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Climate models, weather data, oceanography, hydrology, atmospheric science, environmental monitoring
28,268 datasets
ECCO Version 4 Release 4 provides a 26-year reconstruction of global ocean currents, synthesized from over a dozen satellite and in-situ observation programs. This monthly-averaged dataset interpolates velocity to a regular 0.5-degree grid, offering a dynamically consistent state estimate produced by NASA. The temporal coverage spans from January 1992 to January 2018.
1992-01-01 to 2018-01-01 monthly-averaged dynamic sea surface height data on a regular 0.5-degree grid, produced by NASA's ECCO project. The dataset is a dynamically consistent ocean state estimate from the MITgcm model, constrained by multiple satellite and in-situ observations including altimetry, sea surface temperature, and salinity. It covers a 26-year period relevant for climate and ocean circulation studies.
1992-01-01 to 2018-01-01 daily-averaged dynamic sea surface height and model sea level anomaly data on the native LLC90 grid. The dataset is an ocean and sea-ice state estimate from NASA's ECCO V4r4 project, a dynamically consistent reconstruction of the global ocean state. It assimilates observations from multiple satellite altimeters, radiometers, gravimeters, and in-situ programs like Argo and WOCE.
1992-01-01 to 2018-01-01 monthly-averaged dynamic sea surface height and model sea level anomaly data on the native LLC90 grid. The dataset is a dynamically consistent ocean state estimate from NASA's ECCO project, produced by fitting a 1-degree global MITgcm model run to multiple satellite and in-situ observations.
Daily-averaged dynamic sea surface height data interpolated to a regular 0.5-degree grid. The dataset is a dynamically consistent ocean state estimate from the ECCO V4r4b model, produced by NASA, covering the period from 1992-01-01 to 2018-01-01. It assimilates observations from multiple satellite altimeters and in-situ instruments.
1992-01-01 to 2018-01-01 monthly-averaged dynamic sea surface height and model sea level anomaly data on the native Lat-Lon-Cap 90 (LLC90) model grid. The National Aeronautics and Space Administration produced this dataset as part of the ECCO Version 4 Release 4b (V4r4b) ocean and sea-ice state estimate, which is a dynamically consistent reconstruction fit to multiple satellite and in-situ observations.
ECCO Version 4 Release 4 provides a 26-year daily reconstruction of global sea-ice and snow conditions from 1992 to 2017. This state estimate from NASA combines a dynamical ocean model with observations from satellite altimeters, radiometers, gravimeters, and in-situ sensors. The dataset offers daily-averaged concentration, thickness, and pressure loading on a specialized LLC90 grid.
ECCO Version 4 Release 4 provides daily-averaged sea-ice velocity interpolated to a regular 0.5-degree grid. The dataset is a dynamically consistent reconstruction of ocean and sea-ice states, produced by NASA by fitting a global MITgcm model to multiple satellite and in-situ observations. It covers the period from January 1, 1992, to January 1, 2018.
Global monthly-averaged sea-ice and snow horizontal volume fluxes on the native LLC90 grid from the ECCO Version 4 Release 4 ocean and sea-ice state estimate. The dataset is produced by NASA and covers the period from January 1992 to January 2018. It is a dynamically consistent reconstruction fit to multiple observational constraints including satellite altimetry, sea surface temperature, salinity, and in-situ ocean profiles.
Monthly-averaged sea-ice velocity data from a 26-year, dynamically consistent ocean and sea-ice state estimate produced by NASA's ECCO project. The ECCO Version 4 Release 4 reconstruction assimilates observations from over a dozen satellite missions and in-situ programs like Argo and GO-SHIP. This dataset covers the period from 1992 to 2017 on the native Lat-Lon-Cap 90 (LLC90) computational grid.
1992-01-01 to 2018-01-01 daily-averaged sea-ice salt plume fluxes on the native LLC90 grid from the ECCO Version 4 Release 4 ocean and sea-ice state estimate. The data is a dynamically consistent reconstruction produced by NASA, fitting a 1-degree global MITgcm model to multiple observational constraints including satellite altimetry, sea surface temperature, salinity, and in-situ measurements. Observational constraints include data from satellites like ERS-1/2, TOPEX/Poseidon, Jason series, and CryoSat-2, as well as programs like Argo and GO-SHIP.
Nimbus-5 satellite brightness temperature data measured at 19.35 GHz from December 11, 1972 through May 16, 1977. The data were recovered from original IBM binary tapes and contain calibrated radiances from the Electrically Scanning Microwave Radiometer (ESMR). The ESMR Principal Investigator was Dr. Thomas T. Wilheit, Jr. from NASA Goddard Space Flight Center.
NASA's Global Land Data Assimilation System Version 2.0 (GLDAS-2.0) daily dataset contains a series of land surface parameters simulated from the Catchment Land Surface Model 3.6. It provides a temporally consistent series from January 1948 through December 2014, forced entirely with Princeton meteorological forcing data. The data are archived and distributed in netCDF format by NASA's GES DISC.
NASA's Global Land Data Assimilation System Version 2.0 (GLDAS-2.0) monthly data provides a series of land surface variables. The data are generated by temporally averaging 3-hourly simulations from the Catchment Land Surface Model and cover the period from January 1948 to December 2014. The model is forced with Princeton meteorological data and uses MODIS-based land surface parameters.
36 land surface fields from January 2000 to present, generated by NASA's Global Land Data Assimilation System (GLDAS-2.1). The monthly data product is an average of 3-hourly simulations from the Noah Model 3.6, forced with a combination of model and observational data. This 'Early Product' stream has about a 1.5-month latency and is archived in NetCDF format.
NASA's GLDAS-2.1 Noah Land Surface Model Early Product provides 36 land surface fields from January 2000 to the present. The data is simulated at a 3-hourly temporal resolution and a 0.25 x 0.25 degree spatial grid, forced by a combination of model and observational data. This early production stream has a latency of about 1.5 months before being superseded by the main production data.
36 land surface fields are simulated by the Noah Model 3.6 from January 2000 to the present. NASA's Global Land Data Assimilation System Version 2.1 (GLDAS-2.1) combines model and observational forcing data, including NOAA/GDAS and GPCP precipitation. This specific product, reprocessed in January 2020, is a main production stream replacement for previous versions and uses a MODIS land mask to correct inland water representation.
NASA's Global Land Data Assimilation System Version 2.1 (GLDAS-2.1) provides 34 land surface fields simulated by the VIC Land Surface Model 4.1.2. The dataset offers 3-hourly data at a 1.0 x 1.0 degree spatial resolution, covering the period from January 2000 to the present. It is an 'Early Product' stream with approximately 1.5-month latency, forced by a combination of model and observational data.
NASA's GLDAS-2.0 VIC 3-hourly data set contains a series of land surface variables simulated with the Variable Infiltration Capacity (VIC) 4.1.2 Land Surface Model. The data set covers from January 1948 to December 2014 at a 1.0-degree spatial resolution and is forced by the Princeton meteorological forcing data set. It is archived and distributed in netCDF format by NASA's GES DISC.
36 land surface fields are provided from January 2000 to present, generated by NASA's Global Land Data Assimilation System (GLDAS-2.1). The monthly data product is an Early Product with about 1.5 month latency, created by temporally averaging 3-hourly simulations from the Noah Model 3.6. It is forced with a combination of NOAA/GDAS atmospheric analysis, GPCP precipitation, and AGRMET radiation fields.