Multi-scale snowdrift-permitting modelling of mountain snowpack

• Published in: The Cryosphere
• Main Authors: V. Vionnet, C. B. Marsh, B. Menounos, S. Gascoin, N. E. Wayand, J. Shea, K. Mukherjee, J. W. Pomeroy
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2021
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-15-743-2021; https://doaj.org/article/f8ba05637e2b4b8083f7b631640d3676

The interaction of mountain terrain with meteorological processes causes substantial temporal and spatial variability in snow accumulation and ablation. Processes impacted by complex terrain include large-scale orographic enhancement of snowfall, small-scale processes such as gravitational and wind-induced transport of snow, and variability in the radiative balance such as through terrain shadowing. In this study, a multi-scale modelling approach is proposed to simulate the temporal and spatial evolution of high-mountain snowpacks. The multi-scale approach combines atmospheric data from a numerical weather prediction system at the kilometre scale with process-based downscaling techniques to drive the Canadian Hydrological Model (CHM) at spatial resolutions allowing for explicit snow redistribution modelling. CHM permits a variable spatial resolution by using the efficient terrain representation by unstructured triangular meshes. The model simulates processes such as radiation shadowing and irradiance to slopes, blowing-snow transport (saltation and suspension) and sublimation, avalanching, forest canopy interception and sublimation, and snowpack melt. Short-term, kilometre-scale atmospheric forecasts from Environment and Climate Change Canada's Global Environmental Multiscale Model through its High Resolution Deterministic Prediction System (HRDPS) drive CHM and are downscaled to the unstructured mesh scale. In particular, a new wind-downscaling strategy uses pre-computed wind fields from a mass-conserving wind model at 50 m resolution to perturb the mesoscale HRDPS wind and to account for the influence of topographic features on wind direction and speed. HRDPS-CHM was applied to simulate snow conditions down to 50 m resolution during winter 2017/2018 in a domain around the Kananaskis Valley ( ∼1000 km 2 ) in the Canadian Rockies. Simulations were evaluated using high-resolution airborne light detection and ranging (lidar) snow depth data and snow persistence indexes derived from remotely sensed imagery. Results ...