Towards improved alpine permafrost maps using the energy balance model of the CryoGrid community

The warming of mountain permafrost due to climate change poses significant challenges for slope stability and ecosystem dynamics in alpine regions. Accurate permafrost maps are essential for hazard assessment, as they depict local permafrost conditions and account for meso-scale thermal variability caused by complex alpine topography. Over recent decades, several permafrost maps have been developed using field data (e.g., rock surface temperatures, rock glacier inventories) and statistical models that link permafrost evidence to air temperature, solar radiation, and, in some cases, precipitation.

These models effectively map permafrost in steep alpine rock slopes with limited snow accumulation and estimate permafrost probability in debris-covered slopes based on the distribution of active rock glaciers. However, they are unable to capture the complex thermal regimes associated with variable snow accumulations typical of high mountain environments. In particular, permafrost in intermediately steep slopes (40°–60° inclination) is strongly influenced by snow accumulation patterns, including timing, thickness, and interactions with solar radiation. These slopes, which form a significant portion of alpine landscapes, often exhibit fractured rock, surface debris, and variable snow cover, creating unique conditions for permafrost formation and evolution. Unlike steep rock faces, intermediately steep slopes may retain larger ice volumes due to the refreezing of meltwater from seasonal snow, resulting in distinct thermal regimes and geomorphological behaviors. Their complex micro-topography further amplifies variability in solar radiation and snow distribution, complicating their thermal and mechanical stability.

To address these knowledge gaps, this research applies the CryoGrid community energy and hydrological balance model to simulate temperature dynamics at monitored sites in the French Alps, spanning elevations of 2500 to 3800 m. The initial phase involves calibrating the model using data collected from 2019 to 2024 across diverse snow cover conditions. Calibration focuses on parameters such as maximum snow height, deposited snow fraction, near-surface convection, initial temperature profiles, and albedo, identified as critical for energy balance simulations in prior CryoGrid3 applications in alpine settings.

Once calibrated, the model will be generalized to account for variable slope angles, sun exposures, surface roughness, ground characteristics, and precipitation regimes. These calibration steps will enable spatial application of the model on digital elevation models (DEMs) to generate improved permafrost maps for alpine settings, encompassing steep rock walls, creeping debris slopes, and intermediately steep slopes. Additionally, the model outputs will provide insights into permafrost evolution in diverse mountain slopes and support stakeholders in developing effective risk mitigation strategies.