Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Indian Ocean salinity build-up primes deglacial ocean circulation recovery

Nature volume 617, pages 306–311 (2023)Cite this article

Subjects

Abstract

The Indian Ocean provides a source of salt for North Atlantic deep-water convection sites, via the Agulhas Leakage, and may thus drive changes in the ocean’s overturning circulation1,2,3. However, little is known about the salt content variability of Indian Ocean and Agulhas Leakage waters during past glacial cycles and how this may influence circulation. Here we show that the glacial Indian Ocean surface salt budget was notably different from the modern, responding dynamically to changes in sea level. Indian Ocean surface salinity increased during glacial intensification, peaking in glacial maxima. We find that this is due to rapid land exposure in the Indonesian archipelago induced by glacial sea-level lowering, and we suggest a mechanistic link via reduced input of relatively fresh Indonesian Throughflow waters into the Indian Ocean. Using climate model results, we show that the release of this glacial Indian Ocean salinity via the Agulhas Leakage during deglaciation can directly impact the Atlantic Meridional Overturning Circulation and global climate.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Geographic and hydrographic context of study sites.
Fig. 2: Records of Indian Ocean surface salinification and warming compared with changes in the ITF and sea level.
Fig. 3: Role of salty Indian water mass intrusion  in deglacial AMOC strength.
Fig. 4: Proposed links between sea-level-induced changes in the ITF, Indian surface ocean salinity and the efficiency of the Agulhas Leakage.

Similar content being viewed by others

Data availability

The geochemical datasets produced in this study are freely available at the data repository Pangea at https://doi.pangaea.de/10.1594/PANGAEA.955609. Source data are provided with this paper.

Code availability

Python code was used to calculate the stacks and analyse the ANICE-SELEN image outputs. Both are freely available on Zenodo, for stack calculation (https://zenodo.org/record/7478552 and https://doi.org/10.5281/zenodo.7478552), and ANICE-SELEN image processing (https://zenodo.org/record/7471500 and https://doi.org/10.5281/zenodo.7471500).

References

  1. Beal, L. M. et al. On the role of the Agulhas system in ocean circulation and climate. Nature 472, 429–436 (2011).

  2. Biastoch, A., Böning, C. W., Schwarzkopf, F. U. & Lutjeharms, J. R. E. Increase in Agulhas Leakage due to poleward shift of Southern Hemisphere westerlies. Nature 462, 495–498 (2009).

    Article  ADS  CAS  PubMed  Google Scholar 

  3. Knorr, G. & Lohmann, G. Southern Ocean origin for the resumption of Atlantic thermohaline circulation during deglaciation. Nature 424, 532–536 (2003).

    Article  ADS  CAS  PubMed  Google Scholar 

  4. Sprintall, J., Wijffels, S. E., Molcard, R. & Jaya, I. Direct estimates of the indonesian throughflow entering the Indian Ocean: 2004–2006. J. Geophys. Res. Oceans https://doi.org/10.1029/2008JC005257 (2009).

  5. Sengupta, D., Bharath Raj, G. N. & Shenoi, S. S. C. Surface freshwater from Bay of Bengal runoff and Indonesian Throughflow in the tropical Indian Ocean. Geophys. Res. Lett. https://doi.org/10.1029/2006GL027573 (2006).

  6. Talley, L. D. & Sprintall, J. Deep expression of the Indonesian Throughflow: Indonesian Intermediate Water in the South Equatorial Current. J. Geophys. Res. 110, C10009 (2005).

    Article  ADS  Google Scholar 

  7. Gordon, A. L. et al. Advection and diffusion of Indonesian Throughflow Water within the Indian Ocean South Equatorial Current. Geophys. Res. Lett. 24, 2573–2576 (1997).

    Article  ADS  Google Scholar 

  8. Durgadoo, J. V., Rühs, S., Biastoch, A. & Böning, C. W. B. Indian Ocean sources of Agulhas Leakage. J. Geophys. Res. Oceans. 122, 3481–3499 (2017).

    Article  ADS  Google Scholar 

  9. Gray, W. R. & Evans, D. Nonthermal Influences on Mg/Ca in planktonic foraminifera: a review of culture studies and application to the Last Glacial Maximum. Paleoceanogr. Paleoclimatol. 34, 306–315 (2019).

    Article  ADS  Google Scholar 

  10. Kiefer, T., McCave, I. N. & Elderfield, H. Antarctic control on tropical Indian Ocean sea surface temperature and hydrography. Geophys. Res. Lett. 33, L24612 (2006).

    Article  ADS  Google Scholar 

  11. Waelbroeck, C. et al. A global compilation of late Holocene planktonic foraminiferal δ18O: relationship between surface water temperature and δ18O. Quat. Sci. Rev. 24, 853–868 (2005).

    Article  ADS  Google Scholar 

  12. DiNezio, P. N. et al. Glacial changes in tropical climate amplified by the Indian Ocean. Sci. Adv. https://doi.org/10.1126/sciadv.aat9658 (2018).

  13. Thirumalai, K., DiNezio, P. N., Tierney, J. E., Puy, M. & Mohtadi, M. An El Niño mode in the glacial Indian Ocean? Paleoceanogr. Paleoclimatol. 34, 1316–1327 (2019).

    Article  ADS  Google Scholar 

  14. Clemens, S. C. et al. Remote and local drivers of Pleistocene South Asian summer monsoon precipitation: a test for future predictions. Sci. Adv. 7, eabg3848 (2021).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  15. Nilsson-Kerr, K., Anand, P., Sexton, P. F., Leng, M. J. & Naidu, P. D. Indian summer monsoon variability 140–70 thousand years ago based on multi-proxy records from the Bay of Bengal. Quat. Sci. Rev. 279, 107403 (2022).

    Article  Google Scholar 

  16. Ishikawa, S. & Oda, M. Reconstruction of Indian monsoon variability over the past 230,000 years: planktic foraminiferal evidence from the NW Arabian Sea open-ocean upwelling area. Mar. Micropaleontol. 63, 143–154 (2007).

    Article  ADS  Google Scholar 

  17. Kumar, K. P. & Ramesh, R. Revisiting reconstructed Indian monsoon rainfall variations during the last ∼25 ka from planktonic foraminiferal δ18O from the Eastern Arabian Sea. Quat. Int. 443, 29–38 (2017).

    Article  Google Scholar 

  18. Hanebuth, T. J. J. & Stattegger, K. Depositional sequences on a late Pleistocene–Holocene tropical siliciclastic shelf (Sunda Shelf, Southeast Asia). J. Asian Earth Sci. 23, 113–126 (2004).

    Article  ADS  Google Scholar 

  19. Kudrass, H. R. & Schlüter, H. U. Development of cassiterite-bearing sediments and their relation to late Pleistocene sea-level changes in the Straits of Malacca. Mar. Geol. 120, 175–202 (1994).

    Article  ADS  CAS  Google Scholar 

  20. Petrick, B. et al. Glacial Indonesian Throughflow weakening across the Mid-Pleistocene climatic transition. Sci. Rep. https://doi.org/10.1038/s41598-019-53382-0 (2019).

  21. Hanebuth, T. J. J., Voris, H. K., Yokoyama, Y., Saito, Y. & Okuno, J. Formation and fate of sedimentary depocentres on Southeast Asia’s Sunda Shelf over the past sea-level cycle and biogeographic implications. Earth Sci. Rev. 104, 92–110 (2011).

    Article  ADS  Google Scholar 

  22. de Boer, B., Stocchi, P. & van de Wal, R. S. W. A fully coupled 3-D ice-sheet–sea-level model: algorithm and applications. Geosci. Model Dev. 7, 2141–2156 (2014).

    Article  ADS  Google Scholar 

  23. Holbourn, A., Kuhnt, W. & Xu, J. Indonesian Throughflow variability during the last 140 ka: the Timor Sea outflow. Geol. Soc. Spec. Publ. 355, 283–303 (2011).

    Article  ADS  Google Scholar 

  24. Gordon, A. L., Susanto, R. D. & Vranes, K. Cool Indonesian throughflow as a consequence of restricted surface layer flow. Nature 425, 824–828 (2003).

    Article  ADS  CAS  PubMed  Google Scholar 

  25. Sarr, A. C. et al. Subsiding Sundaland. Geology 47, 119–122 (2019).

    Article  ADS  Google Scholar 

  26. Simon, M. H. et al. Millennial-scale Agulhas Current variability and its implications for salt-leakage through the Indian–Atlantic Ocean gateway. Earth Planet. Sci. Lett. 383, 101–112 (2013).

    Article  ADS  CAS  Google Scholar 

  27. Dickson, A. J. et al. Atlantic overturning circulation and Agulhas Leakage influences on Southeast Atlantic upper ocean hydrography during Marine Isotope Stage 11. Paleoceanography https://doi.org/10.1029/2009PA001830 (2010).

  28. Peeters, F. J. C. et al. Vigorous exchange between the Indian and Atlantic oceans at the end of the past five glacial periods. Nature 430, 661–665 (2004).

    Article  ADS  CAS  PubMed  Google Scholar 

  29. Caley, T., Giraudeau, J., Malaizé, B., Rossignol, L. & Pierre, C. Agulhas Leakage as a key process in the modes of Quaternary climate changes. Proc. Natl Acad. Sci. USA 109, 6835–6839 (2012).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. Bard, E. & Rickaby, R. E. M. Migration of the subtropical front as a modulator of glacial climate. Nature 460, 380–383 (2009).

    Article  ADS  CAS  PubMed  Google Scholar 

  31. De Boer, A. M., Graham, R. M., Thomas, M. D. & Kohfeld, K. E. The control of the Southern Hemisphere westerlies on the position of the Subtropical Front. J. Geophys. Res. Oceans. 118, 5669–5675 (2013).

    Article  ADS  Google Scholar 

  32. Marino, G. et al. Agulhas salt-leakage oscillations during abrupt climate changes of the late Pleistocene. Paleoceanography. 28, 599–606 (2013).

    Article  ADS  Google Scholar 

  33. Zhang, X., Lohmann, G., Knorr, G. & Xu, X. Different ocean states and transient characteristics in Last Glacial Maximum simulations and implications for deglaciation. Clim. Past 9, 2319–2333 (2013).

    Article  Google Scholar 

  34. Lauvset, S. K. et al. An updated version of the global interior ocean biogeochemical data product, GLODAPv2.2021. Earth Syst. Sci. Data Discuss. https://doi.org/10.5194/essd-2021-234 (2021)

  35. Weatherall, P. et al. A new digital bathymetric model of the world’s oceans. Earth Space Sci. 2, 331–345 (2015).

    Article  ADS  Google Scholar 

  36. Schlitzer, R. Ocean Data View https://odv.awi.de (2021).

  37. Pierre, C., Saliège, J. F., Urrutiaguer, M. J., & Giraudeau, J. Stable isotope record of benthic and planktonic foraminifera from ODP Site 175-1087 in the southern Cape Basin, Atlantic Ocean. PANGAEA https://doi.org/10.1594/PANGAEA.701338 (2001).

  38. Martinez-Mendez, G. et al. Contrasting multiproxy reconstructions of surface ocean hydrography in the Agulhas Corridor and implications for the Agulhas Leakage during the last 345,000 years. Paleoceanography https://doi.org/10.1029/2009PA001879 (2010).

  39. Caley, T. et al. High-latitude obliquity as a dominant forcing in the Agulhas current system. Clim. Past 7, 1285–1296 (2011).

    Article  Google Scholar 

  40. Barker, S., Greaves, M. & Elderfield, H. A study of cleaning procedures used for foraminiferal Mg/Ca paleothermometry. Geochem. Geophys. Geosyst. 4, 8407 (2003).

    Article  ADS  Google Scholar 

  41. Rostek, F., Bard, E., Beaufort, L., Sonzogni, C. & Ganssen, G. Sea surface temperature and productivity records for the last 240 kyr on the Arabian Sea. Deep Sea Res. Part II 44, 1461–1480 (1997).

    Article  ADS  CAS  Google Scholar 

  42. Bassinot, F. C. et al. Coarse fraction fluctuations in pelagic carbonate sediments from the tropical Indian Ocean: a 1500-kyr record of carbonate dissolution. Paleoceanography. 9, 579–600 (1994).

    Article  ADS  Google Scholar 

  43. Mohtadi, M. et al. Late Pleistocene surface and thermocline conditions of the eastern tropical Indian Ocean. Quat. Sci. Rev. 29, 887–896 (2010).

    Article  ADS  Google Scholar 

  44. Xu, J., Holbourn, A., Kuhnt, W., Jian, Z. & Kawamura, H. Changes in the thermocline structure of the Indonesian outflow during terminations I and II. Earth Planet. Sci. Lett. 273, 152–162 (2008).

    Article  ADS  CAS  Google Scholar 

  45. Zuraida, R. et al. Evidence for Indonesian Throughflow slowdown during Heinrich events 3–5. Paleoceanography 24, PA2205 (2009).

    Article  ADS  Google Scholar 

  46. Herbert, T. D., Peterson, L. C., Lawrence, K. T. & Liu, Z. Tropical ocean temperatures over the past 3.5 million years. Science 328, 1530–1534 (2010).

    Article  ADS  CAS  PubMed  Google Scholar 

  47. De Garidel-Thoron, T., Rosenthal, Y., Bassinot, F. & Beaufort, L. Stable sea surface temperatures in the western Pacific warm pool over the past 1.75 million years. Nature 433, 294–298 (2005).

    Article  ADS  PubMed  Google Scholar 

  48. Lisiecki, L. E. & Raymo, M. E. A Pliocene–Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography https://doi.org/10.1029/2004PA001071 (2005).

  49. de Boer, B., Lourens, L. J. & Van De Wal, R. S. W. Persistent 400,000-year variability of Antarctic ice volume and the carbon cycle is revealed throughout the Plio–Pleistocene. Nat. Commun. https://doi.org/10.1038/ncomms3999 (2014).

  50. Braconnot, P. et al. Evaluation of climate models using palaeoclimatic data. Nat. Clim. Change 2, 417–424 (2012). 2012 2:6.

    Article  ADS  Google Scholar 

  51. van der Lubbe, H. J. L. et al. Indo-Pacific Walker circulation drove Pleistocene African aridification. Nature 598, 618–623 (2021).

    Article  ADS  PubMed  Google Scholar 

  52. Ahn, S., Khider, D., Lisiecki, L. E. & Lawrence, C. E. A probabilistic Pliocene–Pleistocene stack of benthic δ18O using a profile hidden Markov model. Dyn. Stat. Clim. Syst. https://doi.org/10.1093/climsys/dzx002 (2017).

  53. Bereiter, B. et al. Revision of the EPICA Dome C CO2 record from 800 to 600 kyr before present. Geophys. Res. Lett. 42, 542–549 (2015).

    Article  ADS  Google Scholar 

  54. Bouvier-Soumagnac, Y. & Duplessy, J.-C. Carbon and oxygen isotopic composition of planktonic foraminifera from laboratory culture, plankton tows and recent sediment; implications for the reconstruction of paleoclimatic conditions and of the global carbon cycle. J. Foraminifer. Res. 15, 302–320 (1985).

    Article  Google Scholar 

  55. Pearson, P. N. Oxygen isotopes in foraminifera: overview and historical review. Paleontol. Soc. Pap. 18, 1–38 (2012).

    Article  CAS  Google Scholar 

  56. Howell, P., Pisias, N., Ballance, J., Baughman, J. & Ochs, L. ARAND. GitHub https://github.com/jesstierney/arand (2006).

  57. Spratt, R. M. & Lisiecki, L. E. A late Pleistocene sea level stack. Clim. Past 12, 1079–1092 (2016).

    Article  Google Scholar 

  58. Laskar, J. et al. A long-term numerical solution for the insolation quantities of the Earth. Astron. Astrophys. 428, 261–285 (2004).

    Article  ADS  Google Scholar 

  59. Johnson, T. C. et al. A progressively wetter climate in southern East Africa over the past 1.3 million years. Nature 537, 220–224 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  60. Kathayat, G. et al. Indian monsoon variability on millennial-orbital timescales. Sci. Rep. 6, 24374 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  61. Cheng, H. et al. The Asian monsoon over the past 640,000 years and ice age terminations. Nature 534, 640–646 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  62. de Boer, B., van de Wal, R. S. W., Lourens, L. J., Bintanja, R. & Reerink, T. J. A continuous simulation of global ice volume over the past 1 million years with 3-D ice-sheet models. Clim. Dyn. 41, 1365–1384 (2013).

    Article  Google Scholar 

  63. Elderfield, H. et al. Evolution of ocean temperature and ice volume through the mid-Pleistocene climate transition. Science 337, 704–709 (2012).

    Article  ADS  CAS  PubMed  Google Scholar 

  64. Shackleton, N. J. Oxygen isotopes, ice volume and sea level. Quat. Sci. Rev. 6, 183–190 (1987).

    Article  ADS  Google Scholar 

  65. Grant, K. M. et al. Sea-level variability over five glacial cycles. Nat. Commun. 5, 5076 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  66. Wang, P., Tian, J. & Lourens, L. J. Obscuring of long eccentricity cyclicity in Pleistocene oceanic carbon isotope records. Earth Planet. Sci. Lett. 290, 319–330 (2010).

    Article  ADS  CAS  Google Scholar 

  67. Cartopy: A Cartographic Python Library with A Matplotlib Interface (UK Met Office, 2010).

  68. Natural Earth: Free Vector and Raster Map Data www.naturalearthdata.com (2015).

Download references

Acknowledgements

We thank the members and crew of IODP expedition 361 for their work in collecting and providing the samples. This work was mainly funded through UK NERC grant NE/P000878/1 provided to S.N. by S.B. J.W.B.R. received funding for this work from the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement 805246) which also funded M.D.D. S.N. received further funds from the Ministry of Science and Technology, Taiwan (MOST 111-2636-M-002-020) granted to H. Ren. X.Z. and Y.S. were funded through the Natural Science Foundation of China (41988101 and 42075047) and German Helmholtz Postdoc Program (PD-301). X.Z. also acknowledges support from the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (EarthLab). H.T.M. was funded through the Ministry of Science and Technology, Taiwan (110-2811-M-002-647 and 111-2811-M-002-116).

Author information

Authors and Affiliations

  1. School of Earth and Environmental Sciences, Cardiff University, Cardiff, UK

    Sophie Nuber, Morten B. Andersen, Ian R. Hall & Stephen Barker

  2. School of Earth and Environmental Sciences, University of St Andrews, St Andrews, UK

    Sophie Nuber, James W. B. Rae & Matthew D. Dumont

  3. Department of Geosciences, National Taiwan University, Taipei City, Taiwan

    Sophie Nuber & Huw T. Mithan

  4. State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China

    Xu Zhang

  5. Alfred Wegener Institute, Bremerhaven, Germany

    Yuchen Sun

  6. Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

    Bas de Boer

Authors
  1. Sophie Nuber
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. James W. B. Rae
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xu Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Morten B. Andersen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Matthew D. Dumont
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Huw T. Mithan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yuchen Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bas de Boer
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ian R. Hall
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Stephen Barker
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.N. collected, analysed and interpreted the data. S.N. wrote the paper, with support from all co-authors. J.W.B.R., M.B.A. and S.B. supported the collection, analysis and interpretation of the data, and provided the grant. X.Z. and Y.S. conducted the general circulation model simulations and supported the interpretation of the results. M.D.D. computed the data stacks and supported the interpretation of the results. B.d.B. and H.T.M. conducted model runs and postprocessing of sea-level and land/sea ratio reconstructions and supported the interpretation of the results. The samples were collected by S.B. and I.R.H. on IODP expedition 361. All authors provided comments on the final paper.

Corresponding author

Correspondence to Sophie Nuber.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature thanks Pippa Whitehouse and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 U1476 sea surface hydrography reconstructions in comparison to U1476 benthic oxygen isotopes.

(a), (c), and (f) benthic foraminifera δ18O51 on inverted y-axes (light blue lines), (b) planktonic δ18Ocarbonate from G. ruber on inverted y-axis (green line, n = 371; this study), average analytical error indicated to the right of the record, (d) planktonic Mg/Ca with log-scale y-axis and (e) calculated SSTs (red line, n-383; this study) with Monte-Carlo propagated errors including analysis, age model, and equation calibration errors plotted as red shaded envelope, (g) calculated ice-volume corrected δ18Osw-ivc for the surface ocean as proxy for salinity, derived from the δ18OG.ruber and SST records (dark green; this study) with propagated errors including Monte-Carlo SST-, and δ18OG.ruber -analysis errors plotted as dark green shaded envelope. The centre of each deglaciation is indicated by dashed vertical lines and labelled T1 to T16. Note the increases in SST and δ18Osw-ivc during glacial periods (grey shaded bars).

Source data

Extended Data Fig. 2 Derivation and alternative derivations of the newly presented climate proxies.

(a) Atmospheric CO2 from Antarctic ice cores53 (pink), and by calculation using linear transfer from the LR04 benthic δ18O stack48 (dark red). (b) LR04 benthic δ18O stack48. (c) Resulting SST calculations using the method of ref. 9. with ice core CO253 (pink), and LR0448-based CO2 (dark red). (d) Difference between δ18O of global ice volume49 (blue) and δ18O of U1476 seawater (this study) prior to the ice volume correction (green). The large difference suggests that there is a substantial local salinity signal which cannot be explained by whole ocean changes. (e) Age model comparison using benthic δ18O for all sites in Fig. 2 (refs. 23,28,29,51). (f) U1476 salinity proxy (dark green; this study); dark green diamonds highlight times of salinification onset, and (g) GMSL49 (pink) highlighting sea level stands at times of salinification onset in pink dots. The analysis corresponds to Fig. 2e,f, and results in the same average GMSL stand (dashed pink line) at which salinification occurs. Deglaciations are plotted as dashed vertical lines, and intervals of rising δ18Osw-ivc prior to each glacial termination are indicated with vertical grey bars. Note y-axes in (b), (d), and (e) are inverted.

Source data

Extended Data Fig. 3 Indian Ocean salinity and temperature stack construction.

(a) Age model comparison using benthic δ18O for all cores included in the stacks on an inverted y-axis. The colours of the labels correspond to the coloured lines in all panels. References for all cores are listed in Fig. 1 and Methods. For comparison, the LR04 benthic δ18O stack48  is plotted in a dark red line on top. (b) All SST records which are included in the SST stack. (c) All salinity proxy records which are included in the salinity stack. (d) z-scores of all SST records included in the SST stack, the SST stack (thick black line) with 95th percentile error envelope (grey shaded band), and an SST stack excluding U1476 data with 95th percentile envelope (orange shaded band). (e) z-scores of all salinity proxy records included in the salinity stack, the salinity stack (thick black line) with 95th percentile error envelope (grey shaded band), and a salinity stack excluding U1476 data with 95th percentile envelope (orange shaded band). Note that there is no difference in the onset of the salinification and warming between the black and orange stacks suggesting that U1476 does not force the stack calculations. Intervals of rising δ18Osw-ivc prior to each glacial termination are indicated with vertical grey bars.

Source data

Extended Data Fig. 4 Salinity reconstruction using different global mean sea level corrections.

(a) δ18Osw-ivc records derived using 4 different GMSL reconstructions for the ice volume correction. U1476 δ18Obenthic51 is plotted in b) for lead-lag comparison. Grey bars highlight the early increase in δ18Osw-ivc prior to terminations. The ref. 49 ice volume correction allowed modelled ice volume δ18O to be used (dark green). For other GMSL reconstructions65,66, a change of 1% in δ18Obenthic per 120 m GMSL, or maximum reconstructed GMSL was assumed. The colour of each δ18Osw-ivc record corresponds with the referenced scenario in the other panels. (c) Absolute δ18Osw-ivc amplitude of the glacial δ18Osw-ivc maxima compared to the preceding minima for all 4 δ18Osw-ivc scenarios. The colours of the bars correspond to the referenced scenarios in (a). Note that differences between different scenarios are relatively small. (d) Corresponding ice volume δ18O curves for the 4 GMSL reconstructions. The colours of each line correspond with the referenced scenario in (a). Intervals of rising δ18Osw-ivc prior to each glacial termination are indicated with vertical grey bars in (a). Note y-axes in (b) and (d) are inverted.

Source data

Extended Data Fig. 5 Surface hydrography in the source regions of the ITF and Indian Ocean.

(a) U1476 δ18Osw-ivc (dark green), (b) U1476 Mg/Ca-derived sea surface temperatures (orange) (this study), and (c) U1476 δ18Obenthic51 (thin blue line) from the western Indian Ocean. (d) Alkenone-derived sea surface temperatures (light pink) and (e) δ18Obenthic (thin blue line) from the South China Sea46. (f) Mg/Ca-derived sea surface temperatures (brown) and (g) δ18Obenthic (thin blue line) from the western Pacific warm pool47. Onset of U1476 glacial salinification highlighted in grey bars. Note that both South China Sea, and western Pacific warm pool records do not show a similarly consistent lead-lag pattern between their respective SST and δ18Obenthic data. Note δ18Obenthic data is presented on inverted y-axes.

Source data

Extended Data Fig. 6 Spectral analysis results for U1476 climate proxies.

Spectral analysis of U1476 SST (a), δ18Osw-ivc (b), and δ18Obenthic51 (c); as well as SST z-score stack (e), δ18Osw-ivc z-score stack (f), and LR04 δ18Obenthic stack for comparison (g). Peaks above the red line are significant at the 95% interval. Black dashed vertical lines indicate precession (23 kyr), obliquity (41 kyr), and eccentricity (100 kyr) periodicities. All records were subsampled to 1 kyr prior to analysis.

Source data

Extended Data Fig. 7 Cross spectral analysis results for U1476 climate proxies showing lead-lag characteristics.

Cross spectral analyses showing coherence (red) and phase (black) between U1476 SST, δ18Osw-ivc, and δ18Obenthic51 (top, a–c); and SST stack, δ18Osw-ivc stack, and LR04 δ18Obenthic stack48 (bottom, d–f). Coherence data above the red, and purple, line indicates significant coherence between datasets at the 95%, and 80%, significance level. Phase data at times of significant coherence above the black line (Phase = 0) indicate significant lead of the first variable. Precession (23 kyr), obliquity (41 kyr), and eccentricity (100 kyr) periodicities are indicated by vertical black dashed lines. All records were subsampled to 1 kyr prior to analysis.

Source data

Extended Data Fig. 8 Spectral and cross-spectral analysis results for previously published hydrography data from U1446 in the Bay of Bengal.

(a) Spectral analysis of δ18Obenthic, and (b) δ18Osw-ivc. (c) Phase and coherence between δ18Obenthic and δ18Osw-ivc. Black horizontal line shows Phase = 0; positive phase values indicate δ18Osw-ivc leads δ18Obenthic Coherence data above the red line indicates significant coherence between datasets at the 95% significance level. Precession (23 kyr), obliquity (41 kyr), and eccentricity (100 kyr) periodicities are indicated by vertical black dashed lines. All data that went into this analysis was previously published in (ref. 14). All records were subsampled to 1 kyr prior to analysis.

Source data

Extended Data Fig. 9 Indian Ocean hydroclimate proxies compared to U1476 salinity.

(a) 15° S July summer insolation58. (b)–(d), (f), (h), (j), (l), (n), (p) U1476 δ18Osw-ivc (this study). (c) U1476 δ18Obenthic51 on inverted y-axis. (e) Malawi Lake SST, proxy for African Monsoon variability59. (g) Speleothem δ18OCaCO3 from Dongge Cave, China, proxy for Southeast Asian Summer Monsoon variability61. (i) Speleothem δ18OCaCO3 from Bittoo Cave, India, proxy for Indian Summer Monsoon variability60. (k) TY93-929/P δ18Osw-ivc, Arabian Sea surface ocean salinity proxy40. (m) U1446 δ18Osw-ivc, Bay of Bengal sea surface salinity proxy14. (o) GeoB10038-4 δ18Osw-ivc43, eastern Indian Ocean. Grey vertical bars highlight the period of salinification in U1476 which is also visible in the Arabian Sea, Bay of Bengal, and eastern Indian Ocean sea surface salinity proxies.

Source data

Extended Data Fig. 10 Changes in land surface as a function of changes in global mean sea level.

(a) Pixels occurring within the orange polygon were used to calculate the land/sea ratio in each time-slice map created by the ANICE-SELEN model. (b) Change in land to sea surface ratio in the Indonesian archipelago as modelled by the coupled ice sheet-topography model ANICE-SELEN for a subset of 9 glacial-interglacial cycles in respect to GMSL. Changes occurring from falling and rising sea level are plotted in blue and orange respectively – the hysteresis between falling and rising sea levels likely results from the delayed response of the solid Earth to changes in ocean water surface loading. (c) Slope of the land/sea surface ratio as a function of GMSL to highlight specific sea levels at which the rate of land exposure during sea level fall, or land flooding during sea level rise, is particularly fast with respect to the change in GMSL. Vertical blue shaded bars highlight the GMSL interval within which the change in ratios at GMSL fall is particularly fast. The map in (a) was plotted using the library Cartopy67 in Python. Outlines for countries are taken from ref. 68.

Source data

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nuber, S., Rae, J.W.B., Zhang, X. et al. Indian Ocean salinity build-up primes deglacial ocean circulation recovery. Nature 617, 306–311 (2023). https://doi.org/10.1038/s41586-023-05866-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-023-05866-3

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing