Quantifying uncertainties in climate projections in mountain areas using statistical tools

Abstract

Taking into account the uncertainties associated with climate projections is essential but often overlooked. One main reason for that is the multiplicity of climate projections representing possible future climates as a consequence of uncertainties surrounding developments for greenhouse gases, uncertainties arising from the climate models and the impact models (hydrology, biodiversity etc.), as well as the natural variability of the climate. To describe these different sources of uncertainty and take them into account is not easy for engineers and managers who are more accustomed to reasoning in a determinist framework. This article aims to demonstrate that statistics offers a number of approaches which make it possible to use a given multi-scenario, multimodel climate projection. The simplest propose a descriptive summary of the information, while the more complex approaches can test the significance of the expected changes, separate the different causes of uncertainty and measure the contribution of each to the overall variability. The approach is illustrated by a set of projections for temperature, precipitation and mean snow depth for a mountainous region of the French Alps. It can be easily applied to any variable whose projections have been generated through an impact model which simulates the consequences of a set of climate projections for a given sector defined in social and ecosystem terms.