Modelling of the Seasonal Snow Cover Dynamics for Open and Forested Areas in the Berchtesgaden National Park (Germany) Using the <scp>openAMUNDSEN</scp> Mountain Snow Cover Model

ABSTRACT Mountain snowpacks represent an important source of freshwater whereby most of the seasonally snow‐covered mountain areas are partly forested. Hence, an understanding of the effect of the forest canopy, on top of topographical variations, on the build‐up and melt of a seasonal snow cover is important, for example, for water resources management. In this study, we assess the seasonal snow cover dynamics for open and forested areas in the Berchtesgaden National Park (BGNP) located in South‐East Germany, by applying the mountain snow model openAMUNDSEN. Station‐based meteorological observations are processed and used to force model simulations in 3‐hourly timesteps on a 50 × 50 m spatial grid for the time frame 10/2018 to 09/2023. We use point observations of snow, fractional snow cover maps from Sentinel‐2 and wet snow maps based on Sentinel‐1 to evaluate model results in the open. For the evaluation of the model results inside the forest, we utilise measured ground temperatures from a unique network of 150 microclimate loggers (TOMST TMS‐4) and compare derived snow cover durations (SCDs) and the snow disappearance days (SDDs) to the simulations. The results show that openAMUNDSEN is capable of modelling the spatio‐temporal variations of the snow cover depending on both topography and land cover in the BGNP. Our analysis indicates that the use of a combined dataset consisting of snow cover data derived from remote sensing, point observations in the open and measured ground temperature in the forest can overcome and compensate for limitations of individual data sources. Next steps in the development of the openAMUNDSEN model setup for the BGNP should include the refinement of lateral snow redistribution processes and the development of a forest type distribution map to better represent the small‐scale variability of the leaf area index.