نبذة مختصرة : International audience ; Abstract. Large snow load events are a major hazard for both human societies, in particular buildings and transport safety, and natural ecosystems. National and European frameworks provide guidelines and standards in order to take into account extreme snow load hazard in infrastructure design. However, there is a lack of reference data for their implementation. This is even more challenging in the context of climate change, which modifies the frequency and intensity of major snow load events. In the context of the Framework Partnership Agreement on Copernicus User Uptake, we have developed a pan-European extreme value analysis of annual snow load maxima based on the Mountain Tourism Meteorological and Snow Indicators (MTMSI) dataset available from the Copernicus Climate Change Service. This dataset includes reanalysis data for the period 1962–2015, based on the UERRA (Uncertainties in Ensembles of Regional Reanalyses) reanalysis and snow cover simulations, and past and future climate projections based on regional climate simulations for the period 1951–2100. Here, we describe the evaluation of the MTMSI reanalysis component in terms of annual snow depth maxima against multiple in-situ observation datasets. Results are provided at the NUTS-3 (Nomenclature des unités territoriales statistiques) scale used in MTMSI, for multiple elevations over a large area stretching from the European Alps to the Scandinavian countries. For 75 % of the comparisons between observed and simulated snow depth maxima, we report absolute bias scores between −0.23 and 0.15 m, correlations above 0.59, and a Kling–Gupta Efficiency metric above 0.29. We identify some areas where MTMSI does not adequately portray in-situ observations of snow depth maxima, located in the Alps and coastal areas of the Netherlands, Norway, Sweden, and Croatia. This study thus provides background information for assessing the relevance of this pan-European dataset in terms of annual snow depth maxima, relevant for annual snow mass and ...
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