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agricultureair qualityanalyticsarchivesatmosphereclimateclimate modeldata assimilationdeep learningearth observationenergyenvironmentalforecastgeosciencegeospatialglobalhistoryimagingindustrymachine learningmachine translationmetadatameteorologicalmodelnetcdfopendapradiationsatellite imagerysolarstatisticssustainabilitytime series forecastingwaterweatherzarr
NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The Applied Sciences Program, within the Earth Science Division of the NASA Science Mission Directorate, serves individuals and organizations around the globe by expanding and accelerating societal and economic benefits derived from Earth science, information, and technology research and development.
The Prediction Of Worldwide Energy Resources (POWER) Project, funded through the Applied Sciences Program at NASA Langley Research Center, gathers NASA Earth observation data and parameters related to the fields of surface solar irradiance and meteorology to serve the public in several free, easy-to-access and easy-to-use methods. POWER helps communities become resilient amid observed climate variability by improving data accessibility, aiding research in energy development, building energy efficiency, and supporting agriculture projects.
The POWER project contains over 380 satellite-derived meteorology and solar energy Analysis Ready Data (ARD) at four temporal levels: hourly, daily, monthly, and climatology. The POWER data archive provides data at the native resolution of the source products. The data is updated nightly to maintain near real time availability (2-3 days for meteorological parameters and 5-7 days for solar). The POWER services catalog consists of a series of RESTful Application Programming Interfaces, geospatial enabled image services, and web mapping Data Access Viewer. These three service offerings support data discovery, access, and distribution to the project’s user base as ARD and as direct application inputs to decision support tools.
The latest data version update includes hourly...
cogearth observationgeophysicsgeospatialglobalicenetcdfsatellite imagerystaczarr
The Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE) project has a singular mission: to accelerate ice sheet and glacier research by producing globally comprehensive, high resolution, low latency, temporally dense, multi-sensor records of land ice and ice shelf change while minimizing barriers between the data and the user. ITS_LIVE data currently consists of NetCDF Level 2 scene-pair ice flow products posted to a standard 120 m grid derived from Landsat 4/5/7/8/9, Sentinel-2 optical scenes, and Sentinel-1 SAR scenes. We have processed all land-ice intersecting image pai...
agricultureair temperatureatmospherebiodiversityclimatecoastaldatacenterecosystemsglobalhydrologyicelandmetadatanetcdfoceansopendapwater
M2T1NXSLV (or tavg1_2d_slv_Nx) is an hourly time-averaged 2-dimensional data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of meteorology diagnostics at popularly used vertical levels, such as air temperature at 2-meter (or at 10-meter, 850hPa, 500 hPa, 250hPa), wind components at 50-meter (or at 2-meter, 10-meter, 850 hPa, 500hPa, 250 hPa), sea level pressure, surface pressure, and total precipitable water vapor (or ice water, liquid water). The data field is time-stamped with the central time of an hour starting from 00:30 UTC, e.g.: 00:30, 01:30, … , 23:30 UTC.MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of ~3 weeks after the end of a month. Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes” linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original file.MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.Questions: If you have a question, please read "MERRA-2 File Specification Document", “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page. If that does not answer your question, you may post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov). Read our doc on how to get AWS Credentials to retrieve this data: Details →
agricultureair qualityatmospherebiodiversitycarbonclimatecoastaldatacenterecosystemsglobalhydrologyicelandmetadatanetcdfopendapwater
M2I3NVAER (or inst3_3d_aer_Nv) is an instantaneous 3-dimensional 3-hourly data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of assimilations of aerosol mixing ratio parameters at 72 model layers, such as dust, sulphur dioxide, sea salt, black carbon, and organic carbon. The data field is available every three hour starting from 00:00 UTC, e.g.: 00:00, 03:00, … , 21:00 UTC. Section 4.2 of the MERRA-2 File Specification document provides pressure values nominal for a 1000 hPa surface pressure and refers to the top edge of the layer. The lev=1 is for the top layer, and lev=72 is for the bottom (or surface) model layer. MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of ~3 weeks after the end of a month. Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes” linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original file.MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.Questions: If you have a question, please read "MERRA-2 File Specification Document", “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page. If that does not answer your question, you may post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov). Read our doc on how to get AWS Credentials to retrieve this data: Details →
agricultureair temperatureatmospherebiodiversityclimatecoastaldatacenterecosystemsglobalhydrologyicelandmetadatanetcdfopendapwater
M2I3NPASM (or inst3_3d_asm_Np) is an instantaneous 3-dimensional 3-hourly data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of assimilations of meteorological parameters at 42 pressure levels, such as temperature, wind components, vertical pressure velocity, water vapor, ozone mass mixing ratio, and layer height. The data field is available every three hours starting from 00:00 UTC, e.g.: 00:00, 03:00, … , 21:00 UTC. The information on the pressure levels can be found in the section 4.2 of the MERRA-2 File Specification document. MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of ~3 weeks after the end of a month. Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes” linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original file.MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.Questions: If you have a question, please read "MERRA-2 File Specification Document", “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page. If that does not answer your question, you may post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov). Read our doc on how to get AWS Credentials to retrieve this data: Details →
agricultureair temperatureatmospherebiodiversityclimatecoastaldatacenterecosystemsglobalhydrologyicelandmetadatanetcdfopendapwater
M2I3NVASM (or inst3_3d_asm_Nv) is an instantaneous 3-dimensional 3-hourly data collection in Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of assimilations of meteorological parameters at 72 model layers, such as temperature, wind components, vertical pressure velocity, water vapor, and layer height. The data field is available every three hour starting from 00:00 UTC, e.g.: 00:00, 03:00, … , 21:00 UTC. Section 4.2 of the MERRA-2 File Specification document provides pressure values nominal for a 1000 hPa surface pressure and refers to the top edge of the layer. The lev=1 is for the top layer, and lev=72 is for the bottom (or surface) model layer. MERRA-2 is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-present with the latency of ~3 weeks after the end of a month. Data Reprocessing: Please check “Records of MERRA-2 Data Reprocessing and Service Changes” linked from the “Documentation” tab on this page. Note that a reprocessed data filename is different from the original file.MERRA-2 Mailing List: Sign up to receive information on reprocessing of data, changing of tools and services, as well as data announcements from GMAO. Contact the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov) to be added to the list.Questions: If you have a question, please read "MERRA-2 File Specification Document", “MERRA-2 Data Access – Quick Start Guide”, and FAQs linked from the ”Documentation” tab on this page. If that does not answer your question, you may post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov). Read our doc on how to get AWS Credentials to retrieve this data: Details →
chemical biologychemistryclimatedatacenterdigital assetsgeochemistrygeophysicsgeosciencemarinenetcdfoceans
Argo is an international program to observe the interior of the ocean with a fleet of profiling floats drifting in the deep ocean currents (https://argo.ucsd.edu). Argo GDAC is a dataset of 5 billion in situ ocean observations from 18.000 profiling floats (4.000 active) which started 20 years ago. Argo GDAC dataset is a collection of 18.000 NetCDF files. It is a major asset for ocean and climate science, a contributor to IOCCP reports.
atmosphereclimatecoastaldatacenterglobalhydrologylandmetadatanetcdfopendap
Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.The Integrated Multi-satellitE Retrievals for GPM (IMERG) IMERG is a NASA product estimating global surface precipitation rates at a high resolution of 0.1° every half-hour beginning 2000. It is part of the joint NASA-JAXA Global Precipitation Measurement (GPM) mission, using the GPM Core Observatory satellite as the standard to combine precipitation observations from an international constellation of satellites using advanced techniques. IMERG can be used for global-scale applications as well as over regions with sparse or no reliable surface observations. The fine spatial and temporal resolution of IMERG data allows them to be accumulated to the scale of the application for increased skill. IMERG has three Runs with varying latencies in response to a range of application needs: rapid-response applications (Early Run, 4-h latency), same/next-day applications (Late Run, 14-h latency), and post-real-time research (Final Run, 3.5-month latency). While IMERG strives for consistency and accuracy, satellite estimates of precipitation are expected to have lower skill over frozen surfaces, complex terrain, and coastal zones. As well, the changing GPM satellite constellation over time may introduce artifacts that affect studies focusing on multi-year changes.This dataset is the GPM Level 3 IMERG Early Daily 10 x 10 km (GPM_3IMERGDE) derived from the half-hourly GPM_3IMERGHHE. The derived result represents an early (expedited) estimate of the daily mean precipitation rate in mm/day. The dataset is produced by first computing the mean precipitation rate in (mm/hour) in every grid cell, and then multiplying the result by 24. This minimizes the possible dry bias in versions before "07", in the simple daily totals for cells where less than 48 half-hourly observations are valid for the day. The latter under-sampling is very rare in the combined microwave-infrared (and rain gaug...
climatecoastaldatacenterglobalhydrologyicelandmetadatanetcdfopendap
Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.The Integrated Multi-satellitE Retrievals for GPM (IMERG) IMERG is a NASA product estimating global surface precipitation rates at a high resolution of 0.1° every half-hour beginning 2000. It is part of the joint NASA-JAXA Global Precipitation Measurement (GPM) mission, using the GPM Core Observatory satellite as the standard to combine precipitation observations from an international constellation of satellites using advanced techniques. IMERG can be used for global-scale applications as well as over regions with sparse or no reliable surface observations. The fine spatial and temporal resolution of IMERG data allows them to be accumulated to the scale of the application for increased skill. IMERG has three Runs with varying latencies in response to a range of application needs: rapid-response applications (Early Run, 4-h latency), same/next-day applications (Late Run, 14-h latency), and post-real-time research (Final Run, 3.5-month latency). While IMERG strives for consistency and accuracy, satellite estimates of precipitation are expected to have lower skill over frozen surfaces, complex terrain, and coastal zones. As well, the changing GPM satellite constellation over time may introduce artifacts that affect studies focusing on multi-year changes.This dataset is the GPM Level 3 IMERG Final Daily 10 x 10 km (GPM_3IMERGDF) derived from the half-hourly GPM_3IMERGHH. The derived result represents the Final estimate of the daily mean precipitation rate in mm/day. The dataset is produced by first computing the mean precipitation rate in (mm/hour) in every grid cell, and then multiplying the result by 24. This minimizes the possible dry bias in versions before "07", in the simple daily totals for cells where less than 48 half-hourly observations are valid for the day. The latter under-sampling is very rare in the combined microwave-infrared and rain gauge dataset, variable "precipitation", and appears in higher latitudes. Thus, in most cases users of global "precipitation" data will not notice any difference. This correction, however, is noticeable in the high-quality microwave retrieval, variable "MWprecipitation", where the occurrence of less than 48 valid half-hourly samples per day is very common. The counts of the valid half-hourly samples per day have always been provided as a separate variable, and users of daily data were advised to pay close attention to that variable and use it to calculate the correct precipitation daily rates. Starting with version "07", this is done in production to minimize possible misinterpretations of the data. The counts are still provided in the data, but they are only given to gauge the significance of the daily rates, and reconstruct the simple totals if someone wishes to do so. The latency of the derived Final Daily product depends on the delivery of the IMERG Final Half-Hourly product GPM_IMERGHH. Since the latter are delivered in a batch, once per month for the entire month, with up to 4 months latency, so will be the latency for the Final Daily, plus about 24 hours. Thus, e.g. the Dailies for January can be expected to appear no earlier than April 2. The daily mean rate (mm/day) is derived by first computing the mean precipitation rate (mm/hour) in a grid cell for the data day, and then multiplying the result by 24. Thus, for every grid cell we have Pdaily_mean = S...
atmosphereclimatecoastaldatacenterglobalhydrologylandmetadatanetcdfopendap
Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07.The Integrated Multi-satellitE Retrievals for GPM (IMERG) IMERG is a NASA product estimating global surface precipitation rates at a high resolution of 0.1° every half-hour beginning 2000. It is part of the joint NASA-JAXA Global Precipitation Measurement (GPM) mission, using the GPM Core Observatory satellite as the standard to combine precipitation observations from an international constellation of satellites using advanced techniques. IMERG can be used for ...
air temperatureatmosphereforecastgeosciencegeospatialglobalmeteorologicalmodelnear-surface air temperaturenear-surface relative humiditynetcdfweather
The flagship Numerical Weather Prediction (NWP) model developed and used at the Met Office, is the Unified Model, the same model is used for both weather and climate prediction. For weather forecasting the Met Office runs several configurations of the Unified Model as part of its operational Numerical Weather Prediction suite. The global ensemble (MOGREPS-G) produces forecasts for the whole globe up to a week ahead. The projection used is the Equirectangular Latitude-Longitude and the grid resolution is 20km. The forecast is updated regularly with a time delay and formatted via NetCDF. Please ...
air temperatureatmosphereforecastgeosciencegeospatialglobalmeteorologicalmodelnear-surface air temperaturenear-surface relative humiditynetcdfweather
The flagship Numerical Weather Prediction (NWP) model developed and used at the Met Office, is the Unified Model, the same model is used for both weather and climate prediction. For weather forecasting the Met Office runs several configurations of the Unified Model as part of its operational Numerical Weather Prediction suite. The regional ensemble (MOGREPS-UK) produces forecasts for an area covering the UK for the next five days. In the UK ensemble the model parameters (temperature, pressure, wind, humidity, etc.) are forecast at grid points separated by about 2.2 km, and the model has 70 ver...
air temperatureatmosphereforecastgeosciencegeospatialmodelnear-surface air temperaturenear-surface relative humiditynetcdfweather
The flagship Numerical Weather Prediction model developed and used at the Met Office, is the Unified Model, the same model is used for both weather and climate prediction. For weather forecasting the Met Office runs several configurations of the Unified Model as part of its operational Numerical Weather Prediction suite. Uncovering 2 years' worth of historical data, updated regularly with a time delay. The Global deterministic model is a global configuration of the Met Office Unified Models providing the most accurate short range deterministic forecast by any national meteorological servic...
forecastgeosciencegeospatialglobalmarinemodelnetcdfocean sea surface heightoceansweather
The Global Ocean component of the Met Office Global Coupled Atmosphere-Land-Ocean-Ice system which has been running in operations since May 2022. The system provides a global physical analysis and coupled forecast products providing 3D daily mean fields of temperature and salinity, zonal and meridional velocities; 2D daily mean fields of sea surface height, bottom temperature, mixed layer depth, sea ice fraction, sea ice thickness and sea ice zonal and meridional velocities; and instantaneous hourly fields for sea surface height, sea surface temperature and surface currents. The Met Office Glo...
forecastgeosciencegeospatialglobalmarinemodelnetcdfocean sea surface heightoceansweather
The Met Office runs global wave forecast models to support marine safety and operational decision making. Met Office configurations are developed to be run using the community wave model WAVEWATCH IIITM. The global wave configuration is designed to generate accurate forecasts for open waters of the world’s oceans and larger seas. The Met Office wave models are forced using wind data from the Met Office Global Atmospheric Hi-Res Model. The global wave model is run to provide a five day outlook for wave characteristics defining height, period and direction of waves within a given sea-state. The ...
forecastgeosciencegeospatialmarinemodelnetcdfocean sea surface heightoceansweather
The Northwest European continental shelf physical ocean model predicts temperature, salinity and circulation for waters surrounding the UK.
Ocean physics analysis provides a 6-day forecast for the North-West European Atlantic shelf at 1.5km resolution:
forecastgeosciencegeospatialmarinemodelnetcdfocean sea surface heightoceansweather
Northwest European continental shelf regional wave model predicting sea-state and various sea and swell wave characteristics for waters surrounding the UK.The Met Office runs global and regional wave forecast models to support marine safety and operational decision making. Met Office configurations are developed to be run using the community wave model WAVEWATCH IIITM. The global wave configuration is designed to generate accurate forecasts for open waters of the world's oceans and larger seas, whilst regional configurations are run in order to improve accuracy closer to the coast. The Met...
air temperatureatmosphereforecastgeosciencegeospatialmodelnear-surface air temperaturenear-surface relative humiditynetcdfweather
The flagship Numerical Weather Prediction model developed and used at the Met Office, is the Unified Model, the same model is used for both weather and climate prediction. For weather forecasting the Met Office runs several configurations of the Unified Model as part of its operational Numerical Weather Prediction suite. Uncovering 2 years' worth of historical data, updated regularly with a time delay. The UK deterministic model is a post processed regional downscaled configuration of the Unified Model, covering the UK and Ireland, with a resolution of approximately 0.018 degrees. The Unit...
air temperatureclimateclimate modelclimate projectionsCMIP6cogearth observationenvironmentalglobalmodelNASA Center for Climate Simulation (NCCS)near-surface relative humiditynear-surface specific humiditynetcdfprecipitation
The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed...
floodsglobalnear-surface air temperaturenear-surface specific humiditynetcdfprecipitation
Hydrological extremes, in the form of droughts and floods, have impacts on a wide range of sectors including water availability, food security, and energy production, among others. Given continuing large impacts of droughts and floods and the expectation for significant regional changes projected in the future, there is an urgent need to provide estimates of past events and their future risk, globally. However, current estimates of hydrological extremes are not robust and accurate enough, due to lack of long-term data records, standardized methods for event identification, geographical inconsi...
atmospheredatacenterearth observationgloballandmarinemetadatanetcdfoceansorbit
NASA produces skin sea surface temperature (SST) products from the Infrared (IR) channels of the Moderate-resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite. Terra was launched by NASA on December 18, 1999, into a sun synchronous, polar orbit with a daylight descending node at 10:30 am, to study the global dynamics of the Earth atmosphere, land and oceans. The MODIS captures data in 36 spectral bands at a variety of spatial resolutions. Two SST products can be present in these files. The first is a skin SST produced for both day and night observations, derived from the l...
atmosphereearth observationenvironmentalgeophysicsgeoscienceglobalmeteorologicalmodelnetcdfprecipitationsatellite imageryweather
The Tropical Cyclone Precipitation, Infrared, Microwave and Environmental Dataset (TC PRIMED) is a dataset centered around passive microwave observations of global tropical cyclones from low-Earth-orbiting satellites. TC PRIMED is a compilation of tropical cyclone data from various sources, including 1) tropical cyclone information from the National Oceanic and Atmospheric Administration (NOAA) National Weather Service National Hurricane Center (NHC) and Central Pacific Hurricane Center (CPHC) and the U.S. Department of Defense Joint Typhoon Warning Center, 2) low-Earth-orbiting satellite obse...
atmospheremeteorologicalnear-surface air temperaturenetcdfprecipitation
EM-Earth provides data for precipitation, mean air temperature, air temperature range, and dew-point temperature at 0.1° spatial resolution over global land areas from 1950 to 2019. EM-Earth provides hourly/daily deterministic estimates, and daily probabilistic estimates (25 ensemble members), to meet the diverse requirements of hydrometeorological applications.
atmospherecoastaldatacentergloballandmetadatanetcdfopendap
Version 2 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 2.This land sea mask originated from the NOAA group at SSEC in the 1980s. It was originally produced at 1/6 deg resolution, and then regridded for the purposes of GPCP, TMPA, and IMERG precipitation products. NASA code 610.2, Terrestrial Information Systems Laboratory, restructured this land sea mask to match the IMERG grid, and converted the file to CF-compliant netCDF4. Version 2 was created in May, 2019 to resolve detected inaccuracies in coastal regions.Users sho...
atmosphereclimatedatacenterforecastglobalmetadatanetcdfopendap
These data originate from NOAA/NCEP.The NOAA Climate Prediction Center/NCEP/NWS is making the data available originally in binary format, in a weekly rotating archive. The NASA GES DISC is acquiring the binary files as they become available, converts them into CF (Climate and Forecast) -convention compliant netCDF-4 format, and stores the product in a permanent archive. The original record started from February, 2000, but in June, 2025 it was extended back to January, 1998.The leading edge of data availability is delayed by about 24 hours from real-time to abide by international data exchange agreements between NOAA and EUMETSAT (the METEOSAT data providers).The data contain globally-merged (60°S-60°N) 4-km pixel-resolution IR brightness temperature data (equivalent blackbody temps), merged from the European, Japanese, and U.S. geostationary satellites over the period of record (GOES-8/9/10/11/12/13/14/15/16/17/18/19, METEOSAT-5/7/8/9/10/11, and GMS-5/MTSat-1R/2/Himawari-8/9).The global geo-IR are dynamically calibrated to GOES East, using a 35 day trailing inter-calibration using time/space-matched IR Tb’s at the mid-point between sub-satellite positions. In the event of duplicate data in a grid box, the value with the smaller zenith angle is taken. The data have been corrected for "zenith angle dependence", in which IR temperatures for locations far from satellite nadir are erroneously cold due to a combination of geometric effects and radiometric path extinction effects (Joyce et al. 2001). Finally, the data are re-navigated for parallax, which shifts the geo-location of the GEO-IR footprints to approximately account for the cloud tops that the IR “sees” being displaced away from their actual geographic location when viewed along a slanted path. These corrections allow for the merging of the IR data from the various GEO-satellites with greatly reduced discontinuities at GEO-satellite data boundaries. In the event of duplicate data in a grid box, the value with the smaller zenith angle is taken.The NASA GES DISC is curating these data in a self-documenting, CF-compliant, netCDF-4 format, which allows a broad range of applications to access the data directly, without the need to cope with the original binary data format. In addition to the direct download of netCDF-4 data, the GES DISC provides data download in binary, ASCII, and netCDF-3 formats using the OPeNDAP interface.
atmosphereclimatedata assimilationforecastgeosciencegeospatiallandmeteorologicalmodelnetcdfweather
NSF NCAR is providing a NetCDF-4 structured version of the 0.25 degree atmospheric ECMWF Reanalysis 5 (ERA5) to the AWS ODSP. ERA5 is produced using high-resolution forecasts (HRES) at 31 kilometer resolution (one fourth the spatial resolution of the operational model) and a 62 kilometer resolution ten member 4D-Var ensemble of data assimilation (EDA) in CY41r2 of ECMWF's Integrated Forecast System (IFS) with 137 hybrid sigma-pressure (model) levels in the vertical, up to a top level of 0.01 hPa. Atmospheric data on these levels are interpolated to 37 pressure levels (the same levels as in...
earth observationlandmetadatanetcdforbitradarsentinel-1synthetic aperture radarxmlzarr
The Level-3 OPERA Sentinel-1 Surface Displacement (DISP) product is generated through interferometric time-series analysis of Level-2 Coregistered Sentinel-1 Single Look Complex (CSLC) datasets. Using a hybrid Persistent Scatterer (PS) and Distributed Scatterer (DS) approach, this product quantifies Earth's surface displacement in the radar line-of-sight. The DISP products enable the detection of anthropogenic and natural surface changes, including subsidence, tectonic deformation, and landslides. The OPERA DISP suite comprises complementary datasets derived from Sentinel-1 and NISAR input...
climateclimate modelclimate projectionsCMIP6earth observationnetcdf
CCKP provides open access to a comprehensive suite of climate and climate change resources derived from the latest generation of climate data archives. Products are based on a consistent and transparent approach with a systematic way of pre-processing the raw observed and model-based projection data to enable inter-comparable use across a broad range of applications. Climate products consist of basic climate variables as well as a large collection (70+) of more specialized, application-orientated variables and indices across different scenarios. Precomputed data can be extracted per specified ...
agricultureair qualityair temperatureatmosphereclimateclimate modelclimate projectionsCMIP5CMIP6ecosystemselevationenvironmentalEulerianeventsfloodsfluid dynamicsgeosciencegeospatialhdf5healthHPChydrologyinfrastructureland coverland usemeteorologicalmodelnear-surface air temperaturenear-surface relative humiditynear-surface specific humiditynetcdfopen source softwarephysicspost-processingprecipitationradiationsimulationsuswaterweather
The data are a subset of the EPA Dynamically Downscaled Ensemble (EDDE), Version 1. EDDE is a collection of physics-based modeled data that represent 3D atmospheric conditions for historical and future periods under different scenarios. The EDDE Version 1 datasets cover the contiguous United States at a horizontal grid spacing of 36 kilometers at hourly increments. EDDE Version 1 includes simulations that have been dynamically downscaled from multiple global climate models (GCMs) under both mid- and high-emission scenarios from the Fifth Coupled Model Intercomparison Project (CMIP5) using the...
agricultureair qualityair temperatureatmosphereclimateclimate modelclimate projectionsCMIP5CMIP6ecosystemselevationenvironmentalEulerianeventsfloodsfluid dynamicsgeosciencegeospatialhdf5healthHPChydrologyinfrastructureland coverland usemeteorologicalmodelnear-surface air temperaturenear-surface relative humiditynear-surface specific humiditynetcdfopen source softwarephysicspost-processingprecipitationradiationsimulationsuswaterweather
The data are a subset of the EPA Dynamically Downscaled Ensemble (EDDE), Version 2. EDDE is a collection of physics-based modeled data that represent 3D atmospheric conditions for historical and future periods under different scenarios. The EDDE Version 2 datasets cover the contiguous United States at a horizontal grid spacing of 12 kilometers at hourly increments. EDDE Version 2 will include simulations that have been dynamically downscaled from multiple global climate models (GCMs) under multiple emission scenarios from the Sixth Coupled Model Intercomparison Project (CMIP6) using the Weath...
climatenetcdfprecipitation
GCMs under CMIP6 have been widely used to investigate climate change impacts and put forward associated adaptation and mitigation strategies. However, the relatively coarse spatial resolutions (usually 100~300km) preclude their direct applications at regional scales, which are exactly where the analysis (e.g., hydrological model simulation) is performed. To bridge this gap, a typical approach is to ‘refine’ the information from GCMs through regional climate downscaling experiments, which can be conducted statistically, dynamically, or a combination thereof. Statistical downscaling establishes ...
air qualityatmosphereenvironmentalhealthnetcdf
Fine particulate matter (PM2.5) concentrations are estimated using information from satellite-, simulation- and monitor-based sources. Aerosol optical depth from multiple satellites (MODIS, VIIRS, MISR, SeaWiFS, and VIIRS) and their respective retrievals (Dark Target, Deep Blue, MAIAC) is combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations to produce geophysical estimates that explain most of the variance in ground-based PM2.5 measurements. A subsequent statistical fusion incorporates additional inf...