Currently, avalanche forecasting is made by experts using data from local weather stations and field observations from ski and cross-country ski operators, transport and industrial avalanche monitors, and volunteers who test the snow cover manually.
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 an excellent method for communicating the risk of avalanches,” says the meteorologist Simon Horton.”In many situations, however, there is a fair amount of uncertainty about human assessments 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 meteorologists prepare a more accurate and precise forecast. The results of the study showed that the developed model is consistent with the real observed frequencies of avalanches in Canada over the last 16 years. And it demonstrated above all that the approach has the potential to support avalanche prediction in the future.
