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Over the modern satellite era, substantial climatic changes have been observed in the Antarctic, including atmospheric and oceanic warming, ice sheet thinning and a general Antarctic-wide expansion of sea ice, followed by a more recent rapid loss. Although these changes, featuring strong zonal asymmetry, are partially influenced by increasing greenhouse gas emissions and stratospheric ozone depletion, tropical–polar teleconnections are believed to have a role through Rossby wave dynamics. In this Review, we synthesize understanding of tropical teleconnections to the Southern Hemisphere extratropics arising from the El Niño–Southern Oscillation, Interdecadal Pacific Oscillation and Atlantic Multidecadal Oscillation, focusing on the mechanisms and long-term climatic impacts. These teleconnections have contributed to observed Antarctic and Southern Ocean changes, including regional rapid surface warming, pre-2015 sea ice expansion and its sudden reduction thereafter, changes in ocean heat content and accelerated thinning of most of the Antarctic ice sheet. However, due to limited observations and inherent model biases, uncertainties remain in understanding and assessing the importance of these teleconnections versus those arising from greenhouse gases, ozone recovery and internal variability. Sustained pan-Antarctic efforts towards long-term observations, and more realistic dynamics and parameterizations in high-resolution climate models, offer opportunities to reduce these uncertainties.

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 (NCAR) Community Eart h System 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, intraday 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 subdecadal variability with a weak positive linear trend superimposed. The CESM2 simulates comparable subdecadal variability but with a strong negative linear trend superimposed. The CESM2's annual cycle is 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 the 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 semiannual oscillation of the circumpolar trough. The volatility, which is associated with smaller scale dynamics such as storms, is smaller in the CESM2 than observed.

Autumn sea ice trends in the western Ross Sea dominate increases in Antarctic sea ice and are outside the range simulated by climate models. Here we use a number of independent data sets to show that variability in western Ross Sea autumn ice conditions is largely driven by springtime zonal winds in the high latitude South Pacific, with a lead-time of 5 months. Enhanced zonal winds dynamically thin the ice, allowing an earlier melt out, enhanced solar absorption, and reduced ice cover the next autumn. This seasonal lag relationship has implications for sea ice prediction. Given a weakening trend in springtime zonal winds, this lagged relationship can also explain an important fraction of the observed sea ice increase. An analysis of climate models indicates that they simulate weaker relationships and wind trends than observed. This contributes to weak western Ross Sea ice trends in climate model simulations.Antarctic sea ice extent continues to increase, with autumn sea ice advances in the western Ross Sea particularly anomalous. Here, based on analysis of independent datasets, the authors show that springtime zonal winds in the high latitude South Pacific drive western Ross Sea autumn sea ice conditions.

Climate simulation uncertainties arise from internal variability, model structure, and external forcings. Model intercomparisons (such as the Coupled Model Intercomparison Project; CMIP) and single-model large ensembles have provided insight into uncertainty sources. Under the Community Earth System Model (CESM) project, large ensembles have been performed for CESM2 (a CMIP6-era model) and CESM1 (a CMIP5-era model). We refer to these as CESM2-LE and CESM1-LE. The external forcing used in these simulations has changed to be consistent with their CMIP generation. As a result, differences between CESM2-LE and CESM1-LE ensemble means arise from changes in both model structure and forcing. Here we present new ensemble simulations which allow us to separate the influences of these model structural and forcing differences. Our new CESM2 simulations are run with CMIP5 forcings equivalent to those used in the CESM1-LE. We find a strong influence of historical forcing uncertainty due to aerosol effects on simulated climate. For the historical period, forcing drives reduced global warming and ocean heat uptake in CESM2-LE relative to CESM1-LE that is counteracted by the influence of model structure. The influence of the model structure and forcing vary across the globe, and the Arctic exhibits a distinct signal that contrasts with the global mean. For the 21st century, the importance of scenario forcing differences (SSP3–7.0 for CESM2-LE and RCP8.5 for CESM1-LE) is evident. The new simulations presented here allow us to diagnose the influence of model structure on 21st century change, despite large scenario forcing differences, revealing that differences in the meridional distribution of warming are caused by model structure. Feedback analysis reveals that clouds and their impact on shortwave radiation explain many of these structural differences between CESM2 and CESM1. In the Arctic, albedo changes control transient climate evolution differences due to structural differences between CESM2 and CESM1. [ABSTRACT FROM AUTHOR]

. Climate simulation uncertainties arise from internal variability, model structure, and external forcings. Model intercomparisons (such as the Coupled Model Intercomparison Project; CMIP) and single-model large ensembles have provided insight on uncertainty sources. Under the Community Earth System Model (CESM) project, large ensembles have been performed for CESM2 (a CMIP6-era model) and CESM1 (a CMIP5-era model). We refer to these as CESM2-LE and CESM1-LE. The external forcing used in these simulations changed to be consistent with their CMIP generation. As a result, differences between CESM2-LE and CESM1-LE ensemble means arise from changes in both model structure and forcing. Here we present new ensemble simulations which allow us to separate the influences of these model structural and forcing differences. Our new CESM2 simulations are run with CMIP5 forcings equivalent to those used in the CESM1-LE. We find a strong influence of historical forcing uncertainty due to aerosol effects on simulated climate. For the historical period, forcing drives reduced global warming and ocean heat uptake in CESM2-LE relative to CESM1-LE that is counteracted by the influence of model structure. The influence of model structure and forcing vary across the globe and the Arctic exhibits a distinct signal that contrasts with the global mean. For the 21st century, the importance of scenario forcing differences (SSP3-7.0 for CESM2-LE and RCP8.5 for CESM1-LE) is evident. The new simulations presented here allow us to diagnose the influence of model structure on 21st century change despite large scenario forcing differences, revealing that differences in the meridional distribution of warming are caused by model structure. Feedback analysis reveals that clouds and their impact on shortwave radiation explain many of these structural differences between CESM2 and CESM1. In the Arctic, albedo changes control transient climate evolution differences due to structural differences between CESM2 and CESM1. [ABSTRACT FROM AUTHOR]