The Southern Hemisphere (SH) mid-latitude westerly winds play a central role in the global climate system via Southern Ocean upwelling 1 , carbon exchange with the deep ocean 2 , Agulhas Leakage 3 , and possibly Antarctic ice sheet stability 4. Meridional shifts of the SH westerlies have been hypothesized in response to abrupt North Atlantic Dansgaard-Oeschger (DO) climatic events of the last ice age 5,6 , in parallel with the well-documented shifts of the intertropical convergence zone (ITCZ) 7. Shifting moisture pathways to West Antarctica 8 are consistent with this view, but may represent a Pacific teleconnection pattern 9. The full SH atmospheric-circulation response to the DO cycle and its impact on Antarctic temperature remain unclear 10. Here we use five volcanically-synchronized ice cores to show that the Antarctic temperature response to the DO cycle can be understood as the superposition of two modes: a spatially homogeneous oceanic "bipolar seesaw" mode that lags Northern Hemisphere (NH) climate by about 200 years, and a spatially heterogeneous atmospheric mode that is synchronous with NH abrupt events. Temperature anomalies of the atmospheric mode are similar to those associated with present-day Southern Annular Mode (SAM) variability, rather than the Pacific South America (PSA) pattern. Moreover, deuterium excess records suggest a zonally coherent migration of the SH westerlies over all ocean basins in phase with NH climate. Our work provides a simple conceptual framework for understanding the circum-Antarctic temperature response to abrupt NH climate change. We provide observational evidence for abrupt shifts in the SH westerlies, which has previouslydocumented 1-3 ramifications for global ocean circulation and atmospheric CO 2. These coupled changes highlight the necessity of a global, rather than a purely North Atlantic, perspective on the DO cycle. During the glacial DO cycle, abrupt variations in northward heat transport by the Atlantic Meridional Overturning Circulation (AMOC) affect Greenland and Antarctic temperature oppositely (Fig. 1), via an oceanic teleconnection called the bipolar seesaw 6,11. Antarctica warms during Greenland cold phases (stadials), and cools during Greenland warmth (interstadials), with the gradual nature of Antarctic climate change reflecting buffering by a large heat reservoir 11-likely the global ocean interior 6. The DO cycle affects atmospheric circulation also; the ITCZ shifts southwards during stadials, and northwards during interstadials 7. General Circulation Model (GCM) simulations suggest parallel shifts of the SH westerlies 5,6,12 , but the available observational evidence (a deuterium excess record from West Antarctica 8) cannot distinguish between such shifts and Pacific-only teleconnections 9. Furthermore, the impact of the atmospheric circulation changes on Antarctic climate remains unknown, and models are inconclusive on this question 10,13. We use water stable isotope ratios, a proxy for site temperature 14 , from five Antarctic ice cores: WAIS (West ...

The decline in Barents Sea ice has been implicated in forcing the “warm-Arctic cold-Siberian” (WACS) anomaly pattern via enhanced turbulent heat flux (THF). This study investigates interannual variability in winter [December–February (DJF)] Barents Sea THF and its relationship to Barents Sea ice and the large-scale atmospheric flow. ERA-Interim and observational data from 1979/80 to 2011/12 are used. The leading pattern (EOF1: 33%) of winter Barents Sea THF variability is relatively weakly correlated (r = 0.30) with Barents Sea ice and appears to be driven primarily by atmospheric variability. The sea ice–related THF variability manifests itself as EOF2 (20%, r = 0.60). THF EOF2 is robust over the entire winter season, but its link to the WACS pattern is not. However, the WACS pattern emerges consistently as the second EOF (20%) of Eurasian surface air temperature (SAT) variability in all winter months. When Eurasia is cold, there are indeed weak reductions in Barents Sea ice, but the associated THF anomalies are on average negative, which is inconsistent with the proposed direct atmospheric response to sea ice variability. Lead–lag correlation analyses on shorter time scales support this conclusion and indicate that atmospheric variability plays an important role in driving observed variability in Barents Sea THF and ice cover, as well as the WACS pattern.