Cited by 573Geology and Paleoclimatology ResearchClimate variability and modelsCryospheric studies and observations

Glacial cooling and climate sensitivity revisited

Open access
Tierney, Jessica E., Zhu, Jiang, King, Jonathan, Malevich, Steven B., Hakim, Gregory J., Poulsen, Christopher J.·2020·Nature

Abstract

The Last Glacial Maximum (LGM), one of the best-studied paleoclimatic intervals, offers a prime opportunity to investigate how the climate system responds to changes in greenhouse gases (GHGs) and the cryosphere. Previous work has sought to constrain the magnitude and pattern of glacial cooling from paleothermometers, but the uneven distribution of the proxies, as well as their uncertainties, has challenged the construction of a full-field view of the LGM climate state. Here, we combine a large collection of geochemical proxies for sea-surface temperature with an isotope-enabled climate model ensemble to produce a field reconstruction of LGM temperatures using data assimilation. The reconstruction is validated with withheld proxies as well as independent ice core and speleothem d18O measurements. Our assimilated product provides a precise constraint on global mean LGM cooling of -5.9˚C (-6.3 – -5.6˚C, 95% CI). Given assumptions concerning the radiative forcing of GHGs, ice sheets, and aerosols, this cooling translates to an equilibrium climate sensitivity (ECS) of 3.2˚C (2.2 – 4.3˚C, 95% CI), a value that is higher than previous estimates and but consistent with the traditional consensus range of 2 – 4.5˚C.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41586-020-2617-x

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Over the last ∼50 million years, global average surface temperatures steadily decreased from nearly 30°C during the early Eocene to less than 10°C during the most recent Pleistocene glacial epoch.

    “For example, over the last ∼50 million years, global average surface temperatures have steadily decreased from nearly 30°C during the early Eocene (Burke et al. 2018, Hansen et al. 2013) to less than 10°C during the most recent Pleistocene glacial epoch (e.g., Tierney et al. 2020).”

    From The History of Ocean Oxygenation (2022) · cites this paper as Tierney et al. 2020

    The paper’s LGM temperature-results section reports that global mean surface temperature was 5.9°C lower than in the Late Holocene. It reports a temperature change, not an absolute LGM temperature, so it does not establish the cited claim of less than 10°C. The early-Eocene figure is attributed to other citations in the sentence. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 25

  1. Ballantyne, A., Lavine, M., Crowley, T., Liu, J. & Baker, P. Meta-analysis of tropical surface temperatures during the Last Glacial Maximum. Geophysical Research Letters 32 (2005).
  2. Schneider von Deimling, T., Ganopolski, A., Held, H. & Rahmstorf, S. How cold was the last glacial maximum? Geophysical Research Letters 33 (2006).
  3. Friedrich, T. & Timmermann, A. Using Late Pleistocene sea surface temperature recon- structions to constrain future greenhouse warming. Earth and Planetary Science Letters (2019).
  4. Masson-Delmotte, V. et al. Information from paleoclimate archives. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assess- ment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, 2013).
  5. Brady, E. et al. The connected isotopic water cycle in the Community Earth System Model Version 1. Journal of Advances in Modeling Earth Systems 11, 2547-2566 (2019).
  6. Roe, G. H. & Lindzen, R. S. The mutual interaction between continental-scale ice sheets and atmospheric stationary waves. Journal of Climate 14, 1450-1465 (2001).
  7. Löfverström, M. & Liakka, J. On the limited ice intrusion in Alaska at the LGM. Geophysical Research Letters 43, 11-030 (2016).
  8. Hopcroft, P. O. & Valdes, P. J. How well do simulated last glacial maximum tropical temperatures constrain equilibrium climate sensitivity? Geophysical Research Letters 42, 5533-5539 (2015).
  9. Lee, J.-E., Fung, I., DePaolo, D. J. & Otto-Bliesner, B. Water isotopes during the Last Glacial Maximum: New general circulation model calculations. Journal of Geophysical Research: Atmospheres 113 (2008).
  10. Prentice, I. C., Jolly, D. & Biome 6000 Participants. Mid-Holocene and glacial-maximum vegetation geography of the northern continents and Africa. Journal of Biogeography 27, 507-519 (2000).
  11. Etminan, M., Myhre, G., Highwood, E. & Shine, K. Radiative forcing of carbon dioxide, methane, and nitrous oxide: A significant revision of the methane radiative forcing. Geophysical Research Letters 43, 12-614 (2016).
  12. Knutti, R. & Hegerl, G. C. The equilibrium sensitivity of the Earth's temperature to radiation changes. Nature Geoscience 1, 735 (2008).
  13. Friedrich, T., Timmermann, A., Tigchelaar, M., Timm, O. E. & Ganopolski, A. Non- linear climate sensitivity and its implications for future greenhouse warming. Science Advances 2, e1501923 (2016).
  14. Hurrell, J. W. et al. The community earth system model: A framework for collaborative research. Bulletin of the American Meteorological Society 94, 1339-1360 (2013).
  15. Peltier, W. R., Argus, D. F. & Drummond, R. Space geodesy constrains ice age terminal deglaciation: The global ICE-6G C (VM5a) model. Journal of Geophysical Research: Solid Earth 120, 450-487 (2015).
  16. Zhu, J. et al. Reduced ENSO variability at the LGM revealed by an isotope-enabled Earth system model. Geophysical Research Letters 44, 6984-6992 (2017).
  17. Meehl, G. A. et al. E↵ects of Model Resolution, Physics, and Coupling on Southern Hemisphere Storm Tracks in CESM1.3. Geophysical Research Letters 46, 12408-12416 (2019).
  18. Hakim, G. J. et al. The last millennium climate reanalysis project: Framework and first results. Journal of Geophysical Research: Atmospheres 121, 6745-6764 (2016).
  19. 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. Paleoceanography and Paleoclimatology 34, 306-315 (2019).
  20. Whitaker, J. S. & Hamill, T. M. Ensemble data assimilation without perturbed obser- vations. Monthly Weather Review 130, 1913-1924 (2002).
  21. Houtekamer, P. L. & Mitchell, H. L. A sequential ensemble Kalman filter for atmospheric data assimilation. Monthly Weather Review 129, 123-137 (2001).
  22. Nash, J. E. & Sutcli↵e, J. V. River flow forecasting through conceptual models part ia discussion of principles. Journal of Hydrology 10, 282-290 (1970).
  23. Gaspari, G. & Cohn, S. E. Construction of correlation functions in two and three dimensions. Quarterly Journal of the Royal Meteorological Society 125, 723-757 (1999).
  24. Taylor, K. et al. Estimating shortwave radiative forcing and response in climate models. Journal of Climate 20, 2530-2543 (2007).
  25. Braconnot, P. & Kageyama, M. Shortwave forcing and feedbacks in last glacial maximum and mid-holocene pmip3 simulations. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 373, 20140424 (2015).

Cited by

Sorted by citations

Authors
Tierney, J. E., Zhu, J., King, J., Malevich, S. B., Hakim, G. J., & Poulsen, C. J.
Affiliations
  • University of Arizona (US)
  • NSF National Center for Atmospheric Research (US)
  • University of Washington (US)
  • University of Michigan (US)
Corresponding author
Tierney, Jessica E.
Venue
Nature
Published
2020-08-26
Volume
584
Issue
7822
Pages
569-573
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2996825230
Cited by
573
References
1
Citations by year
2026: 60 · 2025: 92 · 2024: 85 · 2023: 128 · 2022: 108 · 2021: 90 · 2020: 10
FWCI
26.74
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • EarthArXiv (California Digital Library) (submittedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • EarthArXiv (OSF Preprints) (submittedVersion)
  • EarthArXiv (OSF Preprints) (submittedVersion, cc-by)
Funders
National Science Foundation (1602301, 1602223)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Geology and Paleoclimatology Research
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Cryospheric studies and observations
Keywords
Last Glacial Maximum, glacial cooling, equilibrium climate sensitivity, sea surface temperature reconstruction, geochemical proxies, data assimilation, isotope-enabled climate model, speleothem δ18O, greenhouse gas forcing, ice sheets, mineral dust aerosols

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review