Severe weather can occur when some combination of atmospheric ingredients are present. These ingredients are called “convective environments” and refer to quantities that measure, for example, atmospheric instability and wind shear. By combining these convective environments into so-called severe weather proxies, modelers can measure the favorability of occurrence of severe convective storms. Moreover, they can address a recurrent challenge in severe weather modeling: to find a way to robustly analyze phenomena (hail storms, tornadoes, straight-line winds) that are highly intermittent and not resolved in coarse numerical models. CMIP6 models, for example, cannot resolve directly these phenomena because of both temporal and spatial resolution limitations. Therefore, we computed the convective environments for a subset of CMIP6 models and scenarios, and evaluated how severe weather proxies are projected to change as a function of global temperature increase. The results show increases of 5%–20% per °C of global temperature change. However, favorable severe weather proxies do not necessarily mean severe weather events occur, and thus we expect the overall increase to severe weather occurrences to be smaller. This analysis suggests increasing global temperature will affect the occurrence of conditions favorable to severe weather.