1a.Objectives (from AD-416)
This proposal seeks to develop, test and implement a data assimilation system to estimate surface temperature via the fusion of continuous land surface temperature forecasts obtained from numerical weather prediction models with sporadic estimates of surface soil moisture available from existing satellite microwave radiometers.
1b.Approach (from AD-416)
This project objective will be addressed in four separate phases:
1) Phase 1: Apply quality control to existing satellite-based surface soil moisture products.
2) Phase 2: Examine the cross-calibration between existing satellite-based surface soil moisture products.
3) Phase 3: Adapt an Ensemble Kalman filter to integrate the (quality controlled and cross-calibrated) remote sensing products with surface temperature predictions from land surface model.
4) Phase 4: Evaluate the resulting surface temperature product and surface soil moisture retrievals obtained using the surface temperature product.
Quality control filters have been tested to remove satellite observations with excessive error from the set of observations that will be used for the combined product. Differences between satellites have been analyzed and minimized by a cross-calibration algorithm for satellite Ka-band observations. The remaining data have been used to assess the performance of Ka-band to estimate the land surface temperature in comparison to NWP models.