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Title:   Author  item
                                            Bolten, Johnitem
                                            Crow, Wadeitem
                                            Zhan, Xiwuitem
                                            Jackson, Thomasitem
                                            REYNOLDS, C - USDA FAS PECADitem
                                            DOORN, B - USDA FAS PECAD
  Submitted to: BARC Poster Day
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 4/26/2006
                                    Publication  Date: 4/26/2006
                                    Citation: Bolten, J.D., Crow, W.T., Zhan, X., Jackson, T.J., Reynolds, C.A., Doorn, B. 2006. The application of AMSR-E soil moisture for improved global agricultural assessment and forecasting [abstract]. Abs. 03, BARC Poster Day.Interpretive Summary:
                                Technical Abstract: The U.S. Department of Agriculture's (USDA) Production Estimates and Crop Assessment Division (PECAD) is responsible for monitoring and predicting U.S. and international food supplies.  Estimates of crop growth are provided by PECAD's Crop Assessment Data Retrieval and Evaluation (CADRE) Data Base Management System (DBMS) which combines past (~20 years) and present meteorological, remote sensing, crop model and soil moisture model data.  The DBMS utilizes a modification of the Palmer two-layer soil moisture with secondary soil moisture estimates taken from the Air Force Weather Agency (AFWA) Agricultural Meteorology Model, AGRMET.  The current research presents a methodology for integrating direct soil moisture values into the crop model is envisaged to provide a better characterization of surface wetness at the regional scale and enable more accurae monitoring of boundary condition changes in key agricultural areas.  Improved soil moisture accuracy is expted to improve PECAD's crop forecasting capability.  This presentation will provide an overview of the soil moisture model, the assimiltion algorithm, spatial and temperal scaling techniques, and proposed methods of accuracy assessment.


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