Snow on the ground is a key environmental and socio-economic component of mountain regions. Storage of water in the form of snow during the winter period provides freshwater input to ecosystems, agriculture and human consumption. Natural hazards such as snow avalanches and snowmelt floods cause loss of lives and disruption of human activities. Snow plays a pivotal role for numerous socio-economic activities such as hydropower (electricity generation and industry) and winter tourism.
The French Alps have encountered significant changes of snow conditions over the past decades, which can be inferred at the massif scale using the dedicated meteorological analysis system SAFRAN feeding the detailed snowpack model Crocus. Superimposed over a large year-to-year variability, these changes are most pronounced in mid-altitude areas which are highly sensitive to the rain/snow partitioning of precipitation. Such an extensive reanalysis of meteorological and snow conditions has been further used to un-bias and downscale regional climate model projections spanning the XXIst century. The presentation will highlight key results at the scale of the entire French Alps obtained using CMIP3 projections and preliminary results using CMIP5/EUROCORDEX projections.
The interpretation of the numerical simulations spanning the observational era for the past decades and an ensemble of climate projections into the XXIst century not only addresses changes of snow conditions in terms of snow water equivalent, relevant for water resources, but also trends in the seasonality of discharge in selected catchments, avalanche hazard and resort-level snow viability. The latter is currently being developed accounting not only for meteorological drivers of snow on the ground but also socio-economic components of mountain tourism including snow management practices and the spatial organization of ski resorts. This approach seeks at contributing to an integrated representation of the impact of climate change in mountain areas thereby helping to quantitatively assess the resilience of these sensitive environmental and socio-economic systems.