Evaluation of EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment for the Euro-Mediterranean area) historical simulations by high-quality observational datasets in southern Italy: insights on drought assessment

Abstract

Many recent studies indicate climate change as a phenomenon that significantly alters the water cycle in different regions worldwide, also implying new challenges in water resource management and drought risk assessment. To this end, it is of key importance to ascertain the quality of regional climate models (RCMs), which are commonly used for assessing at proper spatial resolutions future impacts of climate change on hydrological events. In this study, we propose a statistical methodological framework to assess the quality of the EURO-CORDEX RCMs concerning their ability to simulate historic climate (temperature and precipitation, the basic variables that determine meteorological drought). We then specifically focus on drought characteristics (duration, accumulated deficit, intensity, and return period) determined by the theory of runs at seasonal and annual timescales by comparison with high-density and high-quality ground-based observational datasets. In particular, the proposed methodology is applied to the Sicily and Calabria regions (southern Italy), where long historical precipitation and temperature series were recorded by the ground-based monitoring networks operated by the former Regional Hydrographic Offices, whose density is considerably greater than observational gridded datasets available at the European level, such as E-OBS or CRU-TS. Results show that among the more skilful models able to reproduce, overall, precipitation and temperature variability as well as drought characteristics, many are based on the CLM-Community RCM, particularly in combination with the HadGEM2 global circulation model (GCM). Nevertheless, the ranking of the models may slightly change depending on the specific variable analysed as well as the temporal and spatial scale of interest. From this point of view, the proposed methodology highlights the skills and weaknesses of the different configurations and can serve as an aid for selecting the most suitable climate model for assessing climate change impacts on drought processes and the underlying variables.