Validation and application of a snow algorithm in the Eurasian continent

The microwave region has sensitivity to the scattering effect of snow grains and leaves. Microwave remote sensing has potential for the measurement of snow water equivalent and water content of vegetation. The longer wavelength is one of the advantages of microwaves. It is long enough to reduce the scattering effect of cloud particles and to make microwave sensors useful in all-weather types. In this study, a new algorithm for snow depth and snow physical temperature by considering the effects of vegetation is developed based on the microwave radiative transfer theory. It is applied to the SSM/I and TMI data and validated by using the in-situ data in Russia and the Tibetan Plateau.