Impact of snow thermal conductivity schemes on pan-Arctic permafrost dynamics in the Community Land Model version 5.0

Abstract. The precise magnitude and timing of permafrost-thaw-related emissions and their subsequent impact on the global climate system remain highly uncertain. This uncertainty stems from the complex quantification of the rate and extent of permafrost thaw, which is influenced by factors such as snow cover and other surface properties. Acting as a thermal insulator, snow cover directly influences surface energy fluxes and can significantly impact the permafrost thermal regime. However, current Earth system models often inadequately represent the nuanced effects of snow cover in permafrost regions, leading to inaccuracies in simulating soil temperatures and permafrost dynamics. Notably, the Community Land Model (CLM5.0) tends to overestimate snowpack thermal conductivity over permafrost regions, resulting in an underestimation of the snow insulating capacity. Using a snow thermal conductivity scheme better adapted for the snowpack typically found in permafrost regions, we seek to resolve thermal insulation underestimation and assess the influence of snow on simulated soil temperatures and permafrost dynamics. Evaluation using two Arctic-wide soil temperature observation datasets reveals that the new snow thermal conductivity scheme reduces the cold-soil temperature bias (root-mean-square error, RMSE = 3.17 to 2.4 °C, using remote sensing data; RMSE = 3.9 to 2.19 °C, using in situ data), demonstrates robustness through sensitivity analysis under lower tundra snow densities, and addresses the overestimation of permafrost extent in the default CLM5.0. This improvement highlights the importance of incorporating realistic snow processes in land surface models for enhanced predictions of permafrost dynamics and their response to climate change.

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Publication Details

Journal
˜The œcryosphere
Published
2025-04-14
DOI
https://doi.org/10.5194/tc-19-1539-2025
Citations
6
Primary Topic
Climate change and permafrost
Type
article
Field-Weighted Citation Impact
7.80

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article

Impact of snow thermal conductivity schemes on pan-Arctic permafrost dynamics in the Community Land Model version 5.0

Heidrun Matthes, Nick Rutter, Victoria Dutch, Leanne Wake et al.
6 citations
˜The œcryosphere
Climate change and permafrost
7.80
article

Impact of snow thermal conductivity schemes on pan-Arctic permafrost dynamics in the Community Land Model version 5.0

Heidrun Matthes, Nick Rutter, Victoria Dutch, Leanne Wake, Adrien Damseaux
article en
6 citations

Abstract

Abstract. The precise magnitude and timing of permafrost-thaw-related emissions and their subsequent impact on the global climate system remain highly uncertain. This uncertainty stems from the complex quantification of the rate and extent of permafrost thaw, which is influenced by factors such as snow cover and other surface properties. Acting as a thermal insulator, snow cover directly influences surface energy fluxes and can significantly impact the permafrost thermal regime. However, current Earth system models often inadequately represent the nuanced effects of snow cover in permafrost regions, leading to inaccuracies in simulating soil temperatures and permafrost dynamics. Notably, the Community Land Model (CLM5.0) tends to overestimate snowpack thermal conductivity over permafrost regions, resulting in an underestimation of the snow insulating capacity. Using a snow thermal conductivity scheme better adapted for the snowpack typically found in permafrost regions, we seek to resolve thermal insulation underestimation and assess the influence of snow on simulated soil temperatures and permafrost dynamics. Evaluation using two Arctic-wide soil temperature observation datasets reveals that the new snow thermal conductivity scheme reduces the cold-soil temperature bias (root-mean-square error, RMSE = 3.17 to 2.4 °C, using remote sensing data; RMSE = 3.9 to 2.19 °C, using in situ data), demonstrates robustness through sensitivity analysis under lower tundra snow densities, and addresses the overestimation of permafrost extent in the default CLM5.0. This improvement highlights the importance of incorporating realistic snow processes in land surface models for enhanced predictions of permafrost dynamics and their response to climate change.

˜The œcryosphereVol. 19(4)
Karlsruhe Institute of Technology (DE), University of East Anglia (GB), Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE), University of Potsdam (DE), Northumbria University (GB)
Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Natural Environment Research Council, Horizon 2020
Openalex Percentile: Top 2%
Climate change and permafrost
7.80
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