Precipitation plays an important role in various processes over the Southern Ocean (SO), ranging from the hydrological cycle to cloud and aerosol processes. The main objective of this study is to characterize SO precipitation properties. We use data from the Southern Ocean Clouds Radiation Aerosol Transport Experimental Study (SOCRATES), and leverage observations from airborne radar, lidar, and in situ probes. For the cold-topped clouds (cloud-top-temperature < 0°C), the phase of precipitation with reflectivity > 0 dBZ is predominately ice, while reflectivity < -10 dBZ is predominately liquid. Liquid-phase precipitation properties are retrieved where radar and lidar are zenith-pointing. The power-law relationships between reflectivity (Z) and rain rate (R) are developed, and the derived Z-R relationships show vertical dependence and sensitivity to the intermediate drops (diameters between 10-40 μm). Using derived Z-R relationships, reflectivity-velocity (ZV) retrieval method, and a radar-lidar retrieval method, we derive rain rate and other precipitation properties. The retrieved rain rate from all three methods shows good agreement with in-situ aircraft estimates. Rain rate features the prevalence of light precipitation (<0.1 mm hr-1). We examine the vertical distribution of precipitation properties, and found that rain rate, precipitation number concentration, precipitation liquid water all decreases as one gets closer to the surface, while precipitation size and width increases. We also examine how cloud base rain rate (RCB) depends on cloud depth (H) and aerosol concentration (Na) for particles with diameter greater than 70nm, and we find a linear relationship between RCB and H3.6Na-1.

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.

Aircraft observations collected during the Southern Ocean Cloud Radiation Aerosol Transport Experimental Study (SOCRATES) in January-February of 2018 are used to evaluate cloud properties from three satellite-imager datasets: (i) the Moderate Resolution Imaging Spectroradiometer (MODIS) level 2 (collection 6.1) cloud product, (ii) the CERES-MODIS Edition 4 cloud product, and (iii) the NASA SatCORPS Himawari-8 cloud product. Overall the satellite retrievals compare well with the in situ observations, with little bias and modest to good correlation coefficients when considering all aircraft profiles for which there are coincident MODIS observations. The Himawari-8 product does, however, show a statistically significant mean bias of about 1.2 μm for effective radius (re) and 2.6 for optical depth (τ) when applied to a larger set of profiles with coincident Himawari-8 observations. The low overall mean-bias in the re retrievals is due in part to compensating errors between cases that are non- or lightly-precipitating, with cases that have heavier precipitation. re is slightly biased high (by about 0.5 to 1.0 μm) for non- and lightly-precipitating cases and biased low by about 3 to 4 μm for heavily-precipitating cases when precipitation exits near cloud top. The bias in non- and lightly-precipitating conditions is due to (at least in part) having assumed a drop size distribution in the retrieval that is too broad. These biases in the re ultimately propagate into the retrieved liquid water path and number concentration.

Cloud droplet number concentration (Nd) is a key microphysical property that is largely controlled by the balance between sources and sinks of aerosols that serve as cloud condensation nuclei (CCN). Despite being a key sink of CCN, the impact of coalescence scavenging on Southern Ocean (SO) cloud is poorly known. We apply a simple source-and-sink budget model based on parameterizations to austral summer aircraft observations to test model behavior and examine the relative influence of processes that determine Nd in SO stratocumulus clouds. The model predicts Nd with little bias and a correlation coefficient of ~0.7 compared with observations. Coalescence scavenging is found to be an important sink of CCN in both liquid and mixed-phase precipitating stratocumulus and reduces the predicted Nd by as much as 90% depending on the precipitation rate. The free tropospheric aerosol source controls Nd more strongly than the surface aerosol source during austral summer.