Statistical downscaling of daily precipitation and temperatures in southern La Plata Basin

La Plata Basin has a considerable socio-economic value, being one of the most important agricultural and hydropower-producing regions in the world. In this region, there is increasing evidence of a changing climate with more frequent and more intense extreme events. Despite the importance of empirical statistical downscaling for regional climate impact studies, few studies have addressed this issue for southern South American regions. In this work, the analogue method was calibrated and validated for simulating local daily precipitation and maximum and minimum temperatures in southern La Plata Basin. The model was trained for the 1979-2000 period and validated for the independent period 2001-2014. Daily fields from NCEP-NCAR Reanalysis 2 were used as predictors and daily observed data from 25 meteorological stations were used as predictands. A variety of potential predictors (including circulation, temperature and humidity variables) and combinations of them over different domain sizes were tested, revealing that the method was more skilful when combined predictors were considered. However, depending on the local predictand and the season of the year different predictor sets may be more appropriate. The method was comprehensively evaluated by means of several skill measures concerning different properties such as mean values, day-to-day variance, daily correspondence, persistence, inter-annual variability, probability distributions and extreme percentiles. The method showed an overall good performance. It tended to overestimate (underestimate) temperature values, especially during winter (summer); however, the day-to-day variance during these seasons was fairly well represented. The method was able to reproduce extreme percentiles and their spatial distributions for the three predictand variables as well as the probability of compound temperature and precipitation extreme events. The performance of the method was very good at estimating seasonal cycles of the different aspects explored. It showed some difficulties in representing the persistence in daily temperatures and the inter-annual variability of seasonal precipitation.