Assessment of future snowfall regimes within the Italian Alps using general circulation models

General Circulation Models GCMs are widely adopted tools to achieve future climate projections. However, one needs to assess their accuracy, which is only possible by comparison of GCMs’ control runs against past observed data. Here, we investigate the accuracy of two GCMs models delivering snowfall that are included within the IPCC panelʹs inventory (HadCM3, CCSM3), by comparison against a comprehensive ground data base (ca. 400 daily snow gauging stations) located in the Italian Alps, during 1990–2009. The GCMs simulations are objectively compared to snowfall volume by regionally evaluated statistical indicators. The CCSM3 model provides slightly better results than the HadCM3, possibly in view of its finer computational grid, but yet the performance of both models is rather poor. We evaluate the bias between models and observations, and we use it as a bulk correction for the GCMsʹ snowfall simulations for the purpose of future snowfall projection. We carry out stationarity analysis via linear regression and Mann Kendall tests upon the observed and simulated snowfall volumes for the control run period, providing contrasting results. We then use the bias adjusted GCMs output for future snowfall projections from the IPCC-A2 scenario. The two analyzed models provide contrasting results about projected snowfall during the 21st century (until 2099). Our approach provides a first order assessment of the expected accuracy of GCM models in depicting past and future snowfall upon the (Italian) Alps. Overall, given the poor depiction of snowfall by the GCMs here tested, we suggest that care should be taken when using their outputs for predictive purposes.