LAUSR

AbstractThis work is aimed to propose a methodology for the identification of areas for which extreme climatological conditions may intensify aridity processes and rainfall deficiency. The proposed procedure, which is based on the analysis of climate projections derived from high-resolution regional simulations, is composed of three main elements. First, extreme temperature, extreme precipitation, and extreme dry periods (in terms of consecutive dry days) are modeled using extreme value theory. Second, an aridity index is used as a proxy of long-term processes leading to aridity. Third, clustering techniques are used to group zones with similar climatic parameters. In this way, areas with the more extreme climate conditions are identified. Possible effects due to selected climate-change scenarios are considered by analyzing possible nonstationary conditions in extreme events and by performing calculations in both a historical period and a projection period (where different scenarios are considered). An ap...