Assessment of snow model uncertainty in relation to the effect of a 1 °C warming using the snow modelling framework openAMUNDSEN

Abstract. Novel climate model data at the kilometer-scale, innovative downscaling techniques, sophisticated snow modelling frameworks and increasing computational capacities are among the elements that currently pave the way for a new phase in high resolution and physically based climate impact studies for the snow hydrology of mountain regions with complex topography. However, while the assessment of climate model uncertainty is well established, the uncertainty originating from the selection of the snow model usually only receives little attention. To investigate the uncertainty induced by the selection of the snow model configuration, we simulate the seasonal snow cover in the complex mountain area of the Berchtesgaden National Park mountains (Germany) under historical conditions (10/2013–09/2023) and for a 10-year period characterized by a 1 °C warming, using a large number of openAMUNDSEN snow model configurations (n = 108) with degree-day as well as physically based snowmelt methods and varying land cover maps and spatial resolutions. The analysis of the resulting snow cover durations and snow disappearance days suggests that differences showing up depending on the selected snowmelt method, land cover map and spatial resolution can be in the same range as the impact of a 1 °C warming, whereby uncertainties in the results are pronounced in the forest covered areas and in the high elevations of the study area. Our results support the identification of critical snow model settings that need to be considered, in particular, when using energy balance instead of degree-day snow models to investigate climate change impacts on the snow hydrology in complex mountain terrain.