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Interglacial Antarctic–Southern Ocean climate decoupling due to moisture source area shifts

Nature Geoscience volume 14, pages 918–923 (2021)Cite this article

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Abstract

Succession of cold glacials and warm interglacials during the Quaternary results from large global climate responses to variable orbital configurations, accompanied by fluctuating greenhouse gas concentrations. Despite the influences of sea ice and atmospheric and ocean circulations in the Southern Ocean on atmospheric CO2 concentrations and climate, past changes in this region remain poorly documented. Here, we present the 800 ka deuterium excess record from the East Antarctica EPICA Dome C ice core, tracking sea surface temperature in evaporative regions of the Indian sector of the Southern Ocean from which moisture precipitated in East Antarctica is derived. We find that low obliquity leads to surface warming in evaporative moisture source regions during each glacial inception, although this relative temperature increase is counterbalanced by global cooling during glacial maxima. Links between the two regions during interglacials depends on the existence of a temperature maximum at the interglacial onset. In its absence, temperature maxima in the evaporative moisture source regions and in East Antarctica were synchronous. For the other interglacials, temperature maxima in the source areas lag early local temperature maxima by several thousand years, probably because of a change in the position of the evaporative source areas.

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Fig. 1: Modelled correlation between d-excess and SAM.
Fig. 2: Water isotopic series and climate reconstruction from three deep ice cores in East Antarctica.
Fig. 3: Link between ΔTsource, d-excess, ΔTsite and orbital parameters.
Fig. 4: Relationship between source and site temperature over glacial termination and interglacials of the past 800 ka.

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Data availability

The data associated with this study were posted on the PANGEA database under the following link: https://doi.org/10.1594/PANGAEA.934094.

Code availability

The ECHAM model code is available under a version of the MPI-M software license agreement (https://www.mpimet.mpg.de/en/science/models/license/). The code of the isotopic version ECHAM6-wiso is available upon request on the AWI’s GitLab repository (https://gitlab.awi.de/mwerner/mpi-esm-wiso).

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Acknowledgements

This work is a contribution to EPICA, a joint European Science Foundation/European Commission (EU) scientific programme, funded by the European Union and by national contributions from Belgium, Denmark, France, Germany, Italy, the Netherlands, Norway, Sweden, Switzerland and the United Kingdom. The main logistic support was provided by Institut Polaire Français Paul-Emile Victor and Programma Nazionale Ricerche in Antartide (at Dome C) and Alfred Wegener Institute (at Dronning Maud Land). We thank the Dome C logistics teams and the drilling team that made the science possible. The research leading to these results has also received funding from the European Research Council under the European Union H2020 Programme (H2020/20192024)/ERC grant agreement no. 817493 ERC ICORDA (A.L., E.F.). We thank E. Michel for useful comments on the manuscript. This study is also part of the project ANR NEANDROOT.

Author information

Author notes

  1. T. Extier

    Present address: EPOC, UMR 5805, CNRS, Université de Bordeaux, Pessac, France

  2. These authors contributed equally: A. Landais, B. Stenni.

Authors and Affiliations

  1. Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France

    A. Landais, V. Masson-Delmotte, J. Jouzel, E. Fourré, B. Minster, T. Extier, F. Vimeux, I. Crotti & A. Grisart

  2. Department of Environmental Sciences, Informatics and Statistics, Ca’ Foscari University of Venice, Venezia, Italy

    B. Stenni & I. Crotti

  3. Institute of Industrial Science, The University of Tokyo, Kashiwa, Japan

    A. Cauquoin

  4. Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parco Area delle Scienze, Parma, Italy

    E. Selmo

  5. Alfred Wegener Institute, Helmholtz Centre for Marine and Polar Research, Bremerhaven, Germany

    M. Werner

  6. HydroSciences Montpellier (HSM), UMR 5569 (UM, CNRS, IRD), Montpellier, France

    F. Vimeux

  7. Department of Earth and Environmental Sciences, Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan

    R. Uemura

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Contributions

A.L., B.S., J.J. and V.M.-D. designed the study. B.S., E.S., B.M. and A.G. performed the measurements. A.C., M.W. and T.E. worked on the modelling aspects. A.L. led the data analyses and the writing of the manuscript with the active contribution of all co-authors.

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Correspondence to A. Landais.

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The authors declare no competing interests.

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Peer review information Nature Geoscience thanks Daniel Lowry, Ben Kopec and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: James Super.

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Extended data

Extended Data Fig. 1 Raw d-excess data.

Comparison between d-excess calculated with initial δD data measured in 2007 (grey) and d-excess calculated with new δD data measured in 2020 (black).

Extended Data Fig. 2 Evolution of the isotopic composition (a: δD vs δ18O, b: ln(1 + δD) vs ln(1 + δ18O), c: d-excess vs δ18O, d: dln vs ln(1 + δ18O)) for the three deep ice cores of the East Antarctic plateau (red – EDC; blue – Dome F; orange – Vostok).

The black line on panel a represents the Global Meteoric Water Line, a linear relationship between δD and δ18O with a slope of 8 (and intercept of 10 ‰). The black line on panel b represents the ln regression determined from surface snow samples by Uemura et al. (2012)1. The solid lines on panel c represent the evolution of d-excess vs δ18O after a running mean over a 2‰ wide window on the δ18O scale, and the dashed lines represent the average d-excess value.

Extended Data Fig. 3 Isotopic records on three deep drilling sites of the East Antarctic plateau.

Comparison of δ18O or δD, d-excess, dln and ΔTsource for the three sites of interest Dome F, Vostok and EDC.

Extended Data Fig. 4 Evolution of δ18O or δD in blue, d-excess in black, dln in yellow and ΔTsource in red, over the last 9 terminations for each site considered in the text, Vostok, Dome F and EDC, all on the AICC2012 timescale.

The blue and orange rectangles correspond to those defined in Fig. 4 of the main text, highlighting maxima in Tsite and d-excess at EDC. Note that the Vostok records could not be well aligned on the AICC2012 timescale over Termination V because of lack of relative dating constraints so that the comparison of Vostok to other sites over Termination V is not meaningful.

Extended Data Fig. 5 Model-data comparison of the SAM variability.

Comparison of the SAM variability as inferred from observations and reanalyses between 1971 and 2000 and as inferred from the ECHAM6—wiso model free simulation for pre-industrial period.

Extended Data Fig. 6 Spectral analysis of the SAM variability from the Marshall series (left) and from the ECHAM6-wiso model (right).

In both cases, we see a peak at 0.22 month-1.

Extended Data Fig. 7 SAM vs temperature correlation.

Map of the correlation between SAM and 2-m temperature (T2m) from the ERA- Interim data (a) and from the ECHAM6-wiso free simulation (b).

Extended Data Fig. 8 SAM vs pressure correlation.

Map of the correlation between SAM and precipitation from the ERA- Interim data (a) and from the ECHAM6-wiso free simulation (b).

Extended Data Fig. 9 dln vs SAM correlation.

Modelled correlation between dln and SAM as obtained from the ECHAM6-wiso model for a pre-industrial run.

Extended Data Table 1 Correlation coefficients between d-excess, dln and Tsource for the three East Antarctic ice cores EDC, Vostok and Dome F
Full size table

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Landais, A., Stenni, B., Masson-Delmotte, V. et al. Interglacial Antarctic–Southern Ocean climate decoupling due to moisture source area shifts. Nat. Geosci. 14, 918–923 (2021). https://doi.org/10.1038/s41561-021-00856-4

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