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connecting satellite observations with water cycle variables through land data assimilation: examples using the nasa geos-5 ldasA land data assimilation system (LDAS) can merge satellite observations (or retrievals) of land surface hydrological conditions, including soil moisture, snow, and terrestrial water storage (TWS), into a numerical model of land surface processes. In theory, the output from such a system is superior to estimates based on the observations or the model alone, thereby enhancing our ability to understand, monitor, and predict key elements of the terrestrial water cycle. In practice, however, satellite observations do not correspond directly to the water cycle variables of interest. The present paper addresses various aspects of this seeming mismatch using examples drawn from recent research with the ensemble-based NASA GEOS-5 LDAS. These aspects include (1) the assimilation of coarse-scale observations into higher-resolution land surface models, (2) the partitioning of satellite observations (such as TWS retrievals) into their constituent water cycle components, (3) the forward modeling of microwave brightness temperatures over land for radiance-based soil moisture and snow assimilation, and (4) the selection of the most relevant types of observations for the analysis of a specific water cycle variable that is not observed (such as root zone soil moisture). The solution to these challenges involves the careful construction of an observation operator that maps from the land surface model variables of interest to the space of the assimilated observations.
Document ID
Document Type
Reprint (Version printed in journal)
Reichle, Rolf H.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
De Lannoy, Gabrielle J. M.
(Universities Space Research Association Columbia, MD, United States)
Forman, Barton A.
(Maryland Univ. College Park, MD, United States)
Draper, Clara S.
(Universities Space Research Association Columbia, MD, United States)
Liu, Qing
(Science Systems and Applications, Inc. Lanham, MD, United States)
Date Acquired
May 28, 2015
Publication Date
February 15, 2013
Publication Information
Publication: Surveys in Geophysics
Volume: 35
Issue: 3
Subject Category
Geosciences (General)
Report/Patent Number
Funding Number(s)
Distribution Limits
Public Use Permitted.
Land data assimilation
Land surface modeling

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