SWarm: A simple regression model to estimate near-surface snowpack warming for back-country avalanche forecasting

Daytime warming in near-surface snowpack layers occurs as a result of short wave radiation penetrating the top portion of the snowpack. While there is some understanding of diurnal temperature fluctuations and their effects on snowpack stability, quantified estimates of their magnitude are not readily available to avalanche forecasters in western Canada. During the winters of 2005 and 2006, near-surface temperatures were measured on a knoll located in the Columbia Mountains of British Columbia. The field dataset was used to develop a near-surface warming model, based on linear regression analysis of predictor variables derived from surface energy flux terms. To facilitate use in large forecast areas where representative meteorological data are typically scarce, consideration was given to the availability of input data. In this dataset, a variable based on daily maximum incoming short wave radiation proved to be the only significant predictor of near-surface daytime warming. Based on slope, aspect, expected cloud cover and number of days since snowfall, the model predicts the magnitude of daytime warming, in a below freezing snowpack, 10 cm below the snow surface with an estimated root mean square error of 1.6 °C.