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Models assume that mixed‐phase clouds consist of uniformly mixed ice crystals and liquid cloud droplets when observations have shown that they consist of clusters, or "pockets," of ice crystals and liquid cloud droplets. We characterize the spatial distribution of cloud phase over the Arctic and the Southern Ocean using active satellite observations and determine the relative importance of collocated meteorological parameters and aerosols from reanalysis to predict how uniformly mixed mixed‐phase clouds are for the first time. We performed a multi‐linear regression fit to the data set to predict the spatial distribution of the ice and liquid pockets. Contrary to what models suggest, mixed‐phase clouds are rarely perfectly homogeneous. Our results suggest that high temperatures are associated with homogeneously mixed ice and liquid pockets. We also find that a high mixing ratio of black carbon is associated with heterogeneously mixed ice and liquid pockets. Plain Language Summary: The representation of clouds in numerical models remains one of the largest uncertainties in predicting our future climate. Clouds can consist solely of liquid droplets, ice crystals, or the coexistence of both hydrometeor types. The latter cloud type is referred to as mixed phase. Climate models assume that liquid droplets and ice crystals are uniformly mixed in space in mixed‐phase clouds, but observations show that mixed‐phase clouds are organized in separate pockets of clustered liquid droplets and ice crystals. This difference in representation has a large impact on the lifetime of clouds and on their role in climate change. Using satellite observations over the Arctic and the Southern Ocean, we quantify the spatial distribution of ice and liquid in clouds. We used a statistical method to determine the relationship between meteorology and aerosols and the spatial distribution of ice and liquid. Our results suggest that high temperatures are associated with homogeneously mixed mixed‐phase clouds and high concentrations of soot are associated with heterogeneously mixed mixed‐phase clouds. Furthermore, pockets of liquid within ice clouds are larger than pockets of ice within liquid clouds. These results will improve the representation of mixed‐phase clouds in large‐scale models. Key Points: Space‐based observations and reanalysis are considered to determine the factors that control how mixed mixed‐phase clouds areLiquid dominated clouds contain small and isolated ice pockets whereas ice dominated clouds contain large and isolated liquid pocketsTemperature and black carbon play an important role in controlling the cloud phase spatial distribution and increasing phase heterogeneity [ABSTRACT FROM AUTHOR]

Black carbon (BC) aerosol particles in the Arctic heat the atmosphere and snow/ice surfaces and may strengthen the snow-albedo feedback that amplifies Arctic warming. Model simulations of BC concentrations in the Arctic depend strongly on the representation of microphysical processes such as aging, activation, and wet removal. Most BC modeling studies have classified BC particles into hydrophobic BC, which cannot form cloud droplets, and hydrophilic BC, which can form cloud droplets, by assuming a globally constant critical supersaturation threshold value (Sthre), without considering its consistency with cloud maximum supersaturation (Smax). Here we show that it is essential to consider the consistency of Sthre with Smax in global model simulations to reduce uncertainties in near-surface ambientBCconcentrations in the Arctic. Previous studies often obtained good agreement between simulated and observed near-surface Arctic BC mass concentrations when a low Sthre (;0.1%) was assumed in their models. However, this Sthre may be too low (activation and wet removal of BCmay be underestimated) for the Arctic, because some recent observations and our model simulations suggest that Smax may actually be higher (;0.3%) there. We also demonstrate that spatially varying Sthre values and their consistency with Smax, which previous studies did not consider, must be represented in models for more accurate estimation of BC budget in the Arctic. Because both Smax and BC-aging speed depend on climatic conditions, our findings are an important step toward better simulations of BC impacts on past, present, and future Arctic climates. [ABSTRACT FROM AUTHOR]