Climate Feedbacks from Internal Variability

The climate sensitivity is determined in part by the effect of surface warming on the Earth's top-of-atmosphere radiative fluxes, a relationship sometimes called the "climate feedback." One way of determining the strength of this feedback is to analyze internal variations in surface temperature and top-of-atmosphere fluxes such as can be found in a preindustrial control run of an atmosphere-ocean general circulation model (AOGCM). We suggest a method for performing this analysis that captures the spatial nature of the climate feedback and apply it to the millenial-scale AOGCM control runs found in the new LongRunMIP database. Given knowledge of the spatial pattern of warming in a run forced by a change in atmospheric CO₂, we can use the spatial feedbacks estimated from the given AOGCM's control runs to predict the shortwave and longwave TOA fluxes in the forced run for a majority of simulations. In addition to predicting the shortwave and longwave feedbacks, we can predict how these feedbacks change with time. We discuss how this method sheds light on the spatial nature of these feedback processes, and the implications for observational estimates of climate sensitivity.