Multi-scale snowdrift-permitting modelling of mountain snowpack
<p>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...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2021-02-01
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| Series: | The Cryosphere |
| Online Access: | https://tc.copernicus.org/articles/15/743/2021/tc-15-743-2021.pdf |
| Summary: | <p>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 <span class="inline-formula">m</span> 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 <span class="inline-formula">m</span> resolution during winter 2017/2018 in a domain around the
Kananaskis Valley (<span class="inline-formula">∼1000 km<sup>2</sup></span>) 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 included model
falsifications and showed that both wind-induced and gravitational snow redistribution need to be
simulated to capture the snowpack variability and the evolution of snow depth and persistence with
elevation across the region. Accumulation of windblown snow on leeward slopes and associated
snow cover persistence were underestimated in a CHM simulation driven by wind fields that did not
capture lee-side flow recirculation and associated wind speed decreases. A terrain-based metric
helped to identify these lee-side areas and improved the wind field and the associated snow
redistribution. An overestimation of snow redistribution from windward to leeward slopes and
subsequent avalanching was still found. The results of this study highlight the need for further
improvements of snowdrift-permitting models for large-scale applications, in particular the
representation of subgrid topographic effects on snow transport.</p> |
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| ISSN: | 1994-0416 1994-0424 |