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 (ΔRcloud) 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 Rcloud. 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 Rcloud anomalies. The Green's function approach performs reasonably well in predicting the response of global mean ΔLCC and net ΔRcloud, but poorly for shortwave and longwave components of ΔRcloud 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 ΔRcloud observed by CERES. The results highlight important nonlocal influences of SST changes on cloud feedback.