MOSH levels of excitement about the publication of this paper, which was led by Vincent Vionnet of Environment Canada and the Centre for Hydrology at the University of Saskatchewan:
https://tc.copernicus.org/articles/15/743/2021/tc-15-743-2021.html
The research builds on the state-of-the-art Canadian Hydrological Model to advance our ability to model snow in mountain environments, which are notoriously tricky places to work. By working on a variable resolution triangular mesh (instead of a regular grid), including redistribution of snow due to both winds and avalanches, and pulling off some difficult wind downscaling, our work generates realistic simulations of snowpack depth compared with airborne LiDAR observations.
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Observed (top left) and modelled snow depths in the Kananaskis study area, Alberta. The full model (top right) includes wind downscaling and accounts for recirculation and gravitational and blowing-snow redistribution. Absent these processes (bottom panels), the model can’t capture the magnitude or complex distribution of observed snow depths.