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Assimilation of Gridded GRACE Terrestrial Water Storage Estimates in the North American Land Data Assimilation SystemThe objective of the North American Land Data Assimilation System (NLDAS) is to provide best available estimates of near-surface meteorological conditions and soil hydrological status for the continental United States. To support the ongoing efforts to develop data assimilation (DA) capabilities for NLDAS, the results of Gravity Recovery and Climate Experiment (GRACE) DA implemented in a manner consistent with NLDAS development are presented. Following previous work, GRACE terrestrial water storage (TWS) anomaly estimates are assimilated into the NASA Catchment land surface model using an ensemble smoother. In contrast to many earlier GRACE DA studies, a gridded GRACE TWS product is assimilated, spatially distributed GRACE error estimates are accounted for, and the impact that GRACE scaling factors have on assimilation is evaluated. Comparisons with quality-controlled in situ observations indicate that GRACE DA has a positive impact on the simulation of unconfined groundwater variability across the majority of the eastern United States and on the simulation of surface and root zone soil moisture across the country. Smaller improvements are seen in the simulation of snow depth, and the impact of GRACE DA on simulated river discharge and evapotranspiration is regionally variable. The use of GRACE scaling factors during assimilation improved DA results in the western United States but led to small degradations in the eastern United States. The study also found comparable performance between the use of gridded and basin averaged GRACE observations in assimilation. Finally, the evaluations presented in the paper indicate that GRACE DA can be helpful in improving the representation of droughts.
Document ID
20170002748
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Kumar, Sujay V. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Zaitchik, Benjamin F. (Johns Hopkins Univ. Baltimore, MD, United States)
Peters-Lidard, Christa D. (NASA Goddard Space Flight Center Greenbelt, MD United States)
Rodell, Matthew (NASA Goddard Space Flight Center Greenbelt, MD United States)
Reichle, Rolf (NASA Goddard Space Flight Center Greenbelt, MD United States)
Li, Bailing (Maryland Univ. College Park, MD, United States)
Jasinski, Michael (NASA Goddard Space Flight Center Greenbelt, MD United States)
Mocko, David (Science Applications International Corp. Greenbelt, MD, United States)
Getirana, Augusto (Maryland Univ. College Park, MD, United States)
De Lannoy, Gabrielle (University Hospital Leuven, Belgium)
Cosh, Michael H. (Agricultural Research Service Hydrology and Remote Sensing Lab. Beltsville, MD, United States)
Hain, Christopher R. (Maryland Univ. College Park, MD, United States)
Anderson, Martha (Agricultural Research Service Hydrology and Remote Sensing Lab. Beltsville, MD, United States)
Arsenault, Kristi R. (Science Applications International Corp. McLean, VA, United States)
Xia, Youlong (National Centers for Environmental Prediction College Park, MD, United States)
Ek, Michael (National Centers for Environmental Prediction College Park, MD, United States)
Date Acquired
March 31, 2017
Publication Date
July 8, 2016
Publication Information
Publication: Journal of Hydrometeorology
Volume: 17
Issue: 7
ISSN: 1525-755X
Subject Category
Earth Resources and Remote Sensing
Geophysics
Report/Patent Number
GSFC-E-DAA-TN41014
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
CONTRACT_GRANT: NNG15HQ01C
Distribution Limits
Public
Copyright
Other