| One of the greatest challenges in projections of future climate change is narrowing the uncertainty in the magnitude and sign of cloud feedback. The main limitations are that cloud processes need to be parameterized in climate models, and long-term observations of cloud cover are limited. In this dissertation we address this problem by studying the interplay of cloud feedbacks with atmospheric circulation and Sea Surface Temperature (SST). We first investigate the response of clouds to external radiative forcing by examining changes in cloud cover and their radiative impact in multiple and independent surface and satellite cloud cover datasets. Observed changes in cloud cover and estimated cloud amount feedback from 1954 to 2008 over the Indo-Pacific Ocean are found to be consistent in sign but significantly smaller in amplitude than changes simulated by an ensemble of historical simulations in the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive over the same period of time. However, climate models are capable of simulating changes in cloud cover of the same strength and pattern as observed, when they are forced with a greater increase in SST. This suggests that observed changes in cloud cover are at least in part forced by anthropogenic emissions. It remains unclear whether observations exhibit unrealistically large trends in cloud cover, or clouds are not sensitive enough to changes in surface temperature in climate models. However, climate models underestimate changes in cloud cover also on shorter and better constrained timescales. The implications of underestimating the strength of a positive cloud feedback is explored using idealized model experiments in the context of internal climate variability. It is found that a positive feedback among cloud cover, SST, and large-scale atmospheric circulation over the subtropical stratocumulus regions affects basin-wide pattern and persistence of SST anomalies in both the Atlantic and Pacific Oceans. Collectively, these findings suggest that climate models underestimate the impacts of cloud feedbacks on the persistence of regional and global SST anomalies, thus potentially underestimating climate sensitivity to future climate change. |
