The accurate representation of cloud droplet number concentration (Nd) is crucial for predicting future climate. However, models often underestimate Nd over the Southern Ocean (SO), where natural sources dominate, and aerosols are composed primarily of marine biogenic sulfate and sea spray. This study uses a range of diverse datasets to evaluate and untangle biases in E3SMv2 simulated clouds, aerosols, and sulfur species. The default E3SMv2 underestimates Nd over SO by a factor of 2 when compared with observations in 3km-resolution simulations. Updating the dimethyl sulfide (DMS) emission and chemistry leads to a better agreement between the model and the observations in Nd and boundary layer aerosols, but low biases persist in the free tropospheric aerosol concentrations larger than 70 nm, possibly attributable to insufficient particle growth. Preliminary evaluation also reveals biases in simulated sulfur species, including overestimation in DMS at high latitudes, and in simulated sulfate mass concentration, highlighting the necessity for further efforts to improve the model treatment of relevant processes.

Recent studies reveal an anti-correlation between global cloud feedback (CF) and effective radiative forcing due to aerosol-cloud interaction (ERFaci) in climate models, but its physical plausibility remains uncertain. Here we investigate whether different turbulence representations, specifically through perturbing turbulence parameters, contribute to this relationship over the global ocean using an E3SMv2 perturbed parameter ensemble. The anti-correlation appears only in the tropical ascent regime. In the Northern Hemisphere midlatitude and high latitude regimes, there is no significant correlation, and in the tropical marine low cloud and Southern Ocean regimes, the correlation is positive. These opposite correlations are primarily driven by opposing CF responses to perturbed parameters. We find that the mean-state turbulent mixing strength affects both CF and ERFaci, enabling strong correlations in certain regimes. This study highlights the complex linkages between CF and ERFaci through turbulent processes across diverse cloud regimes.

Land-atmosphere interactions are central to the evolution of the atmospheric boundary layer and the subsequent formation of clouds and precipitation. Existing global climate models represent these connections with bulk approximations on coarse spatial scales, but observations suggest that small-scale variations in surface characteristics and co-located turbulent and momentum fluxes can significantly impact the atmosphere. Recent model development efforts have attempted to capture this phenomenon by coupling existing representations of subgrid-scale (SGS) heterogeneity between land and atmosphere models. Such approaches are in their infancy and it is not yet clear if they can produce a realistic atmospheric response to surface heterogeneity. Here, we implement a parameterization to capture the effects of SGS heterogeneity in the Community Earth System Model (CESM2), and compare single-column simulations against high-resolution Weather Research and Forecasting (WRF) large-eddy simulations (LESs), which we use as a proxy for observations. The CESM2 experiments increase the temperature and humidity variances in the lowest atmospheric levels, but the response is weaker than in WRF-LES. In part, this is attributed to an underestimate of surface heterogeneity in the land model due to a lack of SGS meteorology, a separation between deep and shallow convection schemes in the atmosphere, and a lack of explicitly represented mesoscale secondary circulations. These results highlight the complex processes involved in capturing the effects of SGS heterogeneity and suggest the need for parameterizations that communicate their influence not only at the surface but also vertically.

Sub-grid topographic heterogeneity has large impacts on surface energy balance and land-atmosphere interactions. However, the impacts of representing sub-grid topographic effects in land surface models (LSMs) on surface energy balance and boundary conditions remain unclear. This study analyzed and evaluated the impacts of sub-grid topographic representations on surface energy balance, turbulent heat flux and scalar (co-)variances in the Energy Exascale Earth System Model (E3SM) land model (ELM). Three sub-grid topographic representations in ELM were compared: (1) the default sub-grid structure (D), (2) the recently developed sub-grid topographic structure (T), and (3) high spatial resolution (1KM). Additionally, two different solar radiation schemes in ELM were compared: (1) the default plane-parallel radiative transfer scheme (PP) and (2) the parameterization scheme (TOP) that accounts for sub-grid topographic effects on solar radiation. A series of simulations with the three grid structures (D, T and 1KM) and two treatments of solar radiation (TOP and PP) were carried out in the Sierra Nevada, California. There are significant differences between TOP and PP in the 1-km simulated surface energy balance, but the differences in the mean values and standard deviations become small when aggregated to the grid-scale (i.e., 0.5°). The T configuration better mimics the 1KM simulations than the D configuration, and better captures the sub-grid topographic effects on surface energy balance as well as surface boundary conditions. These results underline the importance of representing sub-grid topographic heterogeneities in LSMs and motivate future research to understand the sub-grid topographic effects on land-atmosphere interactions over mountain areas.