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  1. Abstract. In the high-latitude Arctic, wintertime sea ice and snowinsulate the relatively warmer ocean from the colder atmosphere. While theclimate warms, wintertime Arctic surface heat fluxes remain dominated by theinsulating effects of snow and sea ice covering the ocean until the sea icethins enough or sea ice concentrations decrease enough to allow for directocean–atmosphere heat fluxes. The Community Earth System Model version 1 LargeEnsemble (CESM1-LE) simulates increases in wintertime conductive heat fluxesin the ice-covered Arctic Ocean by ∼ 7–11 W m−2 bythe mid-21st century, thereby driving an increased warming of theatmosphere. These increased fluxes are due to both thinning sea ice anddecreasing snow on sea ice. The simulations analyzed here use a sub-grid-scaleice thickness distribution. Surface heat flux estimates calculated usinggrid-cell mean values of sea ice thicknesses underestimate mean heat fluxesby ∼16 %–35 % and overestimate changes in conductive heatfluxes by up to ∼36 % in the wintertime Arctic basin evenwhen sea ice concentrations remain above 95 %. These results highlight howwintertime conductive heat fluxes will increase in a warming world evenduring times when sea ice concentrations remain high and that snow and thedistribution of snow significantly impact large-scale calculations ofwintertime surface heat budgets in the Arctic.
  2. Under rising atmospheric greenhouse gas concentrations, the Arctic exhibits amplified warming relative to the globe. This Arctic amplification is a defining feature of global warming. However, the Arctic is also home to large internal variability, which can make the detection of a forced climate response difficult. Here we use results from seven model large ensembles, which have different rates of Arctic warming and sea ice loss, to assess the time of emergence of anthropogenically-forced Arctic amplification. We find that this time of emergence occurs at the turn of the century in all models, ranging across the models by a decade from 1994–2005. We also assess transient changes in this amplified signal across the 21st century and beyond. Over the 21st century, the projections indicate that the maximum Arctic warming will transition from fall to winter due to sea ice reductions that extend further into the fall. Additionally, the magnitude of the annual amplification signal declines over the 21st century associated in part with a weakening albedo feedback strength. In a simulation that extends to the 23rd century, we find that as sea ice cover is completely lost, there is little further reduction in the surface albedo and Arctic amplification saturatesmore »at a level that is reduced from its 21st century value.« less
  3. Abstract. We assess the influence of snow on sea ice in experimentsusing the Community Earth System Model version 2 for a preindustrial and a2xCO2 climate state. In the preindustrial climate, we find that increasingsimulated snow accumulation on sea ice results in thicker sea ice and acooler climate in both hemispheres. The sea ice mass budget response differsfundamentally between the two hemispheres. In the Arctic, increasing snowresults in a decrease in both congelation sea ice growth and surface sea icemelt due to the snow's impact on conductive heat transfer and albedo,respectively. These factors dominate in regions of perennial ice but have asmaller influence in seasonal ice areas. Overall, the mass budget changeslead to a reduced amplitude in the annual cycle of ice thickness. In theAntarctic, with increasing snow, ice growth increases due to snow–iceformation and is balanced by larger basal ice melt, which primarily occursin regions of seasonal ice. In a warmer 2xCO2 climate, the Arctic sea icesensitivity to snow depth is small and reduced relative to that of thepreindustrial climate. In contrast, in the Antarctic, the sensitivity tosnow on sea ice in the 2xCO2 climate is qualitatively similar to thesensitivity in the preindustrial climate. These results underscore theimportance of accuratelymore »representing snow accumulation on sea ice incoupled Earth system models due to its impact on a number of competingprocesses and feedbacks that affect the melt and growth of sea ice.« less
  4. Understanding the variability of Antarctic sea ice is an ongoing challenge given the limitations of observed data. Coupled climate model simulations present the opportunity to examine this variability in Antarctic sea ice. Here, the daily sea ice extent simulated by the newly-released National Center for Atmospheric Research Community Earth Sys-tem Model Version 2 (CESM2) for the historical period (1979–2014), is compared to the satellite-observed daily sea ice extent for the same period. The comparisons are made using a newly-developed suite of statistical metrics that estimates the variability of the sea ice extent on timescales ranging from the long-term decadal to the short term, intra-day scales. Assessed are the annual cycle, trend, day-to-day change, and the volatility, a new statistic that estimates the variability at the daily scale. Results show that the trend in observed daily sea ice is dominated by sub-decadal variability with a weak pos-itive linear trend superimposed. The CESM2 simulates comparable sub-decadal variability but with a strong negative linear trend superimposed. The CESM2’s annual cycleis similar in amplitude to the observed, key differences being the timing of ice advance and retreat. The sea ice begins its advance later, reaches its maximum later and begins retreat later in themore »CESM2. This is confirmed by the day-to-day change. Apparent in all of the sea ice regions, this behavior suggests the influence of the semi-annual oscillation of the circumpolar trough. The volatility, which is associated with smaller scale dynamics such as storms, is smaller in the CESM2 than observed.« less
  5. 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
  6. Abstract

    Robust and nonrobust aspects of Atlantic meridional overturning circulation (AMOC) variability and mechanisms are analyzed in several 600-yr simulations with the Community Earth System Model. The simulations consist of a set of cases where a few loosely constrained ocean model parameter values are changed, a pair of cases where round-off level perturbations are applied to the initial atmospheric temperature field, and a millennium-scale integration. The time scales of variability differ among the cases with the dominant periods ranging from decadal to centennial. These dominant periods are not stationary in time, indicating that a robust characterization of AMOC temporal variability requires long, multimillennium-scale simulations. A robust aspect is that positive anomalies of the Labrador Sea (LS) upper-ocean density and boundary layer depth and the positive phase of the North Atlantic Oscillation lead AMOC strengthening by 2–3 years. Respective contributions of temperature and salinity to these density anomalies vary across the simulations, but in a majority of the cases temperature contributions dominate. Following an AMOC intensification, all cases show that advection of warm and salty waters into the LS region results in near-neutral density anomalies. Analysis of the LS heat budget indicates that temperature acts to increase density in all casesmore »prior to an AMOC intensification, primarily due to losses by sensible and latent heat fluxes. The accompanying salt budget analysis reveals that the salt contribution to density anomalies varies across the cases, taking both positive and negative values.

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