The sensitivity of the global climate is essentially determined by the radiative damping of the global mean surface temperature anomaly through the outgoing radiation from the top of the atmosphere (TOA). Using the TOA fluxes of terrestrial and reflected solar radiation obtained from the Earth radiation budget experiment (ERBE), this study estimates the magnitude of the overall feedback, which modifies the radiative damping of the annual variation of the global mean surface temperature, and compare it with model simulations. Although the pattern of the annually varying anomaly is quite different from that of the global warming, the analysis conducted here may be used for assessing the systematic bias of the feedback that operates on the CO₂-induced warming of the surface temperature. In the absence of feedback effect, the outgoing terrestrial radiation at the TOA is approximately follows the Stefan-Boltzmann’s fourth power of the planetary emission temperature. However, it deviates significantly from the blackbody radiation due to various feedbacks involving water vapor and cloud cover. In addition, the reflected solar radiation is altered by the feedbacks involving sea ice, snow and cloud, thereby affecting the radiative damping of surface temperature. The analysis of ERBE reveals that the radiative damping is weakened by as much as 70% due to the overall effect of feedbacks, and is only 30% of what is expected for the blackbody with the planetary emission temperature. Similar feedback analysis is conducted for three general circulation models of the atmosphere, which was used for the study of cloud feedback in the preceding study. The sign and magnitude of the overall feedback in the three models are similar to those of the observed. However, when it is subdivided into solar and terrestrial components, they are quite different from the observation mainly due to the failure of the models to simulate individually the solar and terrestrial components of the cloud feedback. It is therefore desirable to make the similar comparison not only for the overall feedback but also for its individual components such as albedo- and cloud-feedbacks. Although the pattern of the annually-varying anomaly is quite different from that of global warming, the methodology of the comparative analysis presented here may be used for the identification of the systematic bias of the overall feedback in a model. A proposal is made for the estimation of the best guess value of climate sensitivity using the outputs from many climate models submitted to the Intergovernmental panel on Climate Change.