Palaeoclimate reconstructions of periods with warm climates and high atmospheric CO2 concentrations are crucial for developing better projections of future climate change. Deep-ocean1,2 and high-latitude3 palaeotemperature proxies demonstrate that the Eocene epoch (56 to 34 million years ago) encompasses the warmest interval of the past 66 million years, followed by cooling towards the eventual establishment of ice caps on Antarctica. Eocene polar warmth is well established, so the main obstacle in quantifying the evolution of key climate parameters, such as global average temperature change and its polar amplification, is the lack of continuous high-quality tropical temperature reconstructions. Here we present a continuous Eocene equatorial sea surface temperature record, based on biomarker palaeothermometry applied on Atlantic Ocean sediments. We combine this record with the sparse existing data4,5,6 to construct a 26-million-year multi-proxy, multi-site stack of Eocene tropical climate evolution. We find that tropical and deep-ocean temperatures changed in parallel, under the influence of both long-term climate trends and short-lived events. This is consistent with the hypothesis that greenhouse gas forcing7,8, rather than changes in ocean circulation9,10, was the main driver of Eocene climate. Moreover, we observe a strong linear relationship between tropical and deep-ocean temperatures, which implies a constant polar amplification factor throughout the generally ice-free Eocene. Quantitative comparison with fully coupled climate model simulations indicates that global average temperatures were about 29, 26, 23 and 19 degrees Celsius in the early, early middle, late middle and late Eocene, respectively, compared to the preindustrial temperature of 14.4 degrees Celsius. Finally, combining proxy- and model-based temperature estimates with available CO2 reconstructions8 yields estimates of an Eocene Earth system sensitivity of 0.9 to 2.3 kelvin per watt per square metre at 68 per cent probability, consistent with the high end of previous estimates11.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Additional information

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


  1. 1.

    Lear, C. H., Elderfield, H. & Wilson, P. A. Cenozoic deep-sea temperatures and global ice volumes from Mg/Ca in benthic foraminiferal calcite. Science 287, 269–272 (2000).

  2. 2.

    Zachos, J. C., Dickens, G. R. & Zeebe, R. E. An early Cenozoic perspective on greenhouse warming and carbon-cycle dynamics. Nature 451, 279–283 (2008).

  3. 3.

    Bijl, P. K. et al. Early Palaeogene temperature evolution of the southwest Pacific Ocean. Nature 461, 776–779 (2009).

  4. 4.

    Pearson, P. N. et al. Stable warm tropical climate through the Eocene epoch. Geology 35, 211–214 (2007).

  5. 5.

    Inglis, G. N. et al. Descent toward the Icehouse: Eocene sea surface cooling inferred from GDGT distributions. Paleoceanography 30, 1000–1010 (2015).

  6. 6.

    Evans, D. et al. Eocene greenhouse climate revealed by coupled clumped isotope-Mg/Ca thermometry. Proc. Natl Acad. Sci. USA https://doi.org/10.1073/pnas.1714744115 (2018).

  7. 7.

    Huber, M. et al. Eocene circulation of the Southern Ocean: was Antarctica kept warm by subtropical waters? Paleoceanography 19, PA4026 (2004).

  8. 8.

    Anagnostou, E. et al. Changing atmospheric CO2 concentration was the primary driver of early Cenozoic climate. Nature 533, 380–384 (2016).

  9. 9.

    Kennett, J. P. Cenozoic evolution of Antarctic glaciation, the circum-Antarctic Ocean, and their impact on global paleoceanography. J. Geophys. Res. 82, 3843–3860 (1977).

  10. 10.

    Bijl, P. K. et al. Eocene cooling linked to early flow across the Tasmanian Gateway. Proc. Natl Acad. Sci. USA 110, 9645–9650 (2013).

  11. 11.

    PALAEOSENS Project Members. Making sense of palaeoclimate sensitivity. Nature 491, 683–691 (2012); erratum 494, 130 (2013).

  12. 12.

    Hollis, C. J. et al. Early Paleogene temperature history of the Southwest Pacific Ocean: reconciling proxies and models. Earth Planet. Sci. Lett. 349–350, 53–66 (2012); erratum 374, 258–259 (2013).

  13. 13.

    Sijp, W. P., England, M. H. & Huber, M. Effect of the deepening of the Tasman Gateway on the global ocean. Paleoceanography 26, PA4207 (2011).

  14. 14.

    Huber, M. & Caballero, R. The early Eocene equable climate problem revisited. Clim. Past 7, 603–633 (2011).

  15. 15.

    Lunt, D. J. et al. A model–data comparison for a multi-model ensemble of early Eocene atmosphere–ocean simulations: EoMIP. Clim. Past 8, 1717–1736 (2012).

  16. 16.

    Mascle, J. et al. Proceedings of the Ocean Drilling Program Initial Reports Vol. 159 (ODP/TAMU, College Station, 1996).

  17. 17.

    Wagner, T. Late Cretaceous to early Quaternary organic sedimentation in the eastern Equatorial Atlantic. Palaeogeogr. Palaeoclimatol. Palaeoecol. 179, 113–147 (2002).

  18. 18.

    Kim, J.-H. et al. New indices and calibrations derived from the distribution of crenarchaeal isoprenoid tetraether lipids: implications for past sea surface temperature reconstructions. Geochim. Cosmochim. Acta 74, 4639–4654 (2010).

  19. 19.

    Tierney, J. E. & Tingley, M. P. A. Bayesian, spatially-varying calibration model for the TEX86 proxy. Geochim. Cosmochim. Acta 127, 83–106 (2014).

  20. 20.

    Frieling, J. et al. Extreme warmth and heat-stressed plankton in the tropics during the Paleocene-Eocene Thermal Maximum. Sci. Adv. 3, e1600891 (2017).

  21. 21.

    Frieling, J. et al. Tropical Atlantic climate and ecosystem regime shifts during the Paleocene–Eocene Thermal Maximum. Clim. Past 14, 39–55 (2018).

  22. 22.

    Bohaty, S. M., Zachos, J. C., Florindo, F. & Delaney, M. L. Coupled greenhouse warming and deep-sea acidification in the middle Eocene. Paleoceanography 24, PA2207 (2009).

  23. 23.

    Sluijs, A., Pross, J. & Brinkhuis, H. From greenhouse to icehouse; organic-walled dinoflagellate cysts as paleoenvironmental indicators in the Paleogene. Earth Sci. Rev. 68, 281–315 (2005).

  24. 24.

    Liu, Z. et al. Global cooling during the Eocene-Oligocene climate transition. Science 323, 1187–1190 (2009).

  25. 25.

    Caballero, R. & Langen, P. L. The dynamic range of poleward energy transport in an atmospheric general circulation model. Geophys. Res. Lett. 32, L02705 (2005).

  26. 26.

    Goldner, A., Herold, N. & Huber, M. Antarctic glaciation caused ocean circulation changes at the Eocene-Oligocene transition. Nature 511, 574–577 (2014); erratum 519, 378 (2015).

  27. 27.

    Sluijs, A. et al. Warm and wet conditions in the Arctic region during Eocene Thermal Maximum 2. Nat. Geosci. 2, 777–780 (2009).

  28. 28.

    Kiehl, J. T. & Shields, C. A. Sensitivity of the Palaeocene–Eocene Thermal Maximum climate to cloud properties. Philos. Trans. R. Soc. A 371, 20130093 (2013).

  29. 29.

    Pierrehumbert, R. T. Thermostats, radiator fins, and the local runaway greenhouse. J. Atmos. Sci. 52, 1784–1806 (1995).

  30. 30.

    Matthews, K. J. et al. Global plate boundary evolution and kinematics since the late Paleozoic. Global Planet. Change 146, 226–250 (2016).

  31. 31.

    Hopmans, E. C., Schouten, S. & Sinninghe Damsté, J. S. The effect of improved chromatography on GDGT-based palaeoproxies. Org. Geochem. 93, 1–6 (2016).

  32. 32.

    Hopmans, E. C. et al. A novel proxy for terrestrial organic matter in sediments based on branched and isoprenoid tetraether lipids. Earth Planet. Sci. Lett. 224, 107–116 (2004).

  33. 33.

    Weijers, J. W. H., Lim, K. L. H., Aquilina, A., Sinninghe Damsté, J. S. & Pancost, R. D. Biogeochemical controls on glycerol dialkyl glycerol tetraether lipid distributions in sediments characterized by diffusive methane flux. Geochem. Geophys. Geosystems 12, Q10010 (2011).

  34. 34.

    Zhang, Y. G. et al. Methane index: a tetraether archaeal lipid biomarker indicator for detecting the instability of marine gas hydrates. Earth Planet. Sci. Lett. 307, 525–534 (2011).

  35. 35.

    Blaga, C. I., Reichart, G.-J., Heiri, O. & Damsté, J. S. S. Tetraether membrane lipid distributions in water-column particulate matter and sediments: a study of 47 European lakes along a north–south transect. J. Paleolimnol. 41, 523–540 (2009).

  36. 36.

    Taylor, K. W. R., Huber, M., Hollis, C. J., Hernandez-Sanchez, M. T. & Pancost, R. D. Re-evaluating modern and Palaeogene GDGT distributions: implications for SST reconstructions. Global Planet. Change 108, 158–174 (2013).

  37. 37.

    Schouten, S., Hopmans, E. C., Schefuß, E. & Sinninghe Damsté, J. S. Distributional variations in marine crenarchaeotal membrane lipids: a new tool for reconstructing ancient sea water temperatures? Earth Planet. Sci. Lett. 204, 265–274 (2002).

  38. 38.

    Trommer, G. et al. Distribution of Crenarchaeota tetraether membrane lipids in surface sediments from the Red Sea. Org. Geochem. 40, 724–731 (2009).

  39. 39.

    Ho, S. L. & Laepple, T. Flat meridional temperature gradient in the early Eocene in the subsurface rather than surface ocean. Nat. Geosci. 9, 606–610 (2016).

  40. 40.

    Tierney, J. E., Sinninghe Damsté, J. S., Pancost, R. D., Sluijs, A. & Zachos, J. C. Eocene temperature gradients. Nat. Geosci. 10, 538 (2017).

  41. 41.

    Tierney, J. E. & Tingley, M. P. A. TEX86 surface sediment database and extended Bayesian calibration. Sci. Data 2, 150029 (2015).

  42. 42.

    Kim, J.-H., Schouten, S., Hopmans, E. C., Donner, B. & Sinninghe Damsté, J. S. Global sediment core-top calibration of the TEX86 paleothermometer in the ocean. Geochim. Cosmochim. Acta 72, 1154–1173 (2008).

  43. 43.

    De Rosa, M., Gambacorta, A., Nicolaus, B. & Bu’Lock, J. D. Complex lipids of Caldariella acidophila, a thermoacidophile archaebacterium. Phytochemistry 19, 821–825 (1980).

  44. 44.

    Lai, D., Springstead, J. R. & Monbouquette, H. G. Effect of growth temperature on ether lipid biochemistry in Archaeoglobus fulgidus. Extremophiles 12, 271–278 (2008).

  45. 45.

    Boyd, E. S. et al. Temperature and pH controls on glycerol dibiphytanyl glycerol tetraether lipid composition in the hyperthermophilic crenarchaeon Acidilobus sulfurireducens. Extremophiles 15, 59–65 (2011).

  46. 46.

    Gliozzi, A., Paoli, G., De Rosa, M. & Gambacorta, A. Effect of isoprenoid cyclization on the transition temperature of lipids in thermophilic archaebacteria. Biochim. Biophys. Acta 735, 234–242 (1983).

  47. 47.

    Schouten, S. et al. Intact membrane lipids of “Candidatus Nitrosopumilus maritimus,” a cultivated representative of the cosmopolitan mesophilic group I crenarchaeota. Appl. Environ. Microbiol. 74, 2433–2440 (2008).

  48. 48.

    Pitcher, A. et al. Core and intact polar glycerol dibiphytanyl glycerol tetraether lipids of ammonia-oxidizing archaea enriched from marine and estuarine sediments. Appl. Environ. Microbiol. 77, 3468–3477 (2011).

  49. 49.

    Elling, F. J., Könneke, M., Mußmann, M., Greve, A. & Hinrichs, K.-U. Influence of temperature, pH, and salinity on membrane lipid composition and TEX86 of marine planktonic thaumarchaeal isolates. Geochim. Cosmochim. Acta 171, 238–255 (2015).

  50. 50.

    Zhang, Y. G., Pagani, M. & Wang, Z. Ring Index: a new strategy to evaluate the integrity of TEX86 paleothermometry. Paleoceanography 31, 220–232 (2016).

  51. 51.

    Schouten, S., Forster, A., Panoto, F. E. & Sinninghe Damsté, J. S. Towards calibration of the TEX86 palaeothermometer for tropical sea surface temperatures in ancient greenhouse worlds. Org. Geochem. 38, 1537–1546 (2007).

  52. 52.

    Wuchter, C., Schouten, S., Coolen, M. J. L. & Sinninghe Damsté, J. S. Temperature-dependent variation in the distribution of tetraether membrane lipids of marine Crenarchaeota: implications for TEX86 paleothermometry. Paleoceanography 19, PA4028 (2004).

  53. 53.

    Ho, S. L. et al. Appraisal of TEX86 and thermometries in subpolar and polar regions. Geochim. Cosmochim. Acta 131, 213–226 (2014).

  54. 54.

    Awad, W. K. & Oboh-Ikuenobe, F. E. Early Paleogene dinoflagellate cysts from ODP Hole 959D, Côte d’Ivoire-Ghana Transform Margin, West Africa: new species, biostratigraphy and paleoenvironmental implications. J. Afr. Earth Sci. 123, 123–144 (2016).

  55. 55.

    Shafik, S., Watkins, D. K. & Shin, I. C. Calcareous nannofossil paleogene biostratigraphy, Côte d’Ivoire-Ghana Marginal Ridge, Eastern Equatorial Atlantic. Proc. Ocean Drill. Program Sci. Results 159, 413–431 (1998).

  56. 56.

    Agnini, C. et al. Biozonation and biochronology of Paleogene calcareous nannofossils from low and middle latitudes. Newsl. Stratigr. 47, 131–181 (2014).

  57. 57.

    Gradstein, F. M., Ogg, J. G., Schmitz, M. D. & Ogg, G. M. The Geologic Time Scale 2012 (Elsevier, Amsterdam, 2012).

  58. 58.

    Ravizza, G. & Paquay, F. Os isotope chemostratigraphy applied to organic-rich marine sediments from the Eocene-Oligocene transition on the West African margin (ODP Site 959). Paleoceanography 23, PA2204 (2008).

  59. 59.

    Dalai, T. K., Ravizza, G. E. & Peucker-Ehrenbrink, B. The late Eocene 187Os/188Os excursion: chemostratigraphy, cosmic dust flux and the Early Oligocene glaciation. Earth Planet. Sci. Lett. 241, 477–492 (2006).

  60. 60.

    van der Ploeg, R. et al. Middle Eocene greenhouse warming facilitated by diminished weathering feedback. Nat. Commun. (in the press).

  61. 61.

    Bijl, P. K. et al. Transient middle Eocene atmospheric CO2 and temperature variations. Science 330, 819–821 (2010).

  62. 62.

    Sluijs, A. et al. Southern ocean warming, sea level and hydrological change during the Paleocene-Eocene thermal maximum. Clim. Past 7, 47–61 (2011).

  63. 63.

    Bijl, P. K., Sluijs, A. & Brinkhuis, H. A magneto- and chemostratigraphically calibrated dinoflagellate cyst zonation of the early Palaeogene South Pacific Ocean. Earth Sci. Rev. 124, 1–31 (2013); erratum 134, 160–163 (2014).

  64. 64.

    Fuller, M. & Touchard, Y. in The Cenozoic Southern Ocean: Tectonics, Sedimentation, and Climate Change Between Australia and Antarctica (eds Exon, N. F. et al.) 63–78 (American Geophysical Union, Washington DC, 2004).

  65. 65.

    Dallanave, E. et al. Constraining early to middle Eocene climate evolution of the southwest Pacific and Southern Ocean. Earth Planet. Sci. Lett. 433, 380–392 (2016).

  66. 66.

    Aze, T. et al. Extreme warming of tropical waters during the Paleocene–Eocene Thermal Maximum. Geology 42, 739–742 (2014).

  67. 67.

    Pearson, P. N. et al. Extinction and environmental change across the Eocene-Oligocene boundary in Tanzania. Geology 36, 179–182 (2008).

  68. 68.

    Tripati, A. K. et al. Tropical sea-surface temperature reconstruction for the early Paleogene using Mg/Ca ratios of planktonic foraminifera. Paleoceanography 18, 1101 (2003).

  69. 69.

    Lear, C. H., Bailey, T. R., Pearson, P. N., Coxall, H. K. & Rosenthal, Y. Cooling and ice growth across the Eocene-Oligocene transition. Geology 36, 251–254 (2008).

  70. 70.

    Zhang, Y. G., Pagani, M., Liu, Z., Bohaty, S. M. & DeConto, R. A. 40-million-year history of atmospheric CO2. Philos. Trans. R. Soc. A 371, 20130096 (2013).

  71. 71.

    Boscolo Galazzo, F. et al. The middle Eocene climatic optimum (MECO): a multiproxy record of paleoceanographic changes in the southeast Atlantic (ODP Site 1263, Walvis Ridge). Paleoceanography 29, 1143–1161 (2014).

  72. 72.

    Anand, P., Elderfield, H. & Conte, M. H. Calibration of Mg/Ca thermometry in planktonic foraminifera from a sediment trap time series. Paleoceanography 18, 1050 (2003).

  73. 73.

    Hasiuk, F. J. & Lohmann, K. C. Application of calcite Mg partitioning functions to the reconstruction of paleocean Mg/Ca. Geochim. Cosmochim. Acta 74, 6751–6763 (2010).

  74. 74.

    Evans, D. & Müller, W. Deep time foraminifera Mg/Ca paleothermometry: nonlinear correction for secular change in seawater Mg/Ca. Paleoceanography 27, PA4205 (2012).

  75. 75.

    Erez, J. & Luz, B. Experimental paleotemperature equation for planktonic foraminifera. Geochim. Cosmochim. Acta 47, 1025–1031 (1983).

  76. 76.

    Shackleton, N. J. & Kennett, J. P. Paleotemperature history of the Cenozoic and the initiation of Antarctic glaciation: oxygen and carbon isotope analyses in DSDP Sites 277, 279 and 281. Initial Rep. Deep Sea Drill. Proj. 29, 743–755 (1975).

  77. 77.

    Zachos, J. C., Stott, L. D. & Lohmann, K. C. Evolution of Early Cenozoic marine temperatures. Paleoceanography 9, 353–387 (1994).

  78. 78.

    Kennett, J. P. & Stott, L. D. Abrupt deep-sea warming, palaeoceanographic changes and benthic extinctions at the end of the Palaeocene. Nature 353, 225–229 (1991).

  79. 79.

    Thomas, D. J., Zachos, J. C., Bralower, T. J., Thomas, E. & Bohaty, S. Warming the fuel for the fire: evidence for the thermal dissociation of methane hydrate during the Paleocene–Eocene thermal maximum. Geology 30, 1067–1070 (2002).

  80. 80.

    Coxall, H. K. & Wilson, P. A. Early Oligocene glaciation and productivity in the eastern equatorial Pacific: insights into global carbon cycling. Paleoceanography 26, PA2221 (2011).

  81. 81.

    Westerhold, T., Röhl, U., Donner, B., McCarren, H. K. & Zachos, J. C. A complete high-resolution Paleocene benthic stable isotope record for the central Pacific (ODP Site 1209). Paleoceanography 26, PA2216 (2011).

  82. 82.

    Sexton, P. F. et al. Eocene global warming events driven by ventilation of oceanic dissolved organic carbon. Nature 471, 349–352 (2011).

  83. 83.

    Littler, K., Röhl, U., Westerhold, T. & Zachos, J. C. A high-resolution benthic stable-isotope record for the South Atlantic: implications for orbital-scale changes in Late Paleocene–Early Eocene climate and carbon cycling. Earth Planet. Sci. Lett. 401, 18–30 (2014).

  84. 84.

    Lauretano, V., Hilgen, F. J., Zachos, J. C. & Lourens, L. J. Astronomically tuned age model for the early Eocene carbon isotope events: a new high-resolution δ13C benthic record of ODP Site 1263 between ~49 and ~54 Ma. Newsl. Stratigr. 49, 383–400 (2016).

  85. 85.

    Shackleton, N. J. & Hall, M. A. The late Miocene stable isotope record, Site 926. Proc. Ocean Drill. Program, Sci. Results 154, 367–373 (1997).

  86. 86.

    Pearson, P. N., Foster, G. L. & Wade, B. S. Atmospheric carbon dioxide through the Eocene–Oligocene climate transition. Nature 461, 1110–1113 (2009).

  87. 87.

    Foster, G. L., Royer, D. L. & Lunt, D. J. Future climate forcing potentially without precedent in the last 420 million years. Nat. Commun. 8, 14845 (2017).

  88. 88.

    Pagani, M., Zachos, J. C., Freeman, K. H., Tipple, B. & Bohaty, S. Marked decline in atmospheric carbon dioxide concentrations during the Paleogene. Science 309, 600–603 (2005).

  89. 89.

    Miller, K. G., Wright, J. D. & Browning, J. V. Visions of ice sheets in a greenhouse world. Mar. Geol. 217, 215–231 (2005).

  90. 90.

    Barker, P. F., Diekmann, B. & Escutia, C. Onset of Cenozoic Antarctic glaciation. Deep Sea Res. Part II Top. Stud. Oceanogr. 54, 2293–2307 (2007).

  91. 91.

    Gasson, E. et al. Exploring uncertainties in the relationship between temperature, ice volume, and sea level over the past 50 million years. Rev. Geophys. 50, RG1005 (2012).

  92. 92.

    Gulick, S. P. S. et al. Initiation and long-term instability of the East Antarctic Ice Sheet. Nature 552, 225–229 (2017).

  93. 93.

    Pross, J. et al. Persistent near-tropical warmth on the Antarctic continent during the early Eocene epoch. Nature 488, 73–77 (2012).

  94. 94.

    DeConto, R. M. et al. Thresholds for Cenozoic bipolar glaciation. Nature 455, 652–656 (2008).

  95. 95.

    Gasson, E. et al. Uncertainties in the modelled CO2 threshold for Antarctic glaciation. Clim. Past 10, 451–466 (2014).

  96. 96.

    De Boer, B., van de Wal, R. S. W., Bintanja, R., Lourens, L. J. & Tuenter, E. Cenozoic global ice-volume and temperature simulations with 1-D ice-sheet models forced by benthic δ18O records. Ann. Glaciol. 51, 23–33 (2010).

  97. 97.

    Shields, C. A. et al. The low-resolution CCSM4. J. Clim. 25, 3993–4014 (2012).

  98. 98.

    Lunt, D. J. et al. Earth system sensitivity inferred from Pliocene modelling and data. Nat. Geosci. 3, 60–64 (2010).

  99. 99.

    Byrne, B. & Goldblatt, C. Radiative forcing at high concentrations of well-mixed greenhouse gases. Geophys. Res. Lett. 41, 152–160 (2014).

  100. 100.

    Torsvik, T. H. et al. Phanerozoic polar wander, palaeogeography and dynamics. Earth Sci. Rev. 114, 325–368 (2012).

Download references


In this research, we used samples and data provided by the International Ocean Discovery Program (IODP) and its predecessor, the Ocean Drilling Program. This work was carried out under the programme of the Netherlands Earth System Science Centre (NESSC), financially supported by the Dutch Ministry of Education, Culture and Science. A.S. thanks the European Research Council (ERC) for ERC Starting Grant number 259627 under the European Union Seventh Framework Program. This study was made possible by the Netherlands Organisation for Scientific Research (NWO) grant number 834.11.006, which enabled the purchase of the UHPLC-MS system used for GDGT analyses. P.K.B. and F.P. acknowledge NWO-ALW Veni grants number 863.13.002 and number 863.13.016, respectively. M.H. was funded by the US National Science Foundation (NSF) grant OCE-0902882; the CESM model is also supported by the NSF. C.A. acknowledges the University of Padova grant number BIRD161002. We thank B. Wade (University College London) for converting the Eocene TDP data to GTS2012, P. Sexton (The Open University) for converting the middle Eocene Site 1258 data to GTS2012, J. Kiehl and C. Shields for providing their simulation data, G.-J. Reichart (Royal NIOZ and Utrecht University) for discussions, L. van der Heijden (Utrecht University, now at University of La Rochelle, France), M. Nicolai (Utrecht University), A. Mets (NIOZ), N. Welters, A. van Dijk and D. Kasjaniuk (Utrecht Geolab) for analytical support.

Reviewer information

Nature thanks G. Inglis, C. Lear, K. Littler and S. Robinson for their contribution to the peer review of this work.

Author information


  1. Department of Earth Sciences, Faculty of Geoscience, Utrecht University, Utrecht, The Netherlands

    • Margot J. Cramwinckel
    • , Ilja J. Kocken
    • , Peter K. Bijl
    • , Joost Frieling
    • , Frederik J. Hilgen
    • , Elizabeth L. Kip
    • , Francien Peterse
    • , Robin van der Ploeg
    • , Stefan Schouten
    •  & Appy Sluijs
  2. Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN, USA

    • Matthew Huber
    •  & Aaron Goldner
  3. Department of Geosciences, University of Padova, Padova, Italy

    • Claudia Agnini
  4. Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, Southampton, UK

    • Steven M. Bohaty
  5. MARUM - Center for Marine Environmental Sciences, University of Bremen, Bremen, Germany

    • Ursula Röhl
  6. NIOZ Royal Netherlands Institute for Sea Research, Department of Marine Microbiology and Biogeochemistry and Utrecht University, Den Burg, The Netherlands

    • Stefan Schouten


  1. Search for Margot J. Cramwinckel in:

  2. Search for Matthew Huber in:

  3. Search for Ilja J. Kocken in:

  4. Search for Claudia Agnini in:

  5. Search for Peter K. Bijl in:

  6. Search for Steven M. Bohaty in:

  7. Search for Joost Frieling in:

  8. Search for Aaron Goldner in:

  9. Search for Frederik J. Hilgen in:

  10. Search for Elizabeth L. Kip in:

  11. Search for Francien Peterse in:

  12. Search for Robin van der Ploeg in:

  13. Search for Ursula Röhl in:

  14. Search for Stefan Schouten in:

  15. Search for Appy Sluijs in:


M.J.C., A.S. and M.H. designed the study. M.J.C., F.P., S.S., I.J.K., J.F. and E.L.K. generated and analysed organic geochemical data. M.J.C., A.S., P.K.B., J.F., I.J.K. and E.L.K. generated and analysed palynological data. C.A. generated and analysed nannofossil data. I.J.K., F.J.H., C.A., J.F., R.v.d.P. and M.J.C. developed the age model. M.H. and A.G. performed CESM model simulations. All authors contributed to data and model interpretations. M.J.C., A.S. and M.H. wrote the text, with input from all authors.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Margot J. Cramwinckel.

Extended data figures and tables

  1. Extended Data Fig. 1 Augmented age model of Hole 959D.

    Age–depth plot showing calcareous nannofossil and chemostratigraphic tie-points (diamonds; vertical error bars are indicate the minimum and maximum depth of the tie-point), as presented in Extended Data Table 1b. B, BC and T stand for base, base common and top, respectively. Blue-shaded regions represent depth intervals for which sedimentation rates (blue lines) were calculated. The hiatus of ~1.5 Myr in Core 35 is indicated as a red curly line. Epochs and ages are expressed in Myr ago (Ma), following GTS2012.

  2. Extended Data Fig. 2 Comparison between different TEX86-to-SST calibrations and different GDGT ratios.

    a, TEX86–SST calibration lines (trend lines for BAYSPAR) for one logarithmic and several linear calibrations. Plotted symbols are the Site 959 TEX86 record, to illustrate which part of the calibration is relevant for this study. Compared calibrations are: BAYSPAR19,41 with default settings (search tolerance for 2 TEX86 standard deviations, 0.13; dark-grey line, dark-grey diamonds), BAYSPAR with increased search tolerance (0.2) (dashed line, light-grey diamonds), Kim et al.18 logarithmic \({{\rm{TEX}}}_{86}^{{\rm{H}}}\) core-top calibration (red line, red diamonds), linear core-top calibration18 (light-blue line) and linear subset core-top calibration without Red Sea and polar ocean data18 (dark-blue line). It is of note that the logarithmic \({{\rm{TEX}}}_{86}^{{\rm{H}}}\) starts strongly diverging from the linear BAYSPAR and subset calibrations from TEX86 values of >0.8. b, Site 959 SST record using different TEX86 calibrations. Calibrations and line colours and types are as in a. c, Ratio of crenarchaeol to GDGT-0 against TEX86. Data are from a core-top compilation41 (black circles; Red Sea subset, purple circles) and our Site 959 record (red squares). d, Ring index sensu Zhang et al.50 against TEX86. Data are from a core-top compilation (black circles; Red Sea subset, purple circles) and our Site 959 record (red squares). The exponential regression line of Zhang et al. through the core-top data is plotted as a black line.

  3. Extended Data Fig. 3 Sensitivity of main results to TEX86 calibration.

    a, Top, tropical SST compilation. Proxy data are compiled as described in Methods (red symbols), with all TEX86-based records converted to SST using the BAYSPAR calibration (default settings, search tolerance as described in Methods). The fitted LOESS model is plotted as a black line, with the 95% confidence interval as grey shading. Bottom, ice-free deep-ocean temperature compilation. δ18O-based proxy data are compiled as described in Methods. The fitted LOESS model is plotted as a black line and the 95% confidence interval as dark blue shading. b, Calculated MTG based on LOESS fits of proxy data (lines, propagated 95% confidence intervals shown as shading). The black line with the grey silhouette shows the tropical compilation with \({{\rm{TEX}}}_{86}^{{\rm{H}}}\) calibration and the blue line with the blue silhouette shows the BAYSPAR calibration. c, Proxy (blue diamonds, tropical compilation; red diamonds, Site 959) deep-ocean temperature against tropical SST using the BAYSPAR calibration for TEX86-based records. Lines represent Deming regression analysis through proxy data. The slope (polar amplification factor) is 1.42 ± 0.14 (±1 standard error) for the tropical compilation and 0.75 ± 0.04 for Site 959. Proxy data grouped into 1-Myr bins from 34–58 Myr ago, with error bars representing one standard deviation due to binning. This sensitivity analysis shows that calculated MTGs and the constant polar amplification factor are relatively robust to the specific TEX86 calibration used, although MTGs are less reduced in the early Eocene when using the BAYSPAR calibration. Polar amplification factors are lower, but reflect a linear relationship.

  4. Extended Data Fig. 4 Regression analysis between reconstructed SST and abundance of upwelling indicators.

    a, \({{\rm{TEX}}}_{86}^{{\rm{H}}}\)-based SST (red diamonds, upper left vertical axis), protoperidinioid abundance (percentage of total dinocyst assemblage; brown dots, right vertical axis) and TOC (percentage of sediment; black dots, lower left vertical axis) records of ODP Site 959. Dashed lines represent a hiatus in Site 959. Age is in GTS2012. b, Regression analysis between SST and percentage of protoperidinioid dinocysts of total dinocyst assemblage, showing a non-significant relationship with a very low fit (brown line, 90% confidence interval shown as brown shading; R2 = 0.00, P = 0.75) and a better fit (R2 = 0.35) that is significant (P < 0.01) when only the late Eocene (post-MECO) part of the record is considered (blue–grey line; 90% confidence interval is shown as blue–grey shading). c, Regression analysis between SST and percentage of TOC in sediment, showing a significant negative correlation for the whole record (R2 = 0.39, P < 0.001; dark-grey line, with the 90% confidence interval shown as dark-grey shading) and the late Eocene subset (R2 = 0.37, P < 0.01; blue–grey line, with the 90% confidence interval shown as blue–grey shading).

  5. Extended Data Fig. 5 Eocene multi-proxy tropical SST compilation.

    Compilation presented in Fig. 2, here plotted per site and proxy, with data sources in the key. The abbreviations Moro., Aca., and Turbo. stand for foraminifera genera Morozovella, Acarinina and Turborotalia, respectively. The dashed line in the Site 959 record represents a hiatus. Conservative estimates of propagated calibration and analytical errors (1 s.d.) are ±2.6 °C for \({{\rm{TEX}}}_{86}^{{\rm{H}}}\), ±1.6 °C for δ18O and ±1.3 °C for Mg/Ca. Δ47 uncertainties are as reported in the original study6, with the minimum and maximum per-sample uncertainty. Uncertainties are plotted on the same relative vertical temperature scale as the data to facilitate comparison. The age is in Myr ago, following GTS2012.

  6. Extended Data Fig. 6 Sensitivity of main results to late Eocene ice volume.

    a, Top, tropical SST compilation; proxy data are compiled as described in Methods (red symbols). The fitted LOESS model is plotted as a black line and the 95% confidence interval as grey shading. Bottom, deep-ocean temperature compilation; δ18O-based proxy data are compiled as described in Methods. Ice-free deep-ocean temperatures and fitted LOESS model are shown as grey dots and line, respectively, and the deep-ocean temperature compilation and fitted LOESS model including late Eocene ice volume effect (Methods) as blue dots and line, correspondingly. 95% LOESS confidence intervals are shown as shading. b, Calculated MTG based on LOESS fits of proxy data (lines; propagated 95% confidence intervals are shown as silhouettes). The black line with grey silhouette shows results obtained using ice-free deep-ocean temperatures, and the blue line with blue silhouette includes the late Eocene ice volume effect on the deep-ocean temperature. c, Proxy (blue diamonds, tropical compilation; red diamonds, Site 959) deep-ocean temperature, including the late Eocene ice volume effect, against tropical SST. Lines represent Deming regression analysis through proxy data. The slope (polar amplification factor) is 2.07 ± 0.25 (±1 standard error) for the tropical compilation and 1.19 ± 0.06 for Site 959). Proxy data grouped into 1-Myr bins from 34–58 Myr ago, with error bars representing one standard deviation due to binning. d, Sensitivity of δ18O of Eocene seawater (‰ VSMOW) to the build-up of 0–107 km3 of ice with varying isotopic composition.

  7. Extended Data Fig. 7 Linear relationship between high-latitude and tropical SST.

    Site 1172 TEX86-based SST (record plotted in Fig. 2) against Site 959 TEX86-based SST. Lines represent Deming regression analysis through proxy data (polar amplification factor, 1.66 ± 0.57). Proxy data are grouped into 1-Myr bins from 34–58 Myr ago, with error bars representing one standard deviation due to binning. Peak PETM and peak MECO SSTs are plotted as separate points, which fall within the uncertainty of the regression line.

  8. Extended Data Fig. 8 PETM temperature gradient proxy-model comparison.

    a, Top, tropical SST compilation; proxy data are compiled as described in Methods (red symbols). The fitted LOESS model is plotted as a red line, with the 95% confidence interval as pink shading. Bottom, ice-free deep-ocean temperature compilation; δ18O-based proxy data are compiled as described in Methods. Generalized cross-validation (GCV)-optimized fitted LOESS model (as in Fig. 3) plotted as grey line, with the 95% confidence interval as grey shading. An alternative LOESS model with small bandwidth (0.25 times the GCV-optimized span) that tracks deep-ocean PETM temperature more closely is shown as the blue line, with the 95% confidence interval as blue shading. Data are plotted together with the PETM simulation of Kiehl and Shields28 (black open squares, seasonal range error bars) with altered cloud parameters (CP_PETM). b, Calculated MTG based on LOESS fits of proxy data and of the model simulation CP_PETM. The grey line is obtained using a GCV-optimized fitted LOESS model and the blue line using a smaller-bandwidth deep-ocean LOESS model (propagated 95% confidence intervals are shown as shading). We note that the PETM MTG pattern is complex owing to its sensitivity to the specific records, age models and filtering used, and might have evolved over the course of the event. Nevertheless, peak PETM MTG matches the simulation CP_PETM poorly. The age is in Myr ago, following GTS2012.

  9. Extended Data Fig. 9 Probability distributions of Eocene Earth system sensitivity.

    a, b, ESS estimates using proxy (a) and model (b) temperatures in combination with proxy-based CO2 concentrations, derived as described in Methods. Eocene ESS is separated into the late Eocene relative to the EECO (red), the middle Eocene relative to the EECO (purple) and the middle Eocene relative to late Eocene (blue). ESS estimates of the EECO relative to preindustrial temperature (black) have lower error owing to the high precision of preindustrial CO2 concentration and temperature, but include additional long-term non-CO2 effects.

  10. Extended Data Table 1 Palaeolatitude and age constraints of Site 959 over the Eocene

Supplementary information

  1. Supplementary Data

    This file contains Supplementary Data Tables 1–5. Supplementary Table 1 shows calcareous nannofossil counts, Supplementary Table 2 shows fractional abundances of isoprenoid GDGTs, Supplementary Table 3 shows relative and absolute abundance of upwelling-indicative dinocysts, Supplementary Table 4 shows selected temperature output of CESM simulations EO1–EO4 and EO_CP, and Supplementary Table 5 shows Eocene tropical sea surface temperature compilation.

About this article

Publication history




Issue Date



Further reading


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.