Advances in modelling of snowpack processes utilizing remote sensing technology

Abstract

Application of models over large areas requires enormous amounts of point data which are seldom available. As a result, the use of remote sensing to acquire data for these models becomes a practical alternative because from space areal measurements can be made over entire regions. Remote sensing data sets of snow are being studied and refined for input into energy balance, hydrological, and general circulation models. Snow influences the amount of solar energy retained and returned to space, the utilization of radiant energy in the hydrological cycle, and the atmospheric circulation by interacting with and modifying air masses. The continually evolving remote sensing technology will be used to provide a better understanding of how snow cover influences global climate and a better fundamental understanding of snow accumulation and ablation processes.