Precise interpolar phasing of abrupt climate change during the last ice age

Journal name:
Nature
Volume:
520,
Pages:
661–665
Date published:
DOI:
doi:10.1038/nature14401
Received
Accepted
Published online

The last glacial period exhibited abrupt Dansgaard–Oeschger climatic oscillations, evidence of which is preserved in a variety of Northern Hemisphere palaeoclimate archives1. Ice cores show that Antarctica cooled during the warm phases of the Greenland Dansgaard–Oeschger cycle and vice versa2, 3, suggesting an interhemispheric redistribution of heat through a mechanism called the bipolar seesaw4, 5, 6. Variations in the Atlantic meridional overturning circulation (AMOC) strength are thought to have been important, but much uncertainty remains regarding the dynamics and trigger of these abrupt events7, 8, 9. Key information is contained in the relative phasing of hemispheric climate variations, yet the large, poorly constrained difference between gas age and ice age and the relatively low resolution of methane records from Antarctic ice cores have so far precluded methane-based synchronization at the required sub-centennial precision2, 3, 10. Here we use a recently drilled high-accumulation Antarctic ice core to show that, on average, abrupt Greenland warming leads the corresponding Antarctic cooling onset by 218 ± 92 years (2σ) for Dansgaard–Oeschger events, including the Bølling event; Greenland cooling leads the corresponding onset of Antarctic warming by 208 ± 96 years. Our results demonstrate a north-to-south directionality of the abrupt climatic signal, which is propagated to the Southern Hemisphere high latitudes by oceanic rather than atmospheric processes. The similar interpolar phasing of warming and cooling transitions suggests that the transfer time of the climatic signal is independent of the AMOC background state. Our findings confirm a central role for ocean circulation in the bipolar seesaw and provide clear criteria for assessing hypotheses and model simulations of Dansgaard–Oeschger dynamics.

At a glance

Figures

  1. Records of glacial abrupt millennial-scale climatic variability.
    Figure 1: Records of glacial abrupt millennial-scale climatic variability.

    a, Greenland NGRIP δ18O record1 on GICC05 × 1.0063 chronology (Methods). b, WDC discrete CH4 record on the WD2014 chronology, which is based on layer counting (0–31.2 kyr) and CH4 synchronization to NGRIP (31.2–68 kyr)23. c, WDC δ18O record. d, Antarctic temperature stack (ATS)30 in degrees Celsius relative to the present day on AICC12 × 1.0063 chronology. DO/AIM events are indicated with orange vertical bars, numbered at the bottom of the figure.

  2. Interhemispheric phasing of the bipolar seesaw.
    Figure 2: Interhemispheric phasing of the bipolar seesaw.

    a, Lagged correlation between NGRIP δ18O and WDC d(δ18O)/dt (blue), and between WDC CH4 and d(δ18O)/dt (green). Millennial-scale variability is isolated by using a fourth-order Butterworth bandpass filter (500–10,000-year window); the CH4-synchronized part of the records is used (31.2–68 kyr). b, DO 3–18 stack of NGRIP δ18O (blue), WDC CH4 (green) and WDC δ18O (orange with curve fit), aligned at the midpoint of the DO warming signal. Events are averaged with their original amplitudes and normalized after stacking for convenience of visualization. c, As in b, but for NH abrupt cooling events (that is, the interstadial terminations). df, Histograms of NH lead time associated with ac, respectively, generated by binning solutions from the sensitivity study. The total number of solutions is 4 × 103 in d, and 4 × 105 in e and f. Distribution mean and 2σ probability bounds are listed in the panels. Shaded vertical yellow bars (upper panels) show NH lead time; the error bar represents 2σ as defined for the lower panels.

  3. Timing of the last deglaciation.
    Figure 3: Timing of the last deglaciation.

    a, NGRIP δ18O on GICC05 chronology1. b, WDC CH4. c, WDC δ18O with breakpoints as orange dots and error bars showing the 2σ uncertainty bounds (Extended Data Table 1). d, WDC CO2 data (dots) with spline fit (solid line)26. Period abbreviations: OD, Oldest Dryas; B–A, Bølling–Allerød; ACR, Antarctic Cold Reversal; YD, Younger Dryas; Holoc., Holocene. Vertical orange lines correspond to the midpoints of the WDC CH4 transitions. NGRIP and WDC chronologies are both based on annual-layer counting, and are fully independent.

  4. Difference between gas age and ice age ([Dgr]age) at WAIS Divide.
    Extended Data Fig. 1: Difference between gas age and ice age (Δage) at WAIS Divide.

    a, Comparison of WDC Δage with other Antarctic cores. Ice core abbreviations: EDC, EPICA Dome Concordia; EDML, EPICA Dronning Maud Land; TALDICE, Talos Dome; WDC, WAIS Divide. Δage values are taken from refs 23, 63, 64, 65. The vertical axis is on a logarithmic scale. b, Δage uncertainty bounds obtained from an ensemble of 1,000 alternative Δage scenarios; details are given elsewhere23. A Δage scenario obtained with an alternative densification model (ref. 39 instead of ref. 38) is shown in blue. ce, Histograms of the 1,000 Δage scenarios at 20 kyr bp (c), 40 kyr bp (d) and 60 kyr bp (e); stated values give the distribution mean ± the 2σ standard deviation.

  5. Determining the timing of the abrupt DO transitions.
    Extended Data Fig. 2: Determining the timing of the abrupt DO transitions.

    a, b, DO 17.2, 17.1, 16.2 and 16.1 (from oldest to youngest41) as recorded in NGRIP δ18O (a) and WDC CH4 (b). Horizontal orange bars denote pre-transition and post-transition levels; the transition midpoint (50% of signal amplitude) is indicated by a red dot; the 25% and 75% signal amplitude markers are indicated with blue dots. c, Comparison of WDC CH4 (grey) with EDML CH4 (orange)3, 50, 66. d, Hypothetical gas-age distribution for WDC due to firn densification and gradual bubble closure, using a truncated log-normal distribution67. e, Shift in transition midpoint induced by filtering of the atmospheric record in the firn column.

  6. Cropping of individual records in the stack to prevent overlap of events.
    Extended Data Fig. 3: Cropping of individual records in the stack to prevent overlap of events.

    a, DO/AIM 12, where no cropping is needed. b, DO/AIM 17.1, where the most cropping is needed. Full time series with five-point running average are plotted in grey, and the contributory records are plotted in blue and orange for NGRIP and WDC, respectively. The yellow vertical shading bar in background shows the NH lead time (200 years); the purple rectangle gives the −1,200 to +1,200 time window.

  7. Number of records and fitting procedure.
    Extended Data Fig. 4: Number of records and fitting procedure.

    Number of contributory records to the WDC δ18O stacks for abrupt NH warming (interstadial onset) (a) and for abrupt NH cooling (interstadial termination) (b). Blue rectangles indicate the time window over which the fitting procedure evaluates the fit to the data (−600 to +700 years); shaded vertical yellow bars show NH lead time.

  8. Evaluating the performance of the breakpoint detection algorithm.
    Extended Data Fig. 5: Evaluating the performance of the breakpoint detection algorithm.

    a, Breakpoint detection as a function of data window size using both linear (blue) and quadratic (orange) functions, compared with the BREAKFIT algorithm48 (grey dots with 1σ error bars). The data window is applied symmetrically, meaning that equal numbers of years (half the window size) are used before and after the detected breakpoint. Data falling outside this window are ignored in the fitting procedure. b, Root mean square deviation between the WDC δ18O stack and the fitting curve.

  9. Alternative stacking of AIM events.
    Extended Data Fig. 6: Alternative stacking of AIM events.

    a, Stack of NGRIP δ18O (blue), WDC CH4 (green) and WDC δ18O (orange with fit) for just the major AIM events (4, 8, 12, 14 and 17), aligned at the abrupt NH warming. b, As in a, but for only the minor AIM events (3, 5.1, 5.2, 6, 7, 9, 10, 11, 13, 15, 16 and 18). c, As in a, but for eight randomly selected DO/AIM events. d, As in c, but aligned at the abrupt NH cooling. Events are averaged with their original amplitudes and normalized after stacking for convenience of visualization. eh, Histograms of NH lead time associated with ad, respectively, generated by binning the 4 × 105 solutions from the sensitivity study. The distribution mean and 2σ uncertainty bounds are listed in the panels. Shaded vertical yellow bars (upper panels) show NH lead time.

  10. Timing of sea-salt sodium.
    Extended Data Fig. 7: Timing of sea-salt sodium.

    a, Lagged correlation between NGRIP δ18O and the time derivative of WDC δ18O (orange), and between NGRIP δ18O and the time derivative of WDC ssNa (grey). The dots indicate the maximum (anti-)correlation at 167-year and 229-year NH lead for WDC δ18O and ssNa, respectively. A fourth-order Butterworth bandpass filter with a 500–10,000-year window is applied to the time series to isolate the millennial-scale variability. b, DO3–18 stack of NGRIP δ18O (blue), WDC CH4 (green), WDC δ18O (orange) and WDC ssNa (grey), aligned at the midpoint of the DO warming signal. The estimated breakpoint in the stacks (dots) occurs at t = 218 and 195 years for WDC δ18O and ssNa, respectively. c, As in b, but for the abrupt NH cooling events, with the estimated breakpoint at t = 208 and 199 years for WDC δ18O and ssNa, respectively. Shaded vertical yellow bars show NH lead times.

Tables

  1. Phasing of the bipolar seesaw during the last deglaciation
    Extended Data Table 1: Phasing of the bipolar seesaw during the last deglaciation

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Author information

  1. Lists of participants and their affiliations appear at the end of the paper.

    • WAIS Divide Project Members

Affiliations

  1. College of Earth, Oceanic and Atmospheric Sciences, Oregon State University, Corvallis, Oregon 97331, USA.

    • Christo Buizert,
    • Thomas K. Bauska,
    • Edward J. Brook,
    • Jon S. Edwards,
    • Michael L. Kalk,
    • James E. Lee,
    • Shaun A. Marcott,
    • Logan E. Mitchell,
    • Rachael H. Rhodes &
    • Julia L. Rosen
  2. US Geological Survey National Ice Core Laboratory, Denver, Colorado 80225, USA.

    • Betty Adrian,
    • Brian B. Bencivengo,
    • Geoffrey M. Hargreaves &
    • Richard M. Nunn
  3. School of Earth and Environmental Science, Seoul National University, Seoul 151-742, Korea.

    • Jinho Ahn
  4. Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, USA.

    • Mary Albert &
    • Stephanie Gregory
  5. Department of Geosciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA.

    • Richard B. Alley,
    • John M. Fegyveresi,
    • Todd A. Sowers &
    • Donald E. Voigt
  6. Scripps Institution of Oceanography, University of California at San Diego, La Jolla, California 92093, USA.

    • Daniel Baggenstos,
    • Anais J. Orsi &
    • Jeffrey P. Severinghaus
  7. Department of Physics, University of California at Berkeley, Berkeley, California 94720, USA.

    • Ryan C. Bay &
    • P. Buford Price
  8. Ice Drilling Design and Operations, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA.

    • Charles R. Bentley,
    • Chris J. Gibson,
    • Joshua J. Goetz,
    • Jay A. Johnson,
    • Tanner W. Kuhl,
    • Donald A. Lebar,
    • Nicolai B. Mortensen,
    • Paul J. Sendelbach,
    • Alexander J. Shturmakov,
    • Kristina R. Slawny &
    • Anthony W. Wendricks
  9. Desert Research Institute, Nevada System of Higher Education, Reno, Nevada 89512, USA.

    • Nathan J. Chellman,
    • Olivia J. Maselli,
    • Joseph R. McConnell,
    • Kenneth C. McGwire,
    • Daniel R. Pasteris,
    • Michael Sigl &
    • Kendrick C. Taylor
  10. US Geological Survey, Boulder, Colorado 80309, USA.

    • Gary D. Clow
  11. Department of Chemistry and Biochemistry, South Dakota State University, Brookings, South Dakota 57007, USA.

    • Jihong Cole-Dai &
    • Dave G. Ferris
  12. Department of Earth and Space Sciences, University of Washington, Seattle, Washington 98195-1310, USA.

    • Howard Conway,
    • T. J. Fudge,
    • Bradley R. Markle,
    • Andrew J. Schauer,
    • Spruce W. Schoenemann,
    • Eric J. Steig,
    • Edwin D. Waddington &
    • Mai Winstrup
  13. ADC Management Services, Lakewood, Colorado 80226, USA.

    • Eric Cravens
  14. Department of Geography, University of California at Berkeley, Berkeley, California 94709, USA.

    • Kurt M. Cuffey
  15. Earth and Environmental Science Department, New Mexico Tech, Socorro, New Mexico 87801, USA.

    • Nelia W. Dunbar &
    • Nels Iverson
  16. US Geological Survey, Denver, Colorado 80225, USA.

    • Joan J. Fitzpatrick
  17. Institute of Arctic and Alpine Research, University of Colorado, Boulder, Colorado 80309-0450, USA.

    • Vasileios Gkinis,
    • Tyler R. Jones,
    • Bruce H. Vaughn &
    • James W. C. White
  18. Centre for ice and climate, University of Copenhagen, DK-2100 Copenhagen Ø, Denmark.

    • Vasileios Gkinis,
    • Joel B. Pedro &
    • Mai Winstrup
  19. Antarctic Support Contract, Lockheed Martin US Antarctic Program, Centennial, Colorado 80112, USA.

    • Matthew J. Kippenhan
  20. Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York 10964, USA.

    • Bess G. Koffman
  21. Climate Change Institute and School of Earth and Climate Sciences, University of Maine, Orono, Maine 04469, USA.

    • Karl Kreutz
  22. University of Wisconsin-Madison, Madison, Wisconsin, Wisconsin 53706 USA.

    • Shaun A. Marcott
  23. Antarctic Research Centre, Victoria University of Wellington, Wellington 6012, New Zealand.

    • Peter D. Neff
  24. Space Sciences Laboratory, University of California at Berkeley, Berkeley, California 94720, USA.

    • Kunihiko Nishiizumi &
    • Kees C. Welten
  25. Laboratoire des Sciences du Climat et de l’Environnement, Institut Pierre Simon Laplace, 91191 Gif-Sur-Yvette, France.

    • Anais J. Orsi
  26. Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, Washington 98195, USA.

    • Joel B. Pedro
  27. Department of Geosciences, University of Alaska Fairbanks, Fairbanks, Alaska 99775, USA.

    • Erin C. Pettit
  28. Department of Land Resources and Environmental Sciences, Montana State University, Bozeman, Montana 59717, USA.

    • John C. Priscu
  29. Institute for the Study of Earth, Oceans and Space, University of New Hampshire, Durham, New Hampshire 03824, USA.

    • Joseph M. Souney &
    • Mark S. Twickler
  30. School of Physical Sciences, Lake Superior State University, Sault Sainte Marie, Michigan 49783, USA.

    • Matthew K. Spencer
  31. Department of Earth Sciences, Dartmouth College, Hanover, New Hampshire 03755, USA.

    • Gifford J. Wong
  32. PRIME Laboratory, Purdue University, West Lafayette, Indiana 47907, USA.

    • Thomas E. Woodruff

Consortia

  1. WAIS Divide Project Members

    • Christo Buizert,
    • Betty Adrian,
    • Jinho Ahn,
    • Mary Albert,
    • Richard B. Alley,
    • Daniel Baggenstos,
    • Thomas K. Bauska,
    • Ryan C. Bay,
    • Brian B. Bencivengo,
    • Charles R. Bentley,
    • Edward J. Brook,
    • Nathan J. Chellman,
    • Gary D. Clow,
    • Jihong Cole-Dai,
    • Howard Conway,
    • Eric Cravens,
    • Kurt M. Cuffey,
    • Nelia W. Dunbar,
    • Jon S. Edwards,
    • John M. Fegyveresi,
    • Dave G. Ferris,
    • Joan J. Fitzpatrick,
    • T. J. Fudge,
    • Chris J. Gibson,
    • Vasileios Gkinis,
    • Joshua J. Goetz,
    • Stephanie Gregory,
    • Geoffrey M. Hargreaves,
    • Nels Iverson,
    • Jay A. Johnson,
    • Tyler R. Jones,
    • Michael L. Kalk,
    • Matthew J. Kippenhan,
    • Bess G. Koffman,
    • Karl Kreutz,
    • Tanner W. Kuhl,
    • Donald A. Lebar,
    • James E. Lee,
    • Shaun A. Marcott,
    • Bradley R. Markle,
    • Olivia J. Maselli,
    • Joseph R. McConnell,
    • Kenneth C. McGwire,
    • Logan E. Mitchell,
    • Nicolai B. Mortensen,
    • Peter D. Neff,
    • Kunihiko Nishiizumi,
    • Richard M. Nunn,
    • Anais J. Orsi,
    • Daniel R. Pasteris,
    • Joel B. Pedro,
    • Erin C. Pettit,
    • P. Buford Price,
    • John C. Priscu,
    • Rachael H. Rhodes,
    • Julia L. Rosen,
    • Andrew J. Schauer,
    • Spruce W. Schoenemann,
    • Paul J. Sendelbach,
    • Jeffrey P. Severinghaus,
    • Alexander J. Shturmakov,
    • Michael Sigl,
    • Kristina R. Slawny,
    • Joseph M. Souney,
    • Todd A. Sowers,
    • Matthew K. Spencer,
    • Eric J. Steig,
    • Kendrick C. Taylor,
    • Mark S. Twickler,
    • Bruce H. Vaughn,
    • Donald E. Voigt,
    • Edwin D. Waddington,
    • Kees C. Welten,
    • Anthony W. Wendricks,
    • James W. C. White,
    • Mai Winstrup,
    • Gifford J. Wong &
    • Thomas E. Woodruff

Contributions

Data analysis and Δage modelling were performed by C.B.; annual-layer counting (dating) of upper 2,850 m by M.S., T.J.F., M.W., K.C.T. and K.C.M.; CH4 synchronization (dating) of lower 555 m by C.B., K.M.C., J.P.S. and T.J.F.; age scale validation by N.W.D., N.I., K.C.W., K.N. and T.E.W.; discrete water isotope analysis by E.J.S., A.J.Sc. and S.W.S.; continuous water isotope analysis by J.W.C.W., T.R.J., B.H.V. and V.G.; discrete CH4 analysis by T.A.S., L.E.M., J.E.L., J.S.E., J.L.R. and E.J.B.; continuous CH4 analysis by R.H.R., E.J.B. and J.R.M.; CO2 analysis by S.A.M., M.L.K., T.K.B., J.A. and E.J.B.; δ15N of N2 analysis by D.B., C.B., A.J.O. and J.P.S.; continuous-flow chemical analysis by M.S., O.J.M., N.J.C., D.R.P. and J.R.M.; discrete chemical analysis by J.C.-D., D.G.F., B.G.K., K.K. and G.J.W.; ice core physical properties by R.B.A., J.M.F., D.E.V., M.K.S. and J.J.F.; borehole logging by R.C.B. and G.D.C.; biological studies by J.C.P. and P.B.P.; temperature reconstructions by K.M.C. and G.D.C.; tephrochronology by N.W.D. and N.I.; firn studies by M.A., T.A.S. and S.G.; 10Be analysis by K.C.W. and T.E.W.; field science oversight, D.E.V. and B.H.V.; site selection by H.C., E.D.W. and E.C.P.; science management and sample distribution by M.S.T. and J.M.S.; logistics support, planning and management by M.J.K.; drilling management by A.J.Sh., C.R.B., D.A.L., and A.W.W.; deep drill design by A.J.Sh., J.A.J., N.B.M. and C.J.G.; drilling field management by J.A.J., K.R.S. and N.B.M.; sample collection and drill operations by C.J.G., J.J.G., T.W.K. and P.J.S. The field sample handling leaders were A.J.O., B.G.K., P.D.N. and G.J.W.; sample curation, processing and distribution was performed by G.M.H., B.A., R.M.N., E.C. and B.B.B.; the overall WAIS Divide Project design and management, Chief Scientist and field leader was K.C.T. The manuscript was written by C.B., E.J.S. and J.B.P. with assistance from J.P.S., B.R.M., E.J.B. and K.C.T; all authors discussed the results and contributed to improving the final manuscript. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

Author details

    Extended data figures and tables

    Extended Data Figures

    1. Extended Data Figure 1: Difference between gas age and ice age (Δage) at WAIS Divide. (802 KB)

      a, Comparison of WDC Δage with other Antarctic cores. Ice core abbreviations: EDC, EPICA Dome Concordia; EDML, EPICA Dronning Maud Land; TALDICE, Talos Dome; WDC, WAIS Divide. Δage values are taken from refs 23, 63, 64, 65. The vertical axis is on a logarithmic scale. b, Δage uncertainty bounds obtained from an ensemble of 1,000 alternative Δage scenarios; details are given elsewhere23. A Δage scenario obtained with an alternative densification model (ref. 39 instead of ref. 38) is shown in blue. ce, Histograms of the 1,000 Δage scenarios at 20 kyr bp (c), 40 kyr bp (d) and 60 kyr bp (e); stated values give the distribution mean ± the 2σ standard deviation.

    2. Extended Data Figure 2: Determining the timing of the abrupt DO transitions. (625 KB)

      a, b, DO 17.2, 17.1, 16.2 and 16.1 (from oldest to youngest41) as recorded in NGRIP δ18O (a) and WDC CH4 (b). Horizontal orange bars denote pre-transition and post-transition levels; the transition midpoint (50% of signal amplitude) is indicated by a red dot; the 25% and 75% signal amplitude markers are indicated with blue dots. c, Comparison of WDC CH4 (grey) with EDML CH4 (orange)3, 50, 66. d, Hypothetical gas-age distribution for WDC due to firn densification and gradual bubble closure, using a truncated log-normal distribution67. e, Shift in transition midpoint induced by filtering of the atmospheric record in the firn column.

    3. Extended Data Figure 3: Cropping of individual records in the stack to prevent overlap of events. (406 KB)

      a, DO/AIM 12, where no cropping is needed. b, DO/AIM 17.1, where the most cropping is needed. Full time series with five-point running average are plotted in grey, and the contributory records are plotted in blue and orange for NGRIP and WDC, respectively. The yellow vertical shading bar in background shows the NH lead time (200 years); the purple rectangle gives the −1,200 to +1,200 time window.

    4. Extended Data Figure 4: Number of records and fitting procedure. (346 KB)

      Number of contributory records to the WDC δ18O stacks for abrupt NH warming (interstadial onset) (a) and for abrupt NH cooling (interstadial termination) (b). Blue rectangles indicate the time window over which the fitting procedure evaluates the fit to the data (−600 to +700 years); shaded vertical yellow bars show NH lead time.

    5. Extended Data Figure 5: Evaluating the performance of the breakpoint detection algorithm. (704 KB)

      a, Breakpoint detection as a function of data window size using both linear (blue) and quadratic (orange) functions, compared with the BREAKFIT algorithm48 (grey dots with 1σ error bars). The data window is applied symmetrically, meaning that equal numbers of years (half the window size) are used before and after the detected breakpoint. Data falling outside this window are ignored in the fitting procedure. b, Root mean square deviation between the WDC δ18O stack and the fitting curve.

    6. Extended Data Figure 6: Alternative stacking of AIM events. (626 KB)

      a, Stack of NGRIP δ18O (blue), WDC CH4 (green) and WDC δ18O (orange with fit) for just the major AIM events (4, 8, 12, 14 and 17), aligned at the abrupt NH warming. b, As in a, but for only the minor AIM events (3, 5.1, 5.2, 6, 7, 9, 10, 11, 13, 15, 16 and 18). c, As in a, but for eight randomly selected DO/AIM events. d, As in c, but aligned at the abrupt NH cooling. Events are averaged with their original amplitudes and normalized after stacking for convenience of visualization. eh, Histograms of NH lead time associated with ad, respectively, generated by binning the 4 × 105 solutions from the sensitivity study. The distribution mean and 2σ uncertainty bounds are listed in the panels. Shaded vertical yellow bars (upper panels) show NH lead time.

    7. Extended Data Figure 7: Timing of sea-salt sodium. (416 KB)

      a, Lagged correlation between NGRIP δ18O and the time derivative of WDC δ18O (orange), and between NGRIP δ18O and the time derivative of WDC ssNa (grey). The dots indicate the maximum (anti-)correlation at 167-year and 229-year NH lead for WDC δ18O and ssNa, respectively. A fourth-order Butterworth bandpass filter with a 500–10,000-year window is applied to the time series to isolate the millennial-scale variability. b, DO3–18 stack of NGRIP δ18O (blue), WDC CH4 (green), WDC δ18O (orange) and WDC ssNa (grey), aligned at the midpoint of the DO warming signal. The estimated breakpoint in the stacks (dots) occurs at t = 218 and 195 years for WDC δ18O and ssNa, respectively. c, As in b, but for the abrupt NH cooling events, with the estimated breakpoint at t = 208 and 199 years for WDC δ18O and ssNa, respectively. Shaded vertical yellow bars show NH lead times.

    Extended Data Tables

    1. Extended Data Table 1: Phasing of the bipolar seesaw during the last deglaciation (127 KB)

    Supplementary information

    Excel files

    1. Supplementary Data 1 (4.5 MB)

      This file contains the WAIS Divide d18O, CH4 and ssNa data.

    Zip files

    1. Supplementary Data 2 (27.5 MB)

      This zip file contains the computer code (in Matlab) used in the analyses presented in our paper. It also contains a "readme" file that has some more information. All these files are needed to run the code.

    Additional data