Loading...
Loading...
Climate models, weather data, oceanography, hydrology, atmospheric science, environmental monitoring
27,010 datasets
Version 07 climate-reference precipitation data from the GPM mission's SSMIS sensor on the DMSP F17 satellite. The dataset uses a Bayesian-type GPROF algorithm to retrieve mean rain rates and vertical hydrometeor profiles, with ancillary data from ECMWF-Interim reanalysis for climate consistency. It is produced by NASA's Goddard Space Flight Center and last updated in March 2026.
GPM_2AGPROFF18SSMIS_CLIM is a Version 07 climate-reference dataset from NASA's GES DISC, providing precipitation and atmospheric profiles from the SSMIS sensor on the DMSP F18 satellite. The data uses a Bayesian GPROF algorithm with ECMWF-Interim reanalysis for homogeneous climate records and offers 1.5-hour temporal and 12 km spatial resolution. It is part of a constellation approach to achieve broad 3-hour global coverage.
A NASA satellite dataset provides precipitation profiles and atmospheric water vapor data using a Bayesian retrieval algorithm. The data is derived from the TRMM TMI sensor and processed with homogeneous ECMWF reanalysis ancillary data to create a climate-consistent time series. Version 07 is the current version, superseding older releases.
Version 07 of the GPM GPROF Level 2 algorithm retrieves precipitation and atmospheric profiles from passive microwave sensors on the NOAA-20 satellite and other partner missions. The algorithm uses a Bayesian method with an a-priori database to provide mean rain rates, vertical cloud structure, and uncertainty estimates. This dataset is produced by the National Aeronautics and Space Administration and was last updated in March 2026.
Version 07 climate-referenced precipitation data from the AMSU-B sensor on the NOAA-17 satellite, processed by NASA's GPROF algorithm. The dataset uses ECMWF-Interim reanalysis for homogeneous ancillary data to support long-term climate studies. It provides mean rain rates and vertical cloud structure profiles based on Bayesian retrieval from observed brightness temperatures.
NASA's GPM mission provides Level 2A precipitation data from the NOAA-20 satellite's ATMS sensor. The dataset uses a Bayesian retrieval algorithm and climate-consistent ECMWF reanalysis ancillary data to produce profiles of rain rate and cloud hydrometeors. Version 07 is the current version, last updated in March 2026.
GPM_2AGPROFNOAA21ATMS is a Version 07 dataset from NASA's GES DISC, providing Level 2A precipitation and atmospheric profiles. The data is generated by the GPROF Bayesian algorithm using brightness temperature observations from the ATMS sensor on the NOAA-21 satellite, among other partner sensors, to achieve broad 3-hour global coverage. It includes near-realtime, standard, and climate products differing by latency and ancillary data sources like GANAL and ECMWF reanalysis.
Version 07 climate-reference precipitation data from the ATMS sensor on the NOAA-21 satellite, processed using the GPROF algorithm. The dataset provides 1.5-hour, 17 km resolution retrievals, using ECMWF-Interim reanalysis for homogeneous ancillary data to support long-term climate records. It is produced by the National Aeronautics and Space Administration and was last updated in March 2026.
Version 07 is the current version of this satellite-derived precipitation dataset, superseding older versions. The Goddard Profiling (2AGPROF) algorithm retrieves precipitation and related fields from multiple passive microwave sensors, including the ATMS on the Suomi-NPP satellite, to provide bulk 3-hour global coverage. The data is produced by NASA's Goddard Space Flight Center and was last updated in March 2026.
Version 07 is the current climate-reference product for the GPM GPROF algorithm, using ECMWF-Interim reanalysis for homogeneous ancillary data. The algorithm retrieves precipitation profiles from a constellation of 10 passive microwave sensors, including GMI, TMI, and SSMIS, to provide bulk 3-hour global coverage. NASA produced this dataset, which was last updated on March 13, —.
Offering a biomass index (mg/m³) derived from the Australian Continuous Plankton Recorder survey, a joint project by CSIRO Oceans and Atmosphere and the Australian Antarctic Division. It supports long-term monitoring of plankton communities as indicators of ocean health, climate change response, and fisheries management.
Global precipitation and atmospheric water vapor data retrieved by the GPM GPROF algorithm from a constellation of passive microwave sensors, including the MHS instrument on METOP-B. The dataset is produced by NASA and provides near-realtime, standard, and climate products with differing latency and ancillary data sources. Version 07 is the current version, superseding older releases.
Version 07 is the current climate-referenced precipitation data product from the Global Precipitation Measurement (GPM) mission. The dataset is produced by NASA using a Bayesian algorithm to retrieve precipitation profiles from the MHS radiometer on the METOP-C satellite, with ancillary data from ECMWF reanalysis for climate consistency. It provides a large sampling of global precipitation, contributing to the mission's 3-hour coverage.
Version 07 climate-reference data uses ECMWF-Interim reanalysis for homogeneous ancillary conditions over the climate time series. The Goddard Profiling (GPROF) algorithm retrieves precipitation and cloud hydrometeor profiles from a constellation of 10 passive microwave sensors, providing bulk 3-hour global coverage. This dataset is produced by NASA's GPM mission and was last updated in March 2026.
Version 07 of the GPM_2AGPROFNOAA18MHS_CLIM dataset provides precipitation profiles and related atmospheric fields from the NOAA-18 satellite's Microwave Humidity Sounder (MHS). The data is processed using the GPROF Bayesian algorithm with ECMWF-Interim reanalysis as ancillary data to ensure homogeneity for climate studies. This product is part of the Global Precipitation Measurement (GPM) mission constellation and is produced by the National Aeronautics and Space Administration (NASA).
Version 07 is the current climate-reference version of this dataset, using ECMWF-Interim reanalysis for homogeneous ancillary data. The GPROF algorithm retrieves precipitation profiles from the NOAA-19 MHS passive microwave sensor as part of the GPM constellation, providing a large sampling of global 3-hour coverage. The data is produced by NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC).
Version 07 climate-referenced precipitation data from the GPM mission's SSM/I sensor on the DMSP F15 satellite. The dataset is produced by NASA using the Goddard Profiling (GPROF) algorithm, a Bayesian method that retrieves rain rates and vertical hydrometeor structure from passive microwave brightness temperatures. It uses homogeneous ECMWF-Interim reanalysis as ancillary data to ensure consistency for climate time series, with the last metadata update recorded on 2026-03 13.
Global precipitation and atmospheric water vapor data from the SSM/I sensor on the DMSP F14 satellite, processed using the GPROF algorithm. The dataset is a climate-reference product using ECMWF-Interim reanalysis for homogeneous ancillary data to ensure consistency over time. Version 07 is the current version, produced by NASA's Goddard Space Flight Center.
GPM_2AGPROFF16SSMIS is a Level 2 satellite dataset from NASA's Global Precipitation Measurement mission. The data provides precipitation profiles and related atmospheric fields retrieved from SSMIS radiometer observations using the GPROF Bayesian algorithm. Version 07 is the current and definitive version, superseding all previous releases.
Version 07 is the current version of this global precipitation dataset produced by NASA's GPM mission. The data is generated by the Goddard Profiling (2AGPROF) algorithm, which retrieves precipitation and related fields from a constellation of passive microwave sensors including GMI, SSMIS, and AMSR2. It provides near-real-time, standard, and climate products, differing in latency and ancillary data used, with the main strength being large spatial and temporal sampling.