When compared to baseline unrefined simulations (111km), the mean global climatologies produced by regionally-refined simulations for both CESM-MPAS and CESM-SE are similar, indicating that the technique possesses utility in improving resolvable scales locally while doing no harm to the global solution. We focus on simulated climatology of three CONUS extreme weather phenomena: tropical cyclones, northeastern U.S. snowstorms, and severe convective outbreaks, which are quantified using recently-developed objective detection techniques. Tropical cyclone structure and frequency improves with increased resolution and results imply that realistic patterns of CONUS landfalls can be captured with regional refinement. Individual northeastern U.S. snowstorms are also well-matched to historical observations, although subtle biases in near-surface temperature and precipitation phase highlight under-appreciated dynamical core sensitivities. Operational proxies used for severe weather forecasting (such as the Significant Tornado Parameter) show promise in detecting severe convective storm outbreaks in CESM2, although persistent large-scale biases in predicted column instability demonstrate that some large-scale errors in low-resolution CESM are not necessarily mitigated with finer grid spacing.