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We assess Antarctic sea ice climatology and variability in version 2 of the Community Earth System Model (CESM2), and compare it to that in the older CESM1 and (where appropriate) real-world observations. In CESM2, Antarctic sea ice is thinner and less extensive than in CESM1, though sea ice area is still approximately 1 million km2 greater in CESM2 than in present-day observations. Though there is less Antarctic sea ice in CESM2, the annual cycle of ice growth and melt is more vigorous in CESM2 than in CESM1. A new mushy-layer thermodynamics formulation implemented in the latest version of the Community Ice Code (CICE) in CESM2 accounts for both greater frazil ice forma- tion in coastal polynyas and more snow-to-ice conversion near the edge of the ice pack in the new model. Greater winter ice divergence in CESM2 (relative to CESM1) is due to stronger stationary wave activity and greater wind stress curl over the ice pack. Greater wind stress curl, in turn, drives more warm water upwelling under the ice pack, thinning it and decreasing its extent. Overall, differences between Antarctic sea ice in CESM2 and CESM1 arise due to both differences in their sea ice thermodynamics formulations, and differencesmore »in their coupled atmosphere-ocean states.« less

Abstract. In recent decades, Arctic sea ice has shifted toward ayounger, thinner, seasonal ice regime. Studying and understanding this“new” Arctic will be the focus of a year-long ship campaign beginning inautumn 2019. Lagrangian tracking of sea ice floes in the Community EarthSystem Model Large Ensemble (CESM-LE) during representative “perennial”and “seasonal” time periods allows for understanding of the conditionsthat a floe could experience throughout the calendar year. These modeltracks, put into context a single year of observations, provide guidance onhow observations can optimally shape model development, and how climatemodels could be used in future campaign planning. The modeled floe tracksshow a range of possible trajectories, though a Transpolar Drift trajectoryis most likely. There is also a small but emerging possibility of high-risktracks, including possible melt of the floe before the end of a calendaryear. We find that a Lagrangian approach is essential in order to correctlycompare the seasonal cycle of sea ice conditions between point-basedobservations and a model. Because of high variability in the melt season seaice conditions, we recommend in situ sampling over a large range of ice conditionsfor a more complete understanding of how ice type and surface conditionsaffect the observed processes. We find that sea ice predictability emergesrapidlymore »during the autumn freeze-up and anticipate that process-basedobservations during this period may help elucidate the processes leading tothis change in predictability.« less