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United States Department of Agriculture

Agricultural Research Service

Title: Assimilation of Satellite-Based Soil Moisture into the USDA Global Crop Production Decision Support System

item Bolten, John
item Crow, Wade
item Zhan, X
item Jackson, Thomas
item Reynolds, C

Submitted to: BARC Poster Day
Publication Type: Abstract Only
Publication Acceptance Date: 4/1/2008
Publication Date: 5/1/2008
Citation: Bolten, J.D., Crow, W.T., Zhan, X., Jackson, T.J., Reynolds, C.A. 2008. Assimilation of satellite-based soil moisture into the USDA Global Crop Production Decision Support System [abstract]. Abs. 5. BARC Poster Day.

Interpretive Summary:

Technical Abstract: The timely and accurate monitoring of climate conditions is essential for assessing agriculture efficiency and managing natural resources. Of particular importance is the estimation of near-surface soil moisture, which influences many aspects of local weather and global climate. Soil moisture is also a fundamental data source used in crop growth stage and crop stress models, a primary source used to estimate world food security and agriculture commodity markets. Global estimates of soil moisture are a large component of crop yield fluctuations provided by the US Department of Agriculture (USDA) Production Estimation and Crop Assessment Division (PECAD). The current system utilized by PECAD estimates soil moisture from a 2-layer water balance model based on precipitation and temperature data from World Meteorological Organization (WMO) and US Air Force Weather Agency (AFWA). The accuracy of this system is highly dependent on the data sources used; such as the accuracy, consistency, and spatial and temporal coverage of the land and climatic data input into the models. However, many regions of the globe lack observations at the temporal and spatial resolutions required by PECAD. This study incorporates NASA’s soil moisture remote sensing product provided by the EOS Advanced Microwave Scanning Radiometer (AMSR-E) to the U.S. Department of Agriculture Crop Assessment and Data Retrieval (CADRE) decision support system. A quasi-global-scale operational data assimilation system has been designed and implemented to provide CADRE with a daily product of integrated AMSR-E soil moisture observations with the PECAD two-layer soil moisture product. A methodology of system design and an evaluation of the system performance over the Conterminous United States (CONUS) will be presented.

Last Modified: 07/26/2017
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