The S2M meteorological and snow cover reanalysis over the French mountainous areas: description and evaluation (1958-2021)

Vernay, Matthieu ; Lafaysse, Matthieu ; Monteiro, Diego ; Hagenmuller, Pascal ; Nheili, Rafife ; Samacoïts, Raphaëlle ; Verfaillie, Deborah ; Morin, Samuel

Année de publication
2022
Résumé
<p align=justify>This work introduces the S2M (SAFRAN-SURFEX/ISBA-Crocus-MEPRA) meteorological and snow cover reanalysis in the French Alps, Pyrenees and Corsica, spanning the time period from 1958 to 2021. The simulations are made over elementary areas, referred to as massifs, designed to represent the main drivers of the spatial variability observed in mountain ranges (elevation, slope and aspect). The meteorological reanalysis is performed by the SAFRAN system, which combines information from numerical weather prediction models (ERA-40 reanalysis from 1958 to 2002, ARPEGE from 2002 to 2021) and the best possible set of available in situ meteorological observations. SAFRAN outputs are used to drive the Crocus detailed snow cover model, which is part of the land surface scheme SURFEX/ISBA. This model chain provides simulations of the evolution of the snow cover, underlying ground and the associated avalanche hazard using the MEPRA model. This contribution describes and discusses the main climatological characteristics (climatology, variability and trends) and the main limitations of this dataset. We provide a short overview of the scientific applications using this reanalysis in various scientific fields related to meteorological conditions and the snow cover in mountain areas. An evaluation of the skill of S2M is also displayed, in particular through comparison to 665 independent in situ snow depth observations. Further, we describe the technical handling of this open-access dataset, available at <a href="https://doi.org/10.25326/37#v2020.2" target="_blank">https://doi.org/10.25326/37#v2020.2</a>. The S2M data are provided by Météo-France - CNRS, CNRM, Centre d'Études de la Neige, through AERIS (Vernay et al., 2022).</p>
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