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 Combining double low line 3.17 to 2.4 °C, using remote sensing data; RMSE Combining double low line 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.