The typical coarse resolution of Earth system models (ESMs) ($\sim$100 km) is insufficient to represent atmospheric features critical for aerosols and aerosol-cloud interactions (ACI), contributing to uncertainties in climate predictions. Significant efforts have been made to develop next-generation ESMs for global kilometer-scale resolutions. However, the behavior of aerosol and ACI parameterizations at kilometer scales within a global ESM framework is unclear, and model evaluation at such high resolutions is computationally infeasible. To address this challenge, aerosol and ACI in the Energy Exascale Earth System Model (E3SM) are evaluated at a convection-permitting 3.25 km resolution using the regionally refined mesh (RRM) capability. Kilometer-scale E3SM simulations are performed in four geographical regions with distinct aerosol and cloud conditions. These kilometer-scale simulations are compared with coarse-resolution E3SM simulations and are evaluated against ground-based, aircraft, and satellite measurements. Results show that increasing model resolution moderately improves the multivariable relationships related to ACI, such as the cloud condensation nuclei number versus cloud droplet number (N$\mathrm{_d}$), and N$\mathrm{_d}$ versus the liquid water path. However, its impact on accurately predicting aerosol properties varies by region. Overall, the differences between E3SM simulations at different resolutions are smaller than the differences between model simulations and observations. These results suggest that increasing resolution is insufficient to improve the simulation of aerosol and ACI with existing process representations. Improved process representations are required to achieve more accurate simulations of aerosol and ACI at global kilometer scales.

To understand the future summer precipitation changes over the Great Lakes Region (GLR), we perform an ensemble of regional climate simulations through the Pseudo-Global Warming (PGW) approach. We found that different types of convective precipitation respond to the PGW signal differently. Isolated deep convection (IDC), which is usually concentrated in the southern domain, shows an increase in precipitation to the north of the GLR. Mesoscale convective systems (MCSs), which are usually concentrated upstream of the GLR, shows a shift to the downstream region with increased precipitation. Thermodynamic variables such as convective available potential energy (CAPE) and convective inhibition energy (CIN) are found to be increased in almost the entire studied domain, providing a potential environment more (less) favorable for stronger (weaker) convection systems. Meanwhile, changes in lifting condensation level (LCL) and level of free convection (LFC) show a strong correlation with variations in convective precipitation, underscoring the significance of these thermodynamic factors in controlling precipitation over the domain. Results show that decreased LCL and LCF over places where convective precipitation is increased, is mainly contributed by the atmospheric moisture increase. In response to the prescribed warming perturbation, MCSs show more frequent occurrences downstream, while localized IDCs show more intense rain rate, longer duration, and larger rainfall area.

In this paper, we introduce a testbed for evaluating and comparing climate modeling systems at cloud resolving scales using hindcasts of the June 2012 North American derecho. The testbed is applied to two models: the regionally-refined Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) at horizontal resolutions ranging from 6.5 to 1.625 km and the Weather Research and Forecasting (WRF) model with 4 km grid spacing. We find the simulation results to be highly sensitive to the initial conditions, initialization time, and model configurations, with initial conditions from the Rapid Refresh (RAP) producing the best simulation. Significant improvement is identified in the SCREAM simulations as horizontal grid spacing is refined. While a propagation delay of approximately 2 hours is found in both models, SCREAM at 1.625 km simulates the observed bow echo structure of the derecho well and predicts strong surface gusts that exceed 30 m/s. In comparison, WRF hardly produces surface wind over 25 m/s, and the derecho wind gust in WRF is 42-46% lower than in SCREAM. Moreover, WRF has a lower bias in simulating cold clouds but overestimates the precipitation intensity. Both models well reproduce the observed outgoing longwave radiation spatial patterns (Pearson correlation > 0.88) while they simulate larger areas of composite radar reflectivity > 40 dBZ by up to 4 times and underestimate the precipitating area by ~ 70\% in WRF and 47\% in SCREAM compared to observations.