Derivation of a global soil moisture and vegetation database from passive microwave signals

A series of validation studies for a recently developed soil moisture retrieval algorithm is presented. The approach is largely theoretical, and uses a non-linear iterative optimisation procedure to solve for soil moisture and vegetation optical depth with a radiative transfer model from satellite microwave observations. The new theoretical approach is not dependent on field observations of soil moisture or canopy biophysical measurements and can be used at any wavelength in the microwave region. Details of the model and its development are discussed. Satellite retrievals were derived from 6.6 GHz Nimbus/SMMR brightness temperatures, and were validated with soil moisture data sets from the U.S., Mongolia, and Turkmenistan. Time series of the satellite-derived surface moisture compared well with the available ground observations and precipitation data. The vegetation optical depth showed similar seasonal patterns as the NDVI.

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