Location: Hydrology and Remote Sensing Laboratory2012 Annual Report
1a. Objectives (from AD-416):
To improve model predictions of soil moisture, evapotranspiration and surface runoff used for operational drought monitoring by assimilating remotely sensed signals of soil moisture conditions derived from microwave and thermal band satellite imagery.
1b. Approach (from AD-416):
Assemble remote sensing thermal and microwave remote sensing soil moisture datasets covering North America for 2003-present. Quantify incremental improvement in LIS-Noah model predictions of soil moisture obtained by assimilating thermal and microwave signals and develop optimized assimilation strategy. Compare moisture anomalies from optimized system with standard drought metrics: including operational NOAA drought products, U.S. Drought Monitor drought classifications, and known drought/flooding events.
3. Progress Report:
In Year 1 of this project, the primary accomplishments were to: 1) Assemble remote sensing inputs required to generate soil moisture estimates from thermal infrared (TIR) and microwave (MW) band satellite imagery for assimilation into the National Land Data Assimilation System (NLDAS). 2) Execute a sequence of data assimilation experiments involving single assimilation of TIR and MW soil moisture estimates, and then demonstrating the value added by dual assimilation of both TIR and MW data. Performance is assessed by running NLDAS using a degraded precipitation input dataset, and quantifying improvement in soil moisture estimates achieved through assimilation in comparison with a control run using high quality precipitation data. 3) Optimize the formalism for deriving the TIR-based soil moisture estimate.