From 295ac2d6b63cb05039057a0731ba025893eecc8f Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Mon, 29 Jul 2024 04:12:50 +0000 Subject: [PATCH] Updated datasets 2024-07-29 UTC --- nasa_cmr_catalog.json | 540 +++++++++++++++++++++++++++++++----------- nasa_cmr_catalog.tsv | 42 +++- 2 files changed, 431 insertions(+), 151 deletions(-) diff --git a/nasa_cmr_catalog.json b/nasa_cmr_catalog.json index 30b3a6724..1ec5d6b30 100644 --- a/nasa_cmr_catalog.json +++ b/nasa_cmr_catalog.json @@ -25,58 +25,6 @@ "description": "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 3 aerosol daily and monthly gridded 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.", "license": "not-provided" }, - { - "id": "12-hourly_interpolated_surface_position_from_buoys", - "title": "12-Hourly Interpolated Surface Position from Buoys", - "catalog": "SCIOPS", - "state_date": "1979-01-01", - "end_date": "2009-12-01", - "bbox": "-180, 60, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600619-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600619-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/12-hourly_interpolated_surface_position_from_buoys", - "description": "This data set contains Arctic Ocean daily buoy positions interpolated to hours 0Z and 12Z.", - "license": "not-provided" - }, - { - "id": "12-hourly_interpolated_surface_velocity_from_buoys", - "title": "12-Hourly Interpolated Surface Velocity from Buoys", - "catalog": "SCIOPS", - "state_date": "1979-01-01", - "end_date": "2009-12-02", - "bbox": "-180, 74, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600621-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600621-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/12-hourly_interpolated_surface_velocity_from_buoys", - "description": "This data set contains 12-hourly interpolated surface velocity data from buoys. Point grid: Latitude 74N to 90N - 4 degree increment Longitude 0E to 320E - 20 and 40 degree increment.", - "license": "not-provided" - }, - { - "id": "12_hourly_interpolated_surface_air_pressure_from_buoys", - "title": "12 Hourly Interpolated Surface Air Pressure from Buoys", - "catalog": "SCIOPS", - "state_date": "1979-01-01", - "end_date": "2007-11-30", - "bbox": "-180, 70, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600618-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214600618-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/12_hourly_interpolated_surface_air_pressure_from_buoys", - "description": "Optimally interpolated atmospheric surface pressure over the Arctic Ocean Basin. Temporal format - twice daily (0Z and 12Z) Spatial format - 2 degree latitude x 10 degree longitude - latitude: 70 N - 90 N - longitude: 0 E - 350 E", - "license": "not-provided" - }, - { - "id": "14c_of_soil_co2_from_ipy_itex_cross_site_comparison", - "title": "14C of soil CO2 from IPY ITEX Cross Site Comparison", - "catalog": "SCIOPS", - "state_date": "2008-01-16", - "end_date": "2008-01-21", - "bbox": "-157.4, -36.9, 147.29, 71.3", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214602443-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214602443-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/14c_of_soil_co2_from_ipy_itex_cross_site_comparison", - "description": "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.", - "license": "not-provided" - }, { "id": "200708_CEAMARC_CASO_TRACE_ELEMENT_SAMPLES.v1", "title": "2007-08 CEAMARC-CASO VOYAGE TRACE ELEMENT SAMPLING AROUND AN ICEBERG", @@ -584,6 +532,58 @@ "description": "The ACIDD (Across the Channel Investigating Diel Dynamics) project, in the Santa Barbara Channel, was initially designed to characterize daily variations in phytoplankton populations, but with the Thomas Fire in the Santa Barbara Hills December 2017, this project evolved into a study to characterize the effects of smoke and ash on the mixed layer in the Santa Barbara Channel.", "license": "not-provided" }, + { + "id": "ACOS_L2S.v7.3", + "title": "ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V7.3 (ACOS_L2S) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2009-04-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230297-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230297-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2S.v7.3", + "description": "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.", + "license": "not-provided" + }, + { + "id": "ACOS_L2S.v9r", + "title": "ACOS GOSAT/TANSO-FTS Level 2 Full Physics Standard Product V9r (ACOS_L2S) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2009-04-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1633158704-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1633158704-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2S.v9r", + "description": "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) ", + "license": "not-provided" + }, + { + "id": "ACOS_L2_Lite_FP.v7.3", + "title": "ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V7.3 (ACOS_L2_Lite_FP) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2009-04-21", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230298-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1339230298-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2_Lite_FP.v7.3", + "description": "The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The \"ACOS\" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the \"ACOS\" Level 2 production process.", + "license": "not-provided" + }, + { + "id": "ACOS_L2_Lite_FP.v9r", + "title": "ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V9r (ACOS_L2_Lite_FP) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2009-04-20", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1720416694-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1720416694-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/ACOS_L2_Lite_FP.v9r", + "description": "Version 9r is the current version of the data set. Older versions will no longer be available and are superseded by Version 9r. The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The \"ACOS\" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the \"ACOS\" Level 2 production process.", + "license": "not-provided" + }, { "id": "ACR3L2DM.v1", "title": "ACRIM III Level 2 Daily Mean Data V001", @@ -922,6 +922,19 @@ "description": "Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) is a collection of monthly files (see known issues for gaps) for each year of global emissivity. The ASTER GED data products are generated for 2000 through 2015 using the ASTER Temperature Emissivity Separation (TES) algorithm atmospheric correction method. This algorithm method uses Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheric Profiles product (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) and the MODerate spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model along with the snow cover data from the standard monthly MODIS/Terra snow cover monthly global 0.05 degree product (MOD10CM) (https://doi.org/10.5067/MODIS/MOD10CM.006), and vegetation information from the MODIS monthly gridded NDVI product (MOD13C2) (https://doi.org/10.5067/MODIS/MOD13C2.006). ASTER GED Monthly V041 data products are offered in Hierarchical Data Format 5 (HDF5). The National Aeronautics and Space Administration\u2019s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product.", "license": "not-provided" }, + { + "id": "AIRABRAD.v005", + "title": "AIRS/Aqua L1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005 (AIRABRAD) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2002-05-21", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477366-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477366-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRABRAD.v005", + "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AMSU-A instrument is co-aligned with AIRS so that successive blocks of 3 x 3 AIRS footprints are contained within one AMSU-A footprint. AMSU-A is primarily a temperature sounder that provides atmospheric information in the presence of clouds, which can be used to correct the AIRS infrared measurements for the effects of clouds. This is possible because non-precipitating clouds are for the most part transparent to microwave radiation, in contrast to visible and infrared radiation which are strongly scattered and absorbed by clouds. AMSU-A1 has 13 channels from 50 - 90 GHz and AMSU-A2 has 2 channels from 23 - 32 GHz. The AIRABRAD_005 products are stored in files (often referred to as \"granules\") that contain 6 minutes of data, 30 footprints across track by 45 lines along track.", + "license": "not-provided" + }, { "id": "AIRSAR_INT_JPG.v1", "title": "AIRSAR_ALONGTRACK_INTERFEROMETRY_JPG", @@ -1052,6 +1065,71 @@ "description": "AIRSAR topographic SAR digital elevation model P_Stokes product", "license": "not-provided" }, + { + "id": "AIRSM_CPR_MAT.v3.2", + "title": "AIRS-AMSU variables-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRSM_CPR_MAT) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2006-06-15", + "end_date": "2012-12-14", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224182-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224182-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRSM_CPR_MAT.v3.2", + "description": "This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS/AMSU retrievals at AMSU footprints, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple \"A-train\" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each \"scene\" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time \"matchups\" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRSM_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CH4_total_column|Retrieved total column CH4| (molecules/cm2) CloudFraction|CloudSat/CALIPSO Cloud Fraction| (None) CloudLayers| Number of hydrometeor layers| (count) clrolr|Clear-sky Outgoing Longwave Radiation|(Watts/m**2) CO_total_column|Retrieved total column CO| (molecules/cm2) CPR_Cloud_mask| CPR Cloud Mask |(None) Data_quality| Data Quality |(None) H2OMMRSat|Water vapor saturation mass mixing ratio|(gm/kg) H2OMMRStd|Water Vapor Mass Mixing Ratio |(gm/kg dry air) MODIS_Cloud_Fraction| MODIS 250m Cloud Fraction| (None) MODIS_scene_var |MODIS scene variability| (None) nSurfStd|1-based index of the first valid level|(None) O3VMRStd|Ozone Volume Mixing Ratio|(vmr) olr|All-sky Outgoing Longwave Radiation|(Watts/m**2) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) Sigma-Zero| Sigma-Zero| (dB*100) TAirMWOnlyStd|Atmospheric Temperature retrieved using only MW|(K) TCldTopStd|Cloud top temperature|(K) totH2OStd|Total precipitable water vapor| (kg/m**2) totO3Std|Total ozone burden| (Dobson) TSurfAir|Atmospheric Temperature at Surface|(K) TSurfStd|Surface skin temperature|(K) End of parameter information", + "license": "not-provided" + }, + { + "id": "AIRS_CPR_IND.v4.0", + "title": "AIRS-CloudSat cloud mask and radar reflectivities collocation indexes V4.0 (AIRS_CPR_IND) at GES_DISC", + "catalog": "GES_DISC", + "state_date": "2006-06-15", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224151-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224151-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRS_CPR_IND.v4.0", + "description": "Version 4.1 is the current version of the data set. Previous versions are no longer available and have been superseded by Version 4.1. This is AIRS-AMSU-CloudSat collocation indexes, in netCDF-4 format. These data map CloudSat profile indexes to the collocated AMSU field of views, and AIRS IR footprints, per AIRS 6-min granule time. Hence it can be considered as Level 1. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple \"A-train\" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, & CloudSat), classify each \"scene\" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time \"matchups\" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_IND", + "license": "not-provided" + }, + { + "id": "AIRS_CPR_MAT.v3.2", + "title": "AIRS-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRS_CPR_MAT) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2006-06-15", + "end_date": "2012-12-14", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224153-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1236224153-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRS_CPR_MAT.v3.2", + "description": "This is AIRS-CloudSat collocated subset, in NetCDF-4 format. These data contain collocated: AIRS Level 1b radiances spectra, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple \"A-train\" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each \"scene\" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time \"matchups\" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CldFrcStdErr|Cloud Fraction|(None) CloudLayers| Number of hydrometeor layers| (count) CPR_Cloud_mask| CPR Cloud Mask| (None) DEM_elevation| Digital Elevation Map| (m) dust_flag|Dust Flag|(None) latAIRS|AIRS IR latitude|(deg) Latitude|CloudSat Latitude |(degrees) LayerBase| Height of Layer Base| (m) LayerTop| Height of layer top| (m) lonAIRS|AIRS IR longitude|(deg) Longitude|CloudSat Longitude| (degrees) MODIS_cloud_flag| MOD35_bit_2and3_cloud_flag| (None) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) radiances|Radiances|(milliWatts/m**2/cm**-1/steradian) Sigma-Zero| Sigma-Zero| (dB*100) spectral_clear_indicator|Spectral Clear Indicator|(None) Vertical_binsize|CloudSat vertical binsize| (m) End of parameter information", + "license": "not-provided" + }, + { + "id": "AIRXAMAP.v005", + "title": "AIRS/Aqua Granule map product V005 (AIRXAMAP) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2002-05-21", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1233769004-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1233769004-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRXAMAP.v005", + "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. The AIRS Granule Map Product consists of images of granule coverage in PDF and JPG format. The images are daily ones but updated every 6 minutes to capture any new available granule. Granules are assembled by ascending, descending, in north and south hemisphere, and the maps are in global cylindrical projection and satellite projection for better view.", + "license": "not-provided" + }, + { + "id": "AIRXBCAL.v005", + "title": "AIRS/Aqua L1B Calibration subset V005 (AIRXBCAL) at GES DISC", + "catalog": "GES_DISC", + "state_date": "2002-08-31", + "end_date": "", + "bbox": "-180, -90, 180, 90", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477315-GES_DISC.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1243477315-GES_DISC.html", + "href": "https://cmr.earthdata.nasa.gov/stac/GES_DISC/collections/AIRXBCAL.v005", + "description": "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. AIRS/Aqua Level-1B calibration subset including clear cases, special calibration sites, random nadir spots, and high clouds. The AIRS Visible/Near Infrared (VIS/NIR) level 1B data set contains AIRS visible and near-infrared calibrated and geolocated radiances in W/m^2/micron/steradian. This data set is generated from AIRS level 1A digital numbers (DN), including 4 channels in the 0.4 to 1.0 um region of the spectrum.", + "license": "not-provided" + }, { "id": "AK_AVHRR", "title": "Alaska AVHRR Twice-Monthly Composites", @@ -1143,6 +1221,19 @@ "description": "AM1EPHNE is the Terra Near Real Time (NRT) 2-hour spacecraft Extrapolated ephemeris data file in native format. The file name format is the following: AM1EPHNE.Ayyyyddd.hhmm.vvv.yyyydddhhmmss where from left to right: E = Extrapolated; N = Native format; A = AM1 (Terra); yyyy = data year, ddd = Julian data day, hh = data hour, mm = data minute; vvv = Version ID; yyyy = production year, ddd = Julian production day, hh = production hour, mm = production minute, and ss = production second. Data set information: http://modis.gsfc.nasa.gov/sci_team/", "license": "not-provided" }, + { + "id": "AMZ1-WFI-L4-SR-1", + "title": "AMAZONIA-1/WFI - Level-4-SR - Cloud Optimized GeoTIFF", + "catalog": "INPE", + "state_date": "2024-01-01", + "end_date": "2024-06-09", + "bbox": "-135.151782, -45.613218, 106.18473, 63.78312", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204639-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204639-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/AMZ1-WFI-L4-SR-1", + "description": "AMAZONIA-1/WFI Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG).", + "license": "not-provided" + }, { "id": "APSF", "title": "Aerial Photo Single Frames", @@ -1858,6 +1949,97 @@ "description": "The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Combined ASTER and MODIS Emissivity for Land (CAMEL) dataset provides monthly emissivity uncertainty at 0.05 degree (~5 kilometer) resolution (CAM5K30UC). CAM5K30UC is an estimation of total emissivity uncertainty, comprising 3 independent components of variability: temporal, spatial, and algorithm. Each measure of uncertainty is provided for all 13 hinge points of emissivity and each latitude-longitude point. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/219/cam5k30_v2_user_guide_atbd.pdf). Corresponding emissivity values can be found in the CAM5K30EM data product. Provided in the CAM5K30UC product are layers for algorithm uncertainty, spatial uncertainty, temporal uncertainty, total uncertainty, latitude, longitude, spectral wavelength, CAMEL quality, and total uncertainty quality information. ", "license": "not-provided" }, + { + "id": "CB4-MUX-L4-SR-1", + "title": "CBERS-4/MUX - Level-4-SR - Cloud Optimized GeoTIFF", + "catalog": "INPE", + "state_date": "2016-01-01", + "end_date": "2024-06-09", + "bbox": "-79.392902, -40.793661, 49.863137, 28.185483", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204643-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204643-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/CB4-MUX-L4-SR-1", + "description": "CBERS-4/MUX Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG).", + "license": "not-provided" + }, + { + "id": "CB4-WFI-L4-SR-1", + "title": "CBERS-4/WFI - Level-4-SR - Cloud Optimized GeoTIFF", + "catalog": "INPE", + "state_date": "2016-01-01", + "end_date": "2024-06-09", + "bbox": "-84.468045, -46.643149, 57.533125, 42.454712", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204413-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204413-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/CB4-WFI-L4-SR-1", + "description": "CBERS-4/WFI Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG).", + "license": "not-provided" + }, + { + "id": "CB4A-WFI-L4-SR-1", + "title": "CBERS-4A/WFI - Level-4-SR - Cloud Optimized GeoTIFF", + "catalog": "INPE", + "state_date": "2020-01-01", + "end_date": "2024-06-09", + "bbox": "-81.507167, -38.111915, 51.482289, 39.663251", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204696-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204696-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/CB4A-WFI-L4-SR-1", + "description": "CBERS-4A/WFI Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG).", + "license": "not-provided" + }, + { + "id": "CB4A-WPM-PCA-FUSED-1", + "title": "CBERS-4A/WPM - Multispectral and Panchromatic Bands Fusioned", + "catalog": "INPE", + "state_date": "2023-03-02", + "end_date": "2024-06-16", + "bbox": "-74.678026, -34.572211, -34.099281, 6.02882", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204169-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204169-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/CB4A-WPM-PCA-FUSED-1", + "description": "This collection contains 2 meter high-resolution, RGB products, generated using the Principal Components Fusion (PCA) method, with values coded between 1 and 255, with 0 being reserved for 'No Data'. This product is derived from the original CBERS-4A WPM Level-4 Digital Number with 10 bit of quantization.", + "license": "not-provided" + }, + { + "id": "CBERS-WFI-8D-1", + "title": "CBERS/WFI - Level-4-SR - Data Cube - LCF 8 days", + "catalog": "INPE", + "state_date": "2020-01-01", + "end_date": "2024-05-31", + "bbox": "-76.2226604, -36.733211, -32.761135, 6.013904", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204417-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204417-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/CBERS-WFI-8D-1", + "description": "Earth Observation Data Cube generated from CBERS-4/WFI and CBERS-4A/WFI Level-4 SR products over Brazil extension. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 64 meters of spatial resolution, reprojected and cropped to BDC_LG grid Version 2 (BDC_LG V2), considering a temporal compositing function of 8 days using the Least Cloud Cover First (LCF) best pixel approach.", + "license": "not-provided" + }, + { + "id": "CBERS4-MUX-2M-1", + "title": "CBERS-4/MUX - Level-4-SR - Data Cube - LCF 2 months", + "catalog": "INPE", + "state_date": "2016-01-01", + "end_date": "2024-04-30", + "bbox": "-75.9138367, -34.6755646, -27.9114219, 5.9260044", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204197-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204197-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/CBERS4-MUX-2M-1", + "description": "Earth Observation Data Cube generated from CBERS-4/MUX Level-4 SR product over Brazil extension. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 20 meters of spatial resolution, reprojected and cropped to BDC_MD grid Version 2 (BDC_MD V2), considering a temporal compositing function of 2 months using the Least Cloud Cover First (LCF) best pixel approach.", + "license": "not-provided" + }, + { + "id": "CBERS4-WFI-16D-2", + "title": "CBERS-4/WFI - Level-4-SR - Data Cube - LCF 16 days", + "catalog": "INPE", + "state_date": "2016-01-01", + "end_date": "2024-05-23", + "bbox": "-76.2226604, -36.7332109, -32.7611351, 6.0139036", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204143-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204143-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/CBERS4-WFI-16D-2", + "description": "Earth Observation Data Cube generated from CBERS-4/WFI Level-4 SR product over Brazil extension. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 64 meters of spatial resolution, reprojected and cropped to BDC_LG grid Version 2 (BDC_LG V2), considering a temporal compositing function of 16 days using the Least Cloud Cover First (LCF) best pixel approach.", + "license": "not-provided" + }, { "id": "CDDIS MEASURES products strain rate grids.v1", "title": "CDDIS SESES MEaSUREs products strain rate grids", @@ -2014,19 +2196,6 @@ "description": "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.", "license": "not-provided" }, - { - "id": "CH-OG-1-GPS-10S.v0.0", - "title": "10 sec GPS ground tracking data", - "catalog": "SCIOPS", - "state_date": "2001-05-28", - "end_date": "", - "bbox": "-63.51, -45.69, 170.42, 78.87", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586614-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586614-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/CH-OG-1-GPS-10S.v0.0", - "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)", @@ -2820,19 +2989,6 @@ "description": "The data received from IMS1, HySI which operates in 64 spectral bands in VNIR bands(400-900nm) with 500 meter spatial resolution and swath of 128 kms.", "license": "not-provided" }, - { - "id": "ISERV.v1", - "title": "International Space Station SERVIR Environmental Research and Visualization System V1", - "catalog": "USGS_EROS", - "state_date": "2013-03-27", - "end_date": "", - "bbox": "-180, -90, 180, 90", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1379906336-USGS_EROS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1379906336-USGS_EROS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/USGS_EROS/collections/ISERV.v1", - "description": "Abstract: The ISS SERVIR Environmental Research and Visualization System (ISERV) acquired images of the Earth's surface from the International Space Station (ISS). The goal was to improve automatic image capturing and data transfer. ISERV's main component was the optical assembly which consisted of a 9.25 inch Schmidt-Cassegrain telescope, a focal reducer (field of view enlarger), a digital single lens reflex camera, and a high precision focusing mechanism. A motorized 2-axis pointing mount allowed pointing at targets approximately 23 degrees from nadir in both along- and across-track directions.", - "license": "not-provided" - }, { "id": "KOPRI-KPDC-00000008.v1", "title": "1998 Seismic Data, Antarctica", @@ -3093,6 +3249,19 @@ "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", + "catalog": "LM_FIRMS", + "state_date": "2014-01-28", + "end_date": "", + "bbox": "-180, -80, 180, 80", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1219768065-LM_FIRMS.html", + "href": "https://cmr.earthdata.nasa.gov/stac/LM_FIRMS/collections/MCD14DL_C5_NRT.v005", + "description": "Near Real-Time (NRT) MODIS Thermal Anomalies / Fire locations processed by FIRMS (Fire Information for Resource Management System) - Land Atmosphere Near real time Capability for EOS (LANCE), using swath products (MOD14/MYD14) rather than the tiled MOD14A1 and MYD14A1 products. The thermal anomalies / active fire represent the center of a 1km pixel that is flagged by the MODIS MOD14/MYD14 Fire and Thermal Anomalies algorithm (Giglio 2003) as containing one or more fires within the pixel. This is the most basic fire product in which active fires and other thermal anomalies, such as volcanoes, are identified.MCD14DL are available in the following formats: TXT, SHP, KML, WMS. These data are also provided through the FIRMS Fire Email Alerts. Please note only the TXT and SHP files contain all the attributes.", + "license": "not-provided" + }, { "id": "MIANACP.v1", "title": "MISR Aerosol Climatology Product V001", @@ -3301,32 +3470,6 @@ "description": "MODIS/Aqua Near Real Time (NRT) 5-minute GBAD data in L0 format.", "license": "not-provided" }, - { - "id": "NBII_SAIN2", - "title": "1986-1988 Plot-Transect Installation - Roan Mountain Massif Content Management", - "catalog": "SCIOPS", - "state_date": "1987-01-01", - "end_date": "1988-01-01", - "bbox": "-82.13472, 36.08544, -82.01191, 36.15365", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586476-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586476-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/NBII_SAIN2", - "description": "This data set contains information on a set of transects and plots that were originally installed in 1987 and 1988 on the grassy balds of the Roan Mountain Massif (Round Bald, Engine Gap, Jane Bald, Grassy Ridge, Big Yellow Mountain (also known as Yellow Mountain), Little Hump Mountain, Bradley Gap, and Hump Mountain (also known as Big Hump Mountain). Data collected from the transects and plots were to characterize baseline conditions against which the effects of future vegetation management actions could be evaluated. This legacy dataset contains information on the baseline (pre-management) conditions of the grassy balds based on the field collections and analysis of the data collected at transects and plots installed in 1987 and 1988. More specifically, this legacy dataset contains information on the first vegetation composition analysis and first comprehensive plant inventory conducted on the Roan Mountain grassy bald complex. Information that describes this dataset primarily comes from the following sources: various field reports, memos, letters, grant proposals, hardcopies of the 1987 and 1988 data sheets, photos of the original transects and plots, and interviews with the originators of the transect and plot data. This metadata record documents legacy data to the extent practical, as required by Executive Order 12906, \"Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure\", dated April 11, 1994. Details may be missing, but given the resources available, the information provided herein is as concise as possible at this point in time.", - "license": "not-provided" - }, - { - "id": "NBII_SAIN5", - "title": "1987- 1992 Plot-Transect - Community and Mowing Analysis - Roan Mountain Massif Data", - "catalog": "SCIOPS", - "state_date": "1987-01-01", - "end_date": "1992-01-01", - "bbox": "-82.13472, 36.08544, -82.01191, 36.15365", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586477-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214586477-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/NBII_SAIN5", - "description": "The transects and plots were originally installed in 1987 and 1988 on the grassy balds of the Roan Mountain Massif [Round Bald, Engine Gap, Jane Bald, Grassy Ridge, Big Yellow Mountain (also known as Yellow Mountain), Little Hump Mountain, Bradley Gap, and Hump Mountain (also known as Big Hump Mountain)]. Data collected from the transects were to characterize baseline conditions against which the effects of future vegetation management actions could be evaluated. This legacy data set represents (1) an analysis of data collected from transects and plots that were originally installed in 1987 and 1988 and revisited in 1992, and (2) information on the entry of the 1987, 1988, 1992, 1993, and 1994 data electronically in 1994. Analyses were conducted to document the pre-management conditions of the vegetation on the grassy balds complex of Roan Mountain, and the changes in vegetation on Round Bald and Jane Bald in response to the hand-mowing between 1987-1988 and 1992. This was the second time that a vegetation composition analysis was conducted using the 1987 and 1988 baseline data. Information pertaining to this dataset primarily comes from one report that describes the analyses, electronic files and hardcopies of the raw data, and interviews with the originators of the transect and plot data. This metadata record documents geospatial legacy data to the extent practicable, as required by Executive Order 12906, \"Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure,\" dated April 11, 1994. Details may be missing, but given the resources available, the information provided herein is as concise as possible at this point in time.", - "license": "not-provided" - }, { "id": "NEX-DCP30.v1", "title": "Downscaled 30 Arc-Second CMIP5 Climate Projections for Studies of Climate Change Impacts in the United States", @@ -3353,19 +3496,6 @@ "description": "The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs). The CMIP5 GCM runs were developed in support of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The NEX-GDDP dataset includes downscaled projections for RCP 4.5 and RCP 8.5 from the 21 models and scenarios for which daily scenarios were produced and distributed under CMIP5. Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100. The spatial resolution of the dataset is 0.25 degrees (~25 km x 25 km). The NEX-GDDP dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future global climate patterns at the spatial scale of individual towns, cities, and watersheds. Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run). ", "license": "not-provided" }, - { - "id": "NIPR_UAP_ELF_SYO", - "title": "1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station", - "catalog": "SCIOPS", - "state_date": "2000-01-01", - "end_date": "", - "bbox": "39.6, -69, 39.6, -69", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214590112-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214590112-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/NIPR_UAP_ELF_SYO", - "description": "1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station", - "license": "not-provided" - }, { "id": "NMMIEAI-L2-NRT.v2", "title": "OMPS-NPP L2 NM Aerosol Index swath orbital NRT", @@ -4354,6 +4484,19 @@ "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", + "catalog": "ENVIDAT", + "state_date": "2022-01-01", + "end_date": "2022-01-01", + "bbox": "9.8472494, 46.812044, 9.8472494, 46.812044", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814662-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814662-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/a-numerical-solver-for-heat-and-mass-transport-in-snow-based-on-fenics.v1.0", + "description": "This python code uses the Finite Element library FEniCS (via docker) to solve the one dimensional partial differential equations for heat and mass transfer in snow. The results are written in vtk format. The dataset contains the code and the output data to reproduce the key Figure 5 from the related publication: _Sch\u00fcrholt, K., Kowalski, J., L\u00f6we, H.; Elements of future snowpack modeling - Part 1: A physical instability arising from the non-linear coupling of transport and phase changes, The Cryosphere, 2022_ The code and potential updates can be accessed directly through git via: https://gitlabext.wsl.ch/snow-physics/snowmodel_fenics", + "license": "not-provided" + }, { "id": "a6efcb0868664248b9cb212aba44313d", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from MERIS (ALAMO algorithm), Version 2.2", @@ -4380,6 +4523,19 @@ "description": "The AAMH CPEX dataset contains products obtained from the MetOp-A, MetOp-B, NOAA-18, and NOAA-19 satellites. These data were collected in support of the NASA Convective Processes Experiment (CPEX) field campaign. The CPEX field campaign took place in the North Atlantic-Gulf of Mexico-Caribbean Sea region from 25 May 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.", "license": "not-provided" }, + { + "id": "above-and-below-ground-herbivore-communities-along-elevation.v1.0", + "title": "Above- and below-ground herbivore communities along elevation", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "5.95587, 45.81802, 10.49203, 47.80838", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/above-and-below-ground-herbivore-communities-along-elevation.v1.0", + "description": "Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017. ", + "license": "not-provided" + }, { "id": "aces1am.v1", "title": "ACES Aircraft and Mechanical Data", @@ -4458,6 +4614,58 @@ "description": "The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from the following instruments: Slow/Fast antenna, Electric Field Mill, Optical Pulse Sensors, Searchcoil Magnetometer, Accelerometer, and Gerdien Conductivity Probe. These data were collected at 200KHz from the first 16 telemetry items collected on the aircraft, were initiated by an operator selected trigger (e.g. DOPS), and continued collecting for as long as the trigger continued.", "license": "not-provided" }, + { + "id": "aerosol-data-davos-wolfgang.v1.0", + "title": "Aerosol Data Davos Wolfgang", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "9.853594, 46.835577, 9.853594, 46.835577", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/aerosol-data-davos-wolfgang.v1.0", + "description": "Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 \u2013 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle\u2019s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. ", + "license": "not-provided" + }, + { + "id": "aerosol-data-weissfluhjoch.v1.0", + "title": "Aerosol Data Weissfluhjoch", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "9.806475, 46.832964, 9.806475, 46.832964", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/aerosol-data-weissfluhjoch.v1.0", + "description": "Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 \u2013 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle\u2019s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. ", + "license": "not-provided" + }, + { + "id": "alnus-glutinosa-orientus-ishidae-flavescence-doree.v1.0", + "title": "Alnus glutinosa (L.) Gaertn. and Orientus ishidae (Matsumura, 1902) share phytoplasma genotypes linked to the \u201cFlavescence dor\u00e9e\u201d epidemics", + "catalog": "ENVIDAT", + "state_date": "2021-01-01", + "end_date": "2021-01-01", + "bbox": "8.4484863, 45.8115721, 9.4372559, 46.4586735", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814963-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814963-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/alnus-glutinosa-orientus-ishidae-flavescence-doree.v1.0", + "description": "Flavescence dor\u00e9e (FD) is a grapevine disease caused by associated phytoplasmas (FDp), which are epidemically spread by their main vector Scaphoideus titanus. The possible roles of alternative and secondary FDp plant hosts and vectors have gained interest to better understand the FDp ecology and epidemiology. A survey conducted in the surroundings of a vineyard in the Swiss Southern Alps aimed at studying the possible epidemiological role of the FDp secondary vector Orientus ishidae and the FDp host plant Alnus glutinosa is reported. Data used for the publication. Insects were captured by using a sweeping net (on common alder trees) and yellow sticky traps (Rebell Giallo, Andermatt Biocontrol AG, Switzerland) placed in the vineyard canopy. Insects were later determined and selected for molecular analyses. Grapevines and common alder samples were collected using the standard techniques. The molecular analyses were conducted in order to identify samples infected by the Flavescence dor\u00e9e phytoplasma (16SrV-p) and the Bois Noir phytoplasma (16SrXII-p). A selection of the infected sampled were further characterized by map genotype and sequenced in order to compare the genotypes in insects, grapevines and common alder trees. ", + "license": "not-provided" + }, + { + "id": "alpine3d-simulations-of-future-climate-scenarios-for-graubunden.v1.0", + "title": "Alpine3D simulations of future climate scenarios for Graubunden", + "catalog": "ENVIDAT", + "state_date": "2019-01-01", + "end_date": "2019-01-01", + "bbox": "8.6737061, 46.2216525, 10.6347656, 47.1075228", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814545-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814545-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/alpine3d-simulations-of-future-climate-scenarios-for-graubunden.v1.0", + "description": "This is the simulation dataset from _\"Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland\"_, M. Bavay, T. Gr\u00fcnewald, M. Lehning, Advances in Water Resources __55__, 4-16, 2013 A model study on the impact of climate change on snow cover and runoff has been conducted for the Swiss Canton of Graub\u00fcnden. The model Alpine3D has been forced with the data from 35 Automatic Weather Stations in order to investigate snow and runoff dynamics for the current climate. The data set has then been modified to reflect climate change as predicted for the 2021-2050 and 2070-2095 periods from an ensemble of regional climate models. The predicted changes in snow cover will be moderate for 2021-2050 and become drastic in the second half of the century. Towards the end of the century the snow cover changes will roughly be equivalent to an elevation shift of 800 m. Seasonal snow water equivalents will decrease by one to two thirds and snow seasons will be shortened by five to nine weeks in 2095. Small, higher elevation catchments will show more winter runoff, earlier spring melt peaks and reduced summer runoff. Where glacierized areas exist, the transitional increase in glacier melt will initially offset losses from snow melt. Larger catchments, which reach lower elevations will show much smaller changes since they are already dominated by summer precipitation.", + "license": "not-provided" + }, { "id": "amprimpacts.v1", "title": "Advanced Microwave Precipitation Radiometer (AMPR) IMPACTS", @@ -4537,16 +4745,16 @@ "license": "not-provided" }, { - "id": "blue_ice_core_DML2004_AS", - "title": "101.1 m long horizontal blue ice core collected from Scharffenbergbotnen, DML, Antarctica, in 2003/2004", - "catalog": "SCIOPS", - "state_date": "1970-01-01", - "end_date": "", - "bbox": "-180, -90, 180, -62.83", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214614210-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214614210-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/blue_ice_core_DML2004_AS", - "description": "Horizontal blue ice core collected from the surface of a blue ice area in Scharffenbergbotnen, Heimefrontfjella, DML. Samples were collected in austral summer 2003/2004 and transported to Finland for chemical analyses. The blue ice core is estimated to represent a 1000-year period of climate history 20 - 40 kyr B.P.. The results of the analyses will be available in 2005.", + "id": "ch2014.v1", + "title": "Alpine3D simulations of future climate scenarios CH2014", + "catalog": "ENVIDAT", + "state_date": "2014-01-01", + "end_date": "2014-01-01", + "bbox": "8.227, 46.79959, 8.227, 46.79959", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814657-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789814657-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/ch2014.v1", + "description": "# Overview The CH2014-Impacts initiative is a concerted national effort to describe impacts of climate change in Switzerland quantitatively, drawing on the scientific resources available in Switzerland today. The initiative links the recently developed Swiss Climate Change Scenarios CH2011 with an evolving base of quantitative impact models. The use of a common climate data set across disciplines and research groups sets a high standard of consistency and comparability of results. Impact studies explore the wide range of climatic changes in temperature and precipitation projected in CH2011 for the 21st century, which vary with the assumed global level of greenhouse gases, the time horizon, the underlying climate model, and the geographical region within Switzerland. The differences among climate projections are considered using three greenhouse gas scenarios, three future time periods in the 21st century, and three climate uncertainty levels (Figure 1). Impacts are shown with respect to the reference period 1980-2009 of CH2011, and add to any impacts that have already emerged as a result of earlier climate change. # Experimental Setup Future snow cover changes are simulated with the physics-based model Alpine3D (Lehning et al., 2006). It is applied to two regions: The canton of Graub\u00fcnden and the Aare catchment. These domains are modeled with a Digital Elevation Model (DEM) with a resolution of 200 m \u00d7 200 m. This defines the simulation grid that has to be filled with land cover data and downscaled meteorological input data for each cell for the time period of interest at hourly resolution. The reference data set consists of automatic weather station data. All meteorological input parameters are spatially interpolated to the simulation grid. The reference period comprises only thirteen years (1999\u20132012), because the number of available high elevation weather stations for earlier times is not sufficient to achieve unbiased distribution of the observations with elevation. The model uses projected temperature and precipitation changes for all greenhouse gas scenarios (A1B, A2, and RCP3PD) and CH2011 time periods (2035, 2060, and 2085). # Data Snow cover changes are projected to be relatively small in the near term (2035) (Figure 5.1 top), in particular at higher elevations above 2000 m asl. As shown by Bavay et al. (2013) the spread in projected snow cover for this period is greater between different climate model chains (Chapter 3) than between the reference period and the model chain exhibiting the most moderate change. In the 2085 period much larger changes with the potential to fundamentally transform the snow dominated alpine area become apparent (Figure 5.1 bottom). These changes include a shortening of the snow season by 5\u20139 weeks for the A1B scenario. This is roughly equivalent to an elevation shift of 400\u2013800 m. The slight increase of winter precipitation and therefore snow fall projected in the CH2011 scenarios (with high associated uncertainty) can no longer compensate for the effect of increasing winter temperatures even at high elevations. In terms of Snow Water Equivalents (SWE), the projected reduction is up to two thirds toward the end of the century (2085). A continuous snow cover will be restricted to a shorter time period and/or to regions at increasingly high elevation. In Bern, for example, the number of days per year with at least 5 cm snow depth will decrease by 90% from now 20 days to only 2 days on average. ", "license": "not-provided" }, { @@ -4562,19 +4770,6 @@ "description": "2013 Chesapeake Bay measurements.", "license": "not-provided" }, - { - "id": "darling_sst_82-93", - "title": "1982-1989 and 1993 Seawater Temperatures at the Darling Marine Center", - "catalog": "SCIOPS", - "state_date": "1982-03-01", - "end_date": "1993-12-31", - "bbox": "-71.31, 42.85, -66.74, 47.67", - "url": "https://cmr.earthdata.nasa.gov/search/concepts/C1214621676-SCIOPS.json", - "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C1214621676-SCIOPS.html", - "href": "https://cmr.earthdata.nasa.gov/stac/SCIOPS/collections/darling_sst_82-93", - "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", @@ -4614,6 +4809,19 @@ "description": "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.", "license": "not-provided" }, + { + "id": "envidat-lwf-34.v2019-03-06", + "title": "10-HS Pfynwald", + "catalog": "ENVIDAT", + "state_date": "2019-01-01", + "end_date": "2019-01-01", + "bbox": "7.61211, 46.30279, 7.61211, 46.30279", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815241-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/envidat-lwf-34.v2019-03-06", + "description": "Continuous measurement of soil water content at 10 and 80 cm depth (3 replications) with 10-HS soil moisture probes (Decagon Incorporation, Pullman, WA, USA). ### Purpose: ### Monitoring of the soil water matrix potential ### Paper Citation: ### * Dobbertin, M.; Eilmann, B.; Bleuler, P.; Giuggiola, A.; Graf Pannatier, E.; Landolt, W.; Schleppi, P.; Rigling, A., 2010: Effect of irrigation on needle morphology, shoot and stem growth in a drought-exposed Pinus sylvestris forest. Tree Physiology, 30, 3: 346-360. [doi: 10.1093/treephys/tpp123](http://doi.org/10.1093/treephys/tpp123) ", + "license": "not-provided" + }, { "id": "fife_hydrology_strm_15m_1.v1", "title": "15 Minute Stream Flow Data: USGS (FIFE)", @@ -4822,6 +5030,19 @@ "description": "2014 Lake Erie measurements.", "license": "not-provided" }, + { + "id": "latent-reserves-in-the-swiss-nfi.v1.0", + "title": "'Latent reserves' within the Swiss NFI", + "catalog": "ENVIDAT", + "state_date": "2020-01-01", + "end_date": "2020-01-01", + "bbox": "5.95587, 45.81802, 10.49203, 47.80838", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/latent-reserves-in-the-swiss-nfi.v1.0", + "description": "The files refer to the data used in Portier et al. \"\u2018Latent reserves\u2019: a hidden treasure in National Forest Inventories\" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered \u2018latent reserves\u2019, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Kl\u00f6tzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement. ", + "license": "not-provided" + }, { "id": "law_dome_annual_msa.v1", "title": "150 year MSA sea ice proxy record from Law Dome, Antarctica", @@ -4848,6 +5069,45 @@ "description": "This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757).", "license": "not-provided" }, + { + "id": "mosaic-cbers4-brazil-3m-1", + "title": "CBERS-4/WFI Image Mosaic of Brazil - 3 Months", + "catalog": "INPE", + "state_date": "2020-04-01", + "end_date": "2020-06-30", + "bbox": "-76.6054059, -33.7511817, -27.7877802, 6.3052432", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204634-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204634-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/mosaic-cbers4-brazil-3m-1", + "description": "CBERS-4/WFI image mosaic of Brazil with 64m of spatial resolution. The mosaic was prepared in order to demonstrate the technological capabilities of the Brazil Data Cube project tools. The false color composition is based on the WFI bands 15, 16 and 13 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in April 2020 and ending in June 2020, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 1200 CBERS-4 scenes and was generated based on an existing CBERS-4/WFI image collection.", + "license": "not-provided" + }, + { + "id": "mosaic-cbers4a-paraiba-3m-1", + "title": "CBERS-4A/WFI Image Mosaic of Brazil Para\u00edba State - 3 Months", + "catalog": "INPE", + "state_date": "2020-07-01", + "end_date": "2020-09-30", + "bbox": "-38.8134896, -8.3976443, -34.7223714, -5.87659", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204719-INPE.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C3108204719-INPE.html", + "href": "https://cmr.earthdata.nasa.gov/stac/INPE/collections/mosaic-cbers4a-paraiba-3m-1", + "description": "CBERS-4A/WFI image mosaic of Brazil Para\u00edba State with 55m of spatial resolution. The mosaic was prepared in order to demonstrate the technological capabilities of the Brazil Data Cube project tools. The false color composition is based on the WFI bands 16, 15 and 14 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in July 2020 and ending in September 2020, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 50 CBERS-4A scenes and was generated based on an existing CBERS-4A/WFI image collection.", + "license": "not-provided" + }, + { + "id": "pfynwaldgasexchange.v1.0", + "title": "2013-2020 gas exchange at Pfynwald", + "catalog": "ENVIDAT", + "state_date": "2021-01-01", + "end_date": "2021-01-01", + "bbox": "7.6105556, 46.3001905, 7.6163921, 46.3047564", + "url": "https://cmr.earthdata.nasa.gov/search/concepts/C2789816347-ENVIDAT.json", + "metadata": "https://cmr.earthdata.nasa.gov/search/concepts/C2789816347-ENVIDAT.html", + "href": "https://cmr.earthdata.nasa.gov/stac/ENVIDAT/collections/pfynwaldgasexchange.v1.0", + "description": "Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds. All metadata can be found in the attached documents.", + "license": "not-provided" + }, { "id": "urn:ogc:def:EOP:VITO:VGT_S10.v1", "title": "10 Days Synthesis of SPOT VEGETATION Images (VGT-S10)", diff --git a/nasa_cmr_catalog.tsv b/nasa_cmr_catalog.tsv index d04d7ea98..ae1a1dc82 100644 --- a/nasa_cmr_catalog.tsv +++ b/nasa_cmr_catalog.tsv @@ -1,10 +1,6 @@ id title catalog state_date end_date bbox url description license 0f4324af-fa0a-4aaf-9b97-89a4f3325ce1 DESIS - Hyperspectral Images - Global FEDEO 2018-08-30 -180, -52, 180, 52 https://cmr.earthdata.nasa.gov/search/concepts/C2207458058-FEDEO.json The hyperspectral instrument DESIS (DLR Earth Sensing Imaging Spectrometer) is one of four possible payloads of MUSES (Multi-User System for Earth Sensing), which is mounted on the International Space Station (ISS). DLR developed and delivered a Visual/Near-Infrared Imaging Spectrometer to Teledyne Brown Engineering, which was responsible for integrating the instrument. Teledyne Brown designed and constructed, integrated and tested the platform before delivered to NASA. Teledyne Brown collaborates with DLR in several areas, including basic and applied research for use of data. DESIS is operated in the wavelength range from visible through the near infrared and enables precise data acquisition from Earth's surface for applications including fire-detection, change detection, maritime domain awareness, and atmospheric research. Three product types can be ordered, which are Level 1B (systematic and radiometric corrected), Level 1C (geometrically corrected) and Level 2A (atmospherically corrected). The spatial resolution is about 30m on ground. DESIS is sensitive between 400nm and 1000nm with a spectral resolution of about 3.3nm. DESIS data are delivered in tiles of about 30x30km. For more information concerning DESIS the reader is referred to https://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-13614/ not-provided 11c5f6df1abc41968d0b28fe36393c9d ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 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/C2548143004-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 3 aerosol daily and monthly gridded 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 -12-hourly_interpolated_surface_position_from_buoys 12-Hourly Interpolated Surface Position from Buoys SCIOPS 1979-01-01 2009-12-01 -180, 60, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600619-SCIOPS.json This data set contains Arctic Ocean daily buoy positions interpolated to hours 0Z and 12Z. not-provided -12-hourly_interpolated_surface_velocity_from_buoys 12-Hourly Interpolated Surface Velocity from Buoys SCIOPS 1979-01-01 2009-12-02 -180, 74, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600621-SCIOPS.json This data set contains 12-hourly interpolated surface velocity data from buoys. Point grid: Latitude 74N to 90N - 4 degree increment Longitude 0E to 320E - 20 and 40 degree increment. not-provided -12_hourly_interpolated_surface_air_pressure_from_buoys 12 Hourly Interpolated Surface Air Pressure from Buoys SCIOPS 1979-01-01 2007-11-30 -180, 70, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1214600618-SCIOPS.json Optimally interpolated atmospheric surface pressure over the Arctic Ocean Basin. Temporal format - twice daily (0Z and 12Z) Spatial format - 2 degree latitude x 10 degree longitude - latitude: 70 N - 90 N - longitude: 0 E - 350 E not-provided -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 @@ -44,6 +40,10 @@ ACCLIP_TraceGas_AircraftInSitu_WB57_Data.v1 ACCLIP WB-57 Aircraft In-situ Trace ACEPOL_AircraftRemoteSensing_AirHARP_Data.v1 ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data Version 1 LARC_ASDC 2017-10-18 2020-11-20 -130, 25, -100, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1758588261-LARC_ASDC.json ACEPOL Airborne Hyper Angular Rainbow Polarimeter (AirHARP) Remotely Sensed Data (ACEPOL_AircraftRemoteSensing_AirHARP_Data) are remotely sensed measurements collected by the Airborne Hyper Angular Rainbow Polarimeter (AirHARP) onboard the ER-2 during ACEPOL. In order to improve our understanding of the effect of aerosols on climate and air quality, measurements of aerosol chemical composition, size distribution, height profile, and optical properties are of crucial importance. In terms of remotely sensed instrumentation, the most extensive set of aerosol properties can be obtained by combining passive multi-angle, multi-spectral measurements of intensity and polarization with active measurements performed by a High Spectral Resolution Lidar. During Fall 2017, the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign, jointly sponsored by NASA and the Netherlands Institute for Space Research (SRON), performed aerosol and cloud measurements over the United States from the NASA high altitude ER-2 aircraft. Six instruments were deployed on the aircraft. Four of these instruments were multi-angle polarimeters: the Airborne Hyper Angular Rainbow Polarimeter (AirHARP), the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI), the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) and the Research Scanning Polarimeter (RSP). The other two instruments were lidars: the High Spectral Resolution Lidar 2 (HSRL-2) and the Cloud Physics Lidar (CPL). The ACEPOL operation was based at NASA’s Armstrong Flight Research Center in Palmdale California, which enabled observations of a wide variety of scene types, including urban, desert, forest, coastal ocean and agricultural areas, with clear, cloudy, polluted and pristine atmospheric conditions. The primary goal of ACEPOL was to assess the capabilities of the different polarimeters for retrieval of aerosol and cloud microphysical and optical parameters, as well as their capabilities to derive aerosol layer height (near-UV polarimetry, O2 A-band). ACEPOL also focused on the development and evaluation of aerosol retrieval algorithms that combine data from both active (lidar) and passive (polarimeter) instruments. ACEPOL data are appropriate for algorithm development and testing, instrument intercomparison, and investigations of active and passive instrument data fusion, which is a valuable resource for remote sensing communities as they prepare for the next generation of spaceborne MAP and lidar missions. not-provided ACEPOL_AircraftRemoteSensing_AirSPEX_Data.v1 ACEPOL Airborne Spectrometer for Planetary Exploration (AirSPEX) Remotely Sensed Data Version 1 LARC_ASDC 2017-10-19 2017-11-09 -130, 25, -100, 45 https://cmr.earthdata.nasa.gov/search/concepts/C1758588281-LARC_ASDC.json ACEPOL_AircraftRemoteSensing_AirSPEX_Data are remotely sensed measurements collected by the Airborne Spectrometer for Planetary Exploration (SPEX Airborne) onboard the ER-2 during 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 +ACOS_L2_Lite_FP.v7.3 ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V7.3 (ACOS_L2_Lite_FP) at GES DISC GES_DISC 2009-04-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1339230298-GES_DISC.json "The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process." not-provided +ACOS_L2_Lite_FP.v9r ACOS GOSAT/TANSO-FTS Level 2 bias-corrected XCO2 and other select fields from the full-physics retrieval aggregated as daily files V9r (ACOS_L2_Lite_FP) at GES DISC GES_DISC 2009-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1720416694-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. The ACOS Lite files contain bias-corrected XCO2 along with other select fields aggregated as daily files. Orbital granules of the ACOS Level 2 standard product (ACOS_L2S) are used as input. The ""ACOS"" data set contains Carbon Dioxide (CO2) column averaged dry air mole fraction for all soundings for which retrieval was attempted. These are the highest-level products made available by the OCO Project, using TANSO-FTS spectral radiances. The GOSAT team at JAXA produces GOSAT TANSO-FTS Level 1B (L1B) data products for internal use and for distribution to collaborative partners, such as ESA and NASA. These calibrated products are augmented by the OCO Project with additional geolocation information and further corrections. Thus produced Level 1B products (with calibrated radiances and geolocation) are the input to the ""ACOS"" Level 2 production process." not-provided ACR3L2DM.v1 ACRIM III Level 2 Daily Mean Data V001 LARC 2000-04-05 2013-11-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031504-LARC.json ACR3L2DM_1 is the Active Cavity Radiometer Irradiance Monitor (ACRIM) III Level 2 Daily Mean Data version 1 product consists of Level 2 total solar irradiance in the form of daily means gathered by the ACRIM III instrument on the ACRIMSAT satellite. The daily means are constructed from the shutter cycle results for each day. not-provided ACR3L2SC.v1 ACRIM III Level 2 Shutter Cycle Data V001 LARC 2000-04-05 2013-11-09 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C61787524-LARC.json ACR3L2SC_1 is the Active Cavity Radiometer Irradiance Monitor (ACRIM) III Level 2 Shutter Cycle Data version 1 product contains Level 2 total solar irradiance in the form of shutter cycles gathered by the ACRIM instrument on the ACRIMSAT satellite. not-provided ADAM.Surface.Reflectance.Database ADAM Surface Reflectance Database v4.0 ESA 2005-01-01 2005-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1965336812-ESA.json ADAM enables generating typical monthly variations of the global Earth surface reflectance at 0.1° spatial resolution (Plate Carree projection) and over the spectral range 240-4000nm. The ADAM product is made of gridded monthly mean climatologies over land and ocean surfaces, and of a companion API toolkit that enables the calculation of hyperspectral (at 1 nm resolution over the whole 240-4000 nm spectral range) and multidirectional reflectances (i.e. in any illumination/viewing geometry) depending on user choices. The ADAM climatologies that feed the ADAM calculation tools are: For ocean: monthly chlorophyll concentration derived from SeaWiFS-OrbView-2 (1999-2009); it is used to compute the water column reflectance (which shows large spectral variations in the visible, but is insignificant in the near and mid infrared). monthly wind speed derived from SeaWinds-QuikSCAT-(1999-2009); it is used to calculate the ocean glint reflectance. For land: monthly normalized surface reflectances in the 7 MODIS narrow spectral bands derived from FondsdeSol processing chain of MOD09A1 products (derived from Aqua and Terra observations), on which relies the modelling of the hyperspectral/multidirectional surface (soil/vegetation/snow) reflectance. uncertainty variance-covariance matrix for the 7 spectral bands associated to the normalized surface reflectance. For sea-ice: Sea ice pixels (masked in the original MOD09A1 products) have been accounted for by a gap-filling approach relying on the spatial-temporal distribution of sea ice coverage provided by the CryoClim climatology for year 2005. not-provided @@ -70,6 +70,7 @@ AFOLVIS1A.v1 AfriSAR LVIS L1A Geotagged Images V001 NSIDC_ECS 2016-02-20 2016-03 AG100.v003 ASTER Global Emissivity Dataset, 100 meter, HDF5 V003 LPCLOUD 2000-01-01 2008-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763266348-LPCLOUD.json Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate spectral resolution TRANsmittance (MODTRAN 5.2 radiative transfer model). This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG100 data are available globally at spatial resolution of 100 meters. The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. not-provided AG1km.v003 ASTER Global Emissivity Dataset, 1 kilometer, HDF5 V003 LPCLOUD 2000-01-01 2008-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763266350-LPCLOUD.json Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) land surface temperature and emissivity (LST&E) data products are generated using the ASTER Temperature Emissivity Separation (TES) algorithm with a Water Vapor Scaling (WVS) atmospheric correction method using Moderate Resolution Imaging Spectroradiometer (MODIS) (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) atmospheric profiles and the MODerate Spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model. This dataset is computed from all clear-sky pixels of ASTER scenes acquired from 2000 through 2008. AG1KM data are available globally at spatial resolution of 1 kilometer. The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. not-provided AG5KMMOH.v041 ASTER Global Emissivity Dataset, Monthly, 0.05 deg, HDF5 V041 LPCLOUD 2000-03-01 2015-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763268461-LPCLOUD.json Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Emissivity Dataset (GED) is a collection of monthly files (see known issues for gaps) for each year of global emissivity. The ASTER GED data products are generated for 2000 through 2015 using the ASTER Temperature Emissivity Separation (TES) algorithm atmospheric correction method. This algorithm method uses Moderate Resolution Imaging Spectroradiometer (MODIS) Atmospheric Profiles product (MOD07) (https://modis-atmos.gsfc.nasa.gov/MOD07_L2/index.html) and the MODerate spectral resolution TRANsmittance (MODTRAN) 5.2 radiative transfer model along with the snow cover data from the standard monthly MODIS/Terra snow cover monthly global 0.05 degree product (MOD10CM) (https://doi.org/10.5067/MODIS/MOD10CM.006), and vegetation information from the MODIS monthly gridded NDVI product (MOD13C2) (https://doi.org/10.5067/MODIS/MOD13C2.006). ASTER GED Monthly V041 data products are offered in Hierarchical Data Format 5 (HDF5). The National Aeronautics and Space Administration’s (NASA) Jet Propulsion Laboratory (JPL), California Institute of Technology, developed the ASTER GED product. not-provided +AIRABRAD.v005 AIRS/Aqua L1B AMSU (A1/A2) geolocated and calibrated brightness temperatures V005 (AIRABRAD) at GES DISC GES_DISC 2002-05-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243477366-GES_DISC.json "The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. The AMSU-A instrument is co-aligned with AIRS so that successive blocks of 3 x 3 AIRS footprints are contained within one AMSU-A footprint. AMSU-A is primarily a temperature sounder that provides atmospheric information in the presence of clouds, which can be used to correct the AIRS infrared measurements for the effects of clouds. This is possible because non-precipitating clouds are for the most part transparent to microwave radiation, in contrast to visible and infrared radiation which are strongly scattered and absorbed by clouds. AMSU-A1 has 13 channels from 50 - 90 GHz and AMSU-A2 has 2 channels from 23 - 32 GHz. The AIRABRAD_005 products are stored in files (often referred to as ""granules"") that contain 6 minutes of data, 30 footprints across track by 45 lines along track." not-provided AIRSAR_INT_JPG.v1 AIRSAR_ALONGTRACK_INTERFEROMETRY_JPG ASF 1998-10-25 2004-03-05 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213921626-ASF.json AIRSAR along-track interferometric browse product JPG not-provided AIRSAR_POL_3FP.v1 AIRSAR_POLSAR_3_FREQ_POLARIMETRY ASF 1990-03-02 2004-03-21 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213921661-ASF.json AIRSAR three-frequency polarimetric frame product not-provided AIRSAR_POL_SYN_3FP.v1 AIRSAR_POLSAR_SYNOPTIC_3_FREQ_POLARIMETRY ASF 1990-03-29 1991-07-16 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213928843-ASF.json AIRSAR three-frequency polarimetric synoptic product not-provided @@ -80,6 +81,11 @@ AIRSAR_TOP_DEM_L.v1 AIRSAR_TOPSAR_DEM_L ASF 1993-06-08 2004-12-04 -172.880269, - AIRSAR_TOP_DEM_P.v1 AIRSAR_TOPSAR_DEM_P ASF 1993-06-08 2004-12-04 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213926777-ASF.json AIRSAR topographic SAR digital elevation model PTIF product not-provided AIRSAR_TOP_L-STOKES.v1 AIRSAR_TOPSAR_L-BAND_STOKES ASF 1993-06-08 2004-12-04 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213927939-ASF.json AIRSAR topographic SAR digital elevation model L_Stokes product not-provided AIRSAR_TOP_P-STOKES.v1 AIRSAR_TOPSAR_P-BAND_STOKES ASF 1993-06-08 2004-12-04 -172.880269, -27.388834, -49.704356, 69.25925 https://cmr.earthdata.nasa.gov/search/concepts/C1213928209-ASF.json AIRSAR topographic SAR digital elevation model P_Stokes product not-provided +AIRSM_CPR_MAT.v3.2 AIRS-AMSU variables-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRSM_CPR_MAT) at GES DISC GES_DISC 2006-06-15 2012-12-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236224182-GES_DISC.json "This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS/AMSU retrievals at AMSU footprints, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple ""A-train"" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each ""scene"" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time ""matchups"" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRSM_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CH4_total_column|Retrieved total column CH4| (molecules/cm2) CloudFraction|CloudSat/CALIPSO Cloud Fraction| (None) CloudLayers| Number of hydrometeor layers| (count) clrolr|Clear-sky Outgoing Longwave Radiation|(Watts/m**2) CO_total_column|Retrieved total column CO| (molecules/cm2) CPR_Cloud_mask| CPR Cloud Mask |(None) Data_quality| Data Quality |(None) H2OMMRSat|Water vapor saturation mass mixing ratio|(gm/kg) H2OMMRStd|Water Vapor Mass Mixing Ratio |(gm/kg dry air) MODIS_Cloud_Fraction| MODIS 250m Cloud Fraction| (None) MODIS_scene_var |MODIS scene variability| (None) nSurfStd|1-based index of the first valid level|(None) O3VMRStd|Ozone Volume Mixing Ratio|(vmr) olr|All-sky Outgoing Longwave Radiation|(Watts/m**2) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) Sigma-Zero| Sigma-Zero| (dB*100) TAirMWOnlyStd|Atmospheric Temperature retrieved using only MW|(K) TCldTopStd|Cloud top temperature|(K) totH2OStd|Total precipitable water vapor| (kg/m**2) totO3Std|Total ozone burden| (Dobson) TSurfAir|Atmospheric Temperature at Surface|(K) TSurfStd|Surface skin temperature|(K) End of parameter information" not-provided +AIRS_CPR_IND.v4.0 AIRS-CloudSat cloud mask and radar reflectivities collocation indexes V4.0 (AIRS_CPR_IND) at GES_DISC GES_DISC 2006-06-15 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236224151-GES_DISC.json "Version 4.1 is the current version of the data set. Previous versions are no longer available and have been superseded by Version 4.1. This is AIRS-AMSU-CloudSat collocation indexes, in netCDF-4 format. These data map CloudSat profile indexes to the collocated AMSU field of views, and AIRS IR footprints, per AIRS 6-min granule time. Hence it can be considered as Level 1. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple ""A-train"" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, & CloudSat), classify each ""scene"" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time ""matchups"" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_IND" not-provided +AIRS_CPR_MAT.v3.2 AIRS-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRS_CPR_MAT) at GES DISC GES_DISC 2006-06-15 2012-12-14 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1236224153-GES_DISC.json "This is AIRS-CloudSat collocated subset, in NetCDF-4 format. These data contain collocated: AIRS Level 1b radiances spectra, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project. The basic task is to bring together retrievals of water vapor and cloud properties from multiple ""A-train"" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each ""scene"" (instrument look) using the cloud information, and develop a merged, multi-sensor climatology of atmospheric water vapor as a function of altitude, stratified by the cloud classes. This is a large science analysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, find space/time ""matchups"" between pairs of instruments, and process years of satellite data to produce the climate data records. The short name for this collection is AIRS_CPR_MAT Parameters contained in the data files include the following: Variable Name|Description|Units CldFrcStdErr|Cloud Fraction|(None) CloudLayers| Number of hydrometeor layers| (count) CPR_Cloud_mask| CPR Cloud Mask| (None) DEM_elevation| Digital Elevation Map| (m) dust_flag|Dust Flag|(None) latAIRS|AIRS IR latitude|(deg) Latitude|CloudSat Latitude |(degrees) LayerBase| Height of Layer Base| (m) LayerTop| Height of layer top| (m) lonAIRS|AIRS IR longitude|(deg) Longitude|CloudSat Longitude| (degrees) MODIS_cloud_flag| MOD35_bit_2and3_cloud_flag| (None) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) radiances|Radiances|(milliWatts/m**2/cm**-1/steradian) Sigma-Zero| Sigma-Zero| (dB*100) spectral_clear_indicator|Spectral Clear Indicator|(None) Vertical_binsize|CloudSat vertical binsize| (m) End of parameter information" not-provided +AIRXAMAP.v005 AIRS/Aqua Granule map product V005 (AIRXAMAP) at GES DISC GES_DISC 2002-05-21 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1233769004-GES_DISC.json The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. An AIRS granule has been set as 6 minutes of data, 30 footprints cross track by 45 lines along track. The AIRS Granule Map Product consists of images of granule coverage in PDF and JPG format. The images are daily ones but updated every 6 minutes to capture any new available granule. Granules are assembled by ascending, descending, in north and south hemisphere, and the maps are in global cylindrical projection and satellite projection for better view. not-provided +AIRXBCAL.v005 AIRS/Aqua L1B Calibration subset V005 (AIRXBCAL) at GES DISC GES_DISC 2002-08-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1243477315-GES_DISC.json The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer (R = 1200) aboard the second Earth Observing System (EOS) polar-orbiting platform, EOS Aqua. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. AIRS/Aqua Level-1B calibration subset including clear cases, special calibration sites, random nadir spots, and high clouds. The AIRS Visible/Near Infrared (VIS/NIR) level 1B data set contains AIRS visible and near-infrared calibrated and geolocated radiances in W/m^2/micron/steradian. This data set is generated from AIRS level 1A digital numbers (DN), including 4 channels in the 0.4 to 1.0 um region of the spectrum. not-provided AK_AVHRR Alaska AVHRR Twice-Monthly Composites USGS_LTA 1990-06-16 -179, 51, -116, 70 https://cmr.earthdata.nasa.gov/search/concepts/C1220565954-USGS_LTA.json The goal of the Alaska Advanced Very High Resolution Radiometer (AVHRR) project is to compile a time series data set of calibrated, georegistered daily observations and twice-monthly maximum normalized difference vegetation index (NDVI) composites for Alaska's annual growing season (April-October). This data set has applications for environmental monitoring and for assessing impacts of global climate change. An Alaska AVHRR data set is comprised of twice-monthly maximum NDVI composites of daily satellite observations. The NDVI composites contain 10 bands of information, including AVHRR channels 1-5, maximum NDVI, satellite zenith, solar zenith, and relative azimuth. The daily observations, bands 1-9, have been calibrated to reflectance, scaled to byte data, and geometrically registered to the Albers Equal-Area Conic map projection. The 10th band is a pointer to identify the date and scene ID of the source daily observation (scene) for each pixel. The compositing process required each daily overpass to be registered to a common map projection to ensure that from day to day each 1-km pixel represented the exact same ground location. The Albers Equal-Area Conic map projection provides for equal area representation, which enables easy measurement of area throughout the data. Each daily observation for the growing season was registered to a base image using image-to-image correlation. The NDVI data are calculated from the calibrated, geometrically registered daily observations. The NDVI value is the difference between near-infrared (AVHRR Channel 2) and visible (AVHRR Channel 1) reflectance values divided by total measured reflectance. A maximum NDVI compositing process was used on the daily observations. The NDVI is examined pixel by pixel for each observation during the compositing period to determine and retain the maximum value. Often when displaying data covering large areas, such as AVHRR data, it is beneficial to include an overlay of either familiar linework for reflectance or polygon data sets to derive statistical summaries of regions. All of the linework images represent lines in raster format as 1-km cells and the strata are represented as polygons registered to the AVHRR data. The linework and polygon data sets include international boundaries, Alaskan roads with the Trans-Alaska Pipeline, and a raster polygon mask of the State. not-provided ALOS Alos African Coverage ESA archive ESA 2006-07-09 2009-05-12 -26, -37, 53, 37 https://cmr.earthdata.nasa.gov/search/concepts/C1965336815-ESA.json ALOS Africa is a dataset of the best available (cloud minimal, below 10%) African coverage acquired by AVNIR-2 in OBS mode and PRISM in OB1 mode (all Backward, Nadir and Forward views, in separated products), two different collections one for each instrument. The processing level for both AVNIR-2 and PRISM products is L1B. not-provided ALOS.AVNIR-2.L1C ALOS AVNIR-2 L1C ESA 2006-04-28 2011-04-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689548-ESA.json This collection is providing access to the ALOS-1 AVNIR-2 (Advanced Visible and Near Infrared Radiometer type 2) L1C data acquired by ESA stations in the ADEN zone plus some worldwide data requested by European scientists. The ADEN zone (https://earth.esa.int/eogateway/documents/20142/37627/ALOS-ADEN-Zone.pdf) was the area belonging to the European Data node and covered both the European and the African continents, large part of the Greenland and the Middle East. The full mission is covered, obviously with gaps outside to the ADEN zone: • Time windows: from 2006-04-28 to 2011-04-20 • Orbits: from 1375 to 27898 • Path (corresponds to JAXA track number): from 1 to 670 • Row (corresponds to JAXA scene centre frame number): from 370 to 5230 One single Level 1C product types is offered for the OBS instrument mode: AV2_OBS_1C. not-provided @@ -87,6 +93,7 @@ ALOS.PALSAR.FBS.FBD.PLR.products ALOS PALSAR products ESA 2006-05-02 2011-04-14 ALOSIPY ALOS PALSAR International Polar Year Antarctica ESA 2008-07-25 2010-03-31 -180, -90, 180, -50 https://cmr.earthdata.nasa.gov/search/concepts/C1965336817-ESA.json International Polar Year (IPY), focusing on the north and south polar regions, aimed to investigate the impact of how changes to the ice sheets affect ocean and climate change to the habitats in these regions. IPY was a collaborative project involving over sixty countries for two years from March 2007 to March 2009. To meet the project goal, world space agencies observed these regions intensively using their own Earth observation satellites. One of these satellites, ALOS - with the PALSAR (Phased Array type L-band Synthetic Aperture Radar) sensor - observed these regions independently from day-night conditions or weather conditions. Carrying on this initiative, ESA is providing the ALOS PALSAR IPY Antarctica dataset, which consists of full resolution ALOS PALSAR ScanSAR WB1 products (100m spatial resolution) over Antarctica from July 2008 (cycle 21) to December 2008 (Cycle 24) and from May 2009 (cycle 27) to March 2010 (cycle 31). Missing products between the two periods above is due to L0 data over Antarctica not being available in ADEN archives and not processed to L1. Spatial coverage: Check the spatial coverage of the collection on a _$$map$$ https://tpm-ds.eo.esa.int/smcat/ALOSIPY/ available on the Third Party Missions Dissemination Service. not-provided ALOS_PRISM_L1B Alos PRISM L1B ESA 2006-07-09 2011-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2119689640-ESA.json This collection provides access to the ALOS-1 PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) L1B data acquired by ESA stations in the ADEN zone plus some data requested by European scientists over their areas of interest around the world. The ADEN zone (https://earth.esa.int/eogateway/documents/20142/37627/ALOS-ADEN-Zone.pdf) was the area belonging to the European Data node and covered both the European and African continents, a large part of Greenland and the Middle East. The full mission is covered, though with gaps outside of the ADEN zone: Time window: from 2006-07-09 to 2011-03-31 Orbits: from 2425 to 24189 Path (corresponds to JAXA track number): from 1 to 668 Row (corresponds to JAXA scene centre frame number): from 55 to 7185. Two different Level 1B product types (Panchromatic images in VIS-NIR bands, 2.5 m resolution at nadir) are offered, one for each available sensor mode: PSM_OB1_11 -> composed of up to three views; Nadir, Forward and Backward at 35 km swath PSM_OB2_11 -> composed of up to two views; Nadir view at 70 km width and Backward view at 35 km width. All ALOS PRISM EO-SIP products have, at least, the Nadir view which is used for the frame number identification. All views are packaged together; each view, in CEOS format, is stored in a directory named according to the view ID according to the JAXA naming convention. not-provided AM1EPHNE.v6.1NRT Files containing only extrapolated orbital metadata, to be read via SDP Toolkit, Binary Format LANCEMODIS 2016-01-24 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1426293893-LANCEMODIS.json AM1EPHNE is the Terra Near Real Time (NRT) 2-hour spacecraft Extrapolated ephemeris data file in native format. The file name format is the following: AM1EPHNE.Ayyyyddd.hhmm.vvv.yyyydddhhmmss where from left to right: E = Extrapolated; N = Native format; A = AM1 (Terra); yyyy = data year, ddd = Julian data day, hh = data hour, mm = data minute; vvv = Version ID; yyyy = production year, ddd = Julian production day, hh = production hour, mm = production minute, and ss = production second. Data set information: http://modis.gsfc.nasa.gov/sci_team/ not-provided +AMZ1-WFI-L4-SR-1 AMAZONIA-1/WFI - Level-4-SR - Cloud Optimized GeoTIFF INPE 2024-01-01 2024-06-09 -135.151782, -45.613218, 106.18473, 63.78312 https://cmr.earthdata.nasa.gov/search/concepts/C3108204639-INPE.json AMAZONIA-1/WFI Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG). not-provided APSF Aerial Photo Single Frames USGS_LTA 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220567654-USGS_LTA.json The Aerial Photography Single Frame Records collection is a large and diverse group of imagery acquired by Federal organizations from 1937 to the present. Over 6.4 million frames of photographic images are available for download as medium and high resolution digital products. The high resolution data provide access to photogrammetric quality scans of aerial photographs with sufficient resolution to reveal landscape detail and to facilitate the interpretability of landscape features. Coverage is predominantly over the United States and includes portions of Central America and Puerto Rico. Individual photographs vary in scale, size, film type, quality, and coverage. not-provided AQUARIUS_ANCILLARY_CELESTIALSKY_V1.v1 Aquarius Celestial Sky Microwave Emission Map Ancillary Dataset V1.0 POCLOUD 2011-09-01 2015-06-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2617176761-POCLOUD.json "This datasets contains three maps of L-band (wavelength = 21 cm) brightness temperature of the celestial sky (""Galaxy"") used in the processing of the NASA Aquarius instrument data. The maps report Sky brightness temperatures in Kelvin gridded on the Earth Centered Inertial (ECI) reference frame epoch J2000. They are sampled over 721 Declinations between -90 degrees and +90 degrees and 1441 Right Ascensions between 0 degrees and 360 degrees, all evenly spaced at 0.25 degrees intervals. The brightness temperatures are assumed temporally invariant and polarization has been neglected. They include microwave continuum and atomic hydrogen line (HI) emissions. The maps differ only in how the strong radio source Cassiopeia A has been included into the whole sky background surveys: 1/ TB_no_Cas_A does not include Cassiopeia A and reports only the whole Sky surveys. 2/ TB_Cas_A_1cell spread Cas A total flux homogeneously over 1 map grid cell (i.e. 9.8572E-6 sr). 3/ TB_Cas_A_beam spreads Cas A over surrounding grid cells using a convolution by a Gaussian beam with HPBW of 35 arcmin (equivalent to the instrument used for the Sky surveys). Cassiopeia A is a supernova remnant (SNR) in the constellation Cassiopeia and the brightest extra-solar radio source in the sky at frequencies above 1." not-provided AQUARIUS_L2_SSS_CAP_V5.v5.0 Aquarius CAP Level 2 Sea Surface Salinity, Wind Speed & Direction Data V5.0 POCLOUD 2011-08-26 2015-06-05 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2205121315-POCLOUD.json The version 5.0 Aquarius CAP Level 2 product contains the fourth release of the AQUARIUS/SAC-D orbital/swath data based on the Combined Active Passive (CAP) algorithm. CAP is a P.I. produced dataset developed and provided by JPL. This Level 2 dataset contains sea surface salinity (SSS), wind speed and wind direction data derived from 3 different radiometers and the onboard scatterometer. The CAP algorithm simultaneously retrieves the 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. Each L2 data file covers one 98 minute orbit. 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 @@ -142,6 +149,13 @@ C1_PANF_STUC00GTD.v1 Cartosat-1 PANF Standard Products ISRO 2005-08-05 -180, -9 CAM5K30CF.v002 Combined ASTER and MODIS Emissivity database over Land (CAMEL) Coefficient Monthly Global 0.05Deg V002 LPCLOUD 2000-04-01 2017-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763266335-LPCLOUD.json The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Combined ASTER and MODIS Emissivity for Land (CAMEL) dataset provides monthly coefficients at 0.05 degree (~5 kilometer) resolution (CAM5K30CF). The CAMEL Principal Components Analysis (PCA) input coefficients utilized in the CAMEL high spectral resolution (HSR) algorithm are provided in the CAM5K30CF data product and are congruent to the temporally equivalent CAM5K30EM emissivity data product. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/219/cam5k30_v2_user_guide_atbd.pdf). Provided in the CAM5K30CF product are layers for PCA coefficients, number of PCA coefficients, laboratory version, snow fraction derived from MODIS Snow Cover data (MOD10), latitude, longitude, and the CAMEL quality information. PCA coefficients are dependent on the version of lab PC data and number of PCs used. not-provided CAM5K30EM.v002 Combined ASTER and MODIS Emissivity database over Land (CAMEL) Emissivity Monthly Global 0.05Deg V002 LPCLOUD 2000-04-01 2017-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763266338-LPCLOUD.json The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Combined ASTER and MODIS Emissivity for Land (CAMEL) dataset provides monthly emissivity at 0.05 degree (~5 kilometer) resolution (CAM5K30EM). The CAM5K30EM data product was created by combining the University of Wisconsin-Madison MODIS Infrared Emissivity dataset (UWIREMIS) and the Jet Propulsion Laboratory ASTER Global Emissivity Dataset Version 4 (GED V4). The two datasets have been integrated to capitalize on the unique strengths of each product's characteristics. The integration steps include: adjustment of ASTER GED Version 3 emissivities for vegetation and snow cover variations to produce ASTER GED Version 4, aggregation of ASTER GED Version 4 emissivities from 100 meter resolution to the University of Wisconsin-Madison MODIS Baseline Fit (UWBF) 5 kilometer resolution, merging of the 5 ASTER spectral emissivities with the UWBF emissivity to create CAMEL at 13 hinge points, and extension of the 13 hinge points to high spectral resolution (HSR) utilizing the Principal Component (PC) regression method. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/219/cam5k30_v2_user_guide_atbd.pdf). Provided in the CAM5K30EM product are layers for the CAMEL emissivity, ASTER Normalized Difference Vegetation Index (NDVI), snow fraction derived from MODIS (MOD10), latitude, longitude, CAMEL quality, ASTER quality, and Best Fit Emissivity (BFE) quality information. not-provided CAM5K30UC.v002 Combined ASTER and MODIS Emissivity database over Land (CAMEL) Uncertainty Monthly Global 0.05Deg V002 LPCLOUD 2000-04-01 2017-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2763266343-LPCLOUD.json The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) (https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects) Combined ASTER and MODIS Emissivity for Land (CAMEL) dataset provides monthly emissivity uncertainty at 0.05 degree (~5 kilometer) resolution (CAM5K30UC). CAM5K30UC is an estimation of total emissivity uncertainty, comprising 3 independent components of variability: temporal, spatial, and algorithm. Each measure of uncertainty is provided for all 13 hinge points of emissivity and each latitude-longitude point. Additional details regarding the methodology are available in the User Guide and Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/219/cam5k30_v2_user_guide_atbd.pdf). Corresponding emissivity values can be found in the CAM5K30EM data product. Provided in the CAM5K30UC product are layers for algorithm uncertainty, spatial uncertainty, temporal uncertainty, total uncertainty, latitude, longitude, spectral wavelength, CAMEL quality, and total uncertainty quality information. not-provided +CB4-MUX-L4-SR-1 CBERS-4/MUX - Level-4-SR - Cloud Optimized GeoTIFF INPE 2016-01-01 2024-06-09 -79.392902, -40.793661, 49.863137, 28.185483 https://cmr.earthdata.nasa.gov/search/concepts/C3108204643-INPE.json CBERS-4/MUX Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG). not-provided +CB4-WFI-L4-SR-1 CBERS-4/WFI - Level-4-SR - Cloud Optimized GeoTIFF INPE 2016-01-01 2024-06-09 -84.468045, -46.643149, 57.533125, 42.454712 https://cmr.earthdata.nasa.gov/search/concepts/C3108204413-INPE.json CBERS-4/WFI Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG). not-provided +CB4A-WFI-L4-SR-1 CBERS-4A/WFI - Level-4-SR - Cloud Optimized GeoTIFF INPE 2020-01-01 2024-06-09 -81.507167, -38.111915, 51.482289, 39.663251 https://cmr.earthdata.nasa.gov/search/concepts/C3108204696-INPE.json CBERS-4A/WFI Surface Reflectance product over Brazil. L4 SR product provides orthorectified surface reflectance images. This dataset is provided as Cloud Optimized GeoTIFF (COG). not-provided +CB4A-WPM-PCA-FUSED-1 CBERS-4A/WPM - Multispectral and Panchromatic Bands Fusioned INPE 2023-03-02 2024-06-16 -74.678026, -34.572211, -34.099281, 6.02882 https://cmr.earthdata.nasa.gov/search/concepts/C3108204169-INPE.json This collection contains 2 meter high-resolution, RGB products, generated using the Principal Components Fusion (PCA) method, with values coded between 1 and 255, with 0 being reserved for 'No Data'. This product is derived from the original CBERS-4A WPM Level-4 Digital Number with 10 bit of quantization. not-provided +CBERS-WFI-8D-1 CBERS/WFI - Level-4-SR - Data Cube - LCF 8 days INPE 2020-01-01 2024-05-31 -76.2226604, -36.733211, -32.761135, 6.013904 https://cmr.earthdata.nasa.gov/search/concepts/C3108204417-INPE.json Earth Observation Data Cube generated from CBERS-4/WFI and CBERS-4A/WFI Level-4 SR products over Brazil extension. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 64 meters of spatial resolution, reprojected and cropped to BDC_LG grid Version 2 (BDC_LG V2), considering a temporal compositing function of 8 days using the Least Cloud Cover First (LCF) best pixel approach. not-provided +CBERS4-MUX-2M-1 CBERS-4/MUX - Level-4-SR - Data Cube - LCF 2 months INPE 2016-01-01 2024-04-30 -75.9138367, -34.6755646, -27.9114219, 5.9260044 https://cmr.earthdata.nasa.gov/search/concepts/C3108204197-INPE.json Earth Observation Data Cube generated from CBERS-4/MUX Level-4 SR product over Brazil extension. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 20 meters of spatial resolution, reprojected and cropped to BDC_MD grid Version 2 (BDC_MD V2), considering a temporal compositing function of 2 months using the Least Cloud Cover First (LCF) best pixel approach. not-provided +CBERS4-WFI-16D-2 CBERS-4/WFI - Level-4-SR - Data Cube - LCF 16 days INPE 2016-01-01 2024-05-23 -76.2226604, -36.7332109, -32.7611351, 6.0139036 https://cmr.earthdata.nasa.gov/search/concepts/C3108204143-INPE.json Earth Observation Data Cube generated from CBERS-4/WFI Level-4 SR product over Brazil extension. This dataset is provided in Cloud Optimized GeoTIFF (COG) file format. The dataset is processed with 64 meters of spatial resolution, reprojected and cropped to BDC_LG grid Version 2 (BDC_LG V2), considering a temporal compositing function of 16 days using the Least Cloud Cover First (LCF) best pixel approach. not-provided CDDIS MEASURES products strain rate grids.v1 CDDIS SESES MEaSUREs products strain rate grids CDDIS 1992-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2978524117-CDDIS.json Making Earth System Data Records for Use in Research Environments (MEaSUREs) empowers the research community to participate in developing and generating data products that complement and augment NASA produced and distributed Earth science data products. NASA’s Enhanced Solid Earth Science Earth Science Data Record (ESDR) System (ESESES) continues and extends mature geodetic data product generation and archival as part of the MEaSUREs SESES project providing new, multi-decade, calibrated and validated geodetic-derived ESDRs obtained by the Scripps Institution of Oceanography (SIO) and NASA's Jet Propulsion Laboratory (JPL). These data-derived products include continuous multi-year high-rate GNSS, seismogeodetic, and meteorological time series, a catalog of transient deformation in tectonically active areas known for aseismic motion such as ETS with focus in Cascadia, and continuous estimation and cataloging of total near-surface water content derived from continuous GNSS time series over the continental U.S. not-provided CDDIS MEaSURES products velocities.v1 CDDIS SESES MEaSUREs products velocities CDDIS 1992-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2978562718-CDDIS.json Making Earth System Data Records for Use in Research Environments (MEaSUREs) empowers the research community to participate in developing and generating data products that complement and augment NASA produced and distributed Earth science data products. NASA’s Enhanced Solid Earth Science Earth Science Data Record (ESDR) System (ESESES) continues and extends mature geodetic data product generation and archival as part of the MEaSUREs SESES project providing new, multi-decade, calibrated and validated geodetic-derived ESDRs obtained by the Scripps Institution of Oceanography (SIO) and NASA's Jet Propulsion Laboratory (JPL). These data-derived products include continuous multi-year high-rate GNSS, seismogeodetic, and meteorological time series, a catalog of transient deformation in tectonically active areas known for aseismic motion such as ETS with focus in Cascadia, and continuous estimation and cataloging of total near-surface water content derived from continuous GNSS time series over the continental U.S. not-provided CDDIS_GNSS_products_IGS20.v1 CDDIS GNSS ITRF2020 IGS products (IGS20) CDDIS 1983-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2433571719-CDDIS.json These data-derived products are the International GNSS Service (IGS) Analysis Centers' (AC) contribution to the International Terrestrial Reference Frame (ITRF) 2020. not-provided @@ -154,7 +168,6 @@ CDDIS_MEASURES_products_transients.v1 CDDIS SESES MEaSUREs products plate bounda CDDIS_MEASURES_products_water_storage.v1 CDDIS SESES MEaSUREs products total water storage time series CDDIS 1992-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2042453960-CDDIS.json Making Earth System Data Records for Use in Research Environments (MEaSUREs) empowers the research community to participate in developing and generating data products that complement and augment NASA produced and distributed Earth science data products. NASA’s Enhanced Solid Earth Science Earth Science Data Record (ESDR) System (ESESES) continues and extends mature geodetic data product generation and archival as part of the MEaSUREs SESES project providing new, multi-decade, calibrated and validated geodetic-derived ESDRs obtained by the Scripps Institution of Oceanography (SIO) and NASA's Jet Propulsion Laboratory (JPL). These data-derived products include continuous multi-year high-rate GNSS, seismogeodetic, and meteorological time series, a catalog of transient deformation in tectonically active areas known for aseismic motion such as ETS with focus in Cascadia, and continuous estimation and cataloging of total near-surface water content derived from continuous GNSS time series over the continental U.S. These data products are grids of changes in total water storage over the continental U.S.; continuous estimation and cataloging of total near-surface water content derived from continuous GNSS time series over the continental U.S. not-provided 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 @@ -216,7 +229,6 @@ GreenBay.v0 2010 Measurements made in Green Bay, Wisconsin OB_DAAC 2010-09-17 - IKONOS_MSI_L1B.v1 IKONOS Level 1B Multispectral 4-Band Satellite Imagery CSDA 1999-10-14 2015-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497453433-CSDA.json The IKONOS Level 1B Multispectral 4-Band Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This satellite imagery is in the visible and near-infrared waveband range with data in the blue, green, red, and near-infrared wavelengths. The spatial resolution is 3.2m at nadir and the temporal resolution is approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided IKONOS_Pan_L1B.v1 IKONOS Level 1B Panchromatic Satellite Imagery CSDA 1999-10-24 2015-03-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2497468825-CSDA.json The IKONOS Panchromatic Imagery collection contains satellite imagery acquired from Maxar Technologies (formerly known as DigitalGlobe) by the Commercial Smallsat Data Acquisition (CSDA) Program. Imagery was collected by the IKONOS satellite using the Optical Sensor Assembly instrument across the global land surface from October 1999 to March 2015. This data product includes panchromatic imagery with a spatial resolution of 0.82m at nadir and a temporal resolution of approximately 3 days. The data are provided in National Imagery Transmission Format (NITF) and GeoTIFF formats. This level 1B data is sensor corrected and is an un-projected (raw) product. The data potentially serve a wide variety of applications that require high resolution imagery. Data access is restricted based on a National Geospatial-Intelligence Agency (NGA) license, and investigators must be approved by the CSDA Program. not-provided IMS1_HYSI_GEO.v1.0 IMS-1 HYSI TOA Radiance and Reflectance Product ISRO 2008-06-22 2012-09-10 -6.0364, -78.8236, 152.6286, 78.6815 https://cmr.earthdata.nasa.gov/search/concepts/C1214622602-ISRO.json The data received from IMS1, HySI which operates in 64 spectral bands in VNIR bands(400-900nm) with 500 meter spatial resolution and swath of 128 kms. not-provided -ISERV.v1 International Space Station SERVIR Environmental Research and Visualization System V1 USGS_EROS 2013-03-27 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1379906336-USGS_EROS.json Abstract: The ISS SERVIR Environmental Research and Visualization System (ISERV) acquired images of the Earth's surface from the International Space Station (ISS). The goal was to improve automatic image capturing and data transfer. ISERV's main component was the optical assembly which consisted of a 9.25 inch Schmidt-Cassegrain telescope, a focal reducer (field of view enlarger), a digital single lens reflex camera, and a high precision focusing mechanism. A motorized 2-axis pointing mount allowed pointing at targets approximately 23 degrees from nadir in both along- and across-track directions. not-provided KOPRI-KPDC-00000008.v1 1998 Seismic Data, Antarctica AMD_KOPRI 1998-12-07 1998-12-11 -66.266667, -64.616667, -64.416667, -62.995 https://cmr.earthdata.nasa.gov/search/concepts/C2244292774-AMD_KOPRI.json "Korean Antarctic survey carried out as part of step 2 project in year 2 of 'the Antarctic Undersea Geological Survey' was conducted in the Ⅱ region around the northwestern continent of the Antarctic Peninsula. This area is northwest of Anvers Island, including areas around the pericontinent from the continental shelf to the continental rise zone. The investigation period for this project took a total of 8 days for moving navigation, the survey of the side lines and drilling investigation. After seismic investigation, a surface drilling investigation was conducted in coring point was decided from the reference seismic section. 10 researcher from ‘Korea Ocean Research and Development Institute’ participated in the field survey. We took on lease Russian icebreaker ""Yuzhmorgeologiya""." not-provided KOPRI-KPDC-00000009.v1 1997 Seismic Data, Antarctica AMD_KOPRI 1997-12-23 1997-12-28 -64.699722, -63.525, -62.157778, -62.041389 https://cmr.earthdata.nasa.gov/search/concepts/C2244293126-AMD_KOPRI.json Korean Antarctic survey carried out as part of step 2 project in year 1 of ‘The Antarctic Undersea Geological Survey’ in 1997 was conducted in a continental shelf in the northwestern part of the Antarctic Peninsula. The research period took a total of 8 days, including 6 days for the seismic survey and 2 days for the drilling investigation. We took on lease Norway R/V 'Polar Duke' and 10 researchers from ‘Korea Ocean Research and Development Institute’ participated as field investigation personnel. The Teac single-channel recorder, EPC Recorder, Q/C MicroMax system etc. was used mainly by Sleeve gun used as a sound source, compressor for creating compressed air, DFS-V Recorder for multi-channel Seismic record, 12 –channel geophone of seismic streamers. Additional Gravity Core was used for sediment research through drilling. not-provided KOPRI-KPDC-00000011.v1 1996 Seismic Data, Antarctica AMD_KOPRI 1996-12-17 1996-12-26 -62.766667, -63.583333, -60.233333, -62.733333 https://cmr.earthdata.nasa.gov/search/concepts/C2244293499-AMD_KOPRI.json "Korean Antarctic survey carried out as in year 3 project of 'the Antarctic Undersea Geological Survey' was conducted in the basin region of western part of the Bransfeed Strait between the Antarctic Peninsula and the South Shetland Islands . During the field investigation, the seismic investigation and the drilling investigation was conducted at the same time. The investigation period took 9 days. 10 researchers from ‘Korea Ocean Research and Development Institute’ and 3 academic personnel participated in the cruise as field investigation personnel. We took on lease Russian R/V ""Yuzhmorgeologiya"" which is marine geology, geophysical survey vessel and Icebreaker." not-provided @@ -237,6 +249,7 @@ Leaf_Photosynthesis_Traits_1224.v1 A Global Data Set of Leaf Photosynthetic Rate 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 MIANCARP.v2 MISR Ancillary Radiometric Product V002 LARC 1999-12-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C179031521-LARC.json MIANCARP_2 is the Multi-angle Imaging SpectroRadiometer (MISR) Ancillary Radiometric Product version 2. It is composed of 4 files covering instrument characterization data, pre-flight calibration data, in-flight calibration data, and configuration parameters. The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward, and four cameras pointing aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm. not-provided @@ -253,11 +266,8 @@ MYD04_L2.v6.1NRT MODIS/Aqua Aerosol 5-Min L2 Swath 10km - NRT LANCEMODIS 2017-10 MYD09.v6.1NRT MODIS/Aqua Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km NRT LANCEMODIS 2021-02-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2007652303-LANCEMODIS.json The MODIS/Aqua Atmospherically Corrected Surface Reflectance 5-Min L2 Swath 250m, 500m, 1km NRT, short name MYD09, is computed from the MODIS Level 1B land bands 1, 2, 3, 4, 5, 6, and 7 (centered at 648 nm, 858 nm, 470 nm, 555 nm, 1240 nm, 1640 nm, and 2130 nm, respectively). The product is an estimate of the surface spectral reflectance for each band as it would have been measured at ground level if there were no atmospheric scattering or absorption. The surface-reflectance product is the input for product generation for several land products: vegetation Indices (VIs), BRDF, thermal anomaly, snow/ice, and Fraction of Photosynthetically Active Radiation/Leaf Area Index (FPAR/LAI). not-provided MYD09CMA.v6.1NRT MODIS/Aqua Aerosol Optical Thickness Daily L3 Global 0.05-Deg CMA NRT LANCEMODIS 2021-02-07 -180, -81, 180, 81 https://cmr.earthdata.nasa.gov/search/concepts/C2007652084-LANCEMODIS.json The MODIS/Aqua Aerosol Optical Thickness Daily L3 Global 0.05-Deg CMA Near Real Time (NRT), short name MYD09CMA, is a daily level 3 global product. It is in linear latitude and longitude (Plate Carre) projection with a 0.05Deg spatial resolution. This product is derived from MYD09IDN, MYD09IDT and MYD09IDS for each orbit by compositing the data on the basis of minimum band 3 (459 - 479 nm band) values (after excluding pixels flagged for clouds and high solar zenith angles). not-provided MYDGB0.v6.1NRT MODIS/Aqua 5-minute GBAD data in L0 format - NRT LANCEMODIS 2017-10-20 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1427015288-LANCEMODIS.json MODIS/Aqua Near Real Time (NRT) 5-minute GBAD data in L0 format. not-provided -NBII_SAIN2 1986-1988 Plot-Transect Installation - Roan Mountain Massif Content Management SCIOPS 1987-01-01 1988-01-01 -82.13472, 36.08544, -82.01191, 36.15365 https://cmr.earthdata.nasa.gov/search/concepts/C1214586476-SCIOPS.json "This data set contains information on a set of transects and plots that were originally installed in 1987 and 1988 on the grassy balds of the Roan Mountain Massif (Round Bald, Engine Gap, Jane Bald, Grassy Ridge, Big Yellow Mountain (also known as Yellow Mountain), Little Hump Mountain, Bradley Gap, and Hump Mountain (also known as Big Hump Mountain). Data collected from the transects and plots were to characterize baseline conditions against which the effects of future vegetation management actions could be evaluated. This legacy dataset contains information on the baseline (pre-management) conditions of the grassy balds based on the field collections and analysis of the data collected at transects and plots installed in 1987 and 1988. More specifically, this legacy dataset contains information on the first vegetation composition analysis and first comprehensive plant inventory conducted on the Roan Mountain grassy bald complex. Information that describes this dataset primarily comes from the following sources: various field reports, memos, letters, grant proposals, hardcopies of the 1987 and 1988 data sheets, photos of the original transects and plots, and interviews with the originators of the transect and plot data. This metadata record documents legacy data to the extent practical, as required by Executive Order 12906, ""Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure"", dated April 11, 1994. Details may be missing, but given the resources available, the information provided herein is as concise as possible at this point in time." not-provided -NBII_SAIN5 1987- 1992 Plot-Transect - Community and Mowing Analysis - Roan Mountain Massif Data SCIOPS 1987-01-01 1992-01-01 -82.13472, 36.08544, -82.01191, 36.15365 https://cmr.earthdata.nasa.gov/search/concepts/C1214586477-SCIOPS.json "The transects and plots were originally installed in 1987 and 1988 on the grassy balds of the Roan Mountain Massif [Round Bald, Engine Gap, Jane Bald, Grassy Ridge, Big Yellow Mountain (also known as Yellow Mountain), Little Hump Mountain, Bradley Gap, and Hump Mountain (also known as Big Hump Mountain)]. Data collected from the transects were to characterize baseline conditions against which the effects of future vegetation management actions could be evaluated. This legacy data set represents (1) an analysis of data collected from transects and plots that were originally installed in 1987 and 1988 and revisited in 1992, and (2) information on the entry of the 1987, 1988, 1992, 1993, and 1994 data electronically in 1994. Analyses were conducted to document the pre-management conditions of the vegetation on the grassy balds complex of Roan Mountain, and the changes in vegetation on Round Bald and Jane Bald in response to the hand-mowing between 1987-1988 and 1992. This was the second time that a vegetation composition analysis was conducted using the 1987 and 1988 baseline data. Information pertaining to this dataset primarily comes from one report that describes the analyses, electronic files and hardcopies of the raw data, and interviews with the originators of the transect and plot data. This metadata record documents geospatial legacy data to the extent practicable, as required by Executive Order 12906, ""Coordinating Geographic Data Acquisition and Access: The National Spatial Data Infrastructure,"" dated April 11, 1994. Details may be missing, but given the resources available, the information provided herein is as concise as possible at this point in time." not-provided NEX-DCP30.v1 Downscaled 30 Arc-Second CMIP5 Climate Projections for Studies of Climate Change Impacts in the United States NCCS 1950-01-01 2099-12-31 -125.0208333, 24.0625, -66.4791667, 49.9375 https://cmr.earthdata.nasa.gov/search/concepts/C1542175061-NCCS.json This NASA dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future climate patterns and climate impacts at the scale of individual neighborhoods and communities. This dataset is intended for use in scientific research only, and use of this dataset for other purposes, such as commercial applications, and engineering or design studies is not recommended without consultation with a qualified expert. Community feedback to improve and validate the dataset for modeling usage is appreciated. Email comments to bridget@climateanalyticsgroup.org. Dataset File Name: NASA Earth Exchange (NEX) Downscaled Climate Projections (NEXDCP30), https://portal.nccs.nasa.gov/portal_home/published/NEX.html not-provided NEX-GDDP.v1 NASA Earth Exchange Global Daily Downscaled Projections NCCS 1950-01-01 2100-12-31 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1374483929-NCCS.json The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate scenarios for the globe that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs). The CMIP5 GCM runs were developed in support of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The NEX-GDDP dataset includes downscaled projections for RCP 4.5 and RCP 8.5 from the 21 models and scenarios for which daily scenarios were produced and distributed under CMIP5. Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100. The spatial resolution of the dataset is 0.25 degrees (~25 km x 25 km). The NEX-GDDP dataset is provided to assist the science community in conducting studies of climate change impacts at local to regional scales, and to enhance public understanding of possible future global climate patterns at the spatial scale of individual towns, cities, and watersheds. Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run). not-provided -NIPR_UAP_ELF_SYO 1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station SCIOPS 2000-01-01 39.6, -69, 39.6, -69 https://cmr.earthdata.nasa.gov/search/concepts/C1214590112-SCIOPS.json 1-100Hz ULF/ELF Electromagnetic Wave Observation at Syowa Station not-provided NMMIEAI-L2-NRT.v2 OMPS-NPP L2 NM Aerosol Index swath orbital NRT OMINRT 2011-11-07 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1657477341-OMINRT.json The OMPS-NPP L2 NM Aerosol Index swath orbital V2 for Near Real Time. For the standard product see the OMPS_NPP_NMMIEAI_L2 product in CMR .The aerosol index is derived from normalized radiances using 2 wavelength pairs at 340 and 378.5 nm. Additionally, this data product contains measurements of normalized radiances, reflectivity, cloud fraction, reflectivity, and other ancillary variables. not-provided NMSO2-PCA-L2-NRT.v2 OMPS/NPP PCA SO2 Total Column 1-Orbit L2 Swath 50x50km NRT OMINRT 2011-10-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1439293808-OMINRT.json The OMPS-NPP L2 NM Sulfur Dioxide (SO2) Total and Tropospheric Column swath orbital collection 2 version 2.0 product contains the retrieved sulfur dioxide (SO2) measured by the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) sensor on the Suomi-NPP satellite. A Principle Component Analysis (PCA) algorithm is used to retrieve the SO2 total column amount and column amounts in the lower (centered at 2.5 km), middle (centered at 7.5 km) and upper (centered at 11 km) troposphere, as well as the lower stratosphere (centered at 16 km). Each granule contains data from the daylight portion for a single orbit or about 50 minutes. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14 orbits per day each with a swath width of 2600 km. There are 35 pixels in the cross-track direction, with a pixel resolution of about 50 km x 50 km at nadir. The files are written using the Hierarchical Data Format Version 5 or HDF5. not-provided NMTO3NRT.v2 OMPS-NPP L2 NM Ozone (O3) Total Column swath orbital NRT OMINRT 2011-10-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1439272084-OMINRT.json The OMPS-NPP L2 NM Ozone (O3) Total Column swath orbital product provides total ozone measurements from the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi-NPP satellite.The total column ozone amount is derived from normalized radiances using 2 wavelength pairs 317.5 and 331.2 nm under most conditions, and 331.2 and 360 nm for high ozone and high solar zenith angle conditions. Additionally, this data product contains measurements of UV aerosol index and reflectivity at 331 nm.Each granule contains data from the daylight portion of each orbit measured for a full day. Spatial coverage is global (-90 to 90 degrees latitude), and there are about 14.5 orbits per day, each has typically 400 swaths. The swath width of the NM is about 2800 km with 36 scenes, or pixels, with a footprint size of 50 km x 50 km at nadir. The L2 NM Ozone data are written using the Hierarchical Data Format Version 5 or HDF5. not-provided @@ -334,26 +344,32 @@ XAERDT_L2_ABI_G16.v1 ABI/GOES-16 Dark Target Aerosol 10-Min L2 Full Disk 10 km L 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 +above-and-below-ground-herbivore-communities-along-elevation.v1.0 Above- and below-ground herbivore communities along elevation ENVIDAT 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789814648-ENVIDAT.json Despite the common role of above- and below-ground herbivore communities in mediating ecosystem functioning, our understanding of the variation of species communities along natural gradient is largely strongly biased toward aboveground organisms. This dataset enables to study the variations in assemblages of two dominant groups of herbivores, namely, aboveground orthoptera and belowground nematodes together with their food plants. Herbivores and plant surveys were conducted in 48 natural grasslands along six elevation gradients, selected to span the major macro-climatic and environmental conditions of the Swiss Alps. It compiles herbivores and plant surveys, information on the study sites as well as plant and herbivores functional traits sought to be involved in trophic interactions and to respond to climatic variation along the elevation. Plant functional traits considered are the SLA, the LDMC, the C/N content, the punch strength (i.e. force required to pierce the leave lamina), the mandibular strength for Orthoptera insect. Data were collected during the summer 2016 and 2017. not-provided aces1am.v1 ACES Aircraft and Mechanical Data GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977826980-GHRC_DAAC.json The ACES Aircraft and Mechanical Data consist of aircraft (e.g. pitch, roll, yaw) and mechanical (e.g. aircraft engine speed, tail commands, fuel levels) data recorded by the Altus II Unmanned Aerial Vehicle (Altus II UAV) system during the Altus Cumulus Electrification Study (ACES) based at the Naval Air Facility Key West in Florida. ACES aimed to provide extensive observations of the cloud electrification process and its effects by using the Altus II UAV to collect cloud top observations of thunderstorms. The campaign also worked to validate satellite lightning measurements. The Altus II aircraft and mechanical data files are available from July 10 through August 30, 2002 in MATLAB data format (.mat). not-provided aces1cont.v1 ACES CONTINUOUS DATA V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847043-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August, 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloudelectrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from seven instruments: the Slow/Fast antenna, Electric Field Mill, Dual Optical Pulse Sensor, Searchcoil Magnetometer, Accelerometers, Gerdien Conductivity Probe, and the Fluxgate Magnetometer. Data consists of sensor reads at 50HZ throughout the flight from all 64 channels. not-provided aces1efm.v1 ACES ELECTRIC FIELD MILL V1 GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977847178-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from it's birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data from Electric Field Mills, which yield information about the atmospheric electrical fields above the instruments. not-provided aces1log.v1 ACES LOG DATA GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977853903-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of log data from each flight, and yields instrument and aircraft status throughout the flight. not-provided aces1time.v1 ACES TIMING DATA GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977855412-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August or 2002, ACES researchers overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of timing data used for the experiment. When used it provides: syncclock_time = time found at the syncclock (VSI-SYnCCLOCK-32) in seconds from first file name, syncclock_m_time = time found at the syncclock (VSI-SYnCCLOCK-32) in Matlab dateform format, system_time = system time in seconds from first file name, system_m_time = system time in dateform format, gps_time = time found at the GPS unit in seconds from first file name, gps_m_time = time found at GPS unit in dateform, cmos_time = time found at the computer CMOS in seconds from first file name, cmos_m_time = time found at the computer CMOS in dateform. not-provided aces1trig.v1 ACES TRIGGERED DATA GHRC_DAAC 2002-07-10 2002-08-30 -85, 23, -81, 26 https://cmr.earthdata.nasa.gov/search/concepts/C1977858342-GHRC_DAAC.json The ALTUS Cloud Electrification Study (ACES) was based at the Naval Air Facility Key West in Florida. During August 2002, ACES researchers conducted overflights of thunderstorms over the southwestern corner of Florida. For the first time in NASA research, an uninhabited aerial vehicle (UAV) named ALTUS was used to collect cloud electrification data. Carrying field mills, optical sensors, electric field sensors and other instruments, ALTUS allowed scientists to collect cloud electrification data for the first time from above the storm, from its birth through dissipation. This experiment allowed scientists to achieve the dual goals of gathering weather data safely and testing new aircraft technology. This dataset consists of data collected from the following instruments: Slow/Fast antenna, Electric Field Mill, Optical Pulse Sensors, Searchcoil Magnetometer, Accelerometer, and Gerdien Conductivity Probe. These data were collected at 200KHz from the first 16 telemetry items collected on the aircraft, were initiated by an operator selected trigger (e.g. DOPS), and continued collecting for as long as the trigger continued. not-provided +aerosol-data-davos-wolfgang.v1.0 Aerosol Data Davos Wolfgang ENVIDAT 2020-01-01 2020-01-01 9.853594, 46.835577, 9.853594, 46.835577 https://cmr.earthdata.nasa.gov/search/concepts/C2789814678-ENVIDAT.json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Davos Wolfgang (LON: 9.853594, LAT: 46.835577). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs) and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3788 , TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and DRINCZ: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l minˉ¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the DRoplet Ice Nuclei Counter Zurich (DRINCZ, ETH Zurich) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. not-provided +aerosol-data-weissfluhjoch.v1.0 Aerosol Data Weissfluhjoch ENVIDAT 2020-01-01 2020-01-01 9.806475, 46.832964, 9.806475, 46.832964 https://cmr.earthdata.nasa.gov/search/concepts/C2789814736-ENVIDAT.json Aerosol properties were measured between February 8 and March 31 2019 at the measurement site Weissfluhjoch (LON: 9.806475, LAT: 46.832964). Optical and aerodynamic particle counters, as well as a scanning mobility particle size spectrometer and an ice nuclei counter were deployed to report particle concentrations and size distributions in fine (10-1000 nm) and coarse mode (> 1000 nm), cloud condensation nuclei concentrations (CCNCs), and ice nuclei particle concentrations (ICNCs). The ambient particles were transported via a heated inlet to be distributed to the particle detecting devices inside the setup room. Optical Particle Counter (OPC): Light scattering of a diode laser beam caused by travelling particles is used in the both, the OPC-N3 (0.41 - 38.5 μm) and GT-526S (0.3 – 5 μm), to determine their size and number concentration. For the OPC-N3, particle size spectra and concentration data are used afterwards to calculate PM₁, PM₂,₅ and PM₁₀ (assumptions: particle density: 1.65 g cmˉ³, refractive index: 1.5+i0). Aerodynamic Particle Sizer (APS): The APS (3321, TSI Inc.) measured the particle size distribution for aerodynamic diameters between 0.5 μm and ~20 μm by the particle’s time-of-flight and light-scattering intensity (assumptions: particle density 1 g cmˉ³). Scanning Mobility Particle Size Spectrometer (SMPS): Particle number concentrations in a size range between 12 and 460 nm (electrical mobility diameter) were measured at Davos Wolfgang, using a Scanning Mobility Particle Sizer Spectrometer (SMPS 3938, TSI Inc.). The classifier (3082, TSI Inc.) was equipped with a neutralizer (3088, TSI Inc.) and a differential mobility analyzer working with negative polarity (3081, TSI Inc.). The size selected particles were counted by a water-based condensation particle counter (3787 TSI Inc.). The TSI AIM software was used to provide particle size distributions by applying multiple charge and diffusion loss corrections (assumptions: particle density 1 g cmˉ³). Coriolis μ and LINDA: A microbial air sampler (Coriolis μ, bertin Instruments) was used to collect airborne particles for investigating their ice nucleating ability with a droplet freezing device. Particles larger than 0.5 μm were drawn with an air flow rate of up to 300 l min‾¹ into the cone and centrifuged into the wall of the cone due to the forming vortex. The liquid sample was transferred into the LED based Ice Nucleation Detection Apparatus (LINDA, University of Basel) to study heterogeneous ice formation (immersion freezing mode) of ambient airborne particles. not-provided +alnus-glutinosa-orientus-ishidae-flavescence-doree.v1.0 Alnus glutinosa (L.) Gaertn. and Orientus ishidae (Matsumura, 1902) share phytoplasma genotypes linked to the “Flavescence dorée” epidemics ENVIDAT 2021-01-01 2021-01-01 8.4484863, 45.8115721, 9.4372559, 46.4586735 https://cmr.earthdata.nasa.gov/search/concepts/C2789814963-ENVIDAT.json Flavescence dorée (FD) is a grapevine disease caused by associated phytoplasmas (FDp), which are epidemically spread by their main vector Scaphoideus titanus. The possible roles of alternative and secondary FDp plant hosts and vectors have gained interest to better understand the FDp ecology and epidemiology. A survey conducted in the surroundings of a vineyard in the Swiss Southern Alps aimed at studying the possible epidemiological role of the FDp secondary vector Orientus ishidae and the FDp host plant Alnus glutinosa is reported. Data used for the publication. Insects were captured by using a sweeping net (on common alder trees) and yellow sticky traps (Rebell Giallo, Andermatt Biocontrol AG, Switzerland) placed in the vineyard canopy. Insects were later determined and selected for molecular analyses. Grapevines and common alder samples were collected using the standard techniques. The molecular analyses were conducted in order to identify samples infected by the Flavescence dorée phytoplasma (16SrV-p) and the Bois Noir phytoplasma (16SrXII-p). A selection of the infected sampled were further characterized by map genotype and sequenced in order to compare the genotypes in insects, grapevines and common alder trees. not-provided +alpine3d-simulations-of-future-climate-scenarios-for-graubunden.v1.0 Alpine3D simulations of future climate scenarios for Graubunden ENVIDAT 2019-01-01 2019-01-01 8.6737061, 46.2216525, 10.6347656, 47.1075228 https://cmr.earthdata.nasa.gov/search/concepts/C2789814545-ENVIDAT.json "This is the simulation dataset from _""Response of snow cover and runoff to climate change in high Alpine catchments of Eastern Switzerland""_, M. Bavay, T. Grünewald, M. Lehning, Advances in Water Resources __55__, 4-16, 2013 A model study on the impact of climate change on snow cover and runoff has been conducted for the Swiss Canton of Graubünden. The model Alpine3D has been forced with the data from 35 Automatic Weather Stations in order to investigate snow and runoff dynamics for the current climate. The data set has then been modified to reflect climate change as predicted for the 2021-2050 and 2070-2095 periods from an ensemble of regional climate models. The predicted changes in snow cover will be moderate for 2021-2050 and become drastic in the second half of the century. Towards the end of the century the snow cover changes will roughly be equivalent to an elevation shift of 800 m. Seasonal snow water equivalents will decrease by one to two thirds and snow seasons will be shortened by five to nine weeks in 2095. Small, higher elevation catchments will show more winter runoff, earlier spring melt peaks and reduced summer runoff. Where glacierized areas exist, the transitional increase in glacier melt will initially offset losses from snow melt. Larger catchments, which reach lower elevations will show much smaller changes since they are already dominated by summer precipitation." not-provided amprimpacts.v1 Advanced Microwave Precipitation Radiometer (AMPR) IMPACTS GHRC_DAAC 2020-01-18 2023-03-02 -124.153, 26.507, -64.366, 49.31 https://cmr.earthdata.nasa.gov/search/concepts/C2004708841-GHRC_DAAC.json The Advanced Microwave Precipitation Radiometer (AMPR) IMPACTS dataset consists of brightness temperature measurements collected by the Advanced Microwave Precipitation Radiometer (AMPR) onboard the NASA ER-2 high-altitude research aircraft. AMPR provides multi-frequency microwave imagery, with high spatial and temporal resolution for deriving cloud, precipitation, water vapor, and surface properties. These measurements were taken during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. Funded by NASA’s Earth Venture program, IMPACTS is the first comprehensive study of East Coast snowstorms in 30 years. Data files are available from January 18, 2020, through March 2, 2023, in netCDF-4 format. not-provided amsua15sp.v1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-15 GHRC_DAAC 1998-08-03 -180, -90, 180, 89.756 https://cmr.earthdata.nasa.gov/search/concepts/C1996541017-GHRC_DAAC.json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). NOAA-15 was the first spacecraft to fly AMSU. Launched on 13 May 1998, NOAA-15 is in a sun synchronous near polar orbit. not-provided amsua16sp.v1 ADVANCED MICROWAVE SOUNDING UNIT-A (AMSU-A) SWATH FROM NOAA-16 GHRC_DAAC 2001-05-27 2009-07-30 -180, -89.91, 180, 89.73 https://cmr.earthdata.nasa.gov/search/concepts/C1979956366-GHRC_DAAC.json AMSU-A, the Advanced Microwave Sounding Unit, is a 15-channel passive microwave radiometer used to profile atmospheric temperature and moisture from the earth's surface to ~45 km (3 millibars). All orbits beginning in the day (00:00:00 - 23:59:59 UTC) are stored in one daily HDF-EOS file. Each file contains 15 (channel) arrays, as well as corresponding latitude, longitude, and time. AMSU flies on the National Oceanic and Atmospheric Administration (NOAA) polar orbiting spacecraft as part of the National Polar-orbiting Operational Environmental Satellite System (NPOESS). Launched on 21 September 2000, NOAA-16 is in a sun synchronous near polar orbit. not-provided asas Advanced Solid-state Array Spectroradiometer (ASAS) USGS_LTA 1988-06-26 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220566261-USGS_LTA.json The Advanced Solid-state Array Spectroradiometer (ASAS) data collection contains data collected by the ASAS sensor flown aboard NASA aircraft. A fundamental use of ASAS data is to characterize and understand the directional variability in solar energy scattered by various land surface cover types (e.g.,crops, forests, prairie grass, snow, or bare soil). The sensor's Bidirectional Reflectance Distribution Function determines the variation in the reflectance of a surface as a function of both the view zenith angle and solar illumination angle. The ASAS sensor is a hyperspectral, multiangle, airborne remote sensing instrument maintained and operated by the Laboratory for Terrestrial Physics at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The ASAS instrument is mounted on the underside of either NASA C-130 or NASA P-3 aircraft and is capable of off-nadir pointing from approximately 70 degrees forward to 55 degrees aft along the direction of flight. The aircraft is flown at an altitude of 5000 - 6000 meters (approximately 16,000 - 20,000 ft.). Data in the ASAS collection primarily cover areas over the continental United States, but some ASAS data are also available over areas in Canada and western Africa. The ASAS data were collected between 1988 and 1994. not-provided aster_global_dem ASTER Global DEM USGS_LTA 1970-01-01 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1220567908-USGS_LTA.json ASTER is capable of collecting in-track stereo using nadir- and aft-looking near infrared cameras. Since 2001, these stereo pairs have been used to produce single-scene (60- x 60-kilomenter (km)) digital elevation models (DEM) having vertical (root-mean-squared-error) accuracies generally between 10- and 25-meters (m). The methodology used by Japan's Sensor Information Laboratory Corporation (SILC) to produce the ASTER GDEM involves automated processing of the entire ASTER Level-1A archive. Stereo-correlation is used to produce over one million individual scene-based ASTER DEMs, to which cloud masking is applied to remove cloudy pixels. All cloud-screened DEMS are stacked and residual bad values and outliers are removed. Selected data are averaged to create final pixel values, and residual anomalies are corrected before partitioning the data into 1 degree (°) x 1° tiles. The ASTER GDEM covers land surfaces between 83°N and 83°S and is comprised of 22,702 tiles. Tiles that contain at least 0.01% land area are included. The ASTER GDEM is distributed as Geographic Tagged Image File Format (GeoTIFF) files with geographic coordinates (latitude, longitude). The data are posted on a 1 arc-second (approximately 30–m at the equator) grid and referenced to the 1984 World Geodetic System (WGS84)/ 1996 Earth Gravitational Model (EGM96) geoid. not-provided b673f41b-d934-49e4-af6b-44bbdf164367 AVHRR - Land Surface Temperature (LST) - Europe, Daytime FEDEO 1998-02-23 -24, 28, 57, 78 https://cmr.earthdata.nasa.gov/search/concepts/C2207458008-FEDEO.json "The ""Land Surface Temperature derived from NOAA-AVHRR data (LST_AVHRR)"" is a fixed grid map (in stereographic projection ) with a spatial resolution of 1.1 km. The total size covering Europe is 4100 samples by 4300 lines. Within 24 hours of acquiring data from the satellite, day-time and night-time LSTs are calculated. In general, the products utilise data from all six of the passes that the satellite makes over Europe in each 24 hour period. For the daily day-time LST maps, the compositing criterion for the three day-time passes is maximum NDVI value and for daily night-time LST maps, the criterion is the maximum night-time LST value of the three night-time passes. Weekly and monthly day-time or night-time LST composite products are also produced by averaging daily day-time or daily night-time LST values, respectively. The range of LST values is scaled between –39.5°C and +87°C with a radiometric resolution of 0.5°C. A value of –40°C is used for water. Clouds are masked out as bad values. For additional information, please see: https://wdc.dlr.de/sensors/avhrr/" not-provided -blue_ice_core_DML2004_AS 101.1 m long horizontal blue ice core collected from Scharffenbergbotnen, DML, Antarctica, in 2003/2004 SCIOPS 1970-01-01 -180, -90, 180, -62.83 https://cmr.earthdata.nasa.gov/search/concepts/C1214614210-SCIOPS.json Horizontal blue ice core collected from the surface of a blue ice area in Scharffenbergbotnen, Heimefrontfjella, DML. Samples were collected in austral summer 2003/2004 and transported to Finland for chemical analyses. The blue ice core is estimated to represent a 1000-year period of climate history 20 - 40 kyr B.P.. The results of the analyses will be available in 2005. not-provided +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 @@ -370,6 +386,10 @@ gov.noaa.nodc:GHRSST-OISST_UHR_NRT-GOS-L4-BLK.v2.0 Black Sea Ultra High Resoluti gov.noaa.nodc:GHRSST-REMSS-L2P_GRIDDED_25-TMI.v4.0 GHRSST L2P Gridded Global Subskin Sea Surface Temperature from the Tropical Rainfall Mapping Mission (TRMM) Microwave Imager (TMI) (GDS version 1) GHRSSTCWIC 1998-01-01 2015-04-06 -180, -40, 180, 40 https://cmr.earthdata.nasa.gov/search/concepts/C2213645156-GHRSSTCWIC.json "The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is a well calibrated passive microwave radiometer, similar to SSM/I, that contains lower frequency channels required for sea surface temperature (SST) retrievals. The TRMM is a joint venture between NASA and the Japan Aerospace Exploration Agency (JAXA) to measure precipitation, water vapor, SST and wind in the global tropical regions and was launched in November 1997. The TRMM satellite travels west to east in a 402 km altitude semi-equatorial precessing orbit that results in day-to-day changes in the observation time of any given earth location between 38S and 38N. In contrast to infrared SST observations, microwave retrievals can be measured through most clouds, and are also insensitive to water vapor and aerosols. Remote Sensing Systems is the producer of these gridded TMI SST data for the Group for High Resolution Sea Surface Temperature (GHRSST) Project. Although the product designation is ""L2P_GRIDDED"" it is in actuality a Level 3 Collated (L3C) product as defined in the GHRSST Data Processing Specification (GDS) version 2.0. Its ""L2P_GRIDDED"" name derives from a deprecated specification in the early Pilot Project phase of GHRSST (pre 2008) and has remained for file naming continuity. In this dataset, both ascending (daytime) and descending (daytime) gridded orbital passes on packaged into the same daily file." not-provided gov.noaa.nodc:GHRSST-VIIRS_NPP-NAVO-L2P.v3.0 GHRSST Level 2P 1 m Depth Global Sea Surface Temperature version 3.0 from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi NPP satellite (GDS version 2) GHRSSTCWIC 2013-06-28 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C2213644303-GHRSSTCWIC.json A global Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS). This sensor resides on the Suomi National Polar-orbiting Partnership (Suomi_NPP) satellite launched on 28 October 2011. VIIRS is a whiskbroom scanning radiometer which takes measurements in the cross-track direction within a field of regard of 112.56 degrees using 16 detectors and a double-sided mirror assembly. At a nominal altitude of 829 km, the swath width is 3060 km, providing full daily coverage both on the day and night side of the Earth. The VIIRS instrument is a 22-band, multi-spectral scanning radiometer that builds on the heritage of the MODIS, AVHRR and SeaWiFS sensors for sea surface temperature (SST) and ocean color. For the infrared bands for SST the effective pixel size is 750 meters at nadir and the pixel size variation across the swath is constrained to no more than 1600 meters at the edge of the swath. This L2P SST v3.0 is upgraded from the v2.0 with several significant improvements in processing algorithms, including contamination detection, cloud detection, and data format upgrades. It contains the global near daily-coverage Sea Surface Temperature at 1-meter depth with 750 m (along) x 750 m (cross) spatial resolution in swath coordinates. Each netCDF file has 768 x 3200 pixels in size, in compliance with the GHRSST Data Processing Specification (GDS) version 2 format specifications. not-provided lake_erie_aug_2014.v0 2014 Lake Erie measurements OB_DAAC 2014-08-18 -180, -90, 180, 90 https://cmr.earthdata.nasa.gov/search/concepts/C1633360418-OB_DAAC.json 2014 Lake Erie measurements. not-provided +latent-reserves-in-the-swiss-nfi.v1.0 'Latent reserves' within the Swiss NFI ENVIDAT 2020-01-01 2020-01-01 5.95587, 45.81802, 10.49203, 47.80838 https://cmr.earthdata.nasa.gov/search/concepts/C2789815280-ENVIDAT.json "The files refer to the data used in Portier et al. ""‘Latent reserves’: a hidden treasure in National Forest Inventories"" (2020) *Journal of Ecology*. **'Latent reserves'** are defined as plots in National Forest Inventories (NFI) that have been free of human influence for >40 to >70 years. They can be used to investigate and acquire a deeper understanding of attributes and processes of near-natural forests using existing long-term data. To determine which NFI sample plots could be considered ‘latent reserves’, criteria were defined based on the information available in the Swiss NFI database: * Shrub forests were excluded. * Plots must have been free of any kind of management, including salvage logging or sanitary cuts, for a minimum amount of time. Thresholds of 40, 50, 60 and 70 years without intervention were tested. * To ensure that species composition was not influenced by past management, plots where potential vegetation was classified as deciduous by Ellenberg & Klötzli (1972) had to have an observed proportion of deciduous trees matching the theoretical proportion expected in a natural deciduous forest, as defined by Kienast, Brzeziecki, & Wildi (1994). * Plots had to originate from natural regeneration. * Intensive livestock grazing must never have occurred on the plots. The tables stored here were derived from the first, second and third campaigns of the Swiss NFI. The raw data from the Swiss NFI can be provided free of charge within the scope of a contractual agreement (http://www.lfi.ch/dienstleist/daten-en.php). **** The files 'Data figure 2' to 'Data figure 8' are publicly available and contain the data used to produce the figures published in the paper. The files 'Plot-level data for characterisation of 'latent reserves' and 'Tree-level data for characterisation of 'latent reserves' contain all the data required to reproduce the section of the article concerning the characterisation of 'latent reserves' and the comparison to managed forests. The file 'Data for mortality analyses' contains the data required to reproduce the section of the article concerning tree mortality in 'latent reserves'. The access to these three files is restricted as they contain some raw data from the Swiss NFI, submitted to the Swiss law and only accessible upon contractual agreement. " not-provided law_dome_annual_msa.v1 150 year MSA sea ice proxy record from Law Dome, Antarctica AU_AADC 1841-01-01 1995-12-31 112.806946, -66.76972, 112.806946, -66.76972 https://cmr.earthdata.nasa.gov/search/concepts/C1214313532-AU_AADC.json "This MSA record (1841-1995) is from a Law Dome ice core called ""DSS"" in East Antarctica. It was calibrated against satellite sea ice records and used to reconstruct sea ice extent prior to the satellite era. The following is taken from the abstract of the paper (Curran et al., 2003). The instrumental record of Antarctic sea ice in recent decades does not reveal a clear signature of warming despite observational evidence from coastal Antarctica. This work shows a significant correlation (P less than 0.002) between methanesulphonic acid (MSA) concentrations from a Law Dome ice core and 22 years of satellite-derived sea ice extent (SIE) for the 80 degrees E to 140 degrees E sector. Applying this instrumental calibration to longer term MSA data (1841 to 1995 A.D.) suggests that there has been a 20% decline in SIE since about 1950. The decline is not uniform, showing large cyclical variations, with periods of about 11 years, that confuse trend detection over the relatively short satellite era. This work was completed as part of ASAC project 757 (ASAC_757)." not-provided mbs_wilhelm_msa_hooh.v1 15 year Wilhelm II Land MSA and HOOH shallow ice core record from Mount Brown South (MBS) AU_AADC 1984-01-01 1998-12-31 86.082, -69.13, 86.084, -69.12 https://cmr.earthdata.nasa.gov/search/concepts/C1214313640-AU_AADC.json This work presents results from a short firn core spanning 15 years collected from near Mount Brown, Wilhelm II Land, East Antarctica. Variations of methanesulphonic acid (MSA) at Mount Brown were positively correlated with sea-ice extent from the coastal region surrounding Mount Brown (60-1208 E) and from around the entire Antarctic coast (0-3608 E). Previous results from Law Dome identified this MSA-sea-ice relationship and proposed it as an Antarctic sea-ice proxy (Curran and others, 2003), with the strongest results found for the local Law Dome region. Our data provide supporting evidence for the Law Dome proxy (at another site in East Antarctica), but a deeper Mount Brown ice core is required to confirm the sea-ice decline suggested by Curran and others (2003). Results also indicate that this deeper record may also provide a more circum-Antarctic sea-ice proxy. This work was completed as part of ASAC project 757 (ASAC_757). not-provided +mosaic-cbers4-brazil-3m-1 CBERS-4/WFI Image Mosaic of Brazil - 3 Months INPE 2020-04-01 2020-06-30 -76.6054059, -33.7511817, -27.7877802, 6.3052432 https://cmr.earthdata.nasa.gov/search/concepts/C3108204634-INPE.json CBERS-4/WFI image mosaic of Brazil with 64m of spatial resolution. The mosaic was prepared in order to demonstrate the technological capabilities of the Brazil Data Cube project tools. The false color composition is based on the WFI bands 15, 16 and 13 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in April 2020 and ending in June 2020, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 1200 CBERS-4 scenes and was generated based on an existing CBERS-4/WFI image collection. not-provided +mosaic-cbers4a-paraiba-3m-1 CBERS-4A/WFI Image Mosaic of Brazil Paraíba State - 3 Months INPE 2020-07-01 2020-09-30 -38.8134896, -8.3976443, -34.7223714, -5.87659 https://cmr.earthdata.nasa.gov/search/concepts/C3108204719-INPE.json CBERS-4A/WFI image mosaic of Brazil Paraíba State with 55m of spatial resolution. The mosaic was prepared in order to demonstrate the technological capabilities of the Brazil Data Cube project tools. The false color composition is based on the WFI bands 16, 15 and 14 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in July 2020 and ending in September 2020, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 50 CBERS-4A scenes and was generated based on an existing CBERS-4A/WFI image collection. not-provided +pfynwaldgasexchange.v1.0 2013-2020 gas exchange at Pfynwald ENVIDAT 2021-01-01 2021-01-01 7.6105556, 46.3001905, 7.6163921, 46.3047564 https://cmr.earthdata.nasa.gov/search/concepts/C2789816347-ENVIDAT.json Gas exchange was measured on control, irrigated and irrigation-stop trees at the irrigation experiment Pfynwald, during the years 2013, 2014, 2016-2020. The measurement campaigns served different purposes, resulting in a large dataset containing survey data, CO2 response curves of photosynthesis, light response curves of photosynthesis, and fluorescence measurements. Measurements were done with LiCor 6400 and LiCor 6800 instruments. Until 2016, measurements were done on excised branches or branches lower in the canopy. From 2016 onwards, measurements were done in the top of the canopy using fixed installed scaffolds. All metadata can be found in the attached documents. not-provided urn:ogc:def:EOP:VITO:VGT_S10.v1 10 Days Synthesis of SPOT VEGETATION Images (VGT-S10) FEDEO 1998-04-01 2014-05-31 -180, -56, 180, 75 https://cmr.earthdata.nasa.gov/search/concepts/C2207472890-FEDEO.json The VGT-S10 are near-global or continental, 10-daily composite images which are synthesised from the 'best available' observations registered in the course of every 'dekad' by the orbiting earth observation system SPOT-VEGETATION. The products provide data from all spectral bands (SWIR, NIR, RED, BLUE), the NDVI and auxiliary data on image acquisition parameters. The VEGETATION system allows operational and near real-time applications, at global, continental and regional scales, in very broad environmentally and socio-economically critical fields. The VEGETATION instrument is operational since April 1998, first with VGT1, from March 2003 onwards, with VGT2. More information is available on: https://docs.terrascope.be/#/DataProducts/SPOT-VGT/Level3/Level3 not-provided