", + "end_date": "2022-09-14", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2655162569-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2655162569-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data.v1", + "description": "ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data is the cloud and aerosol remote sensing data from the Roscoe lidar collected during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACCLIP_Aerosol_AircraftInSitu_WB57_Data.v1", + "title": "ACCLIP WB-57 Aircraft In-Situ Aerosol Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-14", + "end_date": "2022-09-14", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2609962127-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2609962127-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_Aerosol_AircraftInSitu_WB57_Data.v1", + "description": "ACCLIP_Aerosol_AircraftInSitu_WB57_Data is the in-situ aerosol data collected during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Particle Analysis by Laser Mass Spectrometry - Next Generation (PALMS-NG), Single Particle Soot Photometer (SP2), Nucleation-Mode Aerosol Size Spectrometer (N-MASS), Printed Optical Particle Spectrometer (POPS), and the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACCLIP_AircraftInSitu_WB57_Water_Data.v1", + "title": "ACCLIP WB-57 Aircraft Water In-situ Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-14", + "end_date": "2022-09-14", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2609920136-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2609920136-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_AircraftInSitu_WB57_Water_Data.v1", + "description": "ACCLIP_AircraftInSitu_WB57_Water_Data is the in-situ water data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Chicago Water Isotope Spectrometer (ChiWIS) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACCLIP_Cloud_AircraftInSitu_WB57_Data.v1", + "title": "ACCLIP WB-57 Aircraft In-situ Cloud Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-14", + "end_date": "2022-09-15", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2609947245-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2609947245-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_Cloud_AircraftInSitu_WB57_Data.v1", + "description": "ACCLIP_Cloud_AircraftInSitu_WB57_Data is the in-situ cloud data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Cloud, Aerosol, and Precipitation Spectrometer (CAPS) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACCLIP_Merge_WB57-Aircraft_Data.v1", + "title": "ACCLIP WB-57 Aircraft Merge Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-16", + "end_date": "2022-09-14", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2609887645-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2609887645-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_Merge_WB57-Aircraft_Data.v1", + "description": "ACCLIP_Merge_WB57-Aircraft_Data is the pre-generated merge files created from a variety of in-situ instrumentation collecting measurements onboard the WB-57 aircraft during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACCLIP_MetNav_AircraftInSitu_WB57_Data.v1", + "title": "ACCLIP WB-57 Meteorological and Navigational Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-14", + "end_date": "2022-09-14", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2566338281-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2566338281-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_MetNav_AircraftInSitu_WB57_Data.v1", + "description": "ACCLIP_MetNav_AircraftInSitu_WB57_Data is the in-situ meteorology and navigational data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Meteorological Measurement System (MMS) and Diode Laser Hygrometer (DLH) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACCLIP_Model_WB57_Data.v1", + "title": "ACCLIP WB-57 Aircraft Model Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-14", + "end_date": "2022-09-14", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2609869612-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2609869612-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_Model_WB57_Data.v1", + "description": "ACCLIP_Model_WB57_Data contains modeled meteorological, chemical, and aerosol data along the flight tracks of the WB-57 aircraft during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACCLIP_TraceGas_AircraftInSitu_WB57_Data.v1", + "title": "ACCLIP WB-57 Aircraft In-situ Trace Gas Data", + "catalog": "LARC_ASDC", + "state_date": "2022-07-14", + "end_date": "2022-09-14", + "bbox": "-180, 16.6, 180, 61.5", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2566342407-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2566342407-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACCLIP_TraceGas_AircraftInSitu_WB57_Data.v1", + "description": "ACCLIP_TraceGas_AircraftInSitu_WB57_Data is the in-situ trace gas data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Airborne Carbon Oxide Sulfide Spectrometer (ACOS), Carbon monOxide Measurement from Ames (COMA), Laser Induced Fluorescence - Nitrogen Oxide (LIF-NO), In Situ Airborne Formaldehyde (ISAF), Carbon Oxide Laser Detector 2 (COLD 2), and the NOAA UAS O3 Photometer (UASO3) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere.", + "license": "not-provided" + }, + { + "id": "ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1", + "title": "ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data Version 1", + "catalog": "LARC_ASDC", + "state_date": "2017-10-18", + "end_date": "2020-11-20", + "bbox": "-130, 25, -100, 45", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588261-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588261-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1", + "description": "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\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 is a valuable resource for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions.", + "license": "not-provided" + }, + { + "id": "ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1", + "title": "ACEPOL Airborne Spectrometer for Planetary Exploration (AirSPEX) Remotely Sensed Data Version 1", + "catalog": "LARC_ASDC", + "state_date": "2017-10-19", + "end_date": "2017-11-09", + "bbox": "-130, 25, -100, 45", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LARC_ASDC/collections/ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1", + "description": "ACEPOL_AircraftRemoteSensing_AirSPEX_Data are remotely sensed measurements collected by the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) onboard the ER-2 during the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. 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", @@ -1221,6 +1442,19 @@ "description": "Metadata record for data from ASAC Project 2357 See the link below for public details on this project. ---- Public Summary from Project ---- Contaminants like PCBs and DDE have hardly been used Antarctica. Hence, this is an excellent place to monitor global background levels of these organochlorines. In this project concentrations in penguins and petrels will be compared to 10 years ago, which will show time trends of global background contamination levels. Data set description From several birds from Hop Island, Rauer Islands near Davis, samples were collected from preenoil (oil that birds excrete to preen their feathers. This preenoil was then analysed for organochlorine pollutants like polychlorinated biphenyls, (PCBs), hexachlorobenzene (HCB), DDE and dieldrin. The species under investigation were the Adelie penguin (Pygoscelis adeliae) and the Southern Fulmar (Fulmarus glacialoides). The samples were collected from adult breeding birds, and stored in -20 degrees C as soon as possible. The analysis was done with relatively standard but very optimised methods, using a gas-chromatograph and mass-selective detection. Data sheets: The data are available in excel-sheets, located at Alterra, The Netherlands (the affiliation of the PI Nico van den Brink.). Data are available on PCB153 (polychlorinated biphenyl congener numbered 153), hexachlorobenzene (HCB), DDE (a metabolite of the pesticide DDT), and dieldrin (an insecticide). The metadata are in 4 sheets (in meta data 2357.xls): 1. 'Concentrations fulmars' 2. 'Morphometric data fulmars' 3. 'Concentrations Adelies' 4. 'Morphometric data Adelies' The column headings are: 1. 'Concentrations fulmars' - Fulmar: bird number, corresponds with sheet 'morphometric data fulmars'. - PCB153: concentration of PCB-congener 153 (ng/g lipids) - HCB: concentration of hexachlorobenzene (ng/g lipids) - DDE: concentration of DDE (ng/g lipids) - Dieldrin: concentration of dieldrin (ng/g lipids) - Sample size weight of collected amount of preenoil 2. Morphometric data fulmars - Fulmar: bird number, corresponds with sheet 'Concentrations fulmars'. - Bill Length (mm): length of bill (tip to base) - Head Length (mm): length of head (tip of bill to back of head) - Tarsus (mm): length of tarsus - Wing Length (cm): length of right wing - Weight (kg): weight of bird (without bag) 3. 'Concentrations Adelies' Adelie: bird number, corresponds with sheet 'morphometric data Adelies'. - PCB153: concentration of PCB-congener 153 (ng/g lipids) - HCB: concentration of hexachlorobenzene (ng/g lipids) - DDE: concentration of DDE (ng/g lipids) - Dieldrin: concentration of dieldrin (ng/g lipids) - Sample size weight of collected amount of preenoil 4. 'Morphometric data Adelies' - Adelie: bird number, corresponds with sheet 'Concentrations Adelies'. - Bill (mm): length of bill (tip to base) - Head Length (mm): length of head (tip of bill to back of head) - Tarsus (mm): length of tarsus - Flipper Length (cm): length of right flipper (wing) - Weight (kg): weight of bird (without bag) In sheets on concentrations: less than d.l.: concentrations below detection limits.", "license": "not-provided" }, + { + "id": "AST14DEM.v003", + "title": "ASTER Digital Elevation Model V003", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-06", + "end_date": "", + "bbox": "-180, -83, 180, 83", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1299783579-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1299783579-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST14DEM.v003", + "description": "The ASTER Digital Elevation Model (AST14DEM) product is generated (https://lpdaac.usgs.gov/documents/996/ASTER_Earthdata_Search_Order_Instructions.pdf) using bands 3N (nadir-viewing) and 3B (backward-viewing) of an (ASTER Level 1A) (https://doi.org/10.5067/ASTER/AST_L1A.003) image acquired by the Visible and Near Infrared (VNIR) sensor. The VNIR subsystem includes two independent telescope assemblies that facilitate the generation of stereoscopic data. The band 3 stereo pair is acquired in the spectral range of 0.78 and 0.86 microns with a base-to-height ratio of 0.6 and an intersection angle of 27.7 degrees. There is a time lag of approximately one minute between the acquisition of the nadir and backward images. For a better understanding, refer to this (diagram) (https://lpdaac.usgs.gov/documents/301/ASTER_Along_Track_Imaging_Geometry.png) depicting the along-track imaging geometry of the ASTER VNIR nadir and backward-viewing sensors. The accuracy of the new LP DAAC produced DEMs will meet or exceed accuracy specifications set for the ASTER relative DEMs by the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/81/AST14_ATBD.pdf). Users likely will find that the DEMs produced by the new LP DAAC system have accuracies approaching those specified in the ATBD for absolute DEMs. Validation testing has shown that DEMs produced by the new system frequently are more accurate than 25 meters root mean square error (RMSE) in xyz dimensions. Improvements/Changes from Previous Versions As of January 2021, the LP DAAC has implemented version 3.0 of the Sensor Information Laboratory Corporation ASTER DEM/Ortho (SILCAST) software, which is used to generate the Level 2 on-demand ASTER Orthorectified and Digital Elevation Model (DEM) products (AST14). The updated software provides digital elevation extraction and orthorectification from ASTER L1B input data without needing to enter ground control points or depending on external global DEMs at 30-arc-second resolution (GTOPO30). It utilizes the ephemeris and attitude data derived from both the ASTER instrument and the Terra spacecraft platform. The outputs are geoid height-corrected and waterbodies are automatically detected in this version. Users will notice differences between AST14DEM, AST14DMO, and AST14OTH products ordered before January 2021 (generated with SILCAST V1) and those generated with the updated version of the production software (version 3.0). Differences may include slight elevation changes over different surface types, including waterbodies. Differences have also been observed over cloudy portions of ASTER scenes. Additional information on SILCAST version 3.0 can be found on the SILCAST website (http://www.silc.co.jp/en/products.html). Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. ", + "license": "not-provided" + }, { "id": "ASTGTM.v003", "title": "ASTER Global Digital Elevation Model V003", @@ -1260,6 +1494,123 @@ "description": "The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator). The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan\u2019s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated. The geographic coverage of the ASTER GDEM extends from 83\u00b0 North to 83\u00b0 South. Each tile is distributed in NetCDF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area. Each ASTGTM_NUMNC file indicates the number of scenes that were processed for each pixel and the source of the data.. The corresponding ASTGTM_NC data product contains a DEM file, which provides elevation information. While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications. Improvements/Changes from Previous Versions \u2022 Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3. \u2022 Separation of rivers from lakes in the water body processing. \u2022 Minimum water body detection size decreased from 1 km2 to 0.2 km2. ", "license": "not-provided" }, + { + "id": "ASTWBD.v001", + "title": "ASTER Global Water Bodies Database V001", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-01", + "end_date": "2013-11-30", + "bbox": "-180, -83, 180, 82", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734433-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734433-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/ASTWBD.v001", + "description": "The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information. The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces. To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required. The geographic coverage of the ASTWBD extends from 83\u00b0N to 83\u00b0S. Each tile is distributed in GeoTIFF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each data product is provided as a zipped file that contains an attribute file with the water body classification information and a DEM file, which provides elevation information in meters. ", + "license": "not-provided" + }, + { + "id": "ASTWBD_ATTNC.v001", + "title": "ASTER Global Water Bodies Database Attributes NetCDF V001", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-01", + "end_date": "2013-11-30", + "bbox": "-180, -83, 180, 82", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734760-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734760-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/ASTWBD_ATTNC.v001", + "description": "The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information. The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces. To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required. The geographic coverage of the ASTWBD extends from 83\u00b0N to 83\u00b0S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_ATTNC file contains an attribute file with the water body classification information. The corresponding ASTWBD_NC data product DEM file, which provides elevation information in meters.", + "license": "not-provided" + }, + { + "id": "ASTWBD_NC.v001", + "title": "ASTER Global Water Bodies Database NetCDF V001", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-01", + "end_date": "2013-11-30", + "bbox": "-180, -83, 180, 82", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734501-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1575734501-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/ASTWBD_NC.v001", + "description": "The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information. The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces. To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required. The geographic coverage of the ASTWBD extends from 83\u00b0N to 83\u00b0S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_NC data product DEM file, which provides elevation information in meters. The corresponding ASTWBD_ATTNC file contains an attribute file with the water body classification information.", + "license": "not-provided" + }, + { + "id": "AST_05.v003", + "title": "ASTER L2 Surface Emissivity V003", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-04", + "end_date": "", + "bbox": "-180, -83, 180, 83", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1299783607-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1299783607-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_05.v003", + "description": "The ASTER L2 Surface Emissivity is an on-demand product ((https://lpdaac.usgs.gov/documents/996/ASTER_Earthdata_Search_Order_Instructions.pdf)) generated using the five thermal infrared (TIR) bands (acquired either during the day or night time) between 8 and 12 \u00b5m spectral range. It contains surface emissivity over the land at 90 meters spatial resolution. Estimates of surface emissivity were thus far only derived using surrogates such as land-cover type or vegetation index. The Temperature/Emissivity Separation (TES) algorithm is used to derive both E (emissivity) and T (surface temperature). The main goals of the TES algorithm include: recovering accurate and precise emissivities for mineral substrates, and estimating accurate and precise surface temperatures especially over vegetation, water and snow.The TES algorithm is executed in the ASTER processing chain following generation of ASTER Level-2 Surface Radiance (TIR). The land-leaving radiance and down-welling irradiance vectors for each pixel are taken in account. Emissivity is estimated using the Normalized Emissivity Method (NEM), and is iteratively compensated for reflected sunlight. The emissivity spectrum is normalized using the average emissivity of each pixel. The minimum-maximum difference (MMD) of the normalized spectrum is calculated and estimates of the minimum emissivity derived through regression analysis. These estimates are used to scale the normalized emissivity and compensate for reflected skylight with the derived refinement of emissivity. ASTER Level 2 data requests for observations that occurred after May 27, 2020 will resort back to using the climatology ozone input. Additional information can be found in the ASTER L2 Processing Options Update (https://lpdaac.usgs.gov/news/aster-l2-processing-options-update/). V003 data set release date: 2002-05-03 Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. As of December 15, 2021, the LP DAAC has implemented changes to ASTER PGE Version 3.4, which will affect all ASTER Level 2 on-demand products. Changes include: \u2022\tAura Ozone Monitoring Instrument (OMI) has been added as one of the ancillary ozone inputs for any observations made after May 27, 2020. The sequence of fallbacks for ozone will remain the same. \u2022\tToolkit has been updated from Version 5.2.17 to 5.2.20. Users may notice minor differences between the two versions. Differences may include minuscule changes in digital numbers around the peripheral of the granule and boundaries of a cloud for Surface Reflectance and Surface Radiance (AST07 and AST09) QA Data Plane depending on the Operating System and libraries being used by the user to process the data. Additionally, Climatology, which is one of the inputs for Ozone and Moisture, Temperature and Pressures (MTP) will be removed from the Earthdata Order Form. It has been observed that PGEs generated with Climatology as an input yield noticeable differences statistically during image and spectral analysis. Climatology will continue to be used as the final default if neither of the first two selectable options are available for Ozone and MTP. Users can check the OPERATIONALQUALITYFLAGEXPLANATION field in the metadata or the output file for atmospheric parameters that were applied. Aura OMI data are no longer available as an input for ASTER Level 2 data acquisitions after October 6, 2023. For data acquired after this date, ozone inputs will automatically fall back to climatology ozone inputs when Aura OMI is selected as an input. For more details, please refer to the Discontinuation of Aura OMI as an Input news announcement (https://lpdaac.usgs.gov/news/discontinuation-of-aura-omi-as-an-ancillary-ozone-input-for-aster-products/). ", + "license": "not-provided" + }, + { + "id": "AST_09XT.v003", + "title": "ASTER L2 Surface Radiance - VNIR and Crosstalk Corrected SWIR V003", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-06", + "end_date": "", + "bbox": "-180, -83, 180, 83", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1299783631-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1299783631-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_09XT.v003", + "description": "The ASTER Surface Radiance VNIR and Crosstalk Corrected SWIR (AST_09XT) is a multi-file product (https://lpdaac.usgs.gov/documents/996/ASTER_Earthdata_Search_Order_Instructions.pdf) that contains atmospherically corrected data for both the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) sensors. The crosstalk phenomenon was discovered during the nascent stage of the Terra Mission. It is whereby the incident light with band 4 caused multiple reflections for the SWIR bands, which resulted in blurred images. This has been corrected with the ASTER L2 Surface Radiance VNIR and Crosstalk Corrected SWIR data product. Each product delivery includes two Hierarchical Data Format - Earth Observing System (HDF-EOS) files: one for the VNIR, and the other for the SWIR. Both the VNIR and the SWIR data are atmospherically corrected using the corresponding bands from an (ASTER Level 1B) (https://doi.org/10.5067/ASTER/AST_L1B.003) image. ASTER Level 2 data requests for observations that occurred after May 27, 2020 will resort back to using the climatology ozone input. Additional information can be found in the ASTER L2 Processing Options Update (https://lpdaac.usgs.gov/news/aster-l2-processing-options-update/). Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. As of December 15, 2021, the LP DAAC has implemented changes to ASTER PGE Version 3.4, which will affect all ASTER Level 2 on-demand products. Changes include: \u2022\tAura Ozone Monitoring Instrument (OMI) has been added as one of the ancillary ozone inputs for any observations made after May 27, 2020. The sequence of fallbacks for ozone will remain the same. \u2022\tToolkit has been updated from Version 5.2.17 to 5.2.20. Users may notice minor differences between the two versions. Differences may include minuscule changes in digital numbers around the peripheral of the granule and boundaries of a cloud for Surface Reflectance and Surface Radiance (AST07 and AST09) QA Data Plane depending on the Operating System and libraries being used by the user to process the data. Additionally, Climatology, which is one of the inputs for Ozone and Moisture, Temperature and Pressures (MTP) will be removed from the Earthdata Order Form. It has been observed that PGEs generated with Climatology as an input yield noticeable differences statistically during image and spectral analysis. Climatology will continue to be used as the final default if neither of the first two selectable options are available for Ozone and MTP. Users can check the OPERATIONALQUALITYFLAGEXPLANATION field in the metadata or the output file for atmospheric parameters that were applied. Aura OMI data are no longer available as an input for ASTER Level 2 data acquisitions after October 6, 2023. For data acquired after this date, ozone inputs will automatically fall back to climatology ozone inputs when Aura OMI is selected as an input. For more details, please refer to the Discontinuation of Aura OMI as an Input news announcement (https://lpdaac.usgs.gov/news/discontinuation-of-aura-omi-as-an-ancillary-ozone-input-for-aster-products/).", + "license": "not-provided" + }, + { + "id": "AST_L1A.v003", + "title": "ASTER L1A Reconstructed Unprocessed Instrument Data V003", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-04", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C14758250-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C14758250-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_L1A.v003", + "description": "The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1A (AST_L1A) contains reconstructed, instrument digital numbers (DNs) derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). Additionally, geometric correction coefficients and radiometric calibration coefficients are calculated and appended to the metadata, but not applied. The spatial resolution is 15 m (VNIR), 30 m (SWIR), and 90 m (TIR) with a temporal coverage of 2000 to present. Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. ", + "license": "not-provided" + }, + { + "id": "AST_L1AE.v003", + "title": "ASTER Expedited L1A Reconstructed Unprocessed Instrument Data V003", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-04", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179460405-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179460405-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_L1AE.v003", + "description": "The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1A Reconstructed Unprocessed Instrument Data (AST_L1AE) global product contains reconstructed, unprocessed instrument digital data derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). This data product is similar to the (AST_L1A) (http://doi.org/10.5067/ASTER/AST_L1A.003) with a few notable exceptions. These include: * The AST_L1AE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments. * The registration quality of the AST_L1AE is likely to be lower than the AST_L1A, and may vary from scene to scene. * The AST_L1AE data product does not contain the VNIR 3B (aft-viewing) Band. * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor. * The AST_L1AE data product is only available for download 30 days after acquisition. It is then removed and reprocessed into an AST_L1A product.", + "license": "not-provided" + }, + { + "id": "AST_L1B.v003", + "title": "ASTER L1B Registered Radiance at the Sensor V003", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-04", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C190733714-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C190733714-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_L1B.v003", + "description": "The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level-1B (AST_L1B) Registered Radiance at the Sensor data product is radiometrically calibrated and geometrically co-registered. Application of intra-telescope and inter-telescope registration corrections for all bands are relative to the reference band for each telescope: Visible and Near Infrared (VNIR) Band 2, Shortwave Infrared (SWIR) Band 6, and Thermal Infrared (TIR) Band 11. The spatial resolution is 15 m (VNIR), 30 m (SWIR), and 90 m (TIR) with a temporal coverage of 2000 to present. Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. ", + "license": "not-provided" + }, + { + "id": "AST_L1BE.v003", + "title": "ASTER Expedited L1B Registered Radiance at the Sensor V003", + "catalog": "LPDAAC_ECS", + "state_date": "2000-03-04", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179460406-LPDAAC_ECS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179460406-LPDAAC_ECS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LPDAAC_ECS/collections/AST_L1BE.v003", + "description": "The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1B Registered Radiance at the Sensor global data product is radiometrically calibrated and geometrically co-registered. Application of intra-telescope and inter-telescope registration corrections for all bands are relative to the reference band for each telescope: Visible and Near Infrared (VNIR) Band 2, Shortwave Infrared (SWIR) Band 6, and Thermal Infrared (TIR) Band 11. The Expedited Level 1B data product is similar to the (AST_L1B) (https://doi.org/10.5067/ASTER/AST_L1B.003) with a few notable exceptions. These include: * The AST_L1BE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments. * The registration quality of the AST_L1BE is likely to be lower than the AST_L1B, and may vary from scene to scene. * The AST_L1BE dataset does not contain the VNIR 3B (aft-viewing) Band. * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor.", + "license": "not-provided" + }, { "id": "ATL02.v006", "title": "ATLAS/ICESat-2 L1B Converted Telemetry Data V006", @@ -1923,136 +2274,6 @@ "description": "This data set comprises GPS ground data of a sample rate of 10 sec, generated by decoding and sampling GPS high rate ground data. This raw data passed no quality control. The data are given in the Rinex 2.1 format.", "license": "not-provided" }, - { - "id": "CIESIN_SEDAC_EPI_2008.v2008.00", - "title": "2008 Environmental Performance Index (EPI)", - "catalog": "SEDAC", - "state_date": "1994-01-01", - "end_date": "2007-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179001707-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179001707-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_EPI_2008.v2008.00", - "description": "The 2008 Environmental Performance Index (EPI) centers on two broad environmental protection objectives: (1) reducing environmental stresses on human health, and (2) promoting ecosystem vitality and sound natural resource management. Derived from a careful review of the environmental literature, these twin goals mirror the priorities expressed by policymakers. Environmental health and ecosystem vitality are gauged using 25 indicators tracked in six well-established policy categories: Environmental Health (Environmental Burden of Disease, Water, and Air Pollution), Air Pollution (effects on ecosystems), Water (effects on ecosystems), Biodiversity and Habitat, Productive Natural Resources (Forestry, Fisheries, and Agriculture), and Climate Change. The 2008 EPI utilizes a proximity-to-target methodology in which performance on each indicator is rated on a 0 to 100 scale (100 represents \u00ef\u00bf\u00bdat target\u00ef\u00bf\u00bd). By identifying specific targets and measuring how close each country comes to them, the EPI provides a foundation for policy analysis and a context for evaluating performance. Issue-by-issue and aggregate rankings facilitate cross-country comparisons both globally and within relevant peer groups. The 2008 EPI is the result of collaboration among the Yale Center for Environmental Law and Policy (YCELP), Columbia University Center for International Earth Science Information Network (CIESIN), World Economic Forum (WEF), and the Joint Research Centre (JRC), European Commission.", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_EPI_2010.v2010.00", - "title": "2010 Environmental Performance Index (EPI)", - "catalog": "SEDAC", - "state_date": "1994-01-01", - "end_date": "2009-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179002147-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179002147-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_EPI_2010.v2010.00", - "description": "The 2010 Environmental Performance Index (EPI) ranks 163 countries on environmental performance based on twenty-five indicators grouped within ten core policy categories addressing environmental health, air quality, water resource management, biodiversity and habitat, forestry, fisheries, agriculture, and climate change in the context of two broad objectives: environmental health and ecosystem vitality. The EPI\u00ef\u00bf\u00bds proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. It was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 28, 2010. The 2010 EPI is the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN).", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_EPI_2012.v2012.00", - "title": "2012 Environmental Performance Index and Pilot Trend Environmental Performance Index", - "catalog": "SEDAC", - "state_date": "2000-01-01", - "end_date": "2010-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000000-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000000-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_EPI_2012.v2012.00", - "description": "The 2012 Environmental Performance Index (EPI) ranks 132 countries on 22 performance indicators in the following 10 policy categories: environmental burden of disease, water (effects on human health), air pollution (effects on human health), air pollution (ecosystem effects), water resources (ecosystem effects), biodiversity and habitat, forestry, fisheries, agriculture and climate change. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. Each indicator has an associated environmental public health or ecosystem sustainability target. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The Pilot Trend Environmental Performance Index (Trend EPI) ranks countries on the change in their environmental performance over the last decade. As a complement to the EPI, the Trend EPI shows who is improving and who is declining over time. The 2012 EPI and Pilot Trend EPI were formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 27, 2012. These are the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN). The Interactive Website for the 2012 EPI is at http://epi.yale.edu/.", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_EPI_2014.v2014.00", - "title": "2014 Environmental Performance Index (EPI)", - "catalog": "SEDAC", - "state_date": "2002-01-01", - "end_date": "2014-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000541-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000541-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_EPI_2014.v2014.00", - "description": "The 2014 Environmental Performance Index (EPI) ranks 178 countries on 20 performance indicators in the following 9 policy categories: health impacts, air quality, water and sanitation, water resources, agriculture, forests, fisheries, biodiversity and habitat, and climate and energy. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2014 EPI and component scores, backcast EPI scores for 2002-2012, and time-series source data. The 2014 EPI was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 25, 2014. These are the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN). The Interactive Website for the 2014 EPI is at http://epi.yale.edu/.", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_EPI_2016.v2016.00", - "title": "2016 Environmental Performance Index (EPI)", - "catalog": "SEDAC", - "state_date": "1950-01-01", - "end_date": "2016-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1419908204-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1419908204-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_EPI_2016.v2016.00", - "description": "The 2016 Environmental Performance Index (EPI) ranks 180 countries on 20 performance indicators in the following 9 policy categories: health impacts, air quality, water and sanitation, water resources, agriculture, forests, fisheries, biodiversity and habitat, and climate and energy. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2016 EPI and component scores, backcast EPI scores for 1950-2016, and time-series source data. The 2016 EPI was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 23, 2016. These are the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and Yale Data-Driven Environmental Solutions Group, Yale University, Columbia University Center for International Earth Science Information Network (CIESIN), and the World Economic Forum (WEF). The Interactive Website for the 2016 EPI is at https://epi.yale.edu.", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_ESI_2000.v2000.00", - "title": "2000 Pilot Environmental Sustainability Index (ESI)", - "catalog": "SEDAC", - "state_date": "1978-01-01", - "end_date": "1999-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179001887-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179001887-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_ESI_2000.v2000.00", - "description": "The 2000 Pilot Environmental Sustainability Index (ESI) is an exploratory effort to construct an index that measures the ability of a nation's economy to achieve sustainable development, with the long term goal of finding a single indicator for environmental sustainability analagous to that of the Gross Domestic Product (GDP). The index covering 56 countries is a composite measure of the current status of a nation's environmental systems, pressures on those systems, human vulnerability to environmental change, national capacity to respond, and contributions to global environmental stewardship. The index was unveiled at the World Economic Forum's annual meeting, January 2000, Davos, Switzerland. The 2000 Pilot ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN).", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_ESI_2001.v2001.00", - "title": "2001 Environmental Sustainability Index (ESI)", - "catalog": "SEDAC", - "state_date": "1980-01-01", - "end_date": "2000-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000220-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1000000220-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_ESI_2001.v2001.00", - "description": "The 2001 Environmental Sustainability Index (ESI) utilizes a refined methodology based on the 2000 Pilot ESI effort, to construct an index covering 122 countries that measures the overall progress towards environmental sustainability. The index is a composite measure of the current status of a nation's environmental systems, pressures on those systems, human vulnerability to environmental change, national capacity to respond, and contributions to global environmental stewardship. The refinements included the addition and deletion of indicators, filling gaps in data coverage, new data sets, and the modification of the aggregation scheme. The index was unveiled at the World Economic Forum's annual meeting, January 2001, Davos, Switzerland. The 2001 ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN).", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_ESI_2002.v2002.00", - "title": "2002 Environmental Sustainability Index (ESI)", - "catalog": "SEDAC", - "state_date": "1980-01-01", - "end_date": "2000-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179001967-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179001967-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_ESI_2002.v2002.00", - "description": "The 2002 Environmental Sustainability Index (ESI) measures overall progress toward environmental sustainability for 142 countries based on environmental systems, stresses, human vulnerability, social and institutional capacity and global stewardship. The addition of a climate change indicator, reduction in number of capacity indicators, and an improved imputation methodology contributed to an improvement from the 2001 ESI. The index was unveiled at the World Economic Forum's annual meeting, January 2002, New York. The 2002 ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN).", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_ESI_2005.v2005.00", - "title": "2005 Environmental Sustainability Index (ESI)", - "catalog": "SEDAC", - "state_date": "1980-01-01", - "end_date": "2000-12-31", - "bbox": "-180, -55, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C179001889-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C179001889-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_ESI_2005.v2005.00", - "description": "The 2005 Environmental Sustainability Index (ESI) is a measure of overall progress towards environmental sustainability, developed for 146 countries. The index provides a composite profile of national environmental stewardship based on a compilation of 21 indicators derived from 76 underlying data sets. The 2005 version of the ESI represents a significant update and improvement on earlier versions; the country ESI scores or rankings should not be compared to earlier versions because of changes to the methodology and underlying data. The index was unveiled at the World Economic Forum's annual meeting, January 2005, Davos, Switzerland. The 2005 ESI is a joint product of the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN), in collaboration with the World Economic Forum (WEF) and the Joint Research Centre (JRC), European Commission.", - "license": "not-provided" - }, - { - "id": "CIESIN_SEDAC_USPAT_USUEXT2015.v1.00", - "title": "2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods", - "catalog": "SEDAC", - "state_date": "2015-01-01", - "end_date": "2015-12-31", - "bbox": "-180, -56, 180, 84", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1648035940-SEDAC.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1648035940-SEDAC.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SEDAC/collections/CIESIN_SEDAC_USPAT_USUEXT2015.v1.00", - "description": "The 2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods data set models urban settlements in the Continental United States (CONUS) as of 2015. When applied to the combination of daytime spectral and nighttime lights satellite data, the machine learning methods achieved high accuracy at an intermediate-resolution of 500 meters at large spatial scales. The input data for these models were two types of satellite imagery: Visible Infrared Imaging Radiometer Suite (VIIRS) Nighttime Light (NTL) data from the Day/Night Band (DNB), and Moderate Resolution Imaging Spectroradiometer (MODIS) corrected daytime Normalized Difference Vegetation Index (NDVI). Although several machine learning methods were evaluated, including Random Forest (RF), Gradient Boosting Machine (GBM), Neural Network (NN), and the Ensemble of RF, GBM, and NN (ESB), the highest accuracy results were achieved with NN, and those results were used to delineate the urban extents in this data set.", - "license": "not-provided" - }, { "id": "CLDMSK_L2_VIIRS_NOAA20_NRT.v1", "title": "VIIRS/NOAA-20 Cloud Mask L2 6-Min Swath 750m (NRT)", @@ -2235,6 +2456,32 @@ "description": "The aerial photography inventoried by the Pilot Land Data System (PLDS) at NASA AMES Research Center has been transferred to the USGS EROS Data Center. The photos were obtained from cameras mounted on high and medium altitude aircraft based at the NASA Ames Research Center. Several cameras with varying focal lengths, lenses and film formats are used, but the Wild RC-10 camera with a focal length of 152 millimeters and a 9 by 9 inch film format is most common. The positive transparencies are typically used for ancillary ground checks in conjunctions with digital processing for the same sites. The aircraft flights, specifically requested by scientists performing approved research, often simultaneously collect data using other sensors on board (e.g. Thematic Mapper Simulators (TMS) and Thermal Infrared Multispectral Scanners). High altitude color infrared photography is used regularly by government agencies for such applications as crop yield forecasting, timber inventory and defoliation assessment, water resource management, land use surveys, water pollution monitoring, and natural disaster assessment. To order, specify the latitude and longitude of interest. You will then be given a list of photos available for that location. In some cases, \"flight books\" are available at EDC that describe the nature of the mission during which the photos were taken and other attribute information. The customer service personnel have access to these books for those photo sets for which the books exist.", "license": "not-provided" }, + { + "id": "EN1_MDSI_MER_FRS_1P.v4", + "title": "Full Resolution Full Swath Geolocated and Calibrated TOA Radiance", + "catalog": "LAADS", + "state_date": "2002-05-17", + "end_date": "2012-04-08", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2151211533-LAADS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2151211533-LAADS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/EN1_MDSI_MER_FRS_1P.v4", + "description": "The Medium Resolution Imaging Spectrometer (MERIS) is one of 10 sensors deployed in March of 2002 on board the polar-orbiting Envisat-1 environmental research satellite by the European Space Agency (ESA). The MERIS instrument is a moderate-resolution wide field-of-view push-broom imaging spectroradiometer capable of sensing in the 390 nm to 1040 nm spectral range. Being a programmable instrument, it had the unique capability of selectively adjusting the width and location of its 15 bands through ground command. The instrument has a 68.5-degree field of view and a swath width of 1150 meters, providing a global coverage every 3 days at 300 m resolution. Communication with the Envisat-1 satellite was lost suddenly on the 8th of April, 2012, just weeks after celebrating its 10th year in orbit. All attempts to re-establish contact were unsuccessful, and the end of the mission was declared on May 9th, 2012. The 4th reprocessing cycle, in 2020, has produced both the full-resolution and reduced-resolution L1 and L2 MERIS products. EN1_MDSI_MER_FRS_1P is the short-name for the MERIS Level-1 full resolution, full swath, geolocated and calibrated top-of-atmosphere (TOA) radiance product. This product contains the TOA upwelling spectral radiance measurements. The in-band reference irradiances for the 15 MERIS bands are computed by averaging the in-band solar irradiance for each pixel. Each pixel\u2019s in-band solar irradiance is computed by integrating the reference solar spectrum with the band-pass of each pixel. The Level-1 product contains 22 data files: 15 files contain radiances for each band (one band per file) along with associated error estimates, and 7 annotation data files. It also includes a Manifest file that provides metadata information describing the product.", + "license": "not-provided" + }, + { + "id": "EN1_MDSI_MER_FRS_2P.v4", + "title": "Full Resolution Full Swath Geophysical Product for Ocean, Land and Atmosphere", + "catalog": "LAADS", + "state_date": "2003-01-01", + "end_date": "2012-04-08", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2151219110-LAADS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2151219110-LAADS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/EN1_MDSI_MER_FRS_2P.v4", + "description": "The Medium Resolution Imaging Spectrometer (MERIS) is one of 10 sensors deployed in March of 2002 on board the polar-orbiting Envisat-1 environmental research satellite by the European Space Agency (ESA). The MERIS instrument is a moderate-resolution wide field-of-view push-broom imaging spectroradiometer capable of sensing in the 390 nm to 1040 nm spectral range. Being a programmable instrument, it had the unique capability of selectively adjusting the width and location of its 15 bands through ground command. The instrument has a 68.5-degree field of view and a swath width of 1150 meters, providing a global coverage every 3 days at 300 m resolution. Communication with the Envisat-1 satellite was lost suddenly on the 8th of April, 2012, just weeks after celebrating its 10th year in orbit. All attempts to re-establish contact were unsuccessful, and the end of the mission was declared on May 9th, 2012. The 4th reprocessing cycle, in 2020, has produced both the full-resolution and reduced-resolution L1 and L2 MERIS products. EN1_MDSI_MER_FRS_2P is the short-name for the MERIS Level-2 full resolution, geophysical product for ocean, land, and atmosphere. This Level-2 product comes in a netCDF4 package that contains both instrument and science measurements, and a Manifest file that provides metadata information describing the product. Each Level-2 product contains 64 measurement files that break down thus: 13 files containing water-leaving reflectance, 13 files containing land surface reflectance and 13 files containing the TOA reflectance (for all bands except those dedicated to measuring atmospheric gas - M11 and M15), and several files containing additional measurements on ocean, land, and atmosphere parameters.", + "license": "not-provided" + }, { "id": "EO:EUM:CM:METOP:ASCSZFR02.v2014-10-07", "title": "ASCAT L1 SZF Climate Data Record Release 2 - Metop", @@ -2937,6 +3184,32 @@ "description": "The Level 2A aerosol/cloud optical products of the Aeolus mission include geo-located consolidated backscatter and extinction profiles, backscatter-to-extinction coefficient, LIDAR ratio, scene classification, heterogeneity index and attenuated backscatter signals. Resolution - Horizontal resolution of L2A optical properties at observation scale (~87 km); Exceptions are group properties (horizontal accumulation of measurements from ~3 km to ~87 km) and attenuated backscatters (~3 km); Note: the resolution of \"groups\" in the L2A can only go down to 5 measurements at the moment, i.e. ~15 km horizontal resolution. This could be configured to go to 1 measurement - Vertical resolution 250-2000 m (Defined by Range Bin Settings https://earth.esa.int/eogateway/instruments/aladin/overview-of-the-main-wind-rbs-changes).", "license": "not-provided" }, + { + "id": "M1_AVH09C1.v6", + "title": "METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg CMG", + "catalog": "LAADS", + "state_date": "2013-01-16", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2187507677-LAADS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2187507677-LAADS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/M1_AVH09C1.v6", + "description": "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 Surface Reflectance Daily L3 Global 0.05 Deg CMG, short-name M1_ AVH09C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The M1_ AVH09C1 consist of BRDF-corrected surface reflectance for bands 1, 2, and 3, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), and thermal data (thermal bands 3, 4, and 5). The AVH09C1 product is available in HDF4 file format. ", + "license": "not-provided" + }, + { + "id": "M1_AVH13C1.v6", + "title": "METOP-B AVHRR Atmospherically Corrected Normalized Difference Vegetation Index Daily L3 Global 0.05 Deg. CMG", + "catalog": "LAADS", + "state_date": "2013-01-16", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2751635237-LAADS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2751635237-LAADS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/M1_AVH13C1.v6", + "description": "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. ", + "license": "not-provided" + }, { "id": "MCD14DL_C5_NRT.v005", "title": "MODIS/Aqua+Terra Thermal Anomalies/Fire locations 1km FIRMS V005 NRT", @@ -4198,6 +4471,19 @@ "description": "The AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H08 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-8 platform served in the operational Himawari position (near 140.7\u00b0E) between October 2014 and 13 December 2022. Himawari-9 replaced Himawari-8 and is currently operational. The Himawari-8/AHI collection record spans from January 2019 through 12th December 2022. The final 19 days of 2022 (December 13 through 31) are served by L2 products derived from the Himawari-9/AHI instrument. The XAERDT_L2_AHI_H08 product is a part of the Geostationary Earth Orbit (GEO)\u2013Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA\u2019s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H08 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H08 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/", "license": "not-provided" }, + { + "id": "XAERDT_L2_AHI_H09.v1", + "title": "AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km", + "catalog": "LAADS", + "state_date": "2022-12-13", + "end_date": "2022-12-31", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2859261579-LAADS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2859261579-LAADS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/XAERDT_L2_AHI_H09.v1", + "description": "The AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H09 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-9 platform currently serves in the operational Himawari position (near 140.7\u00b0E) since it was launched November 2, 2016, and replaces Himawari-8. The Himawari-9/AHI collection record spans from 13th December 2022 through 31st December 2022. The XAERDT_L2_AHI_H09 product is a part of the Geostationary Earth Orbit (GEO)\u2013Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA\u2019s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H09 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H09 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/", + "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", @@ -4510,6 +4796,32 @@ "description": "Seawater Surface Temperature Data Collected between the years 1982-1989 and 1993 off the dock at the Darling Marine Center, Walpole, Maine", "license": "not-provided" }, + { + "id": "eMASL1B.v1", + "title": "Enhanced MODIS Airborne Simulator (eMAS) Calibrated, Geolocated Radiances L1B 50m Data", + "catalog": "LAADS", + "state_date": "2013-08-01", + "end_date": "2019-08-22", + "bbox": "-180, -35, 180, 80", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2801308027-LAADS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2801308027-LAADS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/eMASL1B.v1", + "description": "The Enhanced Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (eMAS)instrument is maintained and operated by the Airborne Sensor Facility at NASA Ames Research Center in Mountain View, California, under the oversight of the EOS Project Science Office at NASA Goddard. Prior to 1995, the MAS was deployed on the NASA's ER-2 and C-130 aircraft platforms using a 12-channel, 8-bit data system that somewhat constrained the full benefit of having a 50-channel scanning spectrometer. Beginning in January 1995, a 50-channel, 16-bit digitizer was used on the ER-2 platform, which greatly enhanced the capability of MAS to simulate MODIS data over a wide range of environmental conditions. Recently, it has undergone extensive upgrades to the optics and other components. New detectors have been installed and the spectral bands have been streamlined. The eMAS instrument is now a 38-channel instrument, sensing in the range from 0.445 to 13.844 um. For more information and for a list of MAS campaign flights visit ladsweb at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/mas/ or, visit the eMAS Homepage at: https://asapdata.arc.nasa.gov/emas/", + "license": "not-provided" + }, + { + "id": "eMASL2CLD.v1", + "title": "Enhanced MODIS Airborne Simulator (eMAS) L2 Cloud Data", + "catalog": "LAADS", + "state_date": "2013-08-01", + "end_date": "2016-09-28", + "bbox": "-180, -35, 180, 80", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2801723593-LAADS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2801723593-LAADS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LAADS/collections/eMASL2CLD.v1", + "description": "The Enhanced Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (eMAS)instrument is maintained and operated by the Airborne Sensor Facility at NASA Ames Research Center in Mountain View, California, under the oversight of the EOS Project Science Office at NASA Goddard. The eMAS instrument is now a 38-channel instrument, sensing in the range from 0.445 to 13.844 um. The Enhanced MODIS Airborne Simulator (eMAS) L2 Cloud Data product (eMASL2CLD) consists of cloud optical and physical parameters. These parameters are derived using remotely sensed infrared and near infrared solar reflected radiances. Multispectral images of the reflectance and brightness temperature at 10 wavelengths between 0.66 and 13.98nm were used to derive the probability of clear sky (or cloud), cloud thermodynamic phase, and the optical thickness and effective radius of liquid water and ice clouds. The eMASL2CLD product files are stored in Hierarchical Data Format (HDF-EOS). All gridded cloud parameters are stored as Scientific Data Sets (SDS) within the file. For more information and for a list of MAS campaign flights visit ladsweb at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/mas/ or, visit the eMAS Homepage at: https://asapdata.arc.nasa.gov/emas/", + "license": "not-provided" + }, { "id": "ef6a9266-a210-4431-a4af-06cec4274726", "title": "Cartosat-1 (IRS-P5) - Panchromatic Images (PAN) - Europe, Monographic", @@ -4562,6 +4874,45 @@ "description": "30 minute rainfall data for the Konza Prairie", "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.", + "license": "not-provided" + }, { "id": "gov.noaa.nodc:GHRSST-AVHRR_SST_METOP_A_GLB-OSISAF-L3C.v1", "title": "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)", diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv index 3bf66f524..ec4ef8036 100644 --- a/nasa_cmr_catalog.tsv +++ b/nasa_cmr_catalog.tsv @@ -7,6 +7,13 @@ 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 @@ -26,6 +33,16 @@ ABLVIS1B.v1 ABoVE LVIS L1B Geolocated Return Energy Waveforms V001 NSIDC_ECS 201 ABLVIS2.v1 ABoVE LVIS L2 Geolocated Surface Elevation Product V001 NSIDC_ECS 2017-06-29 2017-07-17 -158, 48, -104, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1513105984-NSIDC_ECS.json This data set contains surface elevation 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 ABOLVIS1A.v1 ABoVE LVIS L1A Geotagged Images V001 NSIDC_ECS 2017-06-29 2017-07-17 -158, 48, -104, 72 https://cmr.earthdata.nasa.gov/search/concepts/C1673546369-NSIDC_ECS.json This data set contains geotagged images collected over Alaska and Western Canada. The images were taken by the NASA Digital Mapping Camera, paired with the 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 ABoVE_Concise_Experiment_Plan_1617.v1.1 A Concise Experiment Plan for the Arctic-Boreal Vulnerability Experiment ORNL_CLOUD 2014-01-01 2021-12-31 -176.12, 39.42, -66.92, 81.61 https://cmr.earthdata.nasa.gov/search/concepts/C2162145735-ORNL_CLOUD.json This document presents the Concise Experiment Plan for NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) to serve as a guide to the Program as it identifies the research to be conducted under this study. Research for ABoVE will link field-based, process-level studies with geospatial data products derived from airborne and satellite remote sensing, providing a foundation for improving the analysis and modeling capabilities needed to understand and predict ecosystem responses and societal implications. The ABoVE Concise Experiment Plan (ACEP) outlines the conceptual basis for the Field Campaign and expresses the compelling rationale explaining the scientific and societal importance of the study. It presents both the science questions driving ABoVE research as well as the top-level requirements for a study design to address them. not-provided +ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data.v1 ACCLIP WB-57 Aerosol and Cloud Remotely Sensed Data LARC_ASDC 2022-07-14 2022-09-14 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2655162569-LARC_ASDC.json ACCLIP_AerosolCloud_AircraftRemoteSensing_WB57_Data is the cloud and aerosol remote sensing data from the Roscoe lidar collected during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +ACCLIP_Aerosol_AircraftInSitu_WB57_Data.v1 ACCLIP WB-57 Aircraft In-Situ Aerosol Data LARC_ASDC 2022-07-14 2022-09-14 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2609962127-LARC_ASDC.json ACCLIP_Aerosol_AircraftInSitu_WB57_Data is the in-situ aerosol data collected during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Particle Analysis by Laser Mass Spectrometry - Next Generation (PALMS-NG), Single Particle Soot Photometer (SP2), Nucleation-Mode Aerosol Size Spectrometer (N-MASS), Printed Optical Particle Spectrometer (POPS), and the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +ACCLIP_AircraftInSitu_WB57_Water_Data.v1 ACCLIP WB-57 Aircraft Water In-situ Data LARC_ASDC 2022-07-14 2022-09-14 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2609920136-LARC_ASDC.json ACCLIP_AircraftInSitu_WB57_Water_Data is the in-situ water data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Chicago Water Isotope Spectrometer (ChiWIS) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +ACCLIP_Cloud_AircraftInSitu_WB57_Data.v1 ACCLIP WB-57 Aircraft In-situ Cloud Data LARC_ASDC 2022-07-14 2022-09-15 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2609947245-LARC_ASDC.json ACCLIP_Cloud_AircraftInSitu_WB57_Data is the in-situ cloud data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Cloud, Aerosol, and Precipitation Spectrometer (CAPS) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +ACCLIP_Merge_WB57-Aircraft_Data.v1 ACCLIP WB-57 Aircraft Merge Data LARC_ASDC 2022-07-16 2022-09-14 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2609887645-LARC_ASDC.json ACCLIP_Merge_WB57-Aircraft_Data is the pre-generated merge files created from a variety of in-situ instrumentation collecting measurements onboard the WB-57 aircraft during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +ACCLIP_MetNav_AircraftInSitu_WB57_Data.v1 ACCLIP WB-57 Meteorological and Navigational Data LARC_ASDC 2022-07-14 2022-09-14 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2566338281-LARC_ASDC.json ACCLIP_MetNav_AircraftInSitu_WB57_Data is the in-situ meteorology and navigational data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Meteorological Measurement System (MMS) and Diode Laser Hygrometer (DLH) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +ACCLIP_Model_WB57_Data.v1 ACCLIP WB-57 Aircraft Model Data LARC_ASDC 2022-07-14 2022-09-14 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2609869612-LARC_ASDC.json ACCLIP_Model_WB57_Data contains modeled meteorological, chemical, and aerosol data along the flight tracks of the WB-57 aircraft during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +ACCLIP_TraceGas_AircraftInSitu_WB57_Data.v1 ACCLIP WB-57 Aircraft In-situ Trace Gas Data LARC_ASDC 2022-07-14 2022-09-14 -180, 16.6, 180, 61.5 https://cmr.earthdata.nasa.gov/search/concepts/C2566342407-LARC_ASDC.json ACCLIP_TraceGas_AircraftInSitu_WB57_Data is the in-situ trace gas data collection during the Asian Summer Monsoon Chemical & Climate Impact Project (ACCLIP). Data from the Airborne Carbon Oxide Sulfide Spectrometer (ACOS), Carbon monOxide Measurement from Ames (COMA), Laser Induced Fluorescence - Nitrogen Oxide (LIF-NO), In Situ Airborne Formaldehyde (ISAF), Carbon Oxide Laser Detector 2 (COLD 2), and the NOAA UAS O3 Photometer (UASO3) is featured in this collection. Data collection for this product is complete. ACCLIP is an international, multi-organizational suborbital campaign that aims to study aerosols and chemical transport that is associated with the Asian Summer Monsoon (ASM) in the Western Pacific region from 15 July 2022 to 31 August 2022. The ASM is the largest meteorological pattern in the Northern Hemisphere (NH) during the summer and is associated with persistent convection and large anticyclonic flow patterns in the upper troposphere and lower stratosphere (UTLS). This leads to significant enhancements in the UTLS of trace species that originate from pollution or biomass burning. Convection connected to the ASM occurs over South, Southeast, and East Asia, a region with complex and rapidly changing emissions due to its high population density and economic growth. Pollution that reaches the UTLS from this region can have significant effects on the climate and chemistry of the atmosphere, making it important to have an accurate representation and understanding of ASM transport, chemical, and microphysical processes for chemistry-climate models to characterize these interactions and for predicting future impacts on climate. The ACCLIP campaign is conducted by the National Aeronautics and Space Administration (NASA) and the National Center for Atmospheric Research (NCAR) with the primary goal of investigating the impacts of Asian gas and aerosol emissions on global chemistry and climate. The NASA WB-57 and NCAR G-V aircraft are outfitted with state-of-the-art sensors to accomplish this. ACCLIP seeks to address four scientific objectives related to its main goal. The first is to investigate the transport pathways of ASM uplifted air from inside of the anticyclone to the global UTLS. Another objective is to sample the chemical content of air processed in the ASM in order to quantify the role of the ASM in transporting chemically active species and short-lived climate forcing agents to the UTLS to determine their impact on stratospheric ozone chemistry and global climate. Third, information is obtained on aerosol size, mass, and chemical composition that is necessary for determining the radiative effects of the ASM to constrain models of aerosol formation and for contrasting the organic-rich ASM UTLS aerosol population with that of the background aerosols. Last, ACCLIP seeks to measure the water vapor distribution associated with the monsoon dynamical structure to evaluate transport across the tropopause and determine the role of the ASM in water vapor transport in the stratosphere. not-provided +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 the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign. 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 @@ -93,9 +110,19 @@ AQUARIUS_L3_WIND_SPEED_CAP_7DAY_V5.v5.0 Aquarius CAP Level 3 Wind Speed Standard AQUARIUS_L3_WIND_SPEED_CAP_MONTHLY_V5.v5.0 Aquarius CAP Level 3 Wind Speed Standard Mapped Image Monthly Data V5.0 POCLOUD 2011-09-01 2015-06-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2491757162-POCLOUD.json Version 5.0 Aquarius CAP Level 3 products are the fourth release of the AQUARIUS/SAC-D mapped salinity and wind speed data based on the Combined Active Passive (CAP) algorithm. CAP Level 3 standard mapped image products contain gridded 1 degree spatial resolution salinity and wind speed data averaged over 7 day and monthly time scales. This particular dataset is the monthly wind speed V5.0 Aquarius CAP product. CAP is a P.I. produced dataset developed and provided by JPL. The CAP algorithm utilizes data from both the onboard radiometer and scatterometer to simultaneously retrieve salinity, wind speed and direction by minimizing the sum of squared differences between model and observations. The main improvements in CAP V5.0 relative to the previous version include: updates to the Geophysical Model Functions to 4th order harmonics with the inclusion of sea surface temperature (SST) and stability at air-sea interface effects; use of the Canadian Meteorological Center (CMC) SST product as the new source ancillary sea surface temperature data in place of NOAA OI SST. The Aquarius instrument is onboard the AQUARIUS/SAC-D satellite, a collaborative effort between NASA and the Argentinian Space Agency Comision Nacional de Actividades Espaciales (CONAE). The instrument consists of three radiometers in push broom alignment at incidence angles of 29, 38, and 46 degrees incidence angles relative to the shadow side of the orbit. Footprints for the beams are: 76 km (along-track) x 94 km (cross-track), 84 km x 120 km and 96km x 156 km, yielding a total cross-track swath of 370 km. The radiometers measure brightness temperature at 1.413 GHz in their respective horizontal and vertical polarizations (TH and TV). A scatterometer operating at 1.26 GHz measures ocean backscatter in each footprint that is used for surface roughness corrections in the estimation of salinity. The scatterometer has an approximate 390km swath. not-provided ASAC_2201_HCL_0.5.v1 0.5 hour 1 M HCl extraction data for the Windmill Islands marine sediments AU_AADC 1997-10-01 1999-03-31 110, -66, 110, -66 https://cmr.earthdata.nasa.gov/search/concepts/C1214305813-AU_AADC.json These results are for the 0.5 hour extraction of HCl. See also the metadata records for the 4 hour extraction of HCl, and the time trial data for 1 M HCl extractions. A regional survey of potential contaminants in marine or estuarine sediments is often one of the first steps in a post-disturbance environmental impact assessment. Of the many different chemical extraction or digestion procedures that have been proposed to quantify metal contamination, partial acid extractions are probably the best overall compromise between selectivity, sensitivity, precision, cost and expediency. The extent to which measured metal concentrations relate to the anthropogenic fraction that is bioavailable is contentious, but is one of the desired outcomes of an assessment or prediction of biological impact. As part of a regional survey of metal contamination associated with Australia's past waste management activities in Antarctica, we wanted to identify an acid type and extraction protocol that would allow a reasonable definition of the anthropogenic bioavailable fraction for a large number of samples. From a kinetic study of the 1 M HCl extraction of two certified Certified Reference Materials (MESS-2 and PACS-2) and two Antarctic marine sediments, we concluded that a 4 hour extraction time allows the equilibrium dissolution of relatively labile metal contaminants, but does not favour the extraction of natural geogenic metals. In a regional survey of 88 marine samples from the Casey Station area of East Antarctica, the 4 h extraction procedure correlated best with biological data, and most clearly identified those sediments thought to be contaminated by runoff from abandoned waste disposal sites. Most importantly the 4 hour extraction provided better definition of the low to moderately contaminated locations by picking up small differences in anthropogenic metal concentrations. For the purposes of inter-regional comparison, we recommend a 4 hour 1 M HCl acid extraction as a standard method for assessing metal contamination in Antarctica. The fields in this dataset are Location Site Replicate Antimony Arsenic Cadmium Chromium Copper Iron Lead Manganese Nickel Silver Tin Zinc not-provided ASAC_2357.v2 10 year trend of levels of organochlorine pollutants in Antarctic seabirds AU_AADC 2003-12-16 2004-01-18 77.59, -68.93, 77.99, -68.755 https://cmr.earthdata.nasa.gov/search/concepts/C1214305884-AU_AADC.json Metadata record for data from ASAC Project 2357 See the link below for public details on this project. ---- Public Summary from Project ---- Contaminants like PCBs and DDE have hardly been used Antarctica. Hence, this is an excellent place to monitor global background levels of these organochlorines. In this project concentrations in penguins and petrels will be compared to 10 years ago, which will show time trends of global background contamination levels. Data set description From several birds from Hop Island, Rauer Islands near Davis, samples were collected from preenoil (oil that birds excrete to preen their feathers. This preenoil was then analysed for organochlorine pollutants like polychlorinated biphenyls, (PCBs), hexachlorobenzene (HCB), DDE and dieldrin. The species under investigation were the Adelie penguin (Pygoscelis adeliae) and the Southern Fulmar (Fulmarus glacialoides). The samples were collected from adult breeding birds, and stored in -20 degrees C as soon as possible. The analysis was done with relatively standard but very optimised methods, using a gas-chromatograph and mass-selective detection. Data sheets: The data are available in excel-sheets, located at Alterra, The Netherlands (the affiliation of the PI Nico van den Brink.). Data are available on PCB153 (polychlorinated biphenyl congener numbered 153), hexachlorobenzene (HCB), DDE (a metabolite of the pesticide DDT), and dieldrin (an insecticide). The metadata are in 4 sheets (in meta data 2357.xls): 1. 'Concentrations fulmars' 2. 'Morphometric data fulmars' 3. 'Concentrations Adelies' 4. 'Morphometric data Adelies' The column headings are: 1. 'Concentrations fulmars' - Fulmar: bird number, corresponds with sheet 'morphometric data fulmars'. - PCB153: concentration of PCB-congener 153 (ng/g lipids) - HCB: concentration of hexachlorobenzene (ng/g lipids) - DDE: concentration of DDE (ng/g lipids) - Dieldrin: concentration of dieldrin (ng/g lipids) - Sample size weight of collected amount of preenoil 2. Morphometric data fulmars - Fulmar: bird number, corresponds with sheet 'Concentrations fulmars'. - Bill Length (mm): length of bill (tip to base) - Head Length (mm): length of head (tip of bill to back of head) - Tarsus (mm): length of tarsus - Wing Length (cm): length of right wing - Weight (kg): weight of bird (without bag) 3. 'Concentrations Adelies' Adelie: bird number, corresponds with sheet 'morphometric data Adelies'. - PCB153: concentration of PCB-congener 153 (ng/g lipids) - HCB: concentration of hexachlorobenzene (ng/g lipids) - DDE: concentration of DDE (ng/g lipids) - Dieldrin: concentration of dieldrin (ng/g lipids) - Sample size weight of collected amount of preenoil 4. 'Morphometric data Adelies' - Adelie: bird number, corresponds with sheet 'Concentrations Adelies'. - Bill (mm): length of bill (tip to base) - Head Length (mm): length of head (tip of bill to back of head) - Tarsus (mm): length of tarsus - Flipper Length (cm): length of right flipper (wing) - Weight (kg): weight of bird (without bag) In sheets on concentrations: less than d.l.: concentrations below detection limits. not-provided +AST14DEM.v003 ASTER Digital Elevation Model V003 LPDAAC_ECS 2000-03-06 -180, -83, 180, 83 https://cmr.earthdata.nasa.gov/search/concepts/C1299783579-LPDAAC_ECS.json The ASTER Digital Elevation Model (AST14DEM) product is generated (https://lpdaac.usgs.gov/documents/996/ASTER_Earthdata_Search_Order_Instructions.pdf) using bands 3N (nadir-viewing) and 3B (backward-viewing) of an (ASTER Level 1A) (https://doi.org/10.5067/ASTER/AST_L1A.003) image acquired by the Visible and Near Infrared (VNIR) sensor. The VNIR subsystem includes two independent telescope assemblies that facilitate the generation of stereoscopic data. The band 3 stereo pair is acquired in the spectral range of 0.78 and 0.86 microns with a base-to-height ratio of 0.6 and an intersection angle of 27.7 degrees. There is a time lag of approximately one minute between the acquisition of the nadir and backward images. For a better understanding, refer to this (diagram) (https://lpdaac.usgs.gov/documents/301/ASTER_Along_Track_Imaging_Geometry.png) depicting the along-track imaging geometry of the ASTER VNIR nadir and backward-viewing sensors. The accuracy of the new LP DAAC produced DEMs will meet or exceed accuracy specifications set for the ASTER relative DEMs by the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/81/AST14_ATBD.pdf). Users likely will find that the DEMs produced by the new LP DAAC system have accuracies approaching those specified in the ATBD for absolute DEMs. Validation testing has shown that DEMs produced by the new system frequently are more accurate than 25 meters root mean square error (RMSE) in xyz dimensions. Improvements/Changes from Previous Versions As of January 2021, the LP DAAC has implemented version 3.0 of the Sensor Information Laboratory Corporation ASTER DEM/Ortho (SILCAST) software, which is used to generate the Level 2 on-demand ASTER Orthorectified and Digital Elevation Model (DEM) products (AST14). The updated software provides digital elevation extraction and orthorectification from ASTER L1B input data without needing to enter ground control points or depending on external global DEMs at 30-arc-second resolution (GTOPO30). It utilizes the ephemeris and attitude data derived from both the ASTER instrument and the Terra spacecraft platform. The outputs are geoid height-corrected and waterbodies are automatically detected in this version. Users will notice differences between AST14DEM, AST14DMO, and AST14OTH products ordered before January 2021 (generated with SILCAST V1) and those generated with the updated version of the production software (version 3.0). Differences may include slight elevation changes over different surface types, including waterbodies. Differences have also been observed over cloudy portions of ASTER scenes. Additional information on SILCAST version 3.0 can be found on the SILCAST website (http://www.silc.co.jp/en/products.html). Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. not-provided ASTGTM.v003 ASTER Global Digital Elevation Model V003 LPCLOUD 2000-03-01 2013-11-30 -180, -83, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1711961296-LPCLOUD.json The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator). The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan’s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated. The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in GeoTIFF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area. Provided in the ASTER GDEM product are layers for DEM and number of scenes (NUM). The NUM layer indicates the number of scenes that were processed for each pixel and the source of the data. While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications. Improvements/Changes from Previous Versions • Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3. • Separation of rivers from lakes in the water body processing. • Minimum water body detection size decreased from 1 km2 to 0.2 km2. not-provided ASTGTM_NC.v003 ASTER Global Digital Elevation Model NetCDF V003 LPCLOUD 2000-03-01 2013-11-30 -180, -83, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C2439422590-LPCLOUD.json The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator). The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan’s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated. The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in NetCDF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area. Each ASTGTM_NC data product contains a DEM file, which provides elevation information. The corresponding ASTGTM_NUMNC file indicates the number of scenes that were processed for each pixel and the source of the data. While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications. Improvements/Changes from Previous Versions • Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3. • Separation of rivers from lakes in the water body processing. • Minimum water body detection size decreased from 1 km2 to 0.2 km2. not-provided ASTGTM_NUMNC.v003 ASTER Global Digital Elevation Model Attributes NetCDF V003 LPCLOUD 2000-03-01 2013-11-30 -180, -83, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C2439429778-LPCLOUD.json The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator). The development of the ASTER GDEM data products is a collaborative effort between National Aeronautics and Space Administration (NASA) and Japan’s Ministry of Economy, Trade, and Industry (METI). The ASTER GDEM data products are created by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was created from the automated processing of the entire ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) archive of scenes acquired between March 1, 2000, and November 30, 2013. Stereo correlation was used to produce over one million individual scene based ASTER DEMs, to which cloud masking was applied. All cloud screened DEMs and non-cloud screened DEMs were stacked. Residual bad values and outliers were removed. In areas with limited data stacking, several existing reference DEMs were used to supplement ASTER data to correct for residual anomalies. Selected data were averaged to create final pixel values before partitioning the data into 1 degree latitude by 1 degree longitude tiles with a one pixel overlap. To correct elevation values of water body surfaces, the ASTER Global Water Bodies Database (ASTWBD) (https://doi.org/10.5067/ASTER/ASTWBD.001) Version 1 data product was also generated. The geographic coverage of the ASTER GDEM extends from 83° North to 83° South. Each tile is distributed in NetCDF format and projected on the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each of the 22,912 tiles in the collection contain at least 0.01% land area. Each ASTGTM_NUMNC file indicates the number of scenes that were processed for each pixel and the source of the data.. The corresponding ASTGTM_NC data product contains a DEM file, which provides elevation information. While the ASTER GDEM Version 3 data products offer substantial improvements over Version 2, users are advised that the products still may contain anomalies and artifacts that will reduce its usability for certain applications. Improvements/Changes from Previous Versions • Expansion of acquisition coverage to increase the amount of cloud-free input scenes from about 1.5 million in Version 2 to about 1.88 million scenes in Version 3. • Separation of rivers from lakes in the water body processing. • Minimum water body detection size decreased from 1 km2 to 0.2 km2. not-provided +ASTWBD.v001 ASTER Global Water Bodies Database V001 LPDAAC_ECS 2000-03-01 2013-11-30 -180, -83, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1575734433-LPDAAC_ECS.json The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information. The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces. To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required. The geographic coverage of the ASTWBD extends from 83°N to 83°S. Each tile is distributed in GeoTIFF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each data product is provided as a zipped file that contains an attribute file with the water body classification information and a DEM file, which provides elevation information in meters. not-provided +ASTWBD_ATTNC.v001 ASTER Global Water Bodies Database Attributes NetCDF V001 LPDAAC_ECS 2000-03-01 2013-11-30 -180, -83, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1575734760-LPDAAC_ECS.json The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information. The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces. To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required. The geographic coverage of the ASTWBD extends from 83°N to 83°S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_ATTNC file contains an attribute file with the water body classification information. The corresponding ASTWBD_NC data product DEM file, which provides elevation information in meters. not-provided +ASTWBD_NC.v001 ASTER Global Water Bodies Database NetCDF V001 LPDAAC_ECS 2000-03-01 2013-11-30 -180, -83, 180, 82 https://cmr.earthdata.nasa.gov/search/concepts/C1575734501-LPDAAC_ECS.json The ASTER Global Water Bodies Database (ASTWBD) Version 1 data product provides global coverage of water bodies larger than 0.2 square kilometers at a spatial resolution of 1 arc second (approximately 30 meters) at the equator, along with associated elevation information. The ASTWBD data product was created in conjunction with the ASTER Global Digital Elevation Model (ASTER GDEM) Version 3 data product by the Sensor Information Laboratory Corporation (SILC) in Tokyo. The ASTER GDEM Version 3 data product was generated using ASTER Level 1A (https://doi.org/10.5067/ASTER/AST_L1A.003) scenes acquired between March 1, 2000, and November 30, 2013. The ASTWBD data product was then generated to correct elevation values of water body surfaces. To generate the ASTWBD data product, water bodies were separated from land areas and then classified into three categories: ocean, river, or lake. Oceans and lakes have a flattened, constant elevation value. The effects of sea ice were manually removed from areas classified as oceans to better delineate ocean shorelines in high latitude areas. For lake waterbodies, the elevation for each lake was calculated from the perimeter elevation data using the mosaic image that covers the entire area of the lake. Rivers presented a unique challenge given that their elevations gradually step down from upstream to downstream; therefore, visual inspection and other manual detection methods were required. The geographic coverage of the ASTWBD extends from 83°N to 83°S. Each tile is distributed in NetCDF format and referenced to the 1984 World Geodetic System (WGS84)/1996 Earth Gravitational Model (EGM96) geoid. Each ASTWBD_NC data product DEM file, which provides elevation information in meters. The corresponding ASTWBD_ATTNC file contains an attribute file with the water body classification information. not-provided +AST_05.v003 ASTER L2 Surface Emissivity V003 LPDAAC_ECS 2000-03-04 -180, -83, 180, 83 https://cmr.earthdata.nasa.gov/search/concepts/C1299783607-LPDAAC_ECS.json "The ASTER L2 Surface Emissivity is an on-demand product ((https://lpdaac.usgs.gov/documents/996/ASTER_Earthdata_Search_Order_Instructions.pdf)) generated using the five thermal infrared (TIR) bands (acquired either during the day or night time) between 8 and 12 µm spectral range. It contains surface emissivity over the land at 90 meters spatial resolution. Estimates of surface emissivity were thus far only derived using surrogates such as land-cover type or vegetation index. The Temperature/Emissivity Separation (TES) algorithm is used to derive both E (emissivity) and T (surface temperature). The main goals of the TES algorithm include: recovering accurate and precise emissivities for mineral substrates, and estimating accurate and precise surface temperatures especially over vegetation, water and snow.The TES algorithm is executed in the ASTER processing chain following generation of ASTER Level-2 Surface Radiance (TIR). The land-leaving radiance and down-welling irradiance vectors for each pixel are taken in account. Emissivity is estimated using the Normalized Emissivity Method (NEM), and is iteratively compensated for reflected sunlight. The emissivity spectrum is normalized using the average emissivity of each pixel. The minimum-maximum difference (MMD) of the normalized spectrum is calculated and estimates of the minimum emissivity derived through regression analysis. These estimates are used to scale the normalized emissivity and compensate for reflected skylight with the derived refinement of emissivity. ASTER Level 2 data requests for observations that occurred after May 27, 2020 will resort back to using the climatology ozone input. Additional information can be found in the ASTER L2 Processing Options Update (https://lpdaac.usgs.gov/news/aster-l2-processing-options-update/). V003 data set release date: 2002-05-03 Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. As of December 15, 2021, the LP DAAC has implemented changes to ASTER PGE Version 3.4, which will affect all ASTER Level 2 on-demand products. Changes include: • Aura Ozone Monitoring Instrument (OMI) has been added as one of the ancillary ozone inputs for any observations made after May 27, 2020. The sequence of fallbacks for ozone will remain the same. • Toolkit has been updated from Version 5.2.17 to 5.2.20. Users may notice minor differences between the two versions. Differences may include minuscule changes in digital numbers around the peripheral of the granule and boundaries of a cloud for Surface Reflectance and Surface Radiance (AST07 and AST09) QA Data Plane depending on the Operating System and libraries being used by the user to process the data. Additionally, Climatology, which is one of the inputs for Ozone and Moisture, Temperature and Pressures (MTP) will be removed from the Earthdata Order Form. It has been observed that PGEs generated with Climatology as an input yield noticeable differences statistically during image and spectral analysis. Climatology will continue to be used as the final default if neither of the first two selectable options are available for Ozone and MTP. Users can check the OPERATIONALQUALITYFLAGEXPLANATION field in the metadata or the output file for atmospheric parameters that were applied. Aura OMI data are no longer available as an input for ASTER Level 2 data acquisitions after October 6, 2023. For data acquired after this date, ozone inputs will automatically fall back to climatology ozone inputs when Aura OMI is selected as an input. For more details, please refer to the Discontinuation of Aura OMI as an Input news announcement (https://lpdaac.usgs.gov/news/discontinuation-of-aura-omi-as-an-ancillary-ozone-input-for-aster-products/). " not-provided +AST_09XT.v003 ASTER L2 Surface Radiance - VNIR and Crosstalk Corrected SWIR V003 LPDAAC_ECS 2000-03-06 -180, -83, 180, 83 https://cmr.earthdata.nasa.gov/search/concepts/C1299783631-LPDAAC_ECS.json "The ASTER Surface Radiance VNIR and Crosstalk Corrected SWIR (AST_09XT) is a multi-file product (https://lpdaac.usgs.gov/documents/996/ASTER_Earthdata_Search_Order_Instructions.pdf) that contains atmospherically corrected data for both the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) sensors. The crosstalk phenomenon was discovered during the nascent stage of the Terra Mission. It is whereby the incident light with band 4 caused multiple reflections for the SWIR bands, which resulted in blurred images. This has been corrected with the ASTER L2 Surface Radiance VNIR and Crosstalk Corrected SWIR data product. Each product delivery includes two Hierarchical Data Format - Earth Observing System (HDF-EOS) files: one for the VNIR, and the other for the SWIR. Both the VNIR and the SWIR data are atmospherically corrected using the corresponding bands from an (ASTER Level 1B) (https://doi.org/10.5067/ASTER/AST_L1B.003) image. ASTER Level 2 data requests for observations that occurred after May 27, 2020 will resort back to using the climatology ozone input. Additional information can be found in the ASTER L2 Processing Options Update (https://lpdaac.usgs.gov/news/aster-l2-processing-options-update/). Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. As of December 15, 2021, the LP DAAC has implemented changes to ASTER PGE Version 3.4, which will affect all ASTER Level 2 on-demand products. Changes include: • Aura Ozone Monitoring Instrument (OMI) has been added as one of the ancillary ozone inputs for any observations made after May 27, 2020. The sequence of fallbacks for ozone will remain the same. • Toolkit has been updated from Version 5.2.17 to 5.2.20. Users may notice minor differences between the two versions. Differences may include minuscule changes in digital numbers around the peripheral of the granule and boundaries of a cloud for Surface Reflectance and Surface Radiance (AST07 and AST09) QA Data Plane depending on the Operating System and libraries being used by the user to process the data. Additionally, Climatology, which is one of the inputs for Ozone and Moisture, Temperature and Pressures (MTP) will be removed from the Earthdata Order Form. It has been observed that PGEs generated with Climatology as an input yield noticeable differences statistically during image and spectral analysis. Climatology will continue to be used as the final default if neither of the first two selectable options are available for Ozone and MTP. Users can check the OPERATIONALQUALITYFLAGEXPLANATION field in the metadata or the output file for atmospheric parameters that were applied. Aura OMI data are no longer available as an input for ASTER Level 2 data acquisitions after October 6, 2023. For data acquired after this date, ozone inputs will automatically fall back to climatology ozone inputs when Aura OMI is selected as an input. For more details, please refer to the Discontinuation of Aura OMI as an Input news announcement (https://lpdaac.usgs.gov/news/discontinuation-of-aura-omi-as-an-ancillary-ozone-input-for-aster-products/)." not-provided +AST_L1A.v003 ASTER L1A Reconstructed Unprocessed Instrument Data V003 LPDAAC_ECS 2000-03-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C14758250-LPDAAC_ECS.json The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level 1A (AST_L1A) contains reconstructed, instrument digital numbers (DNs) derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). Additionally, geometric correction coefficients and radiometric calibration coefficients are calculated and appended to the metadata, but not applied. The spatial resolution is 15 m (VNIR), 30 m (SWIR), and 90 m (TIR) with a temporal coverage of 2000 to present. Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. not-provided +AST_L1AE.v003 ASTER Expedited L1A Reconstructed Unprocessed Instrument Data V003 LPDAAC_ECS 2000-03-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179460405-LPDAAC_ECS.json The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1A Reconstructed Unprocessed Instrument Data (AST_L1AE) global product contains reconstructed, unprocessed instrument digital data derived from the acquired telemetry streams of the telescopes: Visible and Near Infrared (VNIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR). This data product is similar to the (AST_L1A) (http://doi.org/10.5067/ASTER/AST_L1A.003) with a few notable exceptions. These include: * The AST_L1AE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments. * The registration quality of the AST_L1AE is likely to be lower than the AST_L1A, and may vary from scene to scene. * The AST_L1AE data product does not contain the VNIR 3B (aft-viewing) Band. * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor. * The AST_L1AE data product is only available for download 30 days after acquisition. It is then removed and reprocessed into an AST_L1A product. not-provided +AST_L1B.v003 ASTER L1B Registered Radiance at the Sensor V003 LPDAAC_ECS 2000-03-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C190733714-LPDAAC_ECS.json The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Level-1B (AST_L1B) Registered Radiance at the Sensor data product is radiometrically calibrated and geometrically co-registered. Application of intra-telescope and inter-telescope registration corrections for all bands are relative to the reference band for each telescope: Visible and Near Infrared (VNIR) Band 2, Shortwave Infrared (SWIR) Band 6, and Thermal Infrared (TIR) Band 11. The spatial resolution is 15 m (VNIR), 30 m (SWIR), and 90 m (TIR) with a temporal coverage of 2000 to present. Starting June 23, 2021, radiometric calibration coefficient Version 5 (RCC V5) will be applied to newly observed ASTER data and archived ASTER data products. Details regarding RCC V5 are described in the following journal article. Tsuchida, S., Yamamoto, H., Kouyama, T., Obata, K., Sakuma, F., Tachikawa, T., Kamei, A., Arai, K., Czapla-Myers, J.S., Biggar, S.F., and Thome, K.J., 2020, Radiometric Degradation Curves for the ASTER VNIR Processing Using Vicarious and Lunar Calibrations: Remote Sensing, v. 12, no. 3, at https://doi.org/10.3390/rs12030427. not-provided +AST_L1BE.v003 ASTER Expedited L1B Registered Radiance at the Sensor V003 LPDAAC_ECS 2000-03-04 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179460406-LPDAAC_ECS.json The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Expedited Level 1B Registered Radiance at the Sensor global data product is radiometrically calibrated and geometrically co-registered. Application of intra-telescope and inter-telescope registration corrections for all bands are relative to the reference band for each telescope: Visible and Near Infrared (VNIR) Band 2, Shortwave Infrared (SWIR) Band 6, and Thermal Infrared (TIR) Band 11. The Expedited Level 1B data product is similar to the (AST_L1B) (https://doi.org/10.5067/ASTER/AST_L1B.003) with a few notable exceptions. These include: * The AST_L1BE is available for download within 48 hours of acquisition in support of field calibration and validation efforts, in addition to emergency response for natural disasters where the quick turn-around time from acquisition to availability would prove beneficial in initial damage or impact assessments. * The registration quality of the AST_L1BE is likely to be lower than the AST_L1B, and may vary from scene to scene. * The AST_L1BE dataset does not contain the VNIR 3B (aft-viewing) Band. * This dataset does not have short-term calibration for the Thermal Infrared (TIR) sensor. not-provided ATL02.v006 ATLAS/ICESat-2 L1B Converted Telemetry Data V006 NSIDC_CPRD 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2547589158-NSIDC_CPRD.json This data set (ATL02) contains science-unit-converted time-ordered telemetry data, calibrated for instrument effects, downlinked from the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The data are used by the ATLAS/ICESat-2 Science Investigator-led Processing System (SIPS) for system-level, quality control analysis and as source data for ATLAS/ICESat-2 Level-2 products and Precision Orbit Determination (POD) and Precision Pointing Determination (PPD) computations. not-provided ATL03.v006 ATLAS/ICESat-2 L2A Global Geolocated Photon Data V006 NSIDC_CPRD 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2596864127-NSIDC_CPRD.json This data set (ATL03) contains height above the WGS 84 ellipsoid (ITRF2014 reference frame), latitude, longitude, and time for all photons downlinked by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. The ATL03 product was designed to be a single source for all photon data and ancillary information needed by higher-level ATLAS/ICESat-2 products. As such, it also includes spacecraft and instrument parameters and ancillary data not explicitly required for ATL03. not-provided ATL04.v006 ATLAS/ICESat-2 L2A Normalized Relative Backscatter Profiles V006 NSIDC_CPRD 2018-10-13 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2613553327-NSIDC_CPRD.json ATL04 contains along-track normalized relative backscatter profiles of the atmosphere. The product includes full 532 nm (14 km) uncalibrated attenuated backscatter profiles at 25 times per second for vertical bins of approximately 30 meters. Calibration coefficient values derived from data within the polar regions are also included. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory. not-provided @@ -147,16 +174,6 @@ CEAMARC_CASO_200708030_BIOGEOCHEMISTRYL_SAMPLES.v1 2007-08 V3 CEAMARC-CASO Sampl CEAMARC_CASO_200708030_EVENT_BATHYMETRY_PLOTS.v1 2007-08 V3 CEAMARC-CASO Bathymetry Plots Over Time During Events AU_AADC 2007-12-17 2008-01-26 139.01488, -67.07104, 150.06479, -42.88246 https://cmr.earthdata.nasa.gov/search/concepts/C1214308504-AU_AADC.json A routine was developed in R ('bathy_plots.R') to plot bathymetry data over time during individual CEAMARC events. This is so we can analyse benthic data in relation to habitat, ie. did we trawl over a slope or was the sea floor relatively flat. Note that the depth range in the plots is autoscaled to the data, so a small range in depths appears as a scatetring of points. As long as you look at the depth scale though interpretation will be ok. The R files need a file of bathymetry data in '200708V3_one_minute.csv' which is a file containing a data export from the underway PostgreSQL ship database and 'events.csv' which is a stripped down version of the events export from the ship board events database export. If you wish to run the code again you may need to change the pathnames in the R script to relevant locations. If you have opened the csv files in excel at any stage and the R script gets an error you may need to format the date/time columns as yyyy-mm-dd hh;mm:ss, save and close the file as csv without opening it again and then run the R script. However, all output files are here for every CEAMARC event. Filenames contain a reference to CEAMARC event id. Files are in eps format and can be viewed using Ghostview which is available as a free download on the internet. not-provided CEOS_CalVal_Test_Sites-Algeria3 CEOS Cal Val Test Site - Algeria 3 - Pseudo-Invariant Calibration Site (PICS) USGS_LTA 1972-08-11 5.22, 29.09, 10.01, 31.36 https://cmr.earthdata.nasa.gov/search/concepts/C1220567099-USGS_LTA.json On the background of these requirements for sensor calibration, intercalibration and product validation, the subgroup on Calibration and Validation of the Committee on Earth Observing System (CEOS) formulated the following recommendation during the plenary session held in China at the end of 2004, with the goal of setting-up and operating an internet based system to provide sensor data, protocols and guidelines for these purposes: Background: Reference Datasets are required to support the understanding of climate change and quality assure operational services by Earth Observing satellites. The data from different sensors and the resulting synergistic data products require a high level of accuracy that can only be obtained through continuous traceable calibration and validation activities. Requirement: Initiate an activity to document a reference methodology to predict Top of Atmosphere (TOA) radiance for which currently flying and planned wide swath sensors can be intercompared, i.e. define a standard for traceability. Also create and maintain a fully accessible web page containing, on an instrument basis, links to all instrument characteristics needed for intercomparisons as specified above, ideally in a common format. In addition, create and maintain a database (e.g. SADE) of instrument data for specific vicarious calibration sites, including site characteristics, in a common format. Each agency is responsible for providing data for their instruments in this common format. Recommendation : The required activities described above should be supported for an implementation period of two years and a maintenance period over two subsequent years. The CEOS should encourage a member agency to accept the lead role in supporting this activity. CEOS should request all member agencies to support this activity by providing appropriate information and data in a timely manner. Pseudo-Invariant Calibration Sites (PICS): Algeria 3 is one of six CEOS reference Pseudo-Invariant Calibration Sites (PICS) that are CEOS Reference Test Sites. Besides the nominally good site characteristics (temporal stability, uniformity, homogeneity, etc.), these six PICS were selected by also taking into account their heritage and the large number of datasets from multiple instruments that already existed in the EO archives and the long history of characterization performed over these sites. The PICS have high reflectance and are usually made up of sand dunes with climatologically low aerosol loading and practically no vegetation. Consequently, these PICS can be used to evaluate the long-term stability of instrument and facilitate inter-comparison of multiple instruments. not-provided CH-OG-1-GPS-10S.v0.0 10 sec GPS ground tracking data SCIOPS 2001-05-28 -63.51, -45.69, 170.42, 78.87 https://cmr.earthdata.nasa.gov/search/concepts/C1214586614-SCIOPS.json This data set comprises GPS ground data of a sample rate of 10 sec, generated by decoding and sampling GPS high rate ground data. This raw data passed no quality control. The data are given in the Rinex 2.1 format. not-provided -CIESIN_SEDAC_EPI_2008.v2008.00 2008 Environmental Performance Index (EPI) SEDAC 1994-01-01 2007-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179001707-SEDAC.json The 2008 Environmental Performance Index (EPI) centers on two broad environmental protection objectives: (1) reducing environmental stresses on human health, and (2) promoting ecosystem vitality and sound natural resource management. Derived from a careful review of the environmental literature, these twin goals mirror the priorities expressed by policymakers. Environmental health and ecosystem vitality are gauged using 25 indicators tracked in six well-established policy categories: Environmental Health (Environmental Burden of Disease, Water, and Air Pollution), Air Pollution (effects on ecosystems), Water (effects on ecosystems), Biodiversity and Habitat, Productive Natural Resources (Forestry, Fisheries, and Agriculture), and Climate Change. The 2008 EPI utilizes a proximity-to-target methodology in which performance on each indicator is rated on a 0 to 100 scale (100 represents �at target�). By identifying specific targets and measuring how close each country comes to them, the EPI provides a foundation for policy analysis and a context for evaluating performance. Issue-by-issue and aggregate rankings facilitate cross-country comparisons both globally and within relevant peer groups. The 2008 EPI is the result of collaboration among the Yale Center for Environmental Law and Policy (YCELP), Columbia University Center for International Earth Science Information Network (CIESIN), World Economic Forum (WEF), and the Joint Research Centre (JRC), European Commission. not-provided -CIESIN_SEDAC_EPI_2010.v2010.00 2010 Environmental Performance Index (EPI) SEDAC 1994-01-01 2009-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179002147-SEDAC.json The 2010 Environmental Performance Index (EPI) ranks 163 countries on environmental performance based on twenty-five indicators grouped within ten core policy categories addressing environmental health, air quality, water resource management, biodiversity and habitat, forestry, fisheries, agriculture, and climate change in the context of two broad objectives: environmental health and ecosystem vitality. The EPI�s proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. It was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 28, 2010. The 2010 EPI is the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN). not-provided -CIESIN_SEDAC_EPI_2012.v2012.00 2012 Environmental Performance Index and Pilot Trend Environmental Performance Index SEDAC 2000-01-01 2010-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000000-SEDAC.json The 2012 Environmental Performance Index (EPI) ranks 132 countries on 22 performance indicators in the following 10 policy categories: environmental burden of disease, water (effects on human health), air pollution (effects on human health), air pollution (ecosystem effects), water resources (ecosystem effects), biodiversity and habitat, forestry, fisheries, agriculture and climate change. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. Each indicator has an associated environmental public health or ecosystem sustainability target. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The Pilot Trend Environmental Performance Index (Trend EPI) ranks countries on the change in their environmental performance over the last decade. As a complement to the EPI, the Trend EPI shows who is improving and who is declining over time. The 2012 EPI and Pilot Trend EPI were formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 27, 2012. These are the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN). The Interactive Website for the 2012 EPI is at http://epi.yale.edu/. not-provided -CIESIN_SEDAC_EPI_2014.v2014.00 2014 Environmental Performance Index (EPI) SEDAC 2002-01-01 2014-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000541-SEDAC.json The 2014 Environmental Performance Index (EPI) ranks 178 countries on 20 performance indicators in the following 9 policy categories: health impacts, air quality, water and sanitation, water resources, agriculture, forests, fisheries, biodiversity and habitat, and climate and energy. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2014 EPI and component scores, backcast EPI scores for 2002-2012, and time-series source data. The 2014 EPI was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 25, 2014. These are the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN). The Interactive Website for the 2014 EPI is at http://epi.yale.edu/. not-provided -CIESIN_SEDAC_EPI_2016.v2016.00 2016 Environmental Performance Index (EPI) SEDAC 1950-01-01 2016-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1419908204-SEDAC.json The 2016 Environmental Performance Index (EPI) ranks 180 countries on 20 performance indicators in the following 9 policy categories: health impacts, air quality, water and sanitation, water resources, agriculture, forests, fisheries, biodiversity and habitat, and climate and energy. These categories track performance and progress on two broad policy objectives, environmental health and ecosystem vitality. The EPI's proximity-to-target methodology facilitates cross-country comparisons among economic and regional peer groups. The data set includes the 2016 EPI and component scores, backcast EPI scores for 1950-2016, and time-series source data. The 2016 EPI was formally released in Davos, Switzerland, at the annual meeting of the World Economic Forum on January 23, 2016. These are the result of collaboration between the Yale Center for Environmental Law and Policy (YCELP) and Yale Data-Driven Environmental Solutions Group, Yale University, Columbia University Center for International Earth Science Information Network (CIESIN), and the World Economic Forum (WEF). The Interactive Website for the 2016 EPI is at https://epi.yale.edu. not-provided -CIESIN_SEDAC_ESI_2000.v2000.00 2000 Pilot Environmental Sustainability Index (ESI) SEDAC 1978-01-01 1999-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179001887-SEDAC.json The 2000 Pilot Environmental Sustainability Index (ESI) is an exploratory effort to construct an index that measures the ability of a nation's economy to achieve sustainable development, with the long term goal of finding a single indicator for environmental sustainability analagous to that of the Gross Domestic Product (GDP). The index covering 56 countries is a composite measure of the current status of a nation's environmental systems, pressures on those systems, human vulnerability to environmental change, national capacity to respond, and contributions to global environmental stewardship. The index was unveiled at the World Economic Forum's annual meeting, January 2000, Davos, Switzerland. The 2000 Pilot ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN). not-provided -CIESIN_SEDAC_ESI_2001.v2001.00 2001 Environmental Sustainability Index (ESI) SEDAC 1980-01-01 2000-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1000000220-SEDAC.json The 2001 Environmental Sustainability Index (ESI) utilizes a refined methodology based on the 2000 Pilot ESI effort, to construct an index covering 122 countries that measures the overall progress towards environmental sustainability. The index is a composite measure of the current status of a nation's environmental systems, pressures on those systems, human vulnerability to environmental change, national capacity to respond, and contributions to global environmental stewardship. The refinements included the addition and deletion of indicators, filling gaps in data coverage, new data sets, and the modification of the aggregation scheme. The index was unveiled at the World Economic Forum's annual meeting, January 2001, Davos, Switzerland. The 2001 ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN). not-provided -CIESIN_SEDAC_ESI_2002.v2002.00 2002 Environmental Sustainability Index (ESI) SEDAC 1980-01-01 2000-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179001967-SEDAC.json The 2002 Environmental Sustainability Index (ESI) measures overall progress toward environmental sustainability for 142 countries based on environmental systems, stresses, human vulnerability, social and institutional capacity and global stewardship. The addition of a climate change indicator, reduction in number of capacity indicators, and an improved imputation methodology contributed to an improvement from the 2001 ESI. The index was unveiled at the World Economic Forum's annual meeting, January 2002, New York. The 2002 ESI is the result of collaboration among the World Economic Forum (WEF), Yale Center for Environmental Law and Policy (YCELP), and the Columbia University Center for International Earth Science Information Network (CIESIN). not-provided -CIESIN_SEDAC_ESI_2005.v2005.00 2005 Environmental Sustainability Index (ESI) SEDAC 1980-01-01 2000-12-31 -180, -55, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179001889-SEDAC.json The 2005 Environmental Sustainability Index (ESI) is a measure of overall progress towards environmental sustainability, developed for 146 countries. The index provides a composite profile of national environmental stewardship based on a compilation of 21 indicators derived from 76 underlying data sets. The 2005 version of the ESI represents a significant update and improvement on earlier versions; the country ESI scores or rankings should not be compared to earlier versions because of changes to the methodology and underlying data. The index was unveiled at the World Economic Forum's annual meeting, January 2005, Davos, Switzerland. The 2005 ESI is a joint product of the Yale Center for Environmental Law and Policy (YCELP) and the Columbia University Center for International Earth Science Information Network (CIESIN), in collaboration with the World Economic Forum (WEF) and the Joint Research Centre (JRC), European Commission. not-provided -CIESIN_SEDAC_USPAT_USUEXT2015.v1.00 2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods SEDAC 2015-01-01 2015-12-31 -180, -56, 180, 84 https://cmr.earthdata.nasa.gov/search/concepts/C1648035940-SEDAC.json The 2015 Urban Extents from VIIRS and MODIS for the Continental U.S. Using Machine Learning Methods data set models urban settlements in the Continental United States (CONUS) as of 2015. When applied to the combination of daytime spectral and nighttime lights satellite data, the machine learning methods achieved high accuracy at an intermediate-resolution of 500 meters at large spatial scales. The input data for these models were two types of satellite imagery: Visible Infrared Imaging Radiometer Suite (VIIRS) Nighttime Light (NTL) data from the Day/Night Band (DNB), and Moderate Resolution Imaging Spectroradiometer (MODIS) corrected daytime Normalized Difference Vegetation Index (NDVI). Although several machine learning methods were evaluated, including Random Forest (RF), Gradient Boosting Machine (GBM), Neural Network (NN), and the Ensemble of RF, GBM, and NN (ESB), the highest accuracy results were achieved with NN, and those results were used to delineate the urban extents in this data set. not-provided CLDMSK_L2_VIIRS_NOAA20_NRT.v1 VIIRS/NOAA-20 Cloud Mask L2 6-Min Swath 750m (NRT) ASIPS 2020-10-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2003160566-ASIPS.json The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) NASA Level-2 (L2) Cloud Mask is one of two continuity products designed to sustain the long-term records of both Moderate Resolution Imaging Spectroradiometer (MODIS) and VIIRS heritages. CLDMSK_L2_VIIRS_NOAA20_NRT is the shortname for the NOAA-20 VIIRS Near Real-time incarnation of the Cloud Mask continuity product derived from the MODIS-VIIRS cloud mask (MVCM) algorithm, which itself is based on the MODIS (MOD35) algorithm. MVCM describes a continuity algorithm that is central to both MODIS data (from Terra and Aqua missions) and VIIRS data (from SNPP and Joint Polar Satellite System missions). Please bear in mind that the term MVCM does not appear as an attribute within the product’s metadata. Implemented to consistently handle MODIS and VIIRS inputs, the NOAA-20 VIIRS collection-1 products use calibration-adjusted NASA VIIRS L1B as inputs. The nominal spatial resolution of the NOAA-20 VIIRS L2 Cloud mask is 750 meters. not-provided CLDMSK_L2_VIIRS_SNPP_NRT.v1 VIIRS/SNPP Cloud Mask L2 6-Min Swath 750m (NRT) ASIPS 2019-04-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1607563719-ASIPS.json The Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) NASA Level-2 (L2) Cloud Mask is one of two continuity products designed to sustain the long-term records of both Moderate Resolution Imaging Spectroradiometer (MODIS) and VIIRS heritages. CLDMSK_L2_VIIRS_SNPP is the shortname for the SNPP VIIRS incarnation of the Cloud Mask continuity product derived from the MODIS-VIIRS cloud mask (MVCM) algorithm, which itself is based on the MODIS (MOD35) algorithm. MVCM describes a continuity algorithm that is central to both MODIS data (from Terra and Aqua missions) and VIIRS data (from SNPP and Joint Polar Satellite System missions). Please bear in mind that the term MVCM does not appear as an attribute within the product’s metadata. Implemented to consistently handle MODIS and VIIRS inputs, the SNPP VIIRS collection-1 products use calibration-adjusted NASA VIIRS L1B as inputs. The nominal spatial resolution of the SNPP VIIRS L2 Cloud mask is 750 meters. not-provided CSU Synthetic Attribution Benchmark Dataset.v1 CSU Synthetic Attribution Benchmark Dataset MLHUB 2020-01-01 2023-01-01 -179.5, -89.5, 179.5, 89.5 https://cmr.earthdata.nasa.gov/search/concepts/C2781411899-MLHUB.json This is a synthetic dataset that can be used by users that are interested in benchmarking methods of explainable artificial intelligence (XAI) for geoscientific applications. The dataset is specifically inspired from a climate forecasting setting (seasonal timescales) where the task is to predict regional climate variability given global climate information lagged in time. The dataset consists of a synthetic input X (series of 2D arrays of random fields drawn from a multivariate normal distribution) and a synthetic output Y (scalar series) generated by using a nonlinear function F: R^d -> R.

The synthetic input aims to represent temporally independent realizations of anomalous global fields of sea surface temperature, the synthetic output series represents some type of regional climate variability that is of interest (temperature, precipitation totals, etc.) and the function F is a simplification of the climate system.

Since the nonlinear function F that is used to generate the output given the input is known, we also derive and provide the attribution of each output value to the corresponding input features. Using this synthetic dataset users can train any AI model to predict Y given X and then implement XAI methods to interpret it. Based on the “ground truth” of attribution of F the user can assess the faithfulness of any XAI method.

NOTE: the spatial configuration of the observations in the NetCDF database file conform to the planetocentric coordinate system (89.5N - 89.5S, 0.5E - 359.5E), where longitude is measured in the positive heading east from the prime meridian. not-provided @@ -171,6 +188,8 @@ DLG100K 1:100,000-scale Digital Line Graphs (DLG) from the U.S. Geological Surve E06_OCM_GAC_STGO00GND.v1.0 EOS-06 OCM Global Area Coverage (GAC) - 1080m resolution Standard Products - Oceansat Series ISRO 2023-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2866789316-ISRO.json The main objectives of E06 are to study surface winds and ocean surface strata, observation of chlorophyll concentrations, monitoring of phytoplankton blooms, study of atmospheric aerosols and suspended sediments in the water. This has global coverage for every 2 days and sun glint free data for every 13 days. not-provided E06_OCM_LAC_STGO00GND.v1.0 EOS-06 OCM Local Area Coverage (LAC) - 366m Resolution Standard Products - Oceansat Series ISRO 2023-04-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2866790547-ISRO.json The main objectives of E06 are to study surface winds and ocean surface strata, observation of chlorophyll concentrations, monitoring of phytoplankton blooms, study of atmospheric aerosols and suspended sediments in the water. not-provided EARTH_LAND_USGS_AMES_AIR_PHOTOS Aerial Photographs (from AMES Pilot Land Data System); USGS EDC, Sioux Falls USGS_LTA 1970-01-01 -180, 20, -60, 50 https://cmr.earthdata.nasa.gov/search/concepts/C1220566371-USGS_LTA.json "The aerial photography inventoried by the Pilot Land Data System (PLDS) at NASA AMES Research Center has been transferred to the USGS EROS Data Center. The photos were obtained from cameras mounted on high and medium altitude aircraft based at the NASA Ames Research Center. Several cameras with varying focal lengths, lenses and film formats are used, but the Wild RC-10 camera with a focal length of 152 millimeters and a 9 by 9 inch film format is most common. The positive transparencies are typically used for ancillary ground checks in conjunctions with digital processing for the same sites. The aircraft flights, specifically requested by scientists performing approved research, often simultaneously collect data using other sensors on board (e.g. Thematic Mapper Simulators (TMS) and Thermal Infrared Multispectral Scanners). High altitude color infrared photography is used regularly by government agencies for such applications as crop yield forecasting, timber inventory and defoliation assessment, water resource management, land use surveys, water pollution monitoring, and natural disaster assessment. To order, specify the latitude and longitude of interest. You will then be given a list of photos available for that location. In some cases, ""flight books"" are available at EDC that describe the nature of the mission during which the photos were taken and other attribute information. The customer service personnel have access to these books for those photo sets for which the books exist." not-provided +EN1_MDSI_MER_FRS_1P.v4 Full Resolution Full Swath Geolocated and Calibrated TOA Radiance LAADS 2002-05-17 2012-04-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2151211533-LAADS.json The Medium Resolution Imaging Spectrometer (MERIS) is one of 10 sensors deployed in March of 2002 on board the polar-orbiting Envisat-1 environmental research satellite by the European Space Agency (ESA). The MERIS instrument is a moderate-resolution wide field-of-view push-broom imaging spectroradiometer capable of sensing in the 390 nm to 1040 nm spectral range. Being a programmable instrument, it had the unique capability of selectively adjusting the width and location of its 15 bands through ground command. The instrument has a 68.5-degree field of view and a swath width of 1150 meters, providing a global coverage every 3 days at 300 m resolution. Communication with the Envisat-1 satellite was lost suddenly on the 8th of April, 2012, just weeks after celebrating its 10th year in orbit. All attempts to re-establish contact were unsuccessful, and the end of the mission was declared on May 9th, 2012. The 4th reprocessing cycle, in 2020, has produced both the full-resolution and reduced-resolution L1 and L2 MERIS products. EN1_MDSI_MER_FRS_1P is the short-name for the MERIS Level-1 full resolution, full swath, geolocated and calibrated top-of-atmosphere (TOA) radiance product. This product contains the TOA upwelling spectral radiance measurements. The in-band reference irradiances for the 15 MERIS bands are computed by averaging the in-band solar irradiance for each pixel. Each pixel’s in-band solar irradiance is computed by integrating the reference solar spectrum with the band-pass of each pixel. The Level-1 product contains 22 data files: 15 files contain radiances for each band (one band per file) along with associated error estimates, and 7 annotation data files. It also includes a Manifest file that provides metadata information describing the product. not-provided +EN1_MDSI_MER_FRS_2P.v4 Full Resolution Full Swath Geophysical Product for Ocean, Land and Atmosphere LAADS 2003-01-01 2012-04-08 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2151219110-LAADS.json The Medium Resolution Imaging Spectrometer (MERIS) is one of 10 sensors deployed in March of 2002 on board the polar-orbiting Envisat-1 environmental research satellite by the European Space Agency (ESA). The MERIS instrument is a moderate-resolution wide field-of-view push-broom imaging spectroradiometer capable of sensing in the 390 nm to 1040 nm spectral range. Being a programmable instrument, it had the unique capability of selectively adjusting the width and location of its 15 bands through ground command. The instrument has a 68.5-degree field of view and a swath width of 1150 meters, providing a global coverage every 3 days at 300 m resolution. Communication with the Envisat-1 satellite was lost suddenly on the 8th of April, 2012, just weeks after celebrating its 10th year in orbit. All attempts to re-establish contact were unsuccessful, and the end of the mission was declared on May 9th, 2012. The 4th reprocessing cycle, in 2020, has produced both the full-resolution and reduced-resolution L1 and L2 MERIS products. EN1_MDSI_MER_FRS_2P is the short-name for the MERIS Level-2 full resolution, geophysical product for ocean, land, and atmosphere. This Level-2 product comes in a netCDF4 package that contains both instrument and science measurements, and a Manifest file that provides metadata information describing the product. Each Level-2 product contains 64 measurement files that break down thus: 13 files containing water-leaving reflectance, 13 files containing land surface reflectance and 13 files containing the TOA reflectance (for all bands except those dedicated to measuring atmospheric gas - M11 and M15), and several files containing additional measurements on ocean, land, and atmosphere parameters. not-provided EO:EUM:CM:METOP:ASCSZFR02.v2014-10-07 ASCAT L1 SZF Climate Data Record Release 2 - Metop EUMETSAT 2007-01-01 2014-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1588901388-EUMETSAT.json Reprocessed L1B data from the Advanced Scatterometer (ASCAT) on METOP-A, resampled at full resolution (SZF). Normalized radar cross section (NRCS) of the Earth surface together with measurement time, location (latitude and longitude) and geometrical information (incidence and azimuth angles). The prime objective of the Advanced SCATterometer (ASCAT) is to measure wind speed and direction over the oceans, and the main operational application is the assimilation of ocean winds in NWP models. Other operational applications, based on the use of measurements of the backscattering coefficient, are sea ice edge detection and monitoring, monitoring sea ice, snow cover, soil moisture and surface parameters. This product is also available at 12.5 and 25 km Swath Grids. This is a Fundamental Climate Data Record (FCDR). not-provided EO:EUM:CM:METOP:ASCSZOR02.v2014-10-07 ASCAT L1 SZO Climate Data Record Release 2 - Metop EUMETSAT 2007-01-01 2014-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1588901391-EUMETSAT.json Reprocessed L1B data from the Advanced Scatterometer (ASCAT) on METOP-A, resampled at 25 km Swath Grid (SZO). Normalized radar cross section (NRCS) triplets of the Earth surface together with measurement time, location (latitude and longitude) and geometrical information (incidence and azimuth angles). The prime objective of the Advanced SCATterometer (ASCAT) is to measure wind speed and direction over the oceans, and the main operational application is the assimilation of ocean winds in NWP models. Other operational applications, based on the use of measurements of the backscattering coefficient, are sea ice edge detection and monitoring, monitoring sea ice, snow cover, soil moisture and surface parameters. This product is also available at full resolution and at 12.5 km Swath Grid. This is a Fundamental Climate Data Record (FCDR). not-provided EO:EUM:CM:METOP:ASCSZRR02.v2014-10-07 ASCAT L1 SZR Climate Data Record Release 2 - Metop EUMETSAT 2007-01-01 2014-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1588901394-EUMETSAT.json Reprocessed L1B data from the Advanced Scatterometer (ASCAT) on METOP-A, resampled at 12.5 km Swath Grid (SZR). Normalized radar cross section (NRCS) triplets of the Earth surface together with measurement time, location (latitude and longitude) and geometrical information (incidence and azimuth angles). The prime objective of the Advanced SCATterometer (ASCAT) is to measure wind speed and direction over the oceans, and the main operational application is the assimilation of ocean winds in NWP models. Other operational applications, based on the use of measurements of the backscattering coefficient, are sea ice edge detection and monitoring, monitoring sea ice, snow cover, soil moisture and surface parameters. This product is also available at full resolution and at 25 km Swath Grid. This is a Fundamental Climate Data Record (FCDR). not-provided @@ -225,6 +244,8 @@ LGB_10m_traverse.v1 10 m firn temperature data: LGB traverses 1990-95 AU_AADC 19 Leaf_Carbon_Nutrients_1106.v1 A Global Database of Carbon and Nutrient Concentrations of Green and Senesced Leaves ORNL_CLOUD 1970-01-01 2009-12-31 -159.7, -50, 176.9, 68.5 https://cmr.earthdata.nasa.gov/search/concepts/C2784383820-ORNL_CLOUD.json This data set provides carbon (C), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) concentrations in green and senesced leaves. Vegetation characteristics reported include species growth habit, leaf area, mass, and mass loss with senescence. The data were compiled from 86 selected studies in 31 countries, and resulted in approximately 1,000 data points for both green and senesced leaves from woody and non-woody vegetation as described in Vergutz et al (2012). The studies were conducted from 1970-2009. There are two comma-delimited data files with this data set. not-provided Leaf_Photosynthesis_Traits_1224.v1 A Global Data Set of Leaf Photosynthetic Rates, Leaf N and P, and Specific Leaf Area ORNL_CLOUD 1993-01-01 2010-12-31 -122.4, -43.2, 176.13, 58.42 https://cmr.earthdata.nasa.gov/search/concepts/C2784384781-ORNL_CLOUD.json This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported. The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available. These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file. not-provided Level_2A_aerosol_cloud_optical_products Aeolus L2A Aerosol/Cloud optical product ESA 2021-05-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2207498185-ESA.json "The Level 2A aerosol/cloud optical products of the Aeolus mission include geo-located consolidated backscatter and extinction profiles, backscatter-to-extinction coefficient, LIDAR ratio, scene classification, heterogeneity index and attenuated backscatter signals. Resolution - Horizontal resolution of L2A optical properties at observation scale (~87 km); Exceptions are group properties (horizontal accumulation of measurements from ~3 km to ~87 km) and attenuated backscatters (~3 km); Note: the resolution of ""groups"" in the L2A can only go down to 5 measurements at the moment, i.e. ~15 km horizontal resolution. This could be configured to go to 1 measurement - Vertical resolution 250-2000 m (Defined by Range Bin Settings https://earth.esa.int/eogateway/instruments/aladin/overview-of-the-main-wind-rbs-changes)." not-provided +M1_AVH09C1.v6 METOP-B AVHRR Atmospherically Corrected Surface Reflectance Daily L3 Global 0.05 Deg CMG LAADS 2013-01-16 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2187507677-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 Surface Reflectance Daily L3 Global 0.05 Deg CMG, short-name M1_ AVH09C1 is generated from GIMMS Advanced Processing System (GAPS) BRDF-corrected Surface Reflectance product (AVH01C1). The M1_ AVH09C1 consist of BRDF-corrected surface reflectance for bands 1, 2, and 3, data Quality flags, angles (solar zenith, view zenith, and relative azimuth), and thermal data (thermal bands 3, 4, and 5). The AVH09C1 product is available in HDF4 file format. not-provided +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 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 @@ -322,6 +343,7 @@ WaterBalance_Daily_Historical_GRIDMET.v1.5 Daily Historical Water Balance Produc XAERDT_L2_ABI_G16.v1 ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS 2019-01-01 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859273114-LAADS.json The ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G16 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-16 has been serving in the operational GOES-East position (near -75°W) since December 18, 2017. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G16 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G16 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G16 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ not-provided XAERDT_L2_ABI_G17.v1 ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS 2019-01-01 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859265967-LAADS.json The ABI/GOES-17 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_ABI_G17 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 144 granules over the daylit hours of a 24-hour period. The Geostationary Operational Environmental Satellite – GOES-17 served in the operational GOES-West position (near -137°W), from February 12, 2019, through January 4, 2023. The GOES-16/ABI collection record spans from January 2019 through December 2022. The XAERDT_L2_ABI_G17 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_ABI_G17 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_ABI_G17 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ not-provided XAERDT_L2_AHI_H08.v1 AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS 2019-01-01 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859255251-LAADS.json The AHI/Himawari-08 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H08 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-8 platform served in the operational Himawari position (near 140.7°E) between October 2014 and 13 December 2022. Himawari-9 replaced Himawari-8 and is currently operational. The Himawari-8/AHI collection record spans from January 2019 through 12th December 2022. The final 19 days of 2022 (December 13 through 31) are served by L2 products derived from the Himawari-9/AHI instrument. The XAERDT_L2_AHI_H08 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H08 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H08 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ not-provided +XAERDT_L2_AHI_H09.v1 AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km LAADS 2022-12-13 2022-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2859261579-LAADS.json The AHI/Himawari-09 Dark Target Aerosol 10-Min L2 Full Disk 10 km product, short-name XAERDT_L2_AHI_H09 is provided at 10-km spatial resolution (at-nadir) and a 10-minute full-disk cadence that typically yields about 142 granules over the daylit hours of a 24-hour period (there are no images produced at 02:20 or 14:20 UTC for navigation purposes). The Himawari-9 platform currently serves in the operational Himawari position (near 140.7°E) since it was launched November 2, 2016, and replaces Himawari-8. The Himawari-9/AHI collection record spans from 13th December 2022 through 31st December 2022. The XAERDT_L2_AHI_H09 product is a part of the Geostationary Earth Orbit (GEO)–Low-Earth Orbit (LEO) Dark Target Aerosol project under NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, led by Robert Levy, uses a special version of the MODIS Dark Target (DT) aerosol retrieval algorithm to produce Aerosol Optical Depth (AOD) and other aerosol parameters derived independently from seven sensor/platform combinations, where 3 are in GEO and 4 are in LEO. The 3 GEO sensors include Advanced Baseline Imagers (ABI) on both GOES-16 (GOES-East) and GOES-17 (GOES-West), and Advanced Himawari Imager (AHI) on Himawari-8. The 4 LEO sensors include MODIS on both Terra and Aqua, and VIIRS on both Suomi-NPP and NOAA-20. Adding the LEO sensors reinforces a major goal of this project, which is to render a consistent science maturity level across DT aerosol products derived from both types and sources of orbital satellites. The XAERDT_L2_AHI_H09 product, in netCDF4 format, contains 45 Science Data Set (SDS) layers that include 8 geolocation and 37 geophysical SDSs. For more information consult LAADS product description page at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/XAERDT_L2_AHI_H09 Or, Dark Target aerosol team Page at: https://darktarget.gsfc.nasa.gov/ 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 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 to 25 June 2017. CPEX conducted a total of sixteen DC-8 missions from 27 May to 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 @@ -346,10 +368,15 @@ blue_ice_core_DML2004_AS 101.1 m long horizontal blue ice core collected from Sc 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 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 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 +eMASL1B.v1 Enhanced MODIS Airborne Simulator (eMAS) Calibrated, Geolocated Radiances L1B 50m Data LAADS 2013-08-01 2019-08-22 -180, -35, 180, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2801308027-LAADS.json The Enhanced Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (eMAS)instrument is maintained and operated by the Airborne Sensor Facility at NASA Ames Research Center in Mountain View, California, under the oversight of the EOS Project Science Office at NASA Goddard. Prior to 1995, the MAS was deployed on the NASA's ER-2 and C-130 aircraft platforms using a 12-channel, 8-bit data system that somewhat constrained the full benefit of having a 50-channel scanning spectrometer. Beginning in January 1995, a 50-channel, 16-bit digitizer was used on the ER-2 platform, which greatly enhanced the capability of MAS to simulate MODIS data over a wide range of environmental conditions. Recently, it has undergone extensive upgrades to the optics and other components. New detectors have been installed and the spectral bands have been streamlined. The eMAS instrument is now a 38-channel instrument, sensing in the range from 0.445 to 13.844 um. For more information and for a list of MAS campaign flights visit ladsweb at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/mas/ or, visit the eMAS Homepage at: https://asapdata.arc.nasa.gov/emas/ not-provided +eMASL2CLD.v1 Enhanced MODIS Airborne Simulator (eMAS) L2 Cloud Data LAADS 2013-08-01 2016-09-28 -180, -35, 180, 80 https://cmr.earthdata.nasa.gov/search/concepts/C2801723593-LAADS.json The Enhanced Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (eMAS)instrument is maintained and operated by the Airborne Sensor Facility at NASA Ames Research Center in Mountain View, California, under the oversight of the EOS Project Science Office at NASA Goddard. The eMAS instrument is now a 38-channel instrument, sensing in the range from 0.445 to 13.844 um. The Enhanced MODIS Airborne Simulator (eMAS) L2 Cloud Data product (eMASL2CLD) consists of cloud optical and physical parameters. These parameters are derived using remotely sensed infrared and near infrared solar reflected radiances. Multispectral images of the reflectance and brightness temperature at 10 wavelengths between 0.66 and 13.98nm were used to derive the probability of clear sky (or cloud), cloud thermodynamic phase, and the optical thickness and effective radius of liquid water and ice clouds. The eMASL2CLD product files are stored in Hierarchical Data Format (HDF-EOS). All gridded cloud parameters are stored as Scientific Data Sets (SDS) within the file. For more information and for a list of MAS campaign flights visit ladsweb at: https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/mas/ or, visit the eMAS Homepage at: https://asapdata.arc.nasa.gov/emas/ 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 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 fife_hydrology_strm_15m_1.v1 15 Minute Stream Flow Data: USGS (FIFE) ORNL_CLOUD 1984-12-25 1988-03-04 -96.6, 39.1, -96.6, 39.1 https://cmr.earthdata.nasa.gov/search/concepts/C2977827088-ORNL_CLOUD.json USGS 15 minute stream flow data for Kings Creek on the Konza Prairie not-provided fife_sur_met_rain_30m_2.v1 30 Minute Rainfall Data (FIFE) ORNL_CLOUD 1987-05-29 1987-10-26 -96.6, 39.08, -96.55, 39.11 https://cmr.earthdata.nasa.gov/search/concepts/C2977893818-ORNL_CLOUD.json 30 minute rainfall data for the Konza Prairie 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 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