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Seasonal origin of the thermal maxima at the Holocene and the last interglacial

Nature volume 589, pages 548–553 (2021)Cite this article

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Matters Arising to this article was published on 27 July 2022

Matters Arising to this article was published on 01 December 2021

This article has been updated

Abstract

Proxy reconstructions from marine sediment cores indicate peak temperatures in the first half of the last and current interglacial periods (the thermal maxima of the Holocene epoch, 10,000 to 6,000 years ago, and the last interglacial period, 128,000 to 123,000 years ago) that arguably exceed modern warmth1,2,3. By contrast, climate models simulate monotonic warming throughout both periods4,5,6,7. This substantial model–data discrepancy undermines confidence in both proxy reconstructions and climate models, and inhibits a mechanistic understanding of recent climate change. Here we show that previous global reconstructions of temperature in the Holocene1,2,3 and the last interglacial period8 reflect the evolution of seasonal, rather than annual, temperatures and we develop a method of transforming them to mean annual temperatures. We further demonstrate that global mean annual sea surface temperatures have been steadily increasing since the start of the Holocene (about 12,000 years ago), first in response to retreating ice sheets (12 to 6.5 thousand years ago), and then as a result of rising greenhouse gas concentrations (0.25 ± 0.21 degrees Celsius over the past 6,500 years or so). However, mean annual temperatures during the last interglacial period were stable and warmer than estimates of temperatures during the Holocene, and we attribute this to the near-constant greenhouse gas levels and the reduced extent of ice sheets. We therefore argue that the climate of the Holocene differed from that of the last interglacial period in two ways: first, larger remnant glacial ice sheets acted to cool the early Holocene, and second, rising greenhouse gas levels in the late Holocene warmed the planet. Furthermore, our reconstructions demonstrate that the modern global temperature has exceeded annual levels over the past 12,000 years and probably approaches the warmth of the last interglacial period (128,000 to 115,000 years ago).

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Fig. 1: Application of SAT method at IODP Site U1485.
Fig. 2: Regional seasonal and mean annual temperature reconstructions.
Fig. 3: Holocene warming driven by retreating ice sheets and rising greenhouse gases.
Fig. 4: Evolution and drivers of Holocene and LIG SST.

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Data availability

The datasets generated and compiled for this study are available in the NOAA Database, World Data Service for Paleoclimatology at https://www.ncdc.noaa.gov/paleo/study/31752. International Comprehensive Ocean-Atmosphere Data Set data were provided by the National Oceanic and Atmospheric Administration/Oceanic and Atmospheric Research/Earth System Research Laboratories Physical Sciences Laboratory at https://psl.noaa.gov/. Source data are provided with this paper.

Code availability

A MATLAB code that implements the SAT method is available on GitHub (https://github.com/sambova/SAT).

Change history

  • 01 February 2021

    This Article was amended to correct the Peer review information, which was originally incorrect.

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Acknowledgements

This research used samples and data provided by the International Ocean Discovery Program (IODP). We thank the science party, technical staff and crew of IODP Expedition 363, who together ensured the successful recovery of IODP Site U1485. Funding for this research was provided by NSF grants OCE-1834208 and OCE-1810681, the NSF-sponsored US Science Support Program for IODP, the Institute of Earth, Ocean, and Atmospheric Sciences at Rutgers University, the Chinese NSF (grant NSFC41630527), Chinese MOST (grant 2017YFA0603801), the School of Geography, Nanjing Normal University and the USIEF-Fulbright Program.

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  1. Shital P. Godad

    Present address: Department of Geosciences, National Taiwan University, Taipei, Taiwan

Authors and Affiliations

  1. Department of Marine and Coastal Sciences, Rutgers, State University of New Jersey, New Brunswick, NJ, USA

    Samantha Bova, Yair Rosenthal & Shital P. Godad

  2. Department of Earth and Planetary Sciences, Rutgers University, New Brunswick, NJ, USA

    Yair Rosenthal

  3. Atmospheric Science Program, Department of Geography, The Ohio State University, Columbus, OH, USA

    Zhengyu Liu

  4. School of Geography, Nanjing Normal University, Nanjing, China

    Mi Yan

  5. Open Studio for Ocean-Climate-Isotope Modeling, Pilot National Laboratory for Marine Science and Technology, Qingdao, China

    Mi Yan

Authors
  1. Samantha Bova
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Contributions

S.B. and Y.R. derived the empirical form of the SAT method. S.B. compiled and analysed the proxy datasets and wrote the first manuscript draft. S.B. and S.P.G. collected the geochemical data from Site U1485 under the supervision of Y.R. Z.L. and M.Y. provided access to and interpretation of model results, and the theory explaining the SAT method. All authors provided review and editing.

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Correspondence to Samantha Bova.

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The authors declare no competing interests.

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Peer review information Nature thanks Jeroen Groeneveld, Jennifer Hertzberg, Feng Zhu, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Location map of IODP Site U1485.

Bathymetric map of the northern margin of Papua New Guinea showing the location of IODP Site U1485 (yellow circle)48,104. Contour interval is 500 m. Map constructed using the M_Map software package for MATLAB.

Extended Data Fig. 2 Age–depth model for Holocene and Termination I section of IODP Site U1485.

a, Reservoir age estimates calculated by measuring co-occurring wood and G. ruber 14C ages and subtracting the wood 14C age from planktic foraminifer 14C age. Twelve reservoir age estimates were deemed outliers (see Methods) and are not shown. Shading represents 2σ error estimate. b, Final age model for the upper 27.5 m CCSF-A of Site U1485 constructed using the Bchron age modelling software package for R43. Sedimentation across the Holocene is approximately constant at a rate of 62 cm kyr−1. Shading represents the 3σ error estimate. The red square indicates an outlying 14C date that is not included in the final age model.

Extended Data Fig. 3 Age–depth model for LIG and Termination II section of IODP Site U1485.

Benthic foraminiferal δ18O record from Site U1485 (blue) measured on Cibicidoides pachyderma (>212 μm) plotted with the LR04 benthic stack (black)44 and the benthic foraminifer δ18O record from Site MD95-2042 from the Iberian Margin (purple)45. Dashed lines show tie points used to define age control for the LIG and Termination II section of Site U1485. Depth scale for Site U1485 is CCSF-A. Foraminiferal δ18O for Site U1485 and MD95-2042 are reported relative to the Pee Dee belemnite (PDB) standard.

Extended Data Fig. 4 Mg/Ca-temperature calibration comparison at IODP Site U1485.

a, d, SSTSN records based on the three different calibrations of Anand et al.91, Gray and Evans93 and Tierney et al.92 (BAYMAG) for the LGM-HL and MIS 6-5 intervals; b, e, same plotted as SST anomalies; c, f, calculated mean annual SST anomalies.

Extended Data Fig. 5 SAT method insensitivity to insolation window length.

Application of the SAT method to Mg/Ca SSTSN from Site U1485 (a–d) and October SSTs from the CCSM3 accelerated model simulation (e–h)7. MASST is estimated by regressing seasonal SSTs with insolation averaged over a range of window lengths, from 30 to 270 days, with the same central 30-day interval. Widening the window length changes the slope of the regression between insolation and seasonal SST (d, h) but has a negligible impact on the SAT calculated MASST anomalies. Shaded region in b reflects the 2 s.e. uncertainty.

Extended Data Fig. 6 Locations and temporal availability of proxy records.

a, Map of SST records used in this study showing proxy type and whether the site has a LIG section. See Extended Data Table 1 for a list of records and their citations. b, c, Temporal availability of records over the Holocene and LIG intervals, respectively. Figure constructed using MATLAB and code from Emile-Geay et al.105.

Extended Data Fig. 7 Map of proxy seasonal bias.

Map of SST records used in this study showing the month of best fit between LIG SSTSN and insolation closest to the 30-day window identified using the SAT method. See Extended Data Table 1 for a list of records included. Figure constructed using MATLAB and code from Emile-Geay et al.105.

Extended Data Fig. 8 Application of SAT method to model seasonal SSTs from core locations in the Eastern Equatorial Pacific (EEP), Southern Hemisphere extratropics, Northern Hemisphere extratropics, and tropical Atlantic.

a–d, Proxy SSTSN anomalies plotted with SSTSN output from the nearest grid cell in the CCSM3 accelerated model simulation. e–h, SAT method MASST (blue) calculated from model SSTSN data shown in a–d plotted with the actual model MASST data (black) for each location. All SST anomalies in this figure are calculated relative to values averaged between 115 ka and 116 ka.

Extended Data Table 1 Records included in SST stacks
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Supplementary information

Supplementary Methods

This file contains theoretical derivation of the SAT method and its properties.

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Bova, S., Rosenthal, Y., Liu, Z. et al. Seasonal origin of the thermal maxima at the Holocene and the last interglacial. Nature 589, 548–553 (2021). https://doi.org/10.1038/s41586-020-03155-x

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