Analyzing the dependence of global cloud feedback on the spatial pattern of sea surface temperature change with a Green's function approach

The spatial pattern of sea surface temperature (SST) changes has a large impact on the magnitude of cloud feedback. In this study, we seek a basic understanding of the dependence of cloud feedback on the spatial pattern of warming. Idealized experiments are carried out with an AGCM to calculate the change in global mean cloud-induced radiation anomalies (Delta R-cloud) in response to imposed surface warming/cooling in 74 individual localized oceanic patches''. Then the cloud feedback in response to a specific warming pattern can be approximated as the superposition of global cloud feedback in response to a temperature change in each region, weighted by the magnitude of the local temperature changes. When there is a warming in the tropical subsidence or extratropical regions, the local decrease of LCC results in a positive change in R-cloud. Conversely, warming in tropical ascent regions increases the free-tropospheric temperature throughout the tropics, thereby enhancing the inversion strength over remote regions and inducing positive global low-cloud cover (LCC) anomalies and negative R-cloud anomalies. The Green's function approach performs reasonably well in predicting the response of global mean Delta LCC and net Delta R-cloud, but poorly for shortwave and longwave components of Delta R-cloud due to its ineffectiveness in predicting middle and high cloud cover changes. The approach successfully captures the change of cloud feedback in response to time-evolving CO2-induced warming and captures the interannual variations in Delta R-cloud observed by CERES. The results highlight important nonlocal influences of SST changes on cloud feedback.