Evaluation of extreme temperature events as simulated by CMIP6 models over Central Africa

Extreme temperature events pose significant risks to both natural environments and communities across Central Africa (CA). Gaining deeper insight into how these events vary is crucial to inform effective climate change mitigation and adaptation plans. The present study evaluates the suitability of global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), along with their multi-model ensemble mean (MME), in simulating the recent past spatial variations of extreme temperature events in CA. For this purpose, under the period 1985–2014, we assessed seven relevant indicators based on daily minimum and maximum temperatures, recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI). We examined the spatial patterns of these extreme temperature events as simulated by sixteen CMIP6 models and their MME against CHIRTS and ERA5 observational and reanalysis datasets, focusing on percentile, absolute, and duration-based indices. The results showed that both individual models and the MME demonstrated reasonable skill in reproducing the spatial patterns of most extreme temperature indices, with the MME often showing better agreement with observations. However, the models faced challenges in accurately simulating the frequency of the percentile-based indices, notably TX90p and TN10p, across all sub-regions. Furthermore, the model performance varies depending on the specific index and the climatic sub-region. This study thereby elucidates the capabilities and shortcomings of CMIP6 models in representing extreme temperatures across Central Africa, providing valuable information for developing more reliable regional climate projections and assessing the future impacts of climate change on temperature extremes.