08 Feb 2023
 | 08 Feb 2023
Status: this preprint is open for discussion.

Multi-decadal past winter temperature, precipitation and snow cover information over the European Alps using multiple datasets

Diego Monteiro and Samuel Morin

Abstract. Assessing past distributions, variability and trends of the mountain snow cover and its first order drivers, temperature and precipitation, is key for a wide range of studies and applications. In this study, we compare the results of various modelling systems (global and regional reanalyses ERA5, ERA5-Land, ERA5-Crocus, CERRA-Land, UERRA MESCAN-SURFEX, MTMSI, and regional climate model simulations CNRM-ALADIN and CNRM-AROME driven by the global reanalysis ERA-Interim) against observational references (in-situ, kriged datasets and satellite observations) across the European Alps, from 1950 to 2020. The comparisons are performed in terms of monthly and seasonal snow cover variables (snow depth and snow cover duration) and their main atmospherical drivers (near-surface temperature and precipitation). We assess multi-annual averages of regional and sub-regional mean values, their inter-annual variations, and trends over various time scales.

CNRM-AROME and CNRM-ALADIN simulations, and ERA5-Land exhibit an overestimation of the snow accumulation during winter, increasing with elevations. ERA5, ERA5-Crocus, MESCAN-SURFEX, CERRA-Land and MTMSI offer a satisfying description of the monthly snow evolution albeit a spatial comparison against satellite observation indicates that all datasets overestimate the snow cover duration of the snow cover, especially the melt-out date.

The analysis of the inter-annual variability and trends indicate that modelling snow cover dynamics remain complex across multiple scales, that none of the models evaluated here fully succeed to reproduce, compared to observational reference datasets. Indeed, while most of the evaluated model outputs perform well at representing the inter-annual to multi-decadal winter temperature and precipitation variability, they often fail to address the variability of the snow depth and snow cover duration. We discuss several artifacts potentially responsible for incorrect long-term climate trends in several reanalysis products (ERA5 and MESCAN-SURFEX), which we attribute primarily to the heterogeneities of the observation datasets assimilated.

Reference datasets and some of the evaluated datasets provides past trends in line with current available literature. Over the last 50 years (1968–2017) at a regional scale, the European Alps have experienced a winter warming of 0.3 to 0.4 °C per decade, a weak reduction of winter precipitation, and a substantial decrease of the snowpack characteristics, with a decline of the winter snow depth and the snow cover duration reaching −10 % per decade and −10 days per decade, respectively, especially at low and intermediate elevations.

Overall, we show that no modelling strategy outperforms all others within our sample, and that upstream choices (horizontal resolution, heterogeneity of the observations used for data assimilation in reanalyses, coupling between surface and atmosphere, level of complexity and configuration of the snow scheme etc.) have great consequences on the quality of the datasets and their potential use. Despite their limitations, in many cases these modeling outputs can be used to characterize the main features of the mountain snow cover for a range of applications.

Diego Monteiro and Samuel Morin

Status: open (until 05 Apr 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-166', Anonymous Referee #1, 07 Mar 2023 reply
  • RC2: 'Comment on egusphere-2023-166', Anonymous Referee #2, 08 Mar 2023 reply

Diego Monteiro and Samuel Morin

Diego Monteiro and Samuel Morin


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Short summary
Beyond directly using in-situ observations, often sparsely available in mountain regions, climate model simulations and so-called reanalyses are increasingly used for climate change impacts studies. Here we evaluate such datasets in the European Alps from 1950 to 2020, with a focus on snow cover information and its main drivers air temperature and precipitation. In terms of variability and trends, we identify several limitations, and provide recommendations for future use of these datasets.