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Abstract The accurate representation of cloud droplet number concentration (N_d) is crucial for predicting future climate. However, models often underestimate N_dover 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 data sets to evaluate and untangle biases in Energy Exascale Earth System Model version 2 (E3SMv2) simulated clouds, aerosols, and sulfur species. The default E3SMv2 underestimates N_dover SO by a factor of 2 when compared with observations in 3 km‐resolution simulations. Updating the dimethyl sulfide (DMS) emission and chemistry leads to a better agreement between the model and the observations in N_dand boundary layer aerosols, but low biases persist in the free tropospheric aerosol concentrations larger than 70 nm, possibly attributable to insufficient particle growth. Furthermore, updates to DMS emissions and chemistry resulted in reduced vertical DMS concentrations and improved the overall agreement between simulated and observed DMS vertical profiles. Preliminary evaluation also reveals remaining 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.