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Author(s): Li, X; Cai, W; Meehl, GA; Chen, D; Yuan, X; Raphael, M; Holland, DM; Ding, Q; Fogt, RL; Markle, BR; Wang, G; Bromwich, DH; Turner, J; Xie, SP; Steig, EJ; Gille, ST; Xiao, C; Wu, B; Lazzara, MA; Chen, X; Stammerjohn, S; Holland, PR; Holland, MM; Cheng, X; Price, SF; Wang, Z; Bitz, CM; Shi, J; Gerber, EP; Liang, X; Goosse, H; Yoo, C; Ding, M; Geng, L; Xin, M; Li, C; Dou, T; Liu, C; Sun, W; Wang, X; Song, C | Abstract: 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 Nino–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.

Summertime barotropic high pressure in the Arctic and its induced warmer and wetter atmosphere over sea ice are suggested to be important contributors to September sea ice loss on interannual and interdecadal time scales in the past decades. Using ERA5 and other reanalysis data, we find that atmospheric warming and moistening in the Arctic, synchronized by high latitude atmospheric circulation variability, work in tandem to melt sea ice through increasing downwelling longwave radiation at the surface. To what extent this atmosphere-longwave radiation-sea ice relationship can be captured in CMIP5 and 6 remains unknown and thus addressing this question is the objective of this study. To achieve this goal, we construct a process-oriented metric emphasizing the statistical relationship between atmospheric temperature and humidity with sea ice, which can effectively rank and differentiate the performance of 30 CMIP5 climate models in reproducing the observed connection. Based on our evaluation, we suggest that most available models in CMIP5 and 6 have a limitation in reproducing the full strength of the observed atmosphere–sea ice connection. This limitation likely stems from a weak impact of downwelling longwave radiation in linking sea ice with circulation associated with the weak sensitivity of the temperature and humidity fields to circulation variability in the Arctic. Thus, further efforts should be devoted to understanding the sources of these models’ limitations and improve skill in simulating the effects of atmospheric circulation in coupling temperature, humidity, surface radiation and sea ice together during Arctic summer.

Arctic sea ice melting processes in summer due to internal atmospheric variability have recently received considerable attention. A regional barotropic atmospheric process over Greenland and the Arctic Ocean in summer (June–August), featuring either a year-to-year change or a low-frequency trend toward geopotential height rise, has been identified as an essential contributor to September sea ice loss, in both observations and the CESM1 Large Ensemble (CESM-LE) of simulations. This local melting is further found to be sensitive to remote sea surface temperature (SST) variability in the east-central tropical Pacific Ocean. Here, we utilize five available large “initial condition” Earth system model ensembles and 31 CMIP5 models’ preindustrial control simulations to show that the same atmospheric process, resembling the observed one and the one found in the CESM-LE, also dominates internal sea ice variability in summer on interannual to interdecadal time scales in preindustrial, historical, and future scenarios, regardless of the modeling environment. However, all models exhibit limitations in replicating the magnitude of the observed local atmosphere–sea ice coupling and its sensitivity to remote tropical SST variability in the past four decades. These biases call for caution in the interpretation of existing models’ simulations and fresh thinking about models’ credibility in simulating interactions of sea ice variability with the Arctic and global climate systems. Further efforts toward identifying the causes of these model limitations may provide implications for alleviating the biases and improving interannual- and decadal-time-scale sea ice prediction and future sea ice projection.

Over the past 40 years, the Arctic sea ice minimum in September has declined. The period between 2007 and 2012 showed accelerated melt contributed to the record minima of 2007 and 2012. Here, observational and model evidence shows that the changes in summer sea ice since the 2000s reflect a continuous anthropogenically forced melting masked by interdecadal variability of Arctic atmospheric circulation. This variation is partially driven by teleconnections originating from sea surface temperature (SST) changes in the east-central tropical Pacific via a Rossby wave train propagating into the Arctic [herein referred to as the Pacific–Arctic teleconnection (PARC)], which represents the leading internal mode connecting the pole to lower latitudes. This mode has contributed to accelerated warming and Arctic sea ice loss from 2007 to 2012, followed by slower declines in recent years, resulting in the appearance of a slowdown over the past 11 years. A pacemaker model simulation, in which we specify observed SST in the tropical eastern Pacific, demonstrates a physically plausible mechanism for the PARC mode. However, the model-based PARC mechanism is considerably weaker and only partially accounts for the observed acceleration of sea ice loss from 2007 to 2012. We also explore features of large-scale circulation patterns associated with extreme melting periods in a long (1800 yr) CESM preindustrial simulation. These results further support that remote SST forcing originating from the tropical Pacific can excite significant warm episodes in the Arctic. However, further research is needed to identify the reasons for model limitations in reproducing the observed PARC mode featuring a cold Pacific–warm Arctic connection.

The impact on seasonal polar predictability from improved tropical and midlatitude forecasts is explored using a perfect-model experiment and applying a nudging approach in a GCM. We run three sets of 7-month long forecasts: a standard free-running forecast and two nudged forecasts in which atmospheric winds, temperature, and specific humidity (U, V, T, Q) are nudged toward one of the forecast runs from the free ensemble. The two nudged forecasts apply the nudging over different domains: the tropics (30°S–30°N) and the tropics and midlatitudes (55°S–55°N). We find that the tropics have modest impact on forecast skill in the Arctic or Antarctica both for sea ice and the atmosphere that is mainly confined to the North Pacific and Bellingshausen–Amundsen–Ross Seas, whereas the midlatitudes greatly improve Arctic winter and Antarctic year-round forecast skill. Arctic summer forecast skill from May initialization is not strongly improved in the nudged forecasts relative to the free forecast and is thus mostly a “local” problem. In the atmosphere, forecast skill improvement from midlatitude nudging tends to be largest in the polar stratospheres and decreases toward the surface.

The relative contribution and physical drivers of internal variability in recent Arctic sea ice loss remain open questions, leaving up for debate whether global climate models used for climate projection lack sufficient sensitivity in the Arctic to climate forcing. Here, through analysis of large ensembles of fully coupled climate model simulations with historical radiative forcing, we present an important internal mechanism arising from low-frequency Arctic atmospheric variability in models that can cause substantial summer sea ice melting in addition to that due to anthropogenic forcing. This simulated internal variability shows a strong similarity to the observed Arctic atmospheric change in the past 37 years. Through a fingerprint pattern matching method, we estimate that this internal variability contributes to about 40–50% of observed multi-decadal decline in Arctic sea ice. Our study also suggests that global climate models may not actually underestimate sea ice sensitivities in the Arctic, but have trouble fully replicating an observed linkage between the Arctic and lower latitudes in recent decades. Further improvements in simulating the observed Arctic–global linkage are thus necessary before the Arctic’s sensitivity to global warming in models can be quantified with confidence. Internal low-frequency variability in the Arctic atmosphere can explain about half the summer sea ice decline over the past decades, according to an analysis of large ensembles of fully coupled climate model simulations.

The rapid Arctic sea ice retreat in the early 21st century is believed to be driven by several dynamic and thermodynamic feedbacks, such as ice-albedo feedback and water vapor feedback. However, the role of clouds in these feedbacks remains unclear since the causality between clouds and these processes is complex. Here, we use NASA CERES satellite products and NCAR CESM model simulations to suggest that summertime low clouds have played an important role in driving sea ice melt by amplifying the adiabatic warming induced by a stronger anticyclonic circulation aloft. The upper-level high pressure regulates low clouds through stronger downward motion and increasing lower troposphere relative humidity. The increased low clouds favor more sea ice melt via emitting stronger longwave radiation. Then decreased surface albedo triggers a positive ice-albedo feedback, which further enhances sea ice melt. Considering the importance of summertime low clouds, accurate simulation of this process is a prerequisite for climate models to produce reliable future projections of Arctic sea ice. Summertime low clouds in the Arctic play an important role in inducing sea ice melt as they amplify warming from high pressure systems aloft through radiative effects and feedbacks, according to analyses of observations and model simulations.

An ice-free Arctic summer is a landmark of global change and has the far-reaching climate, environmental, and economic impacts. However, the Coupled Model Intercomparison Project Phase 6 models’ projected occurrence remains notoriously uncertain. Finding emergent constraints to reduce the projection uncertainties has been a foremost challenge. To establish a physical basis for the constraints, we first demonstrate, with numerical experiments, that the observed trend of Arctic ice loss is primarily driven by the Arctic near-surface air temperature. Thus, two constraints are proposed: the Arctic sea ice sensitivity that measures Arctic sea ice response to the local warming, and the Arctic amplification sensitivity that assesses how well the model responds to anthropogenic forcing and allocates heat to the Arctic region. The two constraints are complementary and nearly scenario-independent. The model-projected first Arctic ice-free year significantly depends on the model’s two climate sensitivities. Thus, the first Arctic ice-free year can be predicted by the linear combination of the two Arctic sensitivity measures. Based on model-simulated sensitivity skills, 20 CMIP models are divided into two equal number groups. The ten realistic-sensitivity models project, with a likelihood of 80%, the ice-free Arctic will occur by additional 0.8 °C global warming from 2019 level or before 2040 under the SSP2-4.5 (medium emission) scenario. The ten realistic-sensitivity models’ spread is reduced by about 70% compared to the ten underestimate-sensitivity models’ large spread. The strategy for creating physics-based emergent constraints through numerical experiments may be instrumental for broad application to other fields for advancing robust projection and understanding uncertainty sources.

The Arctic has seen rapid sea-ice decline in the past three decades, whilst warming at about twice the global average rate. Yet the relationship between Arctic warming and sea-ice loss is not well understood. Here, we present evidence that trends in summertime atmospheric circulation may have contributed as much as 60% to the September sea-ice extent decline since 1979. A tendency towards a stronger anticyclonic circulation over Greenland and the Arctic Ocean with a barotropic structure in the troposphere increased the downwelling longwave radiation above the ice by warming and moistening the lower troposphere. Model experiments, with reanalysis data constraining atmospheric circulation, replicate the observed thermodynamic response and indicate that the near-surface changes are dominated by circulation changes rather than feedbacks from the changing sea-ice cover. Internal variability dominates the Arctic summer circulation trend and may be responsible for about 30–50% of the overall decline in September sea ice since 1979. The Arctic is warming and sea ice is declining, but how the two link is unclear. This study shows changes in summertime atmospheric circulation and internal variability may have caused up to 60% of September sea-ice decline since 1979.

Measurements of the 17Oexcess of H2O were obtained from ice cores in West and East Antarctica. Combined with previously published results from East Antarctica, the new data provide the most complete spatial and temporal view of Antarctic 17Oexcess to date. There is a steep spatial gradient of 17Oexcess in present-day precipitation across Antarctica, with higher values in marine-influenced regions and lower values in the East Antarctic interior. There is also a spatial pattern to the change in 17Oexcess between the Last Glacial Maximum (LGM) and Holocene periods. At coastal locations, there is no significant change in 17Oexcess. At both the West Antarctic Ice Sheet Divide site and at Vostok, East Antarctica, the LGM to Early Holocene change in 17Oexcess is about 20 per meg. Atmospheric general circulation model (GCM) experiments show that both the observed spatial gradient of 17Oexcess in modern precipitation, and the spatial pattern of LGM to Early Holocene change, can be explained by kinetic isotope effects during snow formation under supersaturated conditions, requiring a high sensitivity of supersaturation to temperature. The results suggest that fractionation during snow formation is the primary control on 17Oexcess in Antarctic precipitation. Variations in moisture source relative humidity play a negligible role in determining the glacial-interglacial 17Oexcess changes observed in Antarctic ice cores. Additional GCM experiments show that sea ice expansion increases the area over which supersaturating conditions occur, amplifying the effect of colder temperatures. Temperature and sea ice changes alone are sufficient to explain the observed 17Oexcess glacial-interglacial changes across Antarctica.

Significant summer warming over the eastern Antarctic Peninsula in the last 50 years has been attributed to a strengthening of the circumpolar westerlies, widely believed to be anthropogenic in origin. On the western side of the peninsula, significant warming has occurred mainly in austral winter and has been attributed to the reduction of sea ice. The authors show that austral fall is the only season in which spatially extensive warming has occurred on the Antarctic Peninsula. This is accompanied by a significant reduction of sea ice cover off the west coast. In winter and spring, warming is mainly observed on the west side of the peninsula. The most important large-scale forcing of the significant widespread warming trend in fall is the extratropical Rossby wave train associated with tropical Pacific sea surface temperature anomalies. Winter and spring warming on the western peninsula reflects the persistence of sea ice anomalies arising from the tropically forced atmospheric circulation changes in austral fall.

West Antarctic temperature and pressure observations begin onlyin 1957, and reliable satellite observations of Antarctic sea icedate to 1979. Comprehensive observations of glacier dynamicsin the most rapidly changing areas were initiated in the 1990s.Borehole temperature data from the WAIS, although confirmingthe recent rapid rise in temperature, do not resolve decadal-scalevariability in the past

As part of the United States' contribution to the International Trans-Antarctic Scientific Expedition (ITASE), a network of precisely dated and highly resolved ice cores was retrieved from West Antarctica. The ITASE dataset provides a unique record of spatial and temporal variations of stable water isotopes (d 18 O and dD) across West Antarctica. We demonstrate that, after accounting for water vapor diffusion, seasonal information can be suc- cessfully extracted from the ITASE cores. We use meteo- rological reanalysis, weather station, and sea ice data to assess the role of temperature, sea ice, and the state of the large-scale atmospheric circulation in controlling seasonal average water isotope variations in West Antarctica. The strongest relationships for all variables are found in the cores on and west of the West Antarctic Ice Sheet Divide and during austral fall. During this season positive isotope anomalies in the westernmost ITASE cores are strongly related to a positive pressure anomaly over West Antarctica, low sea ice concentrations in the Ross and Amundsen Seas, and above normal temperatures. Analyses suggest that this seasonally distinct climate signal is due to the pronounced meridional oriented circulation and its linkage to enhanced sea ice variations in the adjacent Southern Ocean during fall, both of which also influence local to regional temperatures.