In the current climate change scenario, it is increasingly important to evaluate mountain areas potentially at risk in an efficient and rapid way. Permafrost is one of the main factors determining surface stability in mountain regions. The monitoring network of ground surface thermistors is limited and in several cases the data and metadata are not of easy access. Therefore, modelling is a valid alternative for the prediction of the ground surface temperature (GST). This work presents an update version of the physics-based model PERMACLIM (PERMACLIM 2.0) for the calculation of the mean annual ground surface temperature (MAGST) and for mapping permafrost conditions. PERMACLIM 2.0 presents several updates mainly regarding the realization of the snow depth maps, the calculation of the GST and the classification of the MAGST for detecting permafrost conditions in terms of presence, probability, possibility and absence of permafrost aggradation. The model was tested for the hydrological years 2020 and 2022, on the entire upper Valtellina, in the Northern Central Italian Alps, returning results with a spatial resolution of 10 m. The overall RMSE for MAGST ranges between 0.6 and 0.8 °C. The permafrost conditions were not favourable for the 67.8%, slightly favourable for the 8%, favourable for the 17.9% and very favourable for the 6.2%. The good results obtained and the new design of the model suggest using PERMACLIM 2.0 as a new tool to determine permafrost conditions useful to update the vulnerability and the risk maps in mountain regions.
PERMACLIM 2.0: a Revised Model for High-Resolution Mapping of Permafrost Conditions in Mountain Regions
Riva, Edoardo;Ponti, Stefano;Guglielmin, Mauro
2026-01-01
Abstract
In the current climate change scenario, it is increasingly important to evaluate mountain areas potentially at risk in an efficient and rapid way. Permafrost is one of the main factors determining surface stability in mountain regions. The monitoring network of ground surface thermistors is limited and in several cases the data and metadata are not of easy access. Therefore, modelling is a valid alternative for the prediction of the ground surface temperature (GST). This work presents an update version of the physics-based model PERMACLIM (PERMACLIM 2.0) for the calculation of the mean annual ground surface temperature (MAGST) and for mapping permafrost conditions. PERMACLIM 2.0 presents several updates mainly regarding the realization of the snow depth maps, the calculation of the GST and the classification of the MAGST for detecting permafrost conditions in terms of presence, probability, possibility and absence of permafrost aggradation. The model was tested for the hydrological years 2020 and 2022, on the entire upper Valtellina, in the Northern Central Italian Alps, returning results with a spatial resolution of 10 m. The overall RMSE for MAGST ranges between 0.6 and 0.8 °C. The permafrost conditions were not favourable for the 67.8%, slightly favourable for the 8%, favourable for the 17.9% and very favourable for the 6.2%. The good results obtained and the new design of the model suggest using PERMACLIM 2.0 as a new tool to determine permafrost conditions useful to update the vulnerability and the risk maps in mountain regions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.



