2500, boul. de l'Université
Université de Sherbrooke
819.821.8000 extension 62506
The first signs of climate change and variability have been observed over the last three decades through a variety of strong climate-related feedbacks. The increased occurrence of rain-on-snow (ROS) events is estimated at 0.03 days/ten-day period, which highly contributes to the increase of avalanche risk. Indeed, water infiltration in the snowpack breaks the bonds between snow grains and therefore increases the layer’s weight. Moreover, water percolation through the snowpack creates ice crusts and causes the formation of persistent weak layers. ROS events and local snowmelt are considered as the main factors triggering wet snow avalanches that remain a public safety and an economic matter.
This project aims at improving the avalanche risk estimation in western Canada using micro-wave remote sensing to detect snow melt and then calibrate snow stratigraphy simulations.
To achieve this goal, a snowmelt detection algorithm will be developed and applied to RADARSAT-2 data. The data will be overlapped with Alpine-3D simulations forced beforehand with GEM-LAM 2.5 km predictions. RADARSAT snowmelt detection data will be used to initiate snowmelt in the model, which will then predict water percolation and snowpack stability.
Our research activities focusses on the Rogers Pass area in Glacier National Park, British Columbia.