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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #292607

Title: The potential utility of land surface modeling and data assimilation for satellite soil moisture validation activities

Author
item Crow, Wade

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 5/10/2013
Publication Date: 7/3/2013
Citation: Crow, W.T. 2013. The potential utility of land surface modeling and data assimilation for satellite soil moisture validation activities [abstract]. Proceeding of the 2013 European Space Agency Satellite Soil Moisture & Validation & Application Workshop, July 1-3, 2013, Frascati, Italy. 2013 CDROM.

Interpretive Summary:

Technical Abstract: In the past five years, a number of different modeling and/or data assimilation strategies have been introduced to conduct validation/evaluation of satellite-based surface soil moisture retrievals. These strategies can be (roughly) separated into three separate categories: 1) triple collocation (TC) approaches which utilize land surface model (LSM) output as a single member of a soil moisture triplet, 2) data denial techniques which use auxiliary information (e.g., rainfall, stream flow or satellite-based vegetation index observations) to quantify added skill associated with assimilating surface soil moisture retrievals into a LSM, and 3) adaptive data assimilation techniques which infer soil moisture observation error statistics via the analysis of filtering innovation. This presentation will briefly review the state-of-the-art in these techniques and discuss their potential advantages (and disadvantages) relative to a “traditional” validation analysis against point-scale ground observations. A new evaluation technique, which combines elements of TC (#1 above) with filter innovation analysis (#2 above) will be introduced that compensates for some of the known difficulties in existing model-based evaluation techniques.