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In high‐latitude and mountain regions, local processes such as redistribution by wind, snow metamorphism, and percolation of water produce a complex spatial distribution of snow depths and snow densities. With its strong control on the ground thermal regime, this snow distribution has pronounced effects on ground temperatures at small spatial scales which are typically not resolved by land surface models (LSMs). This limits our ability to simulate the local impacts of climate change on, for example, vegetation and permafrost. Here, we present a tiling approach combining the CryoGrid permafrost model with snow microphysics parametrizations from the CROCUS snow scheme to account for subgrid lateral exchange of snow and water in a process‐based way. We demonstrate that a simple setup with three coupled tiles, each representing a different snow accumulation class with a specific topographic setting, can reproduce the observed spread of winter‐time ground surface temperatures (GST) and end‐of‐season snow distribution for a high‐Arctic site on Svalbard. For the 3‐year study period, the three‐tile simulations showed substantial improvement compared to traditional single‐tile simulations which naturally cannot account for subgrid variability. Among others, the representation of the warmest and coldest 5% of the observed GST distribution was improved by 1–2°C, while still capturing the average of the distribution. The simulations also reveal positive mean annual GSTs at the locations receiving the greatest snow cover. This could be an indication for the onset of localized permafrost degradation which would be obscured in single‐tile simulations. Key Points: In high‐Arctic areas, wind redistribution of snow leads to a strong variability in snow depths and hence ground surface temperaturesA parametrization for lateral transport of snow between three model tiles is implemented in the CryoGrid 3 permafrost modelThe three‐tile setup reproduces the observed spatial variability of snow depths and ground surface temperatures in a process‐based fashion [ABSTRACT FROM AUTHOR]

The article presents a study on the impact of wintertime rain events on the thermal regime of permafrost in Svalbard, Norway. It mentions field measurements and numerical process modeling from the western part of the archipelago which show effect of the events on the ground surface temperature underneath the snow. It also notes the percolation of rain water under the snow pack where it freezes and releases potential heat.

The article presents a study which examines the thermal dynamics of the active layers at permafrost sites in Svalbard, Norway and in the Tibetan Plateau. The study uses a thermal and hydraulic numerical model with parameters such as heat conduction, heat convection and liquid water flow to analyze the applicability of the model and to quantify the process dominating the sites. It is found out that both sites are dominated by the process of heat conduction.

The article assesses the active layer dynamics at the high-arctic continuous permafrost site in Svalbard, Norway. It tackles the thaw depths inferred from non-invasive multi-channel ground-penetrating radar (GPR). It also evaluates the average volumetric soil water content and presents the estimation of the sensible heat content of the soil.