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United States Department of Agriculture

Agricultural Research Service

Title: Evaluating the Added Value of Spaceborne Soil Moisture Products for Land Surface Modeling Applications

Author
item Crow, Wade

Submitted to: International Geoscience and Remote Sensing Symposium Proceedings
Publication Type: Proceedings
Publication Acceptance Date: June 8, 2006
Publication Date: July 31, 2006
Citation: Crow, W.T. 2006. Evaluating the added value of spaceborne soil moisture products for land surface modeling applications. In: Proceedings of the International Geoscience and Remote Sensing Symposium, July 31-August 31, 2006, Denver, Colorado. 2006 CDROM.

Technical Abstract: A novel methodology is introduced for quantifying the value of remotely-sensed soil moisture products for land surface modeling applications. The approach is based on the assimilation of soil moisture retrievals into a simple surface water balance model driven by satellite-based precipitation products. Filter increments (i.e. discrete additions or subtractions of water suggested by the filter) are then compared to antecedent precipitation errors determined using higher quality rain gauge observations. A synthetic twin experiment demonstrates that the correlation coefficient between antecedent precipitation errors and filter increments provides an effective proxy for the accuracy of the soil moisture retrievals themselves. Given the inherent difficulty of directly validating remotely-sensed soil moisture products using ground-based observations, this assimilation-based proxy provides a valuable feedback tool for efforts to optimize soil moisture retrieval strategies and define the geographic extent over which spaceborne soil moisture retrievals contribute value to global land surface modeling. Using real data, the approach is demonstrated for four different remotely-sensed soil moisture datasets over two separate transects in the southern United States. Results suggest that the relative superiority of various retrieval strategies may vary geographically.

Last Modified: 8/27/2014
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