Snow
Models

Snow science often leads to predictive models that include snow deposition, snow melt, and snow hydrology—elements of the Earth's water cycle —which help describe global climate change.

Global climate change models (GCMs) incorporate snow as a factor in their calculations. Some important aspects of snow cover include its albedo (reflectivity of incident radiation, including light) and insulating qualities, which slow the rate of seasonal melting of sea ice. As of 2011, the melt phase of GCM snow models were thought to perform poorly in regions with complex factors that regulate snow melt, such as vegetation cover and terrain. These models typically derive snow water equivalent (SWE) in some manner from satellite observations of snow cover. The International Classification for Seasonal Snow on the Ground defines SWE as "the depth of water that would result if the mass of snow melted completely".

Given the importance of snowmelt to agriculture, hydrological runoff models that include snow in their predictions address the phases of accumulating snowpack, melting processes, and distribution of the meltwater through stream networks and into the groundwater. Key to describing the melting processes are solar heat flux, ambient temperature, wind, and precipitation. Initial snowmelt models used a degree-day approach that emphasized the temperature difference between the air and the snowpack to compute snow water equivalent, SWE. More recent models use an energy balance approach that take into account the following factors to compute Q, the energy available for melt. This requires measurement of an array of snowpack and environmental factors to compute six heat flow mechanisms that contribute to Q.
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