Currently, avalanche forecasts in Canada are made by experienced professionals who rely on data from local weather stations and on-the-ground observations from ski and backcountry ski operators, avalanche control workers for transportation and industry, and volunteers who manually test the snowpack.
Currently, avalanche forecasts in Canada are made by experienced professionals who rely on data from local weather stations and on-the-ground observations from ski and backcountry ski operators, avalanche control workers for transportation and industry, and volunteers who manually test the snowpack.
But simulated snow cover models developed by a team of researchers are able detect and track weak layers of snow and identify avalanche hazard in a completely different way—and can provide forecasters with another reliable tool when local data is insufficient or not available, according to a new study published in the journal Cold Regions Science and Technology.
“As far as natural hazards go, avalanches are still one of the leading causes of fatalities in Canada,” says Simon Horton, a post-doctoral fellow with the SFU Centre for Natural Hazards Research and a forecaster with Avalanche Canada.
“We’ve had these complex models that simulate the layers in the snowpack for a few decades now and they’re getting more and more accurate, but it’s been difficult to find out how to apply that to actual decision-making and improving safety.”
Researchers took 16 years’ worth of daily meteorological, snow cover and avalanche data from two sites in Canada (Whistler and Rogers Pass, both in British Columbia) and Weissfluhjoch in Davos, Switzerland and ran computer simulations that could classify different avalanche situations.
Read more at: Simon Fraser University
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