Quantifying progress across different CMIP phases with the ESMValTool

While systematic biases in annual mean surface temperature and precipitation remain in the CMIP6 multimodel mean, individual models and high-resolution versions of the models show significant reductions in many long-standing biases. Some improvements are also found in the vertical temperature, water vapor, and zonal wind speed distributions, and root-mean-square errors for selected fields are generally smaller with reduced intermodel spread and higher average skill in the correlation patterns relative to observations.

An emerging property of the CMIP6 ensemble is a higher effective climate sensitivity with an increased range between 2.3 and 5.6 K. A possible reason for this increase in some models is improvements in cloud representation resulting in stronger shortwave cloud feedbacks than in their predecessor versions.