Location: Hydrology and Remote Sensing Laboratory2010 Annual Report
1a. Objectives (from AD-416)
Enhance USDA FAS crop yield forecasts via the use of remote sensing and data assimilation technologies.
1b. Approach (from AD-416)
Apply an Ensemble Kalman filter to the assimilation of AMSR-E soil moisture retrievals into the USDA FAS land surface model. Development contingency plans for the discontinuity of AMSR-E data and apply the NASA LIS modeling system.
3. Progress Report
Project has begun preliminary work aimed at quantifying the value of data output from the USDA/FAS soil moisture data assimilation (developed in a previous project) for agricultural yield forecasting and the implementation of the Palmer Land Surface Model (used operational at USDA FAS) into the NASA Land Information System.