Climate change projections for Switzerland based on a Bayesian multi-model approach



Regional projections of future climate with associated uncertainty estimates are increasingly being demanded. Generally, such scenarios rely on a finite number of model projections and are accompanied by considerable uncertainties which cannot be fully quantified. Consequently, probabilistic climate projections are conditioned on several subjective assumptions which can be treated in a Bayesian framework. In this study, a recently developed Bayesian multi-model combination algorithm is applied to regional climate model simulations from the ENSEMBLES project to generate probabilistic projections for Switzerland. The seasonal temperature and precipitation scenarios are calculated relative to 1980–2009 for three 30-year scenario periods (centred at 2035, 2060, and 2085), three regions, and the A1B emission scenario. Projections for two further emission scenarios are obtained by pattern scaling. Key to the Bayesian algorithm is the determination of prior distributions about climatic parameters. It is shown that the prior choice of model projection uncertainty ultimately determines the uncertainty in the climate change signal. Here, we assume that model uncertainty is fully sampled by the climate models available. We have extended the algorithm such that internal decadal variability is also included in all scenario calculations. The A1B scenarios show a significant rise in temperature increasing from 0.9–1.4 °C by 2035 (depending upon region and season), to 2.0–2.9 °C by 2060, and to 2.7–4.1 °C by 2085. Mean precipitation changes are subject to large uncertainties with median changes close to zero. Significant signals are seen towards the end of the century with a summer drying of 18–24% depending on region, and a likely increase of winter precipitation in Switzerland south of the Alps. The A2 scenario implies a warming of 3.2–4.8 °C, and a summer drying of 21–28% by 2085, while in case of the mitigation scenario RCP3PD, climate change could be stabilized to 1.2–1.8 °C of warming and 8–10% of drying. Copyright © 2011 Royal Meteorological Society