New estimates of the Earth radiation budget under cloud-free conditions and cloud radiative effects Free

In previous studies^{1, 2} we derived new estimates for the magnitude of the components of the global mean energy budget using to the extent possible the information contained in direct observations from surface and space. Here we establish complementary estimates for the global mean energy budget specifically under cloud-free conditions. The energy fluxes under cloud-free conditions at the Top of Atmosphere (TOA) can be determined with high accuracy from satellite measurements (CERES-EBAF). For the estimation of their counterparts at the Earth’s surface we follow the approach presented in our recent studies, based on an analysis of 39 state of the art global climate models from CMIP5 and their bias structure compared to a comprehensive set of high quality surface observations from the Baseline Surface Radiation Network (BSRN). Thereby we infer a best estimate of 249 Wm⁻² for the global mean clear-sky downward shortwave radiation at the surface, and a corresponding clear-sky surface shortwave absorption of 216 Wm⁻², considering a global mean surface albedo of 13 %. Combined with a best estimate for the global mean net shortwave influx at the TOA under cloud-free skies from CERES-EBAF of 287 Wm⁻², this leaves an amount of 71 Wm⁻² absorbed shortwave radiation in the cloud-free atmosphere. The 71 Wm⁻² coincide with our earlier estimate for this quantity in Wild et al. (2006)³ based on older models and fewer direct observations, suggesting that this estimate is fairly robust. For the clear-sky downward longwave radiation at the Earth surface we obtain a best estimate of 314 Wm⁻². A comparison of the clear-sky global energy balance diagram presented here with the corresponding all-sky diagram established in our previous studies enables a quantification of the global mean shortwave, longwave and net cloud-radiative effects at the TOA, within the atmosphere and at the surface, as well as an assessment of their representation in climate models.