Multi-components ensembles of future meteorological and natural snow conditions in the Northern French Alps

le 16 avril 2018

Parution d'un article dans The Cryosphère qui présente des projections d'enneigement à 1500m dans la Chartreuse. Les ensembles de projections climatiques sont assez proches jusqu'au milieu du 21e siècle, et tous montrent une poursuite de la réduction continue des conditions de neige interannuelles moyennes, et une variabilité interannuelle maintenue.

Résumé

This article introduces climate variations of annual-scale indicators for seasonal snow and its meteorological drivers, at 1500 m altitude in the Chartreuse mountain range in the Northern French Alps. Past and future variations were computed based on reanalysis and observations from 1958 to 2016, and using CMIP5/EURO-CORDEX GCM/RCM pairs spanning historical (1950-2005) and RCP2.6 (4), RCP4.5 and RCP8.5 (13 each) future scenarios (2006-2100). The adjusted climate model runs were used to drive the multiphysics ensemble configuration of the detailed snowpack model Crocus. Uncertainty arising from physical modeling of snow accounts for 20 % typically, although the multiphysics is likely to have a much smaller impact on trends. Ensembles of climate projections are rather similar until the middle of the 21st century, and all show a continuation of the ongoing reduction in mean interannual snow conditions, and maintained interannual variability. The impact of the RCP becomes significant for the second half of the 21st century, with overall stable conditions with RCP2.6, and continued degradation of snow conditions for RCP4.5 and 8.5, the latter leading to more frequent ephemeral snow conditions. Variations of local meteorological and snow conditions show significant correlation with global temperature variations. Global temperature levels on the order of 1.5°C above pre-industrial levels correspond to a 25 % reduction of winter mean snow depth (reference 1986-2005). Even larger reduction is expected for global temperature levels exceeding 2?C. The method can address other sectorial indicators, in the field of hydropower, mountain tourism or natural hazards.
 

Publié le 29 mai 2020