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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...
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.
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 4-hour time delay and formatted via NetCDF. ...
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 ...
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...
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.
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...
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...