The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. New data formats (e.g., netCDF), temporal averaging and spatial subsetting will be available in the future. The HDISC has the capability to support more hydrology data products and more advanced analysis tools. The goal is to develop HDISC as a data and services portal that supports weather and climate forecast, and water and energy cycle research

Fang, Hongliang

Hrubiak, Patricia

Kato, Hiroko

Rodell, Matthew

Teng, William L.

Vollmer, Bruce E.

NASA Technical Reports Server

GLOBAL LAND DATA ASSIMILATION SYSTEM (GLDAS) PRODUCTS FROM NASA 
HYDROLOGY DATA AND INFORMATION SERVICES CENTER (HDISC) 
Hongliang  an^',^, Patricia L. ~ r u b i a k ' . ~ ,  Hiroko ~ a t o ~ ' ~ ,  Matthew ~ o d e l l ~ ,  
William L.  en^',^, Bruce E. ~o l lmer'  
1 Goddard Earth Sciences Data and Information Services Center, Code 610.2, Goddard Space Flight Center, 
NASA, Greenbelt, MD 2077 1 
2 Hydrological Sciences Branch, Code 614.3, Goddard Space Flight Center, NASA, Greenbelt, MD 20771 
3 ~ y l e  Information Systems, 165 1 Old Meadow Road, McLean, VA 22102 
4 Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20742 
Hongliang.Fang. 1 @nasa.gov; patricia.l.hrubiak@nasa.gov; hiroko.kato@nasa.gov; 
matthew.rodell@nasa.gov; william.l.teng@nasa.gov; bruce.e.vollmer@nasa.gov~ 
ABSTRACT 
The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture 
and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface 
models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information 
Services Center (HDISC), a component of the NASA Goddard Earth Sciences Data and Information Services Center 
(GES DISC). Current data holdings include a set of 1.0 degree resolution data products from the four models, 
covering 1979 to the present; and a 0.25 degree data product from the Noah model, covering 2000 to the present. 
The products are in Gridded Binary (GRIB) format and can be accessed through a number of interfaces. New data 
formats (e.g., netCDF), temporal averaging and spatial subsetting will be available in the future. The HDISC has the 
capability to support more hydrology data products and more advanced analysis tools. The goal is to develop 
HDISC as a data and services portal that supports weather and climate forecast, and water and energy cycle 
research. 
INTRODUCTION 
Global hydrological data such as soil moisture and evaporation are crucial for understanding the land surface 
process and the atmospheric general circulation modeling for climate simulation and weather forecasting. The 
Hydrologic Sciences Branch (HSB) at NASA's Goddard Space Flight Center (GSFC) has collected a series of 
surface hydrological data sets in order to enable a better understanding of the global hydrospheric cycle. These data 
sets include field measurements, parameters simulated from land surface models, and products derived from many 
satellite instruments. 
NASA is mandated by Congress to make its data and products available to the broader user community. The 
Hydrology Data and Information Services Center (HDISC) was developed as part of the NASA Goddard Earth 
Sciences Data and Information Services Center (GES DISC) to archive and support data products generated by the 
GSFC HSB. 
HDISC is a portal to a hydrology-specific, on-line, easy-access archive and distribution system, employing data 
analysis and visualization, data subsetting, and other user-requested techniques for better science data usage. HDISC 
provides convenient access to hydrology data and information from various land surface models. The first products 
hosted are outputs from the Global Land Data Assimilation System (GLDAS) (Rodell et al., 2004). The HDISC has 
the capability to support more hydrology data products and more advanced analysis tools. The goal is to develop 
HDISC as a data and services portal that supports weather and climate forecast, and water and energy cycle 
research. The following sections will introduce the GLDAS project and the data set, and the means to access the data 
set through HDISC. 
BACKGROUND ABOUT THE GLDAS 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 
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GLDAS drives multiple offline (not coupled to the atmosphere) land surface models, integrates a huge quantity 
of observation based data, and executes globally at 2.5' to 1 km resolutions, enabled by the Land Information 
System (LIS) (Kumar et al., 2006). Currently, GLDAS drives four land surface models: Mosaic, Noah, the 
Community Land Model (CLM), and the Variable Infiltration Capacity (VIC). GLDAS products include land 
surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) 
parameters. The temporal resolution for the GLDAS products is 3-hourly. Monthly products are also generated 
through temporal averaging of the 3-hourly products. For example, the total evapotranspiration for April 1979 is the 
average 3-hour mean rate of evapotranspiration over all the 3-hour intervals in April 1979. Output files from these 
four models are briefly described here. Table 1 lists some basic characteristics of the GLDAS data. 
Table 1. Basic characteristics of the GLDAS data. 
IC water balance ( 1 .OO) 
The data used by LIS include parameter data and forcing data. All simulations were initialized on model date 
January 1, 1979 using soil moisture and other state fields from the respective LSM climatology for that day of the 
year. The 1.0 degree resolution data range from 1979 to present for the four models. The 0.25 degree data cover 
2000 to present from the NOAH model. The forcing data set combines multiple data sets for the period of January 1, 
1979 to present: 
1979-1993: bias-corrected ECMWF Reanalysis data (Berg et al., 2003) 
1994-1999: bias-corrected NCAR Reanalysis data (Berg et al., 2003) 
2000: NOAA/GDAS atmospheric analysis fields 
2001-2007: a combination of NOAAJGDAS atmospheric analysis fields, spatially and temporally disaggregated 
NOAA Climate Prediction Center Merged Analysis of Precipitation (CMAP) fields, and observation based 
downward shortwave and longwave radiation fields derived using the method of the Air Force Weather 
Agency's AGRicultural METeorological modeling system (AGRMET) 
In NOAH (0.25"), snow cover data derived from the MODIS sensor aboard NASA's Terra satellite were 
assimilated in order to constrain the modeled snow water equivalent (SWE), using the updating technique described 
by Rodell and Houser (2004). SWE was adjusted when and where there was a discrepancy between the modeled 
SWE state (snow or no snow) and the MODIS snow cover state. A quantity of 10 rnrn SWE was added to pixels 
where the model did not have snow but the fractional MODIS snow cover was greater than 40%. Snow was 
removed from model pixels where MODIS indicated fractional snow cover was less than 10%. 
GLDAS DATA SET IN HDISC 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 
Current GLDAS data hosted at HDISC include a set of 1.0" data products, covering 1979 to the present, from 
the four models and a 0.25" data product, covering 2000 to the present, from the Noah model. Table 2 shows the 
number of files and data volume from each model. 
Table 2. Data volume from each land surface model hosted at HDISC 
The GLDAS LSM data were created using the GRIdded Binary (GRIB) format. GLDAS applies user-defined 
parameter tables for the GRIB files. Table 3 shows a list of parameters provided in the GRIB files. This table shows 
the GRIB Product Definition Section (PDS) ID and the corresponding parameter name. 
Table 3. Geophysical parameters generated from the GLDAS project. 
DATA READING AND INTERPRETATION 
To handle the GLDAS GRIB data, WGRIB, GrADS, or other GRIB readers are required. WGRIB is a program 
to manipulate, inventory, and decode GRIB files (http://www.cpc.ncep.noaa.gov/products/wesley/wgrib.html). 
WGRIB version 1.7.X is recommended to avoid any possible discrepancies caused by different WGRIB versions. 
The Grid Analysis and Display System (GrADS) is an interactive desktop tool for easy access, manipulation, and 
visualization of earth science data (http: / /p~.ads.~ges.~r~gl~i~ds/) .  Examples of using the GrADS to read the GLDAS 
data are shown in Figures 1 and 2, respectively. Figure 1 shows the 0.25 degree 3-hourly top layer soil moisture (0- 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 
10 cm) simulated from the Noah model at OOZ, May 1,2007. Figure 2 shows the 1.0 degree monthly top layer soil 
moisture (0-2 cm) simulated from the Mosaic model in May, 2007. 
GLDAS Noah 3-Hourly 0 . 2 5  de ree Avera e Layer 1 Soil Moisture 
on MAY 0 1 ,  2 0 8 7  a t  ooz fkg/rn2] 
Figure 1. The 0.25 degree 3-hourly top layer soil moisture (0-10 cm) simulated from 
the Noah model at OOZ, May 1,2007. 
GLDAS Mosaic Monthly 1.0 degree Average Layer 1 Soil Moisture 
in May 2 0 0 7  [kg/m2] 
Figure 2. The 1.0 degree monthly top layer soil moisture (0-2 cm) simulated from 
the Mosaic model in May, 2007. 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 
GRIB files identify the contents (e.g., soil moisture, temperature) by parameter numbers. These numbers are 
linked to their respective parameter names in a parameter table. The GLDAS data set applies a user-specific 
parameter table for each model to indicate the content and parameter number. An example of the parameter table for 
the Mosaic model is shown in Table 4. This table shows the PDS ID, the abbreviated and full variable names and 
their units. Users need to set the specific parameter table before using any GRIB reader. 
Table 4. The GRIB parameter table (GRIBTAB) for the MOSAIC output 
-1:-1:-1:-1 
11 1 :SWnet:Net Shortwave Radiation W/mA2 
1 12:LWnet:Net Longwave Radiation W/mA2 
12 1 :Qle:Latent Heat Flux W/mA2 
122:Qh:Sensible Heat Flux W/mA2 
155 :Qg:Ground Heat Flux W/mA2 
13 1:Snowf:Snowfall rate kg/mA2/s 
132:Rainf:Rainfall rate kg/mA2/s 
057:Evap:Total Evapotranspiration kg/mA2/s 
235 :Qs:Surface Runoff kg/mA2/s 
234:Qsb:Subsurface Runoff kglmA2/s 
099:Qsm:Snowmelt kg/mA2/s 
068:DelSoilMoist:Change in soil moisture kg/mA2 
078:DelSWE:Change in snow water equivalent kg/mA2 
138:AvgSurfT:Average Surface Temperature K 
085:SoT:Deep Soil Temperature K 
084:Albedo:Surface Albedo, All Wavelengths - 
065:SWE:Snow Water Equivalent kg/mA2 
086:SoilMl:Average layer 1 soil moisture kg/mA2 
086:SoilM2:Average layer 2 soil moisture kg/mA2 
086:SoilM3:Average layer 3 soil moisture kg/mA2 
207:SoilWet:Total Soil Wetness 
200:ECanop:Interception evaporation kg/mA2/s 
2 10:TVeg:Vegetation transpiration kg/mA2/s 
199:ESoil:Bare soil evaporation kg/mA2/s 
070:RootMoist:Root zone soil moisture kg/mA2 
07 1 :Canopint:Total canopy water storage kg/mA2 
174:ACond:Aerodynamic conductance mls 
032:Wind:Near surface wind magnitude mls 
059:Rainfforc:Rainfall rate kg/mA2/s 
064:Snowfforc:Snowfa11 rate kg/mA2/s 
01 1:Tair:Near surface air temperature K 
05 1 :Qair:Near surface specific humidity kg/kg 
00 1 :PSurf:Surface pressure Pa 
204:SWdown:Surface incident shortwave radiation W/mA2 
205:LWdown:Surface incident longwave radiation W/mA2 
The number of vertical levels for soil moisture (SoilM) is model specific. The generic GRIB table defines the 
different soil layers as SoilM1, . . ., SoilMN, respectively, where N is the number of soil layers. Table 5 lists the 
depths of soil layers used in different land surface models. Terrestrial water storage is the sum of soil moisture in all 
layers, accumulated snow, and plant canopy surface water. Total precipitation is the sum of rainfall and snowfall and 
the total runoff is the sum of subsurface runoff and surface runoff. 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 
Table 5. The depth of soil layers used in different land surface models. 
CLM 2.0 (10 layers) 
Depths 0-0.018,0.018-0.045, 0.045-0.091,0.091-0.166, 0.166-0.289, 0.289-0.493,0.493- 
0.829,0.829-1.383, 1.383-2.296, and 2.296-3.433 m. 
MOS (3 layers) 
Depths 0-0.02,0.02-1.50, and 1.5-3.50 m. 
NOAH (4 layers) 
Depths 0-0.1, 0.1-0.4, 0.4-1.0, and 1.0-2.0 m. 
VIC (3 layers) 
Depths 0-0.1,O.l-1.6, and 1.6-1.9 m. 
ACCESS HDISC DATA 
The HDISC maintains archives of all GLDAS data products. The data are publicly available. The archived data can 
be accessed via anonymous ftp network transfer. The GLDAS data holding and ftp downloading interface is shown 
in Figure 3. The 3-hourly GLDAS data can be downloaded directly via the GES DISC anonymous ftp: 
ftp://apdisc.gsfc.na~a.gc~~/data/s4pa/GLL3ASSUBl'/. The monthly GLDAS data can be downloaded from 
ftp://agdisc.gsfc.na~a.go~/data/s-lpa/GLDAS/ 
, - - &- 2 5 wtp IldiY wf< na%a wlhydroboYlh~do_pe(.6ata arm - b GI- 
- I 
m uors ma are firm t- annctl una *face -3 a a < o a w e e  r a s a r m  em *me o 25 
641- r e s w i m  rs vol Th.  fbr  are m ORB f o r m  They c w d a  - 20 611aerd Per-cr* Th.  
renine ad wbl& l los n t h  D > LMEYTlri Si ~g s d a  a t k  mlom&m -*(cdto r o d t k  dea 
Figure 3. HDISC data holding and ftp downloading page 
Search and Access System 
In addition to the basic anonymous data downloading, HDISC provides several advanced data search and 
downloading services, such as Mirador (Figure 4). Mirador, a Spanish word for a window offering an extensive 
view, is a Google-based search tool that provides keywords searching of Earth science data at the NASA GES 
DISC. In the Mirador interface, GLDAS data can be searched through a keyword (e.g., Noah) and the time span 
(Figure 4a). Once the list of data products is shown in the interface, users can download GLDAS data in batch mode 
(Figure 4b). 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 
Ear c L o ~ o u u o m F . 3 H  
:I IMdSskapdhmsT~Ca* 11- 
GLDASNd3 *&LA 1 . 0 d ~ ~ e m b r 1 a r i W  *GESDlSC 
n_,ur (Cw lDI1M31 lam m End lWlM31 
01801W S c r O ? ~ i M B #  
meaiiu (SurlDI1&3109.@ W hIod m l M 3 1  
- , .ma S,3,!2, 
n.n ( ~ ~ ' m ~ ~ ~ ~ o a r n . m  br 2mie.11 
-WMM S c r O i . ? M B #  
o3:mm s,o?:mt 
Figure 4. Search GLDAS in Mirador (a) and the output page (b) 
Access GLDAS products through the GrADS Data Server (GDS) 
1 GES DISC GrADS Da;a Srrrri oil mlirc - -1 + I  I GES DISC GrADS Data Server on agdirc - directory for I : 11 entries / 
1: GLDAS-CLMlOSUBP-3H: 1 0 Dcgrcc 3-Hourly Data From the CLM Modcl r&u 3d5 &s 
2: GLDAS-CLMlO-MEB: 1 0 Degree Monthly Encrgy Balance Data From the CLM Modcl d o  ddi das 
3: GLDAS-CLMlO-M.WB: 1 0 Degree Monfhiy Water Balance Data From the CLM Modcl :$;: && & 
4: GLDAS-MOSlOSUBP-3H. 1 0 Degree 3-Hourly Data From the Mossc Model d o  ddr dar 
5: GLDAS-MOSlO_M.EB: 1 0 Degree Monthly Energy Balancc Data From the Morrc Model xi: dds das 
1 6: GLDAS-MOSlO_M.WB: 1 0 Degree Monthly Water Balance Data From the Morrc Model t dp  & & I I 7: GLDAS-NOAHO2PSUBP-Y; 0 25 Degree 3-Hourly Data From the Noah Model L dds das I 1 8: GLDAS-NOAHlOSUBP-3H: 1 0 Dcgrcc 3-Hourly Data From the Noah Modcl L ~ O  dds das I I 9: GLDAS-NOAHLO-MXB: I 0 Degree Monthly Enom Balance Data From the Noah Mode1 g!ji hi:: & 
~ 
10: GLDAS-NOAHlO-M.WB: 1 0 Dcgrcc Monthly Water Balance Data From the Noah Modcl rLo ddr dar 
.d 
Figure 5. The HDISC GrADS Data Server (GDS) interface for the GLDAS products 
The GrADS Data Server (GDS) is a stable, secure data server that provides subsetting and analysis services 
across the internet. The core of the GDS is OPeNDAP (formerly DODS), a software framework used for data 
networking that makes local data accessible to remote locations. The GLDAS products are provided to the GDS 
users via http://agclisc.gsfc.nasa.p~~~/dc~ds/. Figure 5 shows the HDISC GDS page, which has links to various 
GLDAS products. GDS users can perform subsetting and analysis operations without first downloading data. The 
GDS subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large data 
set. The GDS analysis capability allows users to retrieve the results of an operation applied to one or more data sets 
on the server. The GDS supports any operation that can be expressed in a single GrADS expression, including basic 
math functions, averages, smoothing, differencing, correlation, and regression. 
Future HDISC direction 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 
HDISC will provide daily GLDAS products through time-averaging of the current 3-hourly data set. New data 
format, such as the NetCDF will be supported in the next phase. More advanced tools will be provided in later 
releases, such as on-the-fly spatial and parameter subsetting and temporal aggregation in Mirador, and an online 
visualization and analysis tool (Giovanni). Giovanni is a Web-based application developed by the GES DISC that 
provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing 
data without having to download the data (http://disc.sci.gsfc.nasa.gov/techlab/giovanni/). Users can access the 
HDISC website (http://disc.gsfc.nasa.gov/hydrology/) for the latest GLDAS data and HDISC news. 
Acknowledgement 
The Global Land Data Assimilation System (GLDAS) project is funded by NASA's Energy and Water Cycle Study 
(NEWS) Program. 
References 
Berg, A. A., J. S. Famiglietti, J. P. Walker, and P. R. Houser (2003). Impact of bias correction to reanalysis products 
on simulations of North American soil moisture and hydrological fluxes. Journal of Geophysicla Research, 
108(D16), 4490. 
Kumar, S. V., C. D. Peters-Lidard, Y. Tian, P. R. Houser, J. Geiger, S. Olden, L. Lighty, J. L. Eastman, B. Doty, P. 
Dirmeyer, J. Adams, K. Mitchell, E. F. Wood, and J. Sheffield (2006). Land Information System - An 
interoperable framework for high resolution land surface modeling. Environmental Modeling and Sojhare, 
21, 1402-1415. 
Rodell, M. and P. R. Houser (2004). Updating a land surface model with MODIS derived snow cover. Journal of 
Hydrometeorology, 5(6): 1064- 1075. 
Rodell, M., P. R. Houser, U. Jambor, J. Gottschalck, K. Mitchell, C.-J. Meng, K. Arsenault, B. Cosgrove, J. 
Radakovich, M. Bosilovich, J. K. Entin, J. P. Walker, D. Lohmann, and D. Toll (2004). The Global Land 
Data Assimilation System. Bulletin of the American Meteorological Society, 85(3): 38 1-394. 
ASPRS 2008 Annual Conference 
Portland, Oregon April 28 - May 2,2008 


Global Land Data Assimilation System (GLDAS) Products from NASA Hydrology Data and Information Services Center (HDISC)

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