Effects of soil texture on the retrieved microwave emissivity at the different frequencies of a desert area and its modeling

In this study, the surface microwave emissivity of North Africa deserts is first retrieved from the AMSR-E (the Advanced Microwave Scanning Radiometer-Earth Observing System) measurements under clear atmospheric conditions. Then, the spectral characteristics of the retrieved emissivity are classified and analyzed with respect to the underlying soil texture types. The analyses indicate that the desert microwave emissivity is closely related with soil texture, and significantly varies with soil particle size and composition. For those soil texture types which are mainly dominated by large-size particles, the emissivity spectra of vertical (horizontal) polarization generally decrease (increase) with frequency. Yet, for those soil texture types which contain fairly small-size particles, the emissivity values are almost constant or slightly increasing (decreasing) with frequency for the vertical (horizontal) polarization. Furthermore, the microwave emissivity of the desert area also exhibits some seasonal variation, especially for the soils composed by small-size particles. The horizontal polarization (H-Pol) emissivity shows stronger seasonal variability than the vertical polarization (V-Pol) emissivity. These desert emissivity features are generally consistent with the simulations by the microwave land emissivity model of Weng et al (2001). The performance of Weng's model over the desert area has been greatly improved with its input parameters explicitly taking into account soil texture information including sand fraction and particle size, e.g., emissivity simulation bias of clay and clay loam decreased from 6%,even 9% to less than 4%. Since Weng's model is an essential component in the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS), it is expected that such improvement would enhance the data assimilation over the desert area, and subsequently improve the accuracy of the numerical weather prediction (NWP) system.