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We present an analysis of long‐term data collected at Utqiaġvik, Alaska, to explore the impacts of cloud processes on the probability of finding supercooled water given cloud temperature,P(L|T), in the topmost unseeded liquid‐bearing layers.P(L|T) has local minima at temperatures around −6°C and −15°C. Simulations using habit‐evolving ice microphysics models suggest that these minima are the result of efficient vapor growth by non‐isometric habits found at these temperatures. We conclude that habit‐dependent vapor growth of ice crystals modulates the macrophysical occurrence of supercooled water in polar clouds, the effect of which should be included in model parametrizations to avoid biases and/or error compensation. Our methodology is adaptable for spherical ice treatments implemented in models (example parametrizations provided), amenable for use with satellite measurements to give global impartial observational targets for model evaluations, and may allow empirical characterization of bulk responses to seeding and possibly secondary ice effects.

Different cloud types are generated over Antarctica as a result of various synoptic conditions. The cloud characteristics affect their impact on the surface energy budget. In this study, the dominating synoptic regimes over Antarctica (centered on the Ross Ice Shelf) are classified using self‐organizing map analysis, applied over long‐term ERA‐Interim 700‐hPa geopotential height data. The corresponding cloud properties over McMurdo Station (measured as part of the AWARE campaign) are described and discussed with respect to the synoptic settings and sea‐ice extent conditions. Cloud radiative forcing calculations are performed as well, and a particular focus is given to the net longwave “radiatively cloudy/opaque” (RO) regime. These results are compared with measurements performed at the West Antarctic Ice Sheet (WAIS) Divide to examine their variability and applicability to other Antarctic locations. It is found that the McMurdo cloud properties are strongly affected by the regional flow patterns and mesoscale cyclonic activity, which often moderates the larger‐scale synoptic regime influence. In contrast, the WAIS clouds are more susceptible to the varying synoptic settings. It is suggested that the positive trend in the (frequent) cyclonic activity near the Antarctic coastal regions makes ice clouds an increasingly prominent contributor for the RO cases, especially during freezeup and maximum sea‐ice conditions.

The surface downwelling longwave radiation component (LW↓) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW↓ signal measured at the surface. In this study, we examine the LW↓ model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 model relative to observations from the ARM West Antarctic Radiation Experiment (AWARE) campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud-layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW↓ during clear-sky conditions, high error variability (standard deviations > 20 W m−2) during any type of cloud occurrence, and negative LW↓ biases when LBCLs are observed (bias magnitudes >15 W m−2 in tenuous LBCL cases and >43 W m−2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW↓ biases in both models is the result of excessive ice formation and growth, which could stem from the model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.