NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Basin-Scale Assessment of the Land Surface Water Budget in the National Centers for Environmental Prediction Operational and Research NLDAS-2 SystemsThe purpose of this study is to evaluate the components of the land surface water budget in the four land surface models (Noah, SAC-Sacramento Soil Moisture Accounting Model, (VIC) Variable Infiltration Capacity Model, and Mosaic) applied in the newly implemented National Centers for Environmental Prediction (NCEP) operational and research versions of the North American Land Data Assimilation System version 2 (NLDAS-2). This work focuses on monthly and annual components of the water budget over 12 National Weather Service (NWS) River Forecast Centers (RFCs). Monthly gridded FLUX Network (FLUXNET) evapotranspiration (ET) from the Max-Planck Institute (MPI) of Germany, U.S. Geological Survey (USGS) total runoff (Q), changes in total water storage (dS/dt, derived as a residual by utilizing MPI ET and USGS Q in the water balance equation), and Gravity Recovery and Climate Experiment (GRACE) observed total water storage anomaly (TWSA) and change (TWSC) are used as reference data sets. Compared to these ET and Q benchmarks, Mosaic and SAC (Noah and VIC) in the operational NLDAS-2 overestimate (underestimate) mean annual reference ET and underestimate (overestimate) mean annual reference Q. The multimodel ensemble mean (MME) is closer to the mean annual reference ET and Q. An anomaly correlation (AC) analysis shows good AC values for simulated monthly mean Q and dS/dt but significantly smaller AC values for simulated ET. Upgraded versions of the models utilized in the research side of NLDAS-2 yield largely improved performance in the simulation of these mean annual and monthly water component diagnostics. These results demonstrate that the three intertwined efforts of improving (1) the scientific understanding of parameterization of land surface processes, (2) the spatial and temporal extent of systematic validation of land surface processes, and (3) the engineering-oriented aspects such as parameter calibration and optimization are key to substantially improving product quality in various land data assimilation systems.
Document ID
20160005952
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Xia, Youlong
(National Centers for Environmental Prediction Washington, DC, United States)
Cosgrove, Brian A.
(National Weather Service Silver Spring, MD, United States)
Mitchell, Kenneth E.
(Prescient Weather Ltd. State College, PA, United States)
Peters-Lidard, Christa D.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Ek, Michael B.
(National Centers for Environmental Prediction Washington, DC, United States)
Brewer, Michael
(National Oceanic and Atmospheric Administration Asheville, NC, United States)
Mocko, David
(Science Applications International Corp. Greenbelt, MD, United States)
Kumar, Sujay V.
(Science Applications International Corp. Greenbelt, MD, United States)
Wei, Helin
(National Centers for Environmental Prediction Washington, DC, United States)
Meng, Jesse
(National Centers for Environmental Prediction Washington, DC, United States)
Luo, Lifeng
(Michigan State Univ. East Lansing, MI, United States)
Date Acquired
May 9, 2016
Publication Date
March 25, 2016
Publication Information
Publication: Journal of Geophysical Research: Atmospheres
Publisher: AGU
Volume: 121
Issue: 6
ISSN: 0148-0227
e-ISSN: 2156-2202
Subject Category
Meteorology And Climatology
Earth Resources And Remote Sensing
Report/Patent Number
GSFC-E-DAA-TN32004
Funding Number(s)
CONTRACT_GRANT: NNG15HQ01C
Distribution Limits
Public
Copyright
Other
Keywords
NLDAS-2
Basin-Scale
Water

Available Downloads

There are no available downloads for this record.
No Preview Available