Validation of passive microwave snow algorithms

When snow covers the ground, some of the microwave energy emitted by the underlying soil is scattered by the snow grains. Therefore, when moving from snow-free to snowcovered land surfaces, a sharp decrease in emissivity and associated brightness temperatures provides a nearly unambiguous indicator of the presence of dry snow. In addition, theoretical and empirical studies have demonstrated that the amount of scattering can be correlated with snow mass or snow water equivalent. Passive microwave satellite remote sensing can greatly enhance large-scale snow measurements based on visible satellite data alone because of the ability to acquire data through clouds or during darkness as well as to provide a measure of snow water equivalent. This study develops a validation methodology and involves the comparison of several different passive microwave snow algorithms, including mid and high-frequency channels, vertical and horizontal polarizations and polarization difference approaches.