Climate feedbacks in a general circulation model incorporating prognostic clouds

This study performs a comprehensive feedback analysis on the Bureau of Mete orology Research Centre General Circulation Model, quantifying all importan t feedbacks operating under an increase in atmospheric CO2. The individual feedbacks are analysed in detail, using an offline radiation perturbation m ethod, looking at long- and shortwave components, latitudinal distributions , cloud impacts, non-linearities under 2xCO(2) and 4xCO(2) warmings and at interannual variability. The water vapour feedback is divided into terms du e to moisture height and amount changes. The net cloud feedback is separate d into terms due to cloud amount, height, water content, water phase, physi cal thickness and convective cloud fraction. Globally the most important fe edbacks were found to be (from strongest positive to strongest negative) th ose due to water vapour, clouds, surface albedo, lapse rate and surface tem perature. For the longwave (LW) response the most important term of the clo ud 'optical property' feedbacks is due to the water content. In the shortwa ve (SW), both water content and water phase changes are important. Cloud am ount and height terms are also important for both LW and SW. Feedbacks due to physical cloud thickness and convective cloud fraction are found to be r elatively small. All cloud component feedbacks (other than height) produce conflicting LW/SW feedbacks in the model. Furthermore, the optical property and cloud fraction feedbacks are also of opposite sign. The result is that the net cloud feedback is the (relatively small) product of conflicting ph ysical processes. Non-linearities in the feedbacks are found to be relative ly small for all but the surface albedo response and some cloud component c ontributions. The cloud impact on non-cloud feedbacks is also discussed: gr eatest impact is on the surface albedo, but impact on water vapour feedback is also significant. The analysis method here proves to be a powerful tool for detailing the contributions from different model processes (and partic ularly those of the clouds) to the final climate model sensitivity.