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United States Department of Agriculture

Agricultural Research Service

Title: Using data assimilation techniques to calibrate soil moisture retrievals

Authors
item Pan, Ming - PRINCETON UNIVERSITY
item Ferguson, Craig - PRINCETON UNIVERSITY
item CROW, WADE
item Wood, Eric - PRINCETON UNIVERSITY

Submitted to: American Geophysical Union
Publication Type: Abstract Only
Publication Acceptance Date: November 5, 2006
Publication Date: December 11, 2006
Citation: Pan, M., Ferguson, C., Crow, W.T., Wood E. 2006. Using data assimilation techniques to calibrate soil moisture retrievals [abstract]. EOS Transactions, American Geophysical Union, Fall Supplements. 87(52):H21I-03.

Technical Abstract: Traditional efforts to quantify the value of remotely-sensed soil moisture retrievals via comparison to ground-based measurements have been hindered by inconsistencies in spatial and temporal scales between the two products. A new method was developed to assess the "skill" of remotely-sensed soil moisture retrievals that does not require ground observations; this was applied successfully at two transects with four different remotely-sensed soil moisture data sets. In this study, we use this newly developed method to calibrate the Land Surface Microwave Emission retrieval Model (LSMEM) across the contiguous United States at a one-degree spatial resolution. LSMEM is implemented to retrieve soil moistures from passive spacebourne radiometer data over a period of several years. Ultimately, performance of the calibrated LSMEM is assessed over the study area. Given the spatial heterogeneity of land cover across the United States, this exercise thoroughly explores the utility and robustness of this method, providing valuable insights for future work.

Last Modified: 7/28/2014
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