This study uses cloud and radiative properties collected from in situ and remote sensing instruments during two coordinated campaigns over the Southern Ocean between Tasmania and Antarctica in January-February 2018 to evaluate the simulations of clouds and precipitation in nudged-meteorology simulations with the CAM6 and AM4 global climate models sampled at the times and locations of the observations. Fifteen SOCRATES research flights sampled cloud water content, cloud droplet number concentration, and particle size distributions in mixed-phase boundary layer clouds at temperatures down to −25°C. The 6-week CAPRICORN2 research cruise encountered all cloud regimes across the region. Data from vertically pointing 94 GHz radars deployed was compared with radar simulator output from both models. Satellite data were compared with simulated top-of-atmosphere (TOA) radiative fluxes. Both models simulate observed cloud properties fairly well within the variability of observations. Cloud base and top in both models are generally biased low. CAM6 overestimates cloud occurrence and optical thickness while cloud droplet number concentrations are biased low, leading to excessive TOA reflected shortwave radiation. In general, low clouds in CAM6 precipitate at the same frequency but are more homogeneous compared to observations. Deep clouds are better simulated but produce snow too frequently. AM4 underestimates cloud occurrence but overestimates cloud optical thickness even more than CAM6, causing excessive outgoing longwave radiation fluxes but comparable reflected shortwave radiation. AM4 cloud droplet number concentrations match observations better than CAM6. Precipitating low and deep clouds in AM4 have too little snow. Further investigation of these microphysical biases is needed for both models.

Marine boundary layer clouds over the colder regions of the ocean often organize into closed or open mesoscale cellular convection (MCC) with cell sizes between 10 and 100 km, modulating cloud water path (CWP), precipitation, and albedo (Agee et al., 1973). MCC is associated with significant mesoscale variations of moisture (∼10% relative humidity perturbation), temperature, and winds (Rothermel & Agee, 1980). MCClike patterns can be simulated in large-eddy simulations, weather, and climate models with horizontal grid resolutions of O (10 km) or less (e.g., Boutle & Abel, 2012). To evaluate their skill requires good documentation and understanding of MCC cloud morphology and scale, of co-variability between observable quantities within closed and open cells, and of the sensitivity of closed and open MCC to potential environmental controlling factors across different boundary-layer cloud regions.There is a 50-year history of MCC observations from in situ and satellite measurements that has advanced our understanding and provided local data that has been used for model comparisons. MCC was first observed by the first weather satellites in the early 1960s (Agee, 1984). MCC covers extensive regions over the eastern subtropical oceans (Muhlbauer et al., 2014;Wood & Hartmann, 2006), with closed cells forming near the coast and open cells occurring toward the warm oceans (Atkinson & Zhang, 1996;Muhlbauer et al., 2014). Closed and open cells can be considered as different stages of the stratocumulus to cumulus transition (Wood, 2012), which is often associated with the advection of clouds over a warmer ocean surface

Mesoscale organization of marine stratocumulus with cell sizes between ∼10 and ∼100 km, manifesting as mesoscale cellular convection (MCC, Agee et al., 1973), is ubiquitous and important in modulating cloud water, precipitation (e.g.,