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The Arctic is undergoing a pronounced and rapid transformation in response to changing greenhouse gasses, including reduction in sea ice extent and thickness. There are also projected increases in near‐surface Arctic wind. This study addresses how the winds trends may be driven by changing surface roughness and/or stability in different Arctic regions and seasons, something that has not yet been thoroughly investigated. We analyze 50 experiments from the Community Earth System Model Version 2 (CESM2) Large Ensemble and five experiments using CESM2 with an artificially decreased sea ice roughness to match that of the open ocean. We find that with a smoother surface there are higher mean wind speeds and slower mean ice speeds in the autumn, winter, and spring. The artificially reduced surface roughness also strongly impacts the wind speed trends in autumn and winter, and we find that atmospheric stability changes are also important contributors to driving wind trends in both experiments. In contrast to the clear impacts on winds, the sea ice mean state and trends are statistically indistinguishable, suggesting that near‐surface winds are not major drivers of Arctic sea ice loss. Two major results of this work are: (a) the near‐surface wind trends are driven by changes in both surface roughness and near‐surface atmospheric stability that are themselves changing from sea ice loss, and (b) the sea ice mean state and trends are driven by the overall warming trend due to increasing greenhouse gas emissions and not significantly impacted by coupled feedbacks with the surface winds.

 

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 differences in their coupled atmosphere-ocean states. 

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 emergesrapidly during the autumn freeze-up and anticipate that process-basedobservations during this period may help elucidate the processes leading tothis change in predictability. 

The sea ice component of the Community Earth System Model version 2 (CESM2) contains new “mushy‐layer” physics that simulates prognostic salinity in the sea ice, with consequent modifications to sea ice thermodynamics and the treatment of melt ponds. The changes to the sea ice model and their influence on coupled model simulations are described here. Two simulations were performed to assess the changes in the vertical thermodynamics formulation with prognostic salinity compared to a constant salinity profile. Inclusion of the mushy layer thermodynamics of Turner et al. (2013,https://doi.org/10.1002/jgrc.20171) in a fully coupled Earth system model produces thicker and more extensive sea ice in the Arctic, with relatively unchanged sea ice in the Antarctic compared to simulations using a constant salinity profile. While this is consistent with the findings of uncoupled ice‐ocean model studies, the role of the frazil and congelation growth is more important in fully coupled simulations. Melt pond drainage is also an important contribution to simulated ice thickness differences as also found in the uncoupled simulations of Turner and Hunke (2015;https://doi.org/10.1002/2014JC010358). However, it is an interaction of the ponds and the snow fraction that impacts the surface albedo and hence the top melt. The changes in the thermodynamics and resulting ice state modify the ice‐ocean‐atmosphere fluxes with impacts on the atmosphere and ocean states, particularly temperature.

 

Arctic and Antarctic sea ice has undergone significant and rapid change with the changing climate. Here, we present preindustrial and historical results from the newly released Community Earth System Model Version 2 (CESM2) to assess the Arctic and Antarctic sea ice. Two configurations of the CESM2 are available that differ only in their atmospheric model top and the inclusion of comprehensive atmospheric chemistry, including prognostic aerosols. The CESM2 configuration with comprehensive atmospheric chemistry has significantly thicker Arctic sea ice year‐round and better captures decreasing trends in sea ice extent and volume over the satellite period. In the Antarctic, both CESM configurations have similar mean state ice extent and volume, but the ice extent trends are opposite to satellite observations. We find that differences in the Arctic sea ice between CESM2 configurations are the result of differences in liquid clouds. Over the Arctic, the CESM2 configuration without prognostic aerosol formation has fewer aerosols to form cloud condensation nuclei, leading to thinner liquid clouds. As a result, the sea ice receives much more shortwave radiation early in the melt season, driving a stronger ice albedo feedback and leading to additional sea ice loss and significantly thinner ice year‐round. The aerosols necessary for the Arctic liquid cloud formation are produced from different precursor emissions and transported to the Arctic. Thus, the main reason sea ice differs in the Arctic is the transport of cloud‐impacting aerosols into the region, while the Antarctic remains relatively pristine from extrapolar aerosol transport.

 

Observations show that increased Arctic cloud cover in the spring is linked with sea ice decline. As the atmosphere and sea ice can influence each other, which one plays the leading role in spring remains unclear. Here we demonstrate, through observational data diagnosis and numerical modeling, that there is active coupling between the atmosphere and sea ice in early spring. Sea ice melting and thus the presence of more open water lead to stronger evaporation and promote cloud formation that increases downward longwave flux, leading to even more ice melt. Spring clouds are a driving force in the disappearance of sea ice and displacing the mechanism of atmosphere‐sea ice coupling from April to June. These results suggest the need to accurately model interactions of Arctic clouds and radiation in Earth System Models in order to improve projections of the future of the Arctic.