Climate feedbacks
My current research focuses on how the energy balance of the atmosphere is amplified or damped due to changes in physical processes (such as clouds, water vapor, lapse rate, and ice albedo) that occur in a warming climate.
At the global scale, feedback analysis is a powerful tool for constraining climate sensitivity through understanding uncertainty in the component model physics. Our focus here is to evaluate the extent to which this framework can be applied to the question of regional climate predictability. We have developed a clean and clear approach to address these challenges. We employ the GFDL AM2 model in aquaplanet mode, coupled to simple ocean mixed-layer and sea-ice schemes, and run under perpetual equinox conditions. This simplified, aquaplanet simulation enables us to investigate the atmospheric response to carbon dioxide without the effects of a seasonal cycle or land-sea distribution, which can obscure the response. Further, we explicitly calculate radiative kernels (necessary to diagnose the feedbacks) for this precise model set-up, thus removing much of the ambiguity in the feedback approximation. We find that linking regional predictability and individual climate feedbacks depends on the balance between local radiative feedbacks and meridional energy transport in response to changes in climate forcing. An important aspect of this energy budget is the linearity of the kernel-calculated feedbacks, which we evaluate. Spatial patterns of these factors can be related to the basic structure of atmospheric circulation, and our results highlight regional differences in the effect of feedbacks on the regional climate response.
