Investigating snow sinks on level sea ice: A case study in the western Arctic
SnowModel-LG reconstructs snow depth and density over sea ice, explicitly resolving important snow sinks like blowing snow sublimation, static surface sublimation and melt, but not snow-ice formation. To examine snow sinks on level sea ice, we coupled SnowModel-LG with HIGHTSI, a 1-D thermodynamic s...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
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| Series: | Journal of Glaciology |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S0022143025000346/type/journal_article |
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| Summary: | SnowModel-LG reconstructs snow depth and density over sea ice, explicitly resolving important snow sinks like blowing snow sublimation, static surface sublimation and melt, but not snow-ice formation. To examine snow sinks on level sea ice, we coupled SnowModel-LG with HIGHTSI, a 1-D thermodynamic sea-ice model, to create SMLG_HS. SMLG_HS simulations of snow depth and level ice thickness were evaluated against high-resolution airborne observations from the western Arctic, highlighting the importance of snow mass redistribution processes, i.e. snow’s tendency to leave level ice and accumulate over deformed ice due to wind-induced redistribution. Not accounting for snow mass redistribution, SMLG_HS overestimates snow depth on level ice, resulting in underestimation of level ice thickness and overestimation of snow-ice thickness. Our case study shows that snow depth on level ice needs to be reduced by 40% to simulate both snow depth and level ice thickness realistically in the western Arctic in April 2017. An independent analysis of snow volume distribution between level and deformed sea ice using airborne radar observations supported the model results and revealed a linear relationship that enables estimating the amount of snow remaining on level ice at the end of winter based on the amount of ice deformation. |
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| ISSN: | 0022-1430 1727-5652 |