FLDAS: Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System

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climate evapotranspiration humidity ldas monthly nasa runoff snow soil-moisture temperature wind


The FLDAS dataset (McNally et al. 2017), was designed to assist with food security assessments in data-sparse, developing country settings. It includes information on many climate-related variables including moisture content, humidity, evapotranspiration, average soil temperature, total precipitation rate, etc.

There are multiple different FLDAS datasets; this one uses Noah version 3.6.1 surface model with CHIRPS-6 hourly rainfall that has been downscaled using the NASA Land Surface Data Toolkit. which is part of the Land Information System framework. Temporal desegregation is required so that daily rainfall inputs can be used in both energy and water balance calculations

For forcing data, this simulation uses a combination of the new version of Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), a quasi-global rainfall dataset designed for seasonal drought monitoring and trend analysis (Funk et al., 2015).



11132 meters


Name Units Description
Evap_tavg kg/m^2/s


LWdown_f_tavg W/m^2

Downward longwave radiation flux

Lwnet_tavg W/m^2

Net longwave radiation flux

Psurf_f_tavg Pa

Surface pressure

Qair_f_tavg Mass fraction

Specific humidity

Qg_tavg W/m^2

Soil heat flux

Qh_tavg W/m^2

Sensible heat net flux

Qle_tavg W/m^2

Latent heat net flux

Qs_tavg kg/m^2/s

Storm surface runoff

Qsb_tavg kg/m^2/s

Baseflow-groundwater runoff

RadT_tavg K

Surface radiative temperature

Rainf_f_tavg kg/m^2/s

Total precipitation rate


Snow cover fraction

SnowDepth_inst m

Snow depth

Snowf_tavg kg/m^2/s

Snowfall rate

SoilMoi00_10cm_tavg Volume fraction

Soil moisture (0 - 10 cm underground)

SoilMoi10_40cm_tavg Volume fraction

Soil moisture (10 - 40 cm underground)

SoilMoi100_200cm_tavg Volume fraction

Soil moisture (100 - 200 cm underground)

SoilMoi40_100cm_tavg Volume fraction

Soil moisture (40 - 100 cm underground)

SoilTemp00_10cm_tavg K

Soil temperature (0 - 10 cm underground)

SoilTemp10_40cm_tavg K

Soil temperature (10 - 40 cm underground)

SoilTemp100_200cm_tavg K

Soil temperature (100 - 200 cm underground)

SoilTemp40_100cm_tavg K

Soil temperature (40 - 100 cm underground)

SWdown_f_tavg W/m^2

Surface downward shortwave radiation

SWE_inst kg/m^2

Snow water equivalent

Swnet_tavg W/m^2

Net shortwave radiation flux

Tair_f_tavg K

Near surface air temperature

Wind_f_tavg m/s

Near surface wind speed

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.


  • If you use these data in your research or applications, please include a reference in your publication(s) similar to the following example: Amy McNally NASA/GSFC/HSL (2018), FLDAS Noah Land Surface Model L4 Global Monthly 0.1 x 0.1 degree (MERRA-2 and CHIRPS), Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: [Data Access Date], doi:10.5067/5NHC22T9375G

  • McNally, A., Arsenault, K., Kumar, S., Shukla, S., Peterson, P., Wang, S., Funk, C., Peters-Lidard, C.D., & Verdin, J. P. (2017). A land data assimilation system for sub-Saharan Africa food and water security applications. Scientific Data, 4, 170012.

Explore with Earth Engine

Code Editor (JavaScript)

var dataset=ee.ImageCollection('NASA/FLDAS/NOAH01/C/GL/M/V001')
              .filter(ee.Filter.date('2018-11-01', '2018-12-01'));
var layer = dataset.select('Evap_tavg');

var band_viz = {
  min: 0.0,
  max: 0.00005,
  opacity: 1.0,
  palette: ['black', 'blue', 'purple', 'cyan', 'green', 'yellow', 'red']

Map.setCenter(30.0, 30.0, 2);
Map.addLayer(layer, band_viz, 'Average Evapotranspiration');

Open in Code Editor