The clear sky greenhouse effect (G) is defined as the trapping of infrared radiation by the atmosphere in the absence of clouds. The magnitude and variability of G is an important element in the understanding of Earth’s energy balance; yet the quantification of the governing factors of G is poor. The global mean G averaged over 2000 to 2016 is 130‐133 Wm−2 across datasets. We use satellite observations from CERES EBAF to calculate the monthly anomalies in the clear sky greenhouse effect (∆G). We quantify the contributions to ∆G due to changes in surface temperature, atmospheric temperature, and water vapor by performing partial radiation perturbation experiments using ERA‐Interim and GFDL AM4 climatological data. Water vapor in the middle troposphere and upper troposphere is found to contribute equally to the global mean and tropical mean ∆G. Holding relative humidity (RH) fixed in the radiative transfer calculations captures the temporal variability of global mean ∆G while variations in RH control the regional ∆G signal. The variations in RH are found to help generate the clear sky super greenhouse effect (SGE). 36% of Earth’s area exhibits SGE and this disproportionately contributes to 70% of the globally averaged magnitude of ∆G. In the global mean, G’s sensitivity to surface temperature is 3.1‐4.0 Wm−2K−1 and the clear sky longwave feedback parameter is 1.5‐2.0 Wm−2K−1. CERES observations lie at the more sensitive ends of these ranges and the spread arises from its cloud removal treatment, suggesting that it is difficult to constrain clear sky feedbacks