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There is low confidence in projections of Antarctic sea ice area (SIA), due to deficiencies in climate model sea ice processes. Ensemble regression techniques can help to reduce this uncertainty. We investigate relationships between SIA climatology and 21st century change in the Coupled Model Intercomparison Project, phase 6 (CMIP6) multi‐model ensemble. In summer, under a strong forcing scenario, each model loses the majority of its sea ice. Therefore, models with greater historical SIA exhibit greater reductions, so the observed climatology of SIA strongly constrains projections. Ensemble spread in historical summer SIA is smaller than in CMIP phase 5 (CMIP5), and CMIP6 gives a more robust constraint on future SIA. In winter, by 2100 under a strong forcing scenario, 40% of SIA disappears on average, and ensemble spread in historical mean SIA explains approximately half the spread in projected change. A greater winter ice loss in CMIP6 than CMIP5 is explained by the higher climate sensitivities of some CMIP6 models. Plain Language Summary: Antarctic sea ice area is important for ecosystems, human activity, and for the dynamics of the atmosphere and ocean. However, major climate change assessments such as the Intergovernmental Panel on Climate Change Sixth Assessment Report have placed little confidence in projections of Antarctic sea ice area. This is because climate models struggle to simulate many aspects of sea ice area as observed by satellites. However, not all models should be treated equally. Models with relatively more sea ice area in the recent past project greater losses in the future, especially in summer. This suggests that models with historical sea ice area closest to what we have observed may be more reliable in their future simulations. We use this information in a simple statistical model to show that, firstly, the newest climate models largely show near‐total sea ice loss in summer by the end of the 21st century, which was not universally true for older climate models. Secondly, newer climate models lose more winter sea ice than their predecessors in the same time period, which is related to the known greater global warming response to given greenhouse gas concentrations in the newer models. Key Points: We compare Coupled Model Intercomparison Project (CMIP), phase 5 and the CMIP, phase 6 (CMIP6) projections of Antarctic sea ice loss, assessing drivers of uncertainty and the robustness of projectionsUnder strong forcing, CMIP6 models lose most Antarctic summer sea ice by 2100, so projections are constrained by historical climatologyIncreased winter sea ice loss in CMIP6 is related to increased equilibrium climate sensitivity [ABSTRACT FROM AUTHOR]

One of the major globally relevant systematic biases in previous generations of climate models has been an equatorward bias in the latitude of the Southern Hemisphere (SH) mid‐latitude tropospheric eddy driven westerly jet. The far‐reaching implications of this for Southern Ocean heat and carbon uptake and Antarctic land and sea ice are key reasons why addressing this bias is a high priority. It is therefore of primary importance to evaluate the representation of the SH westerly jet in the latest generation of global climate and earth system models that comprise the Coupled Model Intercomparison Project Phase 6 (CMIP6). In this paper we assess the representation of major indices of SH extratropical atmospheric circulation in CMIP6 by comparison against both observations and the previous generation of CMIP5 models. Indices assessed are the latitude and speed of the westerly jet, variability of the Southern Annular Mode (SAM), and representation of the Amundsen Sea Low (ASL). These are calculated from the historical forcing simulations of both CMIP5 and CMIP6 for time periods matching available observational and reanalysis data sets. From the 39 CMIP6 models available at the time of writing there is an overall reduction in the equatorward bias of the annual mean westerly jet from 1.9° in CMIP5 to 0.4° in CMIP6 and from a seasonal perspective the reduction is clearest in austral spring and summer. This is accompanied by a halving of the bias of SAM decorrelation timescales compared to CMIP5. However, no such overall improvements are evident for the ASL. Plain Language Summary: Computer models that simulate the position, strength, and spatio‐temporal behavior of winds in the Southern Hemisphere around the continent of Antarctica often show typical errors when compared to reality. This can impact answers to very relevant questions, such as how much heat and carbon are taken up by the ocean or how the sea ice cover will evolve in the future. Here we document how the newly available next generation of global climate models that form the basis for the next Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) performs with respect to observed Southern Hemisphere winds. We also analyze potential improvements compared to the previous generation of computer models. Overall, some important differences to observations (biases) are much smaller than in the previous models (by up to 50%). Other diagnostics are, however, virtually unchanged, which indicates that the improvements are rather limited between model generations. However, our study could help to identify possible reasons for the remaining biases and to further reduce errors in upcoming models. Key Points: Representation of Southern Hemisphere mid‐latitude tropospheric westerlies is improved in the Coupled Model Intercomparison Project Phase 6Key improvements are a reduced equatorward bias in jet latitude and more realistic timescales of variabilityThere is no clear improvement in the representation of the Amundsen Sea Low [ABSTRACT FROM AUTHOR]

Polar lows are intense, small-scale cyclones in the high latitudes. Typically, polar lows are initiated through baroclinic processes, but they sometimes evolve into a post-baroclinic mature stage where air-sea interaction becomes more important. In this stage some polar lows have developed hurricane-like cloud structures, and idealized axisymmetric hurricane models have indicated that air-sea interaction-fuelled pressure drops of up to 50 hPa are theoretically possible in polar environments. Here we study a polar low that formed in an extreme marine cold air outbreak over the Barents Sea and which had cloud structures with similarities to hurricanes. Using a high-resolution weather model, we artificially modified the sea-surface temperatures ( SSTs) to assess if the polar low was close to developing into a true hurricane-like system, with air-sea interaction processes leading to intensification in the post-baroclinic, mature phase of its life cycle. The polar low simulations with SSTs augmented by 2-6 K produced more intense mature phases than the control experiment (with unmodified SSTs). The intensity of the polar low in the last of these, which it must be pointed out was unrealistic with an SST increase of 6 K, surpassed the intensity in the earlier baroclinic phase. The experiment where the SSTs were reduced by 2 K did not produce a much weaker polar low than the control run. Broadly speaking, our experiments suggest that in this case large and unrealistic SST increases would be needed for apparently hurricane-like polar lows to exhibit true hurricane-like behaviour, but nevertheless air-sea interaction did drive a more intense and prolonged mature phase. [ABSTRACT FROM AUTHOR]

ABSTRACT Climate model results suggest that future climate change in Antarctica will be accompanied by continued strengthening and poleward contraction of the Southern Ocean westerly wind belt. Paleoclimate records suggest past changes in the westerly winds can be abrupt and that healing of the Antarctic ozone hole could lead to poleward contraction of the westerlies and increased meridional atmospheric transport of warm air regionally into Antarctica. An abrupt shift to more meridional circulation could lead to notable changes in moisture availability for extra-Antarctic regions, increased Antarctic ice sheet disintegration and more rapid sea-level rise. [ABSTRACT FROM AUTHOR]

On the basis of ERA40 and NCEP/NCAR Reanalysis (NNR) and simulations from CCCma, CCSM, CSIRO, HadCM3, MIROC-MEDRES and GFDL, which support the Intergovernmental Panel on Climate Change (IPCC) 4th Assessment Report (AR4), we demonstrated that the amplitude of the annual and the semi-annual harmonics delivered by the ERA40 and NNR is dominated by distinct seasonal variability. The maximum first harmonic amplitude of near surface temperature 2-metre air temperature (t2m) according the NNR is located over the Plateau of East Antarctica, whereas analyses for ERA40 show maximum amplitude over the west Antarctic ice sheet. The spatial pattern of the first harmonic of t2m in NNR more closely corresponds to station observations, suggesting that the seasonal cycle of t2m over Antarctica may be biased in ERA-40. A comparison between the global climate models (GCMs) and NNR demonstrates that the models satisfactorily simulate the amplitude of the first and second harmonics; however, the modelling results differ among themselves in terms of the amplitude values. Larger seasonal variability is identified for CCCma, HadCM3 and MIROC-MEDRES with values as high as 20 °C over the Antarctic plateau. We have further identified that the CSIRO GCM does not reproduce the seasonal amplitude of t2m as compared to other models, which is primarily due to its overestimation of the cloud cover and weak seasonal changes of precipitation. Calculations of the harmonic analysis based upon greenhouse warming (GW) conditions reveal that there is no substantial seasonal difference between the amplitude of the first harmonic as projected by GW and present day (PD) simulations over the Antarctic continent. Over the polar ocean, however, the amplitude of the first harmonic is reduced in all climate models under future conditions. In order to narrow down the uncertainties on future climate projections, analyses of the cloud forcing which include the short- and long-wave radiation and the surface mass balance (SMB) may provide substantial information on the cause of the discrepancies as simulated by climate models over the Antarctic region. Copyright © 2010 Royal Meteorological Society [ABSTRACT FROM AUTHOR]