Currently, avalanche forecasting is done by experts using data from local weather stations and field observations from ski and cross-country ski operators, avalanche monitors for transport and industry, and volunteers who test manually the snowpack.
According to a new study published in Cold Regions Science and Technology journal, simulated snow cover models developed by a team of Canadian researchers can detect and track thin layers of snow. This can detect avalanche risk in a unique way, and also provide forecasters with an additional reliable tool when local data is insufficient or unavailable.
Among the natural hazards, that of avalanches still causes avoidable deaths. There have been forecasting models for a few decades already, and they are constantly improving, but they are not being applied effectively. Today the simulations developed by the researchers could determine the risk of avalanches, both natural and artificial, for all types of problems. Fresh snow, wet snow, gusts of wind, persistent weak layers, everything.
Predict avalanches, save lives
"Describing the typical situations that can be encountered is a great way to communicate the risk of avalanches," says the meteorologist. Simon Horton. "In many situations, however, there is a fair amount of uncertainty about the human assessment of what phenomena these types of scenery they will be able to produce ".
This is where having more automated solutions that can help predict potential hazards can help forecasters prepare a more accurate and precise forecast. The results of the study showed that the model developed is consistent with the actual observed avalanche frequencies in Canada over the past 16 years. And above all it has shown that the approach has the potential to support avalanche forecasting in the future.
