The complexity of the Earth’s atmospheric system makes quantifying radiative forcing difficult. Though limited by uncertainties, radiative forcing drives surface temperature change and is important for understanding Earth’s climate system. To better understand uncertainties in the current Community Atmosphere Model version 5 (CAM5), a research team led by U.S. Department of Energy scientists at Pacific Northwest National Laboratory developed and applied a sensitivity analysis framework to analyze the variance of the simulated radiative flux (FNET) at the top of atmosphere in the present-day climate. The team found that the global mean FNET variance is dominated by the cloud forcing variance with the assigned parameter ranges. They found that most selected cloud microphysics- and emission-related parameters have statistically significant impacts on the global mean FNET. Three cloud microphysics parameters, associated with the fall speed of cloud ice and snow, and the limiter of cloud droplet number, have a smaller impact than the auto-conversion size threshold for ice to snow. And overall, these four cloud microphysics-related parameters have a larger impact on high clouds than on low clouds. The team’s more comprehensive approach not only estimates the contribution of each parameter to model sensitivity but also provides its statistical significance. This is an important quantification, rarely obtained due to the limited sampled space of parameter uncertainty.