Multi-physics ensemble modelling of Arctic tundra snowpack properties DOI Creative Commons

Georgina Jean Woolley,

Nick Rutter, Leanne Wake

et al.

˜The œcryosphere, Journal Year: 2024, Volume and Issue: 18(12), P. 5685 - 5711

Published: Dec. 6, 2024

Abstract. Sophisticated snowpack models such as Crocus and SNOWPACK struggle to properly simulate profiles of density specific surface area (SSA) within Arctic snowpacks due underestimation wind-induced compaction, misrepresentation basal vegetation influencing compaction metamorphism, omission water vapour flux transport. To improve the simulation SSA, parameterisations snow physical processes that consider effect high wind speeds, presence vegetation, alternate thermal conductivity formulations were implemented into an ensemble version Soil, Vegetation, Snow 2 (SVS2-Crocus) land model, creating SVS2-Crocus. The versions default SVS2-Crocus driven with in situ meteorological data evaluated using measurements properties (snow equivalent, SWE; depth; density; SSA) at Trail Valley Creek (TVC), Northwest Territories, Canada, over 32 years (1991–2023). Results show both can correct magnitude SWE (root-mean-square error, RMSE, for ensembles – 55 kg m−2) depth (default RMSE 0.22 m; 0.18 m) TVC comparison measurements. Wind-induced effectively compacts layers snowpack, increasing density, reducing by 41 % (176 m−3 103 m−3). Parameterisations are less effective 67 m−3; 65 m−3), reaffirming need transport low-density layers. top 100 members produced lower continuous ranked probability scores (CRPS) than when simulating profiles. top-performing featured modifications raise speeds increase prevent snowdrift viscosity Selecting these process representations will profiles, which is crucial many applications.

Language: Английский

Multi-physics ensemble modelling of Arctic tundra snowpack properties DOI Creative Commons

Georgina Jean Woolley,

Nick Rutter, Leanne Wake

et al.

˜The œcryosphere, Journal Year: 2024, Volume and Issue: 18(12), P. 5685 - 5711

Published: Dec. 6, 2024

Abstract. Sophisticated snowpack models such as Crocus and SNOWPACK struggle to properly simulate profiles of density specific surface area (SSA) within Arctic snowpacks due underestimation wind-induced compaction, misrepresentation basal vegetation influencing compaction metamorphism, omission water vapour flux transport. To improve the simulation SSA, parameterisations snow physical processes that consider effect high wind speeds, presence vegetation, alternate thermal conductivity formulations were implemented into an ensemble version Soil, Vegetation, Snow 2 (SVS2-Crocus) land model, creating SVS2-Crocus. The versions default SVS2-Crocus driven with in situ meteorological data evaluated using measurements properties (snow equivalent, SWE; depth; density; SSA) at Trail Valley Creek (TVC), Northwest Territories, Canada, over 32 years (1991–2023). Results show both can correct magnitude SWE (root-mean-square error, RMSE, for ensembles – 55 kg m−2) depth (default RMSE 0.22 m; 0.18 m) TVC comparison measurements. Wind-induced effectively compacts layers snowpack, increasing density, reducing by 41 % (176 m−3 103 m−3). Parameterisations are less effective 67 m−3; 65 m−3), reaffirming need transport low-density layers. top 100 members produced lower continuous ranked probability scores (CRPS) than when simulating profiles. top-performing featured modifications raise speeds increase prevent snowdrift viscosity Selecting these process representations will profiles, which is crucial many applications.

Language: Английский

Citations

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