Robustness of CMIP6 Historical Global Mean Temperature Simulations: Trends, Long‐Term Persistence, Autocorrelation, and Distributional Shape

Summary

Abstract Multi‐model climate experiments carried out as part of different phases of the Coupled Model Intercomparison Project (CMIP) are crucial to evaluate past and future climate change. The reliability of models' simulations is often gauged by their ability to reproduce the historical climate across many time scales. This study compares the global mean surface air temperature from 29 CMIP6 models with observations from three datasets. We examine (1) warming and cooling rates in five subperiods from 1880 to 2014, (2) autocorrelation and long‐term persistence, (3) models' performance based on probabilistic and entropy metrics, and (4) the distributional shape of temperature. All models simulate the observed long‐term warming trend from 1880 to 2014. The late twentieth century warming (197