Satellite observations using microwave radiometers operating near the window regions are strongly affected by surface emissivity. Presently, the measurements obtained over land are not directly utilized in numerical weather prediction models because of uncertainties in estimating the emissivity. This study develops a new model to quantify the land emissivity over various surface conditions. For surfaces such as snow, deserts, and vegetation, volumetric scattering was calculated using a two-stream radiative transfer approximation. The reflection and transmission at the surface-air interface and lower boundary were derived by modifying the Fresnel equations to account for cross-polarization and surface roughness effects. Several techniques were utilized to compute the optical parameters for the medium, which is used in the radiative transfer solution. In the case of vegetation, geometrical optics is used because the leaf size is typically larger than the wavelength. For snow and deserts, a dense medium theory was adopted to take into account the coherent scattering of closely spaced particles. The emissivity spectra at frequencies between 4.9 and 94 GHz simulated and compared with the ground-based radiometer measurements for bare soil, grass land, and snow conditions. It is shown that the features including the spectra, variability, and polarization agree well with the measurements. The simulated global distribution of land surface emissivity is also compared with the satellite retrievals from the Advanced Microwave Sounding Unit (AMSU). It is found that the largest discrepancies primarily occur over high latitudes where the snow properties are complex and least understood.
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