We demonstrate that the relationship between the abundance of particulate surface area observed at sea-level and measurements of backscattered light by a ceilometer can be used to classify the mixing state of the atmospheric layer beneath the lowest observed cloud, where the relationship is defined by the Spearman Rank correlation. The accuracy of this correlation-based method was compared to two methods of detecting boundary layer decoupling based on radiosonde measurements. An optimized version of the new methodology correctly determined the mixing state of the below-cloud layer for 76 ± 4% of the radiosondes available for comparison. Further, it was more accurate than an alternative ground-based metric used to determine the below-cloud mixing state. For the majority of the time series in which the correlation analysis could be applied, the below-cloud boundary layer was well-mixed (54%), or else fog was present (27%), which indicated that aerosol particles observed at sea-level often have a direct pathway into low-cloud (81%). In the remaining analysis period, the near-surface atmospheric layer was stable and the atmospheric layer near the ocean surface was decoupled from the overlying cloud (19%). Forecasts from the Antarctic Mesoscale Prediction System also support our findings, showing that conditions that mix aerosol particles from the ocean surface to the lowest observed cloud occur 84% of the time over the open Southern Ocean. As a result, aerosol particles measured near sea-level are often tightly coupled to low-cloud formation over the Southern Ocean, highlighting the utility of shipborne aerosol observations in the region.

Modeling the shortwave radiation balance over the Southern Ocean region remains a challenge for Earth system models. To investigate whether this is related to the representation of aerosol-cloud interactions, we compared measurements of the total number concentration of sea spray generated particles within the Southern Ocean region to model predictions thereof. Measurements were conducted from a container laboratory aboard the R/V Tangaroa throughout an austral summer voyage to the Ross Sea. We used source-receptor modeling to calculate the sensitivity of our measurements to upwind surface fluxes. From this approach, we could constrain empirical parameterizations of sea spray surface flux based on surface wind speed and sea surface temperature. A newly tuned parameterization for the flux of sea spray particles based on the near-surface wind speed is presented. Comparisons to existing model parameterizations revealed that present model parameterizations led to over-estimations of sea spray concentrations. In contrast to previous studies, we found that including sea surface temperature as an explanatory variable did not substantially improve model-measurement agreement. To test whether or not the parameterization may be applicable globally, we conducted a similar regression analysis using a database of in situ whitecap measurements. We found that the key fitting parameter within this regression agreed well the parameterization of sea spray flux. Finally, we compared calculations from the best model of surface flux to boundary layer measurements collected onboard an aircraft throughout the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES), finding good agreement overall.