Using historical temperature to constrain the climate sensitivity, the transient climate response, and aerosol-induced cooling

Abstract

Abstract. The most recent generation of climate models that has informed the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC) is characterized by the presence of several models with larger equilibrium climate sensitivities (ECSs) and transient climate responses (TCRs) than exhibited by the previous generation. Partly as a result, AR6 did not use any direct quantifications of ECSs and TCRs based on the 4×CO2 and 1pctCO2 simulations and relied on other evidence when assessing the Earth's actual ECS and TCR. Here I use historical observed global-mean temperature and simulations produced under the Detection and Attribution Model Intercomparison Project to constrain the ECS, TCR, and historical aerosol-related cooling. I introduce additivity criteria that disqualify 8 of the participating 16 models from consideration in multi-model averaging calculations. Based on the remaining eight models, I obtain an average adjusted ECS of 3.5 ± 0.4 K and a TCR of 1.8 ± 0.3 K (both at 68 % confidence). Both are consistent with the AR6 estimates but with substantially reduced uncertainties. Furthermore, importantly I find that the optimal cooling due to short-lived climate forcers consistent with the observed temperature record should, on average, be about 47 % ± 39 % of what these models simulate in their aerosol-only simulations, yielding a multi-model mean, global-mean, and annual-mean cooling due to near-term climate forcers for 2000–2014, relative to 1850–1899, of 0.24 ± 0.11 K (at 68 % confidence). This is consistent with but at the lower end of the very likely uncertainty range of the IPCC's AR6. There is a correlation between the models' ECSs and their aerosol-related cooling, whereby large-ECS models tend to be associated also with strong aerosol-related cooling. The results imply that a reduction in the aerosol-related cooling, along with a more moderate adjustment of the greenhouse-gas-related warming for most models, would bring the historical global-mean temperature simulated by these models into better agreement with observations.