Since the 1960's, remote sensing instruments aboard Earth-orbiting satellites have provided scientists with snowfall data. As the technology of these instruments has changed, so have the methods of using remote sensing data to calculate snow cover, snow depth, and snow-water equivalent. Spectral characteristics of snow are highly variable based on a number of factors, including grain size, depth, terrain, and age. Previous research has shown that an index can be generated using reflectance values from remote sensing data that makes classification of snow-covered land much easier.

In table form of a workshop on "Assessing the feasibility of an integrated modeling/remote sensing approach for predicting Great Lakes ice dynamics" held Oct. 8-9, 1997. Cf. p. 2.

The Great Lakes exert a considerable influence on the weather of the surrounding area, causing fog, clouds, breezes, snowfall, and other lake effects. This work explains the atmospheric processes underlying the characteristic weather patterns of the region.