Influence of cloud feedback on annual variation of global mean surface temperature

The goal of this study is to estimate the cloud radiative feedback effect on the annual variation of the global mean surface temperature using radiative flux data from the Earth Radiation Budget Experiment. We found that the influence of the cloud feedback upon the change of the global mean surface temperature is quite small, though the increase of the temperature is as much as 3.3 K from January to July. On a global scale, we found no significant relationship between either solar reflectivity of clouds or effective cloud top height and the annual cycle of surface temperature. The same analysis was repeated using the output from three general circulation models, which explicitly predict microphysical properties of cloud cover. On a global scale, both solar cloud reflectivity and cloud top height increase significantly xvith the increase of surface temperature, in contrast to the observation. The comparative analysis conducted here could be used as an effective test for evaluating the cloud feedback process of a model.