Abstract

The largest source of uncertainty among climate models simulating the climate system response to increased atmospheric carbon dioxide concentrations is the cloud feedback, the amplification or dampening of the warming from the carbon dioxide forcing by clouds. Refining our knowledge of the cloud feedback is therefore essential to gaining a more precise understanding of how the climate system will adjust as anthropogenic emissions continue to raise carbon dioxide concentrations. Accordingly, this project’s objective is to analyze the strength of the cloud feedback using model output from the newest phase of the Coupled Model Intercomparison Project (CMIP), CMIP6. To achieve this goal, output is examined from two general circulation models, the IPSL-CM6A-LR and the BCC-CSM2-MR, for two CMIP6 experiments, an abrupt carbon dioxide quadrupling scenario, and a pre-industrial control scenario (for comparison). Figures are plotted and statistical calculations are performed using the computing program Python to analyze the model output. The analyzed output for each of the models show that when carbon dioxide concentrations are quadrupled, most areas of the globe undergo significant changes in the net cloud radiative effect (CRE), the difference in the global radiation flux balance between cloudy and clear conditions. The net CRE changes such that the cloud feedback is positive, meaning that clouds adjust in a way that amplifies the warming from the carbon dioxide forcing.