Does Model Sensitivity to Changes in CO2 Provide a Measure of Sensitivity to Other Forcings?

Simulation of both the climate of the twentieth century and a future climate change requires taking into account numerous forcings, while climate sensitivities of general circulation models are defined as the equilibrium surface warming due to a doubling of atmospheric CO2 concentration. A number of simulations with the Massachusetts Institute of Technology (MIT) climate model of intermediate complexity with different forcings have been carried out to study to what extent sensitivity to changes in CO2 concentration (SCO2) represent sensitivities to other forcings. The MIT model, similar to other models, shows a strong dependency of the simulated surface warming on the vertical structure of the imposed forcing. This dependency is a result of “semidirect” effects in the simulations with localized tropospheric heating. A method for estimating semidirect effects associated with different feedback mechanisms is presented. It is shown that forcing that includes these effects is a better measure of expected surface warming than a forcing that accounts for stratospheric adjustment only. Simulations with the versions of the MIT model with different strengths of cloud feedback show that, for the range of sensitivities produced by existing GCMs, SCO2 provides a good measure of the model sensitivity to other forcings. In the case of strong cloud feedback, sensitivity to the increase in CO2 concentration overestimates model sensitivity to both negative forcings, leading to the cooling of the surface and “black carbon”–like forcings with elevated heating. This is explained by the cloud feedback being less efficient in the case of increasing sea ice extent and snow cover or by the above-mentioned semidirect effects, which are absent in the CO2 simulations, respectively.