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Hydrology DISC

 Please also check the LDAS FAQ at the NASA Land Data Assimilation Systems for questions/answers regarding LDAS data products. 

Is there an LDAS user mailing list and how to subscribe?

NASA GES DISC has created an email list for better dissemination of NLDAS- and GLDAS-related information (e.g., new data releases, new data service releases, data reprocessing updates, data delays or outages).  The email address of this mailing list is

To subscribe to the mailing list, please fill out the request form at You will receive an email requesting confirmation. Once confirmed, your request will be held for approval by the list moderator. Upon approval you will be notified by the moderator via email. This is a private list, which means that the list of members is not available to non-members.

Please note that this mailing list will be used by NASA GES DISC only for disseminating NLDAS- and GLDAS-related information. For questions on NLDAS- and GLDAS-related data and services, please continue to send email to

What are the GLDAS products?

The Global Land Data Assimilation System (GLDAS) data products consist of time series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) parameters simulated by four land surface models (CLM, Mosaic, Noah and VIC). The 1.0 degree resolution data range from 1979 to present for the four models. The 0.25 degree data cover 2000 to present for the NOAH model. For more information about GLDAS, see

What are the differences among LDAS, NLDAS, and GLDAS?

The Land Data Assimilation Systems (LDAS) are being developed to enable more accurate reanalysis and forecast simulations by numerical weather prediction (NWP) models. Specifically, these systems will reduce the errors in the stores of soil moisture and energy which are often present in NWP models and which degrade the accuracy of forecasts. The LDAS are being implemented at 1/8 degree (about 15 kilometer) resolution across North America (NLDAS) and at 1/4 degree resolution globally (GLDAS). The systems are currently forced by terrestrial (NLDAS) and space-based (GLDAS) precipitation data, space-based radiation data, and numerical model output. NLDAS is currently running retrospectively and in near real-time. For more information about LDAS, see

What is the GRIB format? How can I interpret it?

The GRIB (GRIdded Binary) format is a mathematically concise data format commonly used in meteorology to store historical and forecasted weather data. For more details about the GRIB format, please see

WGRIB, GrADS, or other GRIB readers are required for reading the GLDAS data. WGRIB is a program to manipulate, inventory, and decode GRIB files. The source code and installation instructions for WGRIB are available from

The Grid Analysis and Display System (GrADS) is an interactive desktop tool for easy access, manipulation, and visualization of earth science data. The format of the data may be either binary, GRIB, NetCDF, or HDF. The documentation and software for GrADS can be found at

Why should I use GRIBTAB files to decode the GRIB files?

The GLDAS products were created using the GRIB format, but a specific parameter table was used in the encoding process. To read the GLDAS GRIB data, it is necessary to download the GRIBTAB and set the environmental variables first before using any GRIB readers! For more information, please see

What are the land surface models used in GLDAS?

Currently, GLDAS drives four land surface models: Mosaic, Noah, the Community Land Model (CLM), and the Variable Infiltration Capacity (VIC). More information about the models is available at the Land Data Assimilation Systems (LDAS) and Land Information System (LIS) Web sites.

Can I obtain the source codes for the land surface models?

Yes. The source codes for the land surface models can be obtained from the Land Information System (LIS) website. The LIS source code currently includes 3 land surface models: CLM, Noah and VIC.

Can I obtain the forcing data set that was used in GLDAS?

Forcing data are atmospheric inputs to the land surface models, including precipitation (rain and snow), radiation, and surface wind, temperature, pressure, and humidity (see Table 2 of GLDAS-1 and GLDAS-2 README documents).  They are included in the land surface model output files and can be obtained from the Hydrology Data Holdings website. For more information about the original data sources of GLDAS forcing data, please visit

Can I obtain the land surface parameter data sets used in GLDAS?

Land surface parameters are properties of the land surface (e.g., soil, land cover, and topography) that change at a time step of a day or longer. They can be obtained from .

Should I use GLDAS Version 1 (GLDAS-1) or GLDAS Version 2 (GLDAS-2)?

GLDAS-1 uses a mix of meteorological forcing (input) datasets for the period 1979 to present.  That results in some serious discontinuities around 1993, 1995, and 1999-2001.  From mid-2001 onward the GLDAS-1 forcing is consistent and includes high quality observational precipitation and solar radiation.  GLDAS-2 uses the Princeton meteorological forcing dataset, which is a reanalysis product that has been bias corrected using observation based products, for the period 1948-2010.  Thus if you need a long term record for evaluating trends or other applications that require consistency over a long period, GLDAS-2 is better for you.  However, if you are mainly interested in the recent period, roughly 2002 to present, and/or you require frequent updates to within 1-2 months of real time, then GLDAS-1 is a better choice for you.

What is the GrADS data server?

The GrADS Data Server (GDS, formerly known as the GrADS-DODS Server) is a stable, secure data server that provides subsetting and analysis services across the Internet. The core of the GDS is OPeNDAP, a software framework used for data networking which makes local data accessible to remote locations. GDS subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The GDS analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. Examples of analysis operations include basic math functions, averages, smoothing, differencing, correlation, and regression; the GDS supports any operation that can be expressed in a single GrADS expression.

Can you give an example of retrieving GLDAS data via GDS?

Users can retrieve GLDAS data from a GDS server using analysis tools such as GrADS, Ferret, Matlab, or IDL. Below is an example of a GrADS script to access the GDS server and draw the "Layer 10 soil moisture" (soilmoist10) parameter from the CLM model.



'set lon -180 180'

'set lat -60 90'

'set gxout grfill'

'set grads off'

'd soilm10'

'run cbarn'

'draw title GLDAS CLM 3-Hourly 1.0 degree Average Layer 10 Soil Moisture\ on Jan 2, 1979 at 00Z[k]'

How to retrieve GLDAS and NLDAS data via GDS as ASCII text?


The GDS can provide subsets of any data set it serves, in ASCII comma-delimited format. To retrieve a subset, enter a URL of the form http://gds-base-url/dataset.ascii?constraint.

The constraint portion of the URL should be an OPeNDAP constraint expression. Here are some basic constraints:

  • A constraint of the form "var" will request the complete contents of the variable.
  • A constraint of the form "var[a:b]" will return the subset of the variable defined by a and b.
  • A constraint of the form "var[a:n:b]" will  return every n th element of the subset defined by a and b, starting  with element a.

For subsets of variables with multiple dimensions, each dimension must have a constraint. So a constraint for a subset of a three-dimensional variable would appear as var[a1:b1][a2:b2][a3:b3] or var[a1:n1:b1][a2:n2:b2][a3:n3:b3].

For more information, please visit GrADS-DODS Server - User's Guide GDS.

IMPORTANT:  Due to the time limit of each Web session,  please specify a short time range at an attempt.  Otherwise,  if Web Session Timeout, nothing will be returned.

1. An example for GLDAS  (An example for NLDAS is also provided below.)

Here is an example for retrieving GLDAS NOAH Model 0.25 Degree 3-Hourly Data, subsetted by parameter and geo-region, as ASCII text,[0:2][389:392][417:418].

The result is as below.

evap, [3][4][2]
[0][0], 9.999E20, 9.999E20
[0][1], 9.999E20, 9.999E20
[0][2], 1.571E-5, 9.999E20
[0][3], 1.464E-5, 1.357E-5
[1][0], 9.999E20, 9.999E20
[1][1], 9.999E20, 9.999E20
[1][2], 6.4900023E-6, 9.999E20
[1][3], 5.5800024E-6, 5.9800022E-6
[2][0], 9.999E20, 9.999E20
[2][1], 9.999E20, 9.999E20
[2][2], 4.0999976E-6, 9.999E20
[2][3], 3.4199975E-6, 3.5399976E-6
time, [3]
730175.0, 730175.125, 730175.25
lat, [4]
37.375, 37.625, 37.875, 38.125
lon, [2]
-75.625, -75.375

The expression evap[0:2][389:392][417:418] is an array expression; the numbers are array indexes, starting from 0; and "evap" is the variable name for "total evapotranspiration kg/m^2/s."

The dimension information is listed at the end of the results page. For this example, they are time, latitude, and longitude.

The time indexes, "730175.0, 730175.125, and 730175.25," are for days referenced from 00z01Jan0001. For this GLDAS NOAH Model 0.25 Degree 3-Hourly Data, corresponding time steps are 00Z24Feb2000, 03Z24Feb2000, and 06Z24Feb2000.

Here are the formulas for computing latitude, longitude, and index for 0.25 degree GLDAS.

 lat or lon to index: 
    latIndex = [lat - (-59.875)]/0.25
    lonIndex = [lon - (-179.875)]/0.25
 index to lat or lon:        

    lat = latIndex*0.25 + (-59.875)     
    lon = lonIndex*0.25 + (-179.875)

Information about GLDAS parameters and their corresponding variable names, as well as dimension information, can be found via GDS at More information about other GLDAS data sets are available at

2. An example for NLDAS

Here is an example for retrieving NLDAS-2 Mosaic Model 0.125 Degree Hourly Data, subsetted by parameter and geo-region, as ASCII text,[0:4][80:82][330:333].

The result is as below.

arainsfc, [5][3][4]
[0][0], 1.7018, 1.8356, 1.714, 1.515
[0][1], 2.383, 1.9492, 1.502, 1.4482
[0][2], 2.1638, 1.7084, 1.7128, 1.6206

[1][0], 1.8774, 2.0668, 1.9701, 1.7782
[1][1], 2.5921, 2.1661, 1.7055, 1.6803
[1][2], 2.3214, 1.8743, 1.9219, 1.8595

[2][0], 1.9778, 2.1998, 2.1181, 1.9308
[2][1], 2.8006, 2.363, 1.8781, 1.8675
[2][2], 2.5706, 2.0942, 2.166, 2.1133

[3][0], 1.7215, 1.9087, 1.8323, 1.6653
[3][1], 2.4163, 2.0321, 1.61, 1.596
[3][2], 2.1993, 1.7856, 1.8408, 1.7904

[4][0], 1.4244, 1.5505, 1.4612, 1.3039
[4][1], 1.8815, 1.552, 1.2063, 1.1733
[4][2], 1.6083, 1.2801, 1.2941, 1.2346

time, [5]
722452.0, 722452.0416666666, 722452.0833333334, 722452.125, 722452.1666666666
lat, [3]
35.063, 35.188, 35.313
lon, [4]
-83.688, -83.563, -83.438, -83.313

The result can be explained in the same way described in the example for GLDAS.

Here are the formulas for computing latitude, longitude, and index for 0.125 degree NLDAS.

 lat or lon to index: 
    latIndex = [lat - (25.0625)]/0.125
    lonIndex = [lon - (-124.9375)]/0.125
 index to lat or lon:        

    lat = latIndex*0.125 + (25.0625)     
    lon = lonIndex*0.125 + (-124.9375)

More details about How to Obtain Spatial Subsetted Time Series in ASCII Format via GDS please visit GES DISC Services Cookbook at

Information about NLDAS parameters and their corresponding variable names, as well as dimension information, can be found via GDS at More information about other NLDAS data sets are available at

What is the height of GLDAS near surface wind, temperature, and specific humidity?

The height of GLDAS near surface wind, temperature, and specific humidity is varies across model outputs depending on the choice of forcing data.  For the GLDAS data (forced by GDAS) at GES DISC NASA, the wind height is at 10 m,  temperature and  specific humidity are at 2m.

How to convert the rainfall unit of kg/m^2 to mm?

The unit of kg/m^2 is equivalent to mm,  as 1000 cm^3  of water has a mass of very nearly 1 kg at 4°C .

         kg/m^2 ==> m*kg/m^3 ==> m*kg/(100cm)^3 ==> 1000*mm*kg/(1000*1000*cm^3)  ==> 1000mm/1000 ==> mm

At any temperature other than 4 °C, the density of water is in fact lower (water is most dense at 4 °C). However, the change is very small at most temperatures, and so to a very close approximation, the mass of 1000 cm^3 of water is 1 kg at most temperatures. Therefore,  the rainfall unit of kg/m^2, as a very close approximation at most temperature, is equivalent to unit of mm.

Why was I prompted for a password to FTP data?
An ftp site is usually configured to allow certain number of clients to access the ftp site concurrently and certain number of connections concurrently per host (user). For example,  the up limit of concurrent connections to, is configured as 10 per user.  If you want to download data from the ftp site, you should limit your concurrent connections less that 10, otherwise some ftp attempts will fail to connect to the ftp site.
In the case an ftp connection failed due to too may concurrent connections, if  you use command line, you would get a message like below: 
“530 Sorry, the maximum number of clients (10) from your host are already connected.” 
However, if you use a method other than plain command line, you will get a different message. For example, you may be prompted for a password.  If you use “wget”, you can use “wget –S”. The “-S” option enables server-response and will print the headers sent by HTTP servers and responses sent by FTP servers.
Why globally averaged  GLDAS Snow Water Equivalent (SWE) shows a upward trend?
In GLDAS, there is no ice sheet model that melts/displays snow over glacier, so that the snow keeps accumulating over Greenland and surrounding areas near North Pole. If you want to see the trend of globally averaged SWE, first create a map of permanent snow where there is always SWE over the entire period, and then do global average, with those grid boxes masked out.


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Last updated: Jul 08, 2016 08:04 AM ET