GLDAS-2.2: Global Land Data Assimilation System

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Dataset Provider
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3-hourly climate evaporation forcing geophysical gldas humidity ldas nasa precipitation pressure radiation soil soil-moisture surface temperature wind


NASA Global Land Data Assimilation System Version 2 (GLDAS-2) has three components: GLDAS-2.0, GLDAS-2.1, and GLDAS-2.2. GLDAS-2.0 is forced entirely with the Princeton meteorological forcing input data and provides a temporally consistent series from 1948 through 2014. GLDAS-2.1 is forced with a combination of model and observation data from 2000 to present. GLDAS-2.2 product suites use data assimilation (DA), whereas the GLDAS-2.0 and GLDAS-2.1 products are "open-loop" (i.e., no data assimilation). The choice of forcing data, as well as DA observation source, variable, and scheme, vary for different GLDAS-2.2 products.GLDAS-2.2 is new to the GES DISC archive and currently includes a main product from CLSM-F2.5 with Data Assimilation for the Gravity Recovery and Climate Experiment (GRACE-DA) from February 2003 to present. The GLDAS-2.2 data are available in two production streams: main and Early, only main one is ingested.

The GLDAS-2.2 GRACE-DA product was simulated with Catchment-F2.5 in Land Information System (LIS) Version 7. The data product contains 24 land surface fields from February 1, 2003 to present.

The simulation started on February 1, 2003 using the conditions from the GLDAS-2.0 Daily Catchment model simulation, forced with the meteorological analysis fields from the operational European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System. The total terrestrial water anomaly observation from GRACE satellite was assimilated (Li et al, 2019). Due to the data agreement with ECMWF, this GLDAS-2.2 daily product does not include the meteorological forcing fields.


Provider's Note: the names with extension _tavg are variables averaged over the past 3-hours, the names with extension '_acc' are variables accumulated over the past 3-hours, the names with extension '_inst' are instantaneous variables, and the names with '_f' are forcing variables.


27830 meters


Name Units Min Max Description
ACond_tavg m/s 0.000379* 5.99291*

Aerodynamic conductance

AvgSurfT_tavg K 179.818* 324.265*

Average surface skin temperature

CanopInt_tavg kg/m^2 0* 1.57295*

Plant canopy surface water

ECanop_tavg kg/m^2/s -0.021881* 5.3e-05*

Canopy water evaporation

ESoil_tavg kg/m^2/s -0.003637* 0.001172*

Direct evaporation from bare soil

EvapSnow_tavg kg/m^2/s -0.021057* 0.000728*

Snow Evaporation

Evap_tavg kg/m^2/s -0.02737* 0.00121*


GWS_tavg mm 77.0153* 3599.01*

Ground water storage

Lwnet_tavg W/m^2 -221.308* 490.842*

Net long-wave radiation flux

Qg_tavg W/m^2 -344.072* 174.036*

Heat flux

Qh_tavg W/m^2 -2851.75* 54076.7*

Sensible heat net flux

Qle_tavg W/m^2 -53856.6* 2983.65*

Latent heat net flux

Qsb_tavg kg/m^2/s 0* 0.000416*

Baseflow-groundwater runoff

Qsm_tavg kg/m^2/s 0* 0.018311*

Snow melt

Qs_tavg kg/m^2/s 0* 0.020244*

Storm surface runoff

SnowDepth_tavg m 0* 8.57951*

Snow depth

SnowT_tavg K 179.818* 324.265*

Snow Surface temperature

SoilMoist_P_tavg kg/m^2 109.394* 4049.02*

Profile Soil moisture

SoilMoist_RZ_tavg kg/m^2 32.3665* 478.397*

Root Zone Soil moisture

SoilMoist_S_tavg kg/m^2 0.001389* 9.56*

Surface Soil moisture

SWE_tavg kg/m^2 0* 3688.07*

Snow depth water equivalent

Swnet_tavg W/m^2 0* 421.784*

Net short wave radiation flux

TVeg_tavg kg/m^2/s -0.000371* 0.001654*


TWS_tavg mm 109.394* 5084.16*

Terrestrial water storage

* estimated min or max value

Image Properties

Image Properties

Name Type Description
end_hour DOUBLE

End hour

start_hour DOUBLE

Start hour

Terms of Use

Terms of Use

Distribution of data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) is funded by NASA's Science Mission Directorate (SMD). Consistent with NASA Earth Science Data and Information Policy, data from the GES DISC archive are available free to the user community. For more information visit the GES DISC Data Policy page.


  • Li, B., M. Rodell, S. Kumar, H. Beaudoing, A. Getirana, B. F. Zaitchik, et al. (2019) Global GRACE data assimilation for groundwater and drought monitoring: Advances and challenges. Water Resources Research, 55, 7564-7586.

  • Additional references

Explore with Earth Engine

Code Editor (JavaScript)

var dataset = ee.ImageCollection('NASA/GLDAS/V022/CLSM/G025/DA1D')
                  .filter('2010-06-01', '2010-06-02'));
var averageSurfaceSkinTemperatureK ='AvgSurfT_tavg');
var averageSurfaceSkinTemperatureKVis = {
  min: 258,
  max: 316,
  palette: ['1303ff', '42fff6', 'f3ff40', 'ff5d0f'],
Map.setCenter(71.72, 52.48, 3.0);
    averageSurfaceSkinTemperatureK, averageSurfaceSkinTemperatureKVis,
    'Average Surface Skin Temperature [K]');
Open in Code Editor