Integration of Satellite-Retrieved Soil Moisture Observations with a Global Two-Layer Soil Moisture Model

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 daily precipitation and temperature data. However, many regions of the globe lack climate observations at the temporal and spatial resolutions required by PECAD. This study integrates 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. An Ensemble Kalman Filter (EnKF) has been designed to optimally merge the AMSR-E observations with the PECAD soil moisture outputs when available. A methodology of system design and an evaluation of the system performance over the Conterminous United States (CONUS) is presented.