Evaluation of CMIP6 models in the representation of observed extreme temperature indices trends in South America

Abstract

The consequences of climate change are particularly noticeable through extreme events, which have already changed in intensity and frequency worldwide. This study aims to evaluate the ability of 33 CMIP6 models to simulate the observed trends of four extreme temperature indices in South America during the period 1979–2014. We use daily minimum and maximum temperatures from an observational database, ERA5 reanalysis, and CMIP6 models to estimate the international indices: cold nights, warm nights, cold days, and warm days. Trends are calculated using Sen’s slope for different seasons and spatial scales (continental, sub-regional, and at each grid point) and tested with the Mann–Kendall test. All databases agree on an increase (decrease) in the frequency of warm (cold) extremes in South America, with the most intense changes in the austral spring. In particular, the warm nights index and the northern sub-regions of South America show the most pronounced trends. In contrast, in the southern sub-regions of South America, the observations do not indicate significant trends of the minimum temperature indices, which differ from the trends estimated by the CMIP6 ensemble median and most of the individual models. In general, the ensemble median simulates significant long-term changes at almost all grid points, unlike the observations and reanalysis. Finally, the simulated trends related to minimum temperature are slightly better represented than those related to maximum temperatures. Nevertheless, neither model stands out as the best, and all of them have difficulty simulating trends, especially for cold days.