Extreme indices of temperature and precipitation in South America: trends and intercomparison of regional climate models

Regional Climate Models (RCMs) provide climate information required for evaluating vulnerability, impacts, and adaptation at finer scales than their global driving models. As they explicitly resolve the basic conservation and state equations, they solve physics with more detail, conserving teleconnection of larger scales provided by Global Climate Models (GCMs). In South America (SA), the regional simulations have been historically evaluated principally on climatological aspects, but the representativeness of extremes still needs a more profound assessment. This study aims to analyze three RCMs (RegCM4-7, REMO2015, and Eta) driven by different GCMs in SA, focusing on their capacity to reproduce extreme historical indices of daily precipitation and temperature. The indices of maximum consecutive 5 days precipitation (Rx5day), Consecutive Dry Days (CDD), daily maximum and minimum annual temperature (TXx and TNn, respectively) were evaluated regarding the historical spatio-temporal variability and trends. Furthermore, their projections for the 2071-2099 period, under the Representative Concentration Pathway 8.5 scenario, were analyzed. The historical behavior of RCMs (1981-2005) was compared with two gridded products: Climate Prediction Center (CPC) and agrometeorological indicators derived from the fifth generation of global reanalysis produced by the ECMWF (AgERA5), previously compared with records from meteorological stations to evaluate them. The results show that the highest differences within the gridded products and stations were observed in the regions with more scarce surface stations (North and West of SA) and with complex topography (The Andes Cordillera), being more pronounced in the precipitation-based indices. We found that RCMs generally show more agreement in the spatial variability than in the inter-annual variability for all the indices and SA regions. When analyzing the observed trends, all models better reproduced the long-term variability of extreme temperature indices than those of rainfall. More disagreement was observed for Rx5day and CDD indices trends, including substantial spatial heterogeneities in both magnitude and sign of tendency. Climate change projections exhibited significant agreement to warmer conditions in TXx and TNn, but precipitation signals differed between RCMs and the driving GCM within each regional model. Maximum dry spells are expected to increase in almost all SA regions, whereas the climate change signals in extreme precipitation events are more consistent over southeastern SA (northern and southwestern SA), with positive (negative) changes by the end of the century.