The Mediterranean region is one of the most responsive areas to climate change and was identified as a major “hot-spot” based on global climate change analyses. This study provides insight into local climate changes in the Mediterranean region under the scope of the InTheMED project, which is part of the PRIMA programme. Precipitation and temperature were analyzed in an historical period and until the end of this century for five pilot sites, located between the two shores of the Mediterranean region. We used an ensemble of 17 Regional Climate Models, developed in the framework of the EURO-CORDEX initiative, under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Over the historical period, the temperature presents upward trends, which are statistically significant for some sites, while precipitation does not show significant tendencies. These trends will be maintained in the future as predicted by the climate models projections: all models indicate a progressive and robust warming in all study areas and moderate change in total annual precipitation, but some seasonal variations are identified. Future changes in droughts events over the Mediterranean region were studied considering the maximum duration of the heat waves, their peak temperature, and the number of consecutive dry days. All pilot sites are expected to increase the maximum duration of heat waves and their peak temperature. Furthermore, the maximum number of consecutive dry days is expected to increase for most of the study areas.

Missing data is a frequent problem in meteorological and hydrological temporal observation data sets. Finding effective solutions to this problem is essential because complete time series are required to conduct reliable analyses. This study used daily rainfall data from 60 rain gauges spatially distributed within Portugal's Guadiana River basin over a 30-year reference period (1976–2005). Gap-filling approaches using kriging-based interpolation methods (i.e. ordinary kriging and simple cokriging) are presented and compared to a deterministic approach proposed by the Food and Agriculture Organization (FAO method). The suggested procedure consists of fitting monthly semi-variogram models using the average daily rainfall from all available meteorological stations for each month in a reference period. This approach makes it possible to use only 12 monthly semi-variograms instead of one for each day of the gap period. Ordinary kriging and simple cokriging are used to estimate the missing daily precipitation using the semi-variograms of the month of interest. The cokriging method is applied considering the elevation data as the secondary variable. One year of data were removed from some stations to assess the efficacy of the proposed approaches, and the missing precipitation data were estimated using the three procedures. The methods were validated through a cross-validation process and compared using different performance metrics. The results showed that the geostatistical methods outperformed the FAO method in daily estimation. In the investigated study area, cokriging did not significantly improve the estimates compared to ordinary kriging, which was deemed the best interpolation method for a large majority of the rainfall stations.