What is the effect of unresolved internal climate variability on climate sensitivity estimates?

Many studies have attempted to estimate the equilibrium climate sensitivity (CS) to the doubling of CO 2 concentrations. One common methodology is to compare versions of Earth models of intermediate complexity (EMICs) to spatially and/or temporally averaged historical observations. Despite the persistent efforts, CS remains uncertain. It is, thus far, unclear what is driving this uncertainty. Moreover, the effects of the internal climate variability on the CS estimates obtained using this method have not received thorough attention in the literature. Using a statistical approximator (“emulator”) of an EMIC, we show in an observation system simulation study that unresolved internal climate variability appears to be a key driver of CS uncertainty (as measured by the 68% credible interval). We first simulate many realizations of pseudo‒observations from an emulator at a “true” prescribed CS, and then reestimate the CS using the pseudo‒observations and an inverse parameter estimation method. We demonstrate that a single realization of the internal variability can result in a sizable discrepancy between the best CS estimate and the truth. Specifically, the average discrepancy is 0.84°C, with the feasible range up to several °C. The results open the possibility that recent climate sensitivity estimates from global observations and EMICs are systematically considerably lower or higher than the truth, since they are typically based on the same realization of climate variability. This possibility should be investigated in future work. We also find that estimation uncertainties increase at higher climate sensitivities, suggesting that a high CS might be difficult to detect.