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United States Department of Agriculture

Agricultural Research Service

Title: Implementation of a global-scale operational data assimilation system for satellite-based soil moisture retrievals

item Bolten, John
item Crow, Wade
item Zhan, X
item Reynolds, Curt

Submitted to: International Society for Optical Engineering
Publication Type: Proceedings
Publication Acceptance Date: 8/5/2008
Publication Date: 8/15/2008
Citation: Bolten, J.D., Crow, W.T., Zhan, X., Reynolds, C.A. 2008. Implementation of a global-scale operational data assimilation system for satellite-based soil moisture retrievals. 2008 SPIE Optics and Photonics Conference, August 10-14, 2008, San Diego, California. 2008 CDROM.

Interpretive Summary:

Technical Abstract: Timely and accurate monitoring of global weather anomalies and drought conditions is essential for assessing global crop conditions. Soil moisture observations are particularly important for 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; particularly 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) into 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 a daily product of integrated AMSR-E soil moisture observations with the PECAD two-layer soil moisture model forecasts. A methodology of the system design and a brief evaluation of the system performance over the Conterminous United States (CONUS) is presented.

Last Modified: 06/27/2017
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