GLDAS-2¶

Global Land Data Assimilation System Version 2 (GLDAS-2.0, 2.1 and 2.2 — NASA global land surface model output from Noah, CLSM and VIC)

Available

At a glance¶

Note on period: GLDAS-2.0 covers 1948-01-01 03Z to 2014-12-31 21Z (Princeton forcing); GLDAS-2.1 runs from 2000-01-01 to the present; GLDAS-2.2 from 2003-02-01 to the present. On 2026-10-13 the GLDAS-2.1 and 2.2 main products extended to 2026-06-30 and the Early Products (_EP) to 2026-09-16. Early Products are a rolling archive of roughly the last 2–3 months and are deleted once the main products appear.

Overview¶

GLDAS is NASA GSFC's global land product: land surface models are driven by observation-based precipitation and radiation plus atmospheric analyses to produce soil moisture, snow, evapotranspiration, runoff and surface energy fluxes over all land. The current generation, GLDAS-2, has three streams: 2.0, a consistent 1948–2014 rerun forced by the Princeton dataset; 2.1, a near-real-time record from 2000 forced by GDAS, GPCP and AGRMET; and 2.2, a daily Catchment-model product forced by ECMWF analyses with GRACE/GRACE-FO terrestrial water storage assimilated. 2.0 and 2.1 are open-loop simulations with no data assimilation, and provide Noah 3.6, CLSM-F2.5 and VIC 4.1.2 output on 0.25° and 1° grids.

What changes with the successor¶

GLDAS-1 → GLDAS-2.1¶

Transition: 2020-06

GLDAS-1 production ended with March 2020 data and all GLDAS-1 products were removed from GES DISC on 30 June 2020. GLDAS-2.1, with new forcing and upgraded land surface models, replaces it.

Sources: GLDAS-1 products will be decommissioned on 6/30/2020 (NASA LDAS) · README for NASA GLDAS Version 2 Data

Available variables¶

Main variables from the GLDAS-2 README tables and a GES DISC file (GLDAS_NOAH10_M 2.0). Names are the netCDF variable names and are case-sensitive (Noah uses Tveg_tavg, CLSM and VIC use TVeg_tavg). Variables with _f are forcing, not model output. The 3-hourly groups below use the Noah 0.25°/1° names; CLSM and VIC share the flux and snow names and differ only in the soil variables.

instantaneous mean accumulated maximum minimum static — instantaneous: value at the time stamp · mean/accumulated/maximum/minimum: over the indicated interval · static: does not change with time

Energy fluxes (3-hourly, mean over the previous 3 hours)¶

Water fluxes (3-hourly)¶

Surface and soil states (Noah 3-hourly, instantaneous)¶

Forcing (_f, 3-hourly)¶

CLSM and VIC 1° only (3-hourly)¶

Monthly files (GLDAS_*_M — same variable names as 3-hourly)¶

GLDAS-2.2 CLSM daily (GLDAS_CLSM025_DA1_D, 24-hour means)¶

The full variable list is in the official documentation.

How to get the data¶

• NASA GES DISC — GLDAS dataset list — HTTPS download / earthaccess / Earthdata Search / OPeNDAP / subsetting
  • Short names follow GLDAS__ (e.g. GLDAS_NOAH025_3H, GLDAS_NOAH10_M, GLDAS_CLSM025_DA1_D), and versions are 2.0, 2.1 and 2.2. Early Products carry an _EP suffix (e.g. GLDAS_NOAH025_3H_EP). A free Earthdata Login is required. The old server (hydro1.gesdisc.eosdis.nasa.gov) may close after 30 September 2026, so switch to data.gesdisc.earthdata.nasa.gov or earthaccess.
• NASA Earthdata Search — Web search and ordering / subsetting
  • Pick a collection, time range and region to get granule lists and download scripts.
• AWS us-west-2 direct access (S3) — Cloud storage (S3, in-region us-west-2 only)
  • Example: s3://gesdisc-cumulus-prod-protected/GLDAS/GLDAS_NOAH025_3H.2.1/ — temporary credentials are required.
• NASA Giovanni — Web maps and time series; NetCDF, GeoTIFF and KMZ downloads
  • Handy for checking area-mean time series or maps before downloading.

Example code¶

Uses earthaccess to download the 2020 Noah 0.25° monthly files (V2.1) and convert them over Korea to monthly precipitation (mm), monthly surface runoff (mm) and volumetric top-layer soil moisture. Each file is a global field, so bounding_box only narrows the search; the actual cropping is done in xarray.

import earthaccess
import xarray as xr

earthaccess.login()  # free NASA Earthdata account
results = earthaccess.search_data(
    short_name="GLDAS_NOAH025_M", version="2.1",
    temporal=("2020-01-01", "2020-12-31"),
    bounding_box=(124, 33, 132, 39),   # (west, south, east, north)
)
files = earthaccess.download(results, "gldas_noah025_m")

ds = xr.open_mfdataset(files, combine="by_coords")
sub = ds.sel(lon=slice(124, 132), lat=slice(33, 39))
days = sub["time"].dt.days_in_month

precip_mm = sub["Rainf_f_tavg"] * 86400 * days   # monthly mean rate (kg m-2 s-1) -> monthly total (mm)
qs_mm = sub["Qs_acc"] * 8 * days                 # monthly mean of 3-hour totals -> monthly runoff (mm)
sm_vol = sub["SoilMoi0_10cm_inst"] / 100.0       # 0-10 cm layer, kg m-2 -> m3 m-3
print(precip_mm.mean(["lat", "lon"]).values)

Practical tips¶

• GLDAS-2.0 (Princeton forcing) and 2.1 (GDAS, GPCP, AGRMET) use different forcing, so values differ even in their 2000–2014 overlap. The README itself warns that combining 2.0, 2.1 and 2.2 into one series may introduce discontinuities. If you must splice them, check the differences in the overlap and state the join date in your paper.
• Forcing also changes within GLDAS-2.1: January 2000 to February 2001 used only GDAS and GPCP; AGRMET radiation was added from March 2001; AGRMET has an apparent climatology shift after 2011 that scaling could not remove; and from 2025-06-09 the radiation input is GALWEM. Check these dates in trend analyses.
• GLDAS-2.2 is a separate daily CLSM product with ECMWF forcing and GRACE/GRACE-FO assimilation. Its files contain no forcing variables, and its values differ from 2.1 CLSM (1°) even though the model is the same. It is the one to use for terrestrial water storage and groundwater studies.
• Early Products (_EP) are deleted when the main products appear and do not match them (2.1 EP is run without GPCP precipitation, 2.2 EP without GRACE assimilation). If you filled the latest months with EP data, replace them with the main products later.
• Soil moisture is in kg m-2 (water depth in the layer, mm). To compare with volumetric water content (m3 m-3), divide by the layer thickness in mm (÷100 for Noah 0–10 cm, ÷300 for 10–40 cm).
• _acc variables in monthly files are 'kg m-2 per 3 hours'. Do not read the kg m-2 label as a monthly total; multiply by 8 × days in the month.
• There is no glacier or ice-sheet model, so snow water equivalent accumulates indefinitely over Greenland, some other Arctic points and permanently frozen parts of the Himalaya. Mask these cells before computing global totals or means.
• In October 2020, invalid model values over inland water were masked with the MODIS (MOD44W) land mask. Re-download any 2.0 or 2.1 3-hourly or monthly data obtained before 1 November 2020.
• Snow density computed from SWE and snow depth in the GLDAS-2.0 CLSM 0.25° daily product is invalid, because snow depth did not account for snow-cover fraction. The 2.1 3-hourly/monthly and 2.2 daily products are not affected.

Notices and change history¶

References for your paper¶

Dataset citation¶

GLDAS-2.1 Noah 0.25° 3-hourly (GES DISC) — DOI 10.5067/E7TYRXPJKWOQ

@misc{gldas21_noah025_3h,
  author    = {Beaudoing, H. and Rodell, M.},
  title     = {{GLDAS} Noah Land Surface Model {L4} 3 hourly 0.25 x 0.25 degree, Version 2.1},
  year      = {2020},
  publisher = {Goddard Earth Sciences Data and Information Services Center (GES DISC)},
  address   = {Greenbelt, MD, USA},
  doi       = {10.5067/E7TYRXPJKWOQ}
}

GLDAS-2.1 Noah 0.25° monthly (GES DISC) — DOI 10.5067/SXAVCZFAQLNO

@misc{gldas21_noah025_m,
  author    = {Beaudoing, H. and Rodell, M.},
  title     = {{GLDAS} Noah Land Surface Model {L4} monthly 0.25 x 0.25 degree, Version 2.1},
  year      = {2020},
  publisher = {Goddard Earth Sciences Data and Information Services Center (GES DISC)},
  address   = {Greenbelt, MD, USA},
  doi       = {10.5067/SXAVCZFAQLNO}
}

GLDAS-2.0 Noah 0.25° 3-hourly (GES DISC) — DOI 10.5067/342OHQM9AK6Q

@misc{gldas20_noah025_3h,
  author    = {Beaudoing, H. and Rodell, M.},
  title     = {{GLDAS} Noah Land Surface Model {L4} 3 hourly 0.25 x 0.25 degree, Version 2.0},
  year      = {2019},
  publisher = {Goddard Earth Sciences Data and Information Services Center (GES DISC)},
  address   = {Greenbelt, MD, USA},
  doi       = {10.5067/342OHQM9AK6Q}
}

GLDAS-2.2 CLSM 0.25° daily GRACE-DA1 (GES DISC) — DOI 10.5067/TXBMLX370XX8

@misc{gldas22_clsm025_da1_d,
  author    = {Li, B. and Beaudoing, H. and Rodell, M.},
  title     = {{GLDAS} Catchment Land Surface Model {L4} daily 0.25 x 0.25 degree {GRACE-DA1}, Version 2.2},
  year      = {2020},
  publisher = {Goddard Earth Sciences Data and Information Services Center (GES DISC)},
  address   = {Greenbelt, MD, USA},
  doi       = {10.5067/TXBMLX370XX8}
}

Reference papers¶

GLDAS reference paper — DOI 10.1175/BAMS-85-3-381

@article{rodell2004gldas,
  author  = {Rodell, M. and Houser, P. R. and Jambor, U. and Gottschalck, J. and Mitchell, K. and Meng, C.-J. and Arsenault, K. and Cosgrove, B. and Radakovich, J. and Bosilovich, M. and Entin, J. K. and Walker, J. P. and Lohmann, D. and Toll, D.},
  title   = {The Global Land Data Assimilation System},
  journal = {Bulletin of the American Meteorological Society},
  volume  = {85},
  number  = {3},
  pages   = {381--394},
  year    = {2004},
  doi     = {10.1175/BAMS-85-3-381}
}

GLDAS-2.2 GRACE data assimilation — DOI 10.1029/2018WR024618

@article{li2019graceda,
  author  = {Li, Bailing and Rodell, Matthew and Kumar, Sujay and Beaudoing, Hiroko Kato and Getirana, Augusto and Zaitchik, Benjamin F. and de Goncalves, Luis Gustavo and Cossetin, Camila and Bhanja, Soumendra and Mukherjee, Abhijit and Tian, Siyuan and Tangdamrongsub, Natthachet and Long, Di and Nanteza, Jamiat and Lee, Jejung and Policelli, Frederick and Goni, Ibrahim B. and Daira, Djoret and Bila, Mohammed and de Lannoy, Gabrielle and Mocko, David and Steele-Dunne, Susan C. and Save, Himanshu and Bettadpur, Srinivas},
  title   = {Global {GRACE} Data Assimilation for Groundwater and Drought Monitoring: Advances and Challenges},
  journal = {Water Resources Research},
  volume  = {55},
  number  = {9},
  pages   = {7564--7586},
  year    = {2019},
  doi     = {10.1029/2018WR024618}
}

Acknowledgements¶

Cite the DOI of each product you actually used (model, resolution, interval, version). DOIs for the other products are tabulated in the README (e.g. GLDAS-2.1 Noah 1° monthly 10.5067/LWTYSMP3VM5Z, CLSM 1° 3-hourly 10.5067/VCO8OCV72XO0, VIC 1° 3-hourly 10.5067/ZOG6BCSE26HV, 2.2 Early Product 10.5067/IIU5JWU2AGRP). NASA asks that publications include: "The data used in this study were acquired as part of the mission of NASA's Earth Science Division and archived and distributed by the Goddard Earth Sciences (GES) Data and Information Services Center (DISC)." If you use GLDAS-2.2, also follow the README guidance on acknowledging the ECMWF forcing.

Information on the datasets used in this study was compiled with the help of the Korean Climate Data Navigator (KCDN) (Sim, 2026; https://doi.org/10.5281/zenodo.23300923).

Links¶

• NASA LDAS — GLDAS
• README for NASA GLDAS Version 2 Data (variable tables, time conventions, DOI table)
• GES DISC GLDAS_NOAH025_3H 2.1
• GES DISC GLDAS_CLSM025_DA1_D 2.2
• NASA LDAS news (GLDAS, NLDAS, FLDAS)