气候变化领域集成服务门户(CCPortal): Multi-scale snowdrift-permitting modelling of mountain snowpack

CCPortal

DOI	10.5194/tc-15-743-2021
	Multi-scale snowdrift-permitting modelling of mountain snowpack
	Vionnet V.; Marsh C.B.; Menounos B.; Gascoin S.; Wayand N.E.; Shea J.; Mukherjee K.; Pomeroy J.W.
发表日期	2021
ISSN	19940416
起始页码	743
结束页码	769
卷号	15 期号:2
英文摘要	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 (g km2) 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. © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License.
英文关键词	downscaling; forest canopy; interception; lidar; modeling; mountain region; remote sensing; satellite imagery; seasonal variation; snow accumulation; snow cover; snowpack; spatial variation; spatiotemporal analysis; wind direction; wind velocity; Alberta; Canada; Kananaskis Valley; Rocky Mountains; Trachinotus falcatus
语种	英语
来源期刊	Cryosphere
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/202448
作者单位	Centre for Hydrology, University of Saskatchewan, Saskatoon, Canada; Environmental Numerical Prediction Research, Environment and Climate Change Canada, Dorval, QC, Canada; Natural Resources and Environmental Studies Institute and Geography Program, University of Northern British Columbia, Prince George, V2N 4Z9, Canada; Centre d'Études Spatiales de la Biosphère, UPS/CNRS/IRD/INRAE/CNES, Toulouse, France
推荐引用方式 GB/T 7714	Vionnet V.,Marsh C.B.,Menounos B.,et al. Multi-scale snowdrift-permitting modelling of mountain snowpack[J],2021,15(2).
APA	Vionnet V..,Marsh C.B..,Menounos B..,Gascoin S..,Wayand N.E..,...&Pomeroy J.W..(2021).Multi-scale snowdrift-permitting modelling of mountain snowpack.Cryosphere,15(2).
MLA	Vionnet V.,et al."Multi-scale snowdrift-permitting modelling of mountain snowpack".Cryosphere 15.2(2021).