Simon Horton, Stanislaw Nowak and Pascal Haegeli
Proceedings of the 2018 International Snow Science Workshop in Innsbruck, Austria
Publication year: 2018

Abstract

Although weather forecast models play a key role in avalanche forecasting, snowpack models have had limited uptake. As the quantity of weather and snowpack data grows with increasing computer power, methods to distill meaningful patterns will become more important. We generated spatially distributed snowpack data for over 15,000 km2 of western Canada during the 2017-18 winter. The snow cover model SNOWPACK was forced with meteorological data from a numerical weather prediction model on a 2.5 km grid. We developed visualization software to explore multiple snow profiles at the same time and shared it in real-time with six avalanche safety organizations. The visualization tool revealed common features in the profiles that could be aligned according to their deposition date. A case study at Mike Wiegele Helicopter Skiing found the visualizations contained many of the snowpack features described in their operational hazard assessments. Improvements to the visualizations and further post-processing of the model output could allow practitioners to interact with snowpack models in more meaningful ways.

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