Literature DB >> 36215472

Spatial patterns of climate change across the Paleocene-Eocene Thermal Maximum.

Jessica E Tierney1, Jiang Zhu2, Mingsong Li3, Andy Ridgwell4, Gregory J Hakim5, Christopher J Poulsen6, Ross D M Whiteford7, James W B Rae7, Lee R Kump8.   

Abstract

The Paleocene-Eocene Thermal Maximum (PETM; 56 Ma) is one of our best geological analogs for understanding climate dynamics in a "greenhouse" world. However, proxy data representing the event are only available from select marine and terrestrial sedimentary sequences that are unevenly distributed across Earth's surface, limiting our view of the spatial patterns of climate change. Here, we use paleoclimate data assimilation (DA) to combine climate model and proxy information and create a spatially complete reconstruction of the PETM and the climate state that precedes it ("PETM-DA"). Our data-constrained results support strong polar amplification, which in the absence of an extensive cryosphere, is related to temperature feedbacks and loss of seasonal snow on land. The response of the hydrological cycle to PETM warming consists of a narrowing of the Intertropical Convergence Zone, off-equatorial drying, and an intensification of seasonal monsoons and winter storm tracks. Many of these features are also seen in simulations of future climate change under increasing anthropogenic emissions. Since the PETM-DA yields a spatially complete estimate of surface air temperature, it yields a rigorous estimate of global mean temperature change (5.6 ∘C; 5.4 ∘C to 5.9 ∘C, 95% CI) that can be used to calculate equilibrium climate sensitivity (ECS). We find that PETM ECS was 6.5 ∘C (5.7 ∘C to 7.4 ∘C, 95% CI), which is much higher than the present-day range. This supports the view that climate sensitivity increases substantially when greenhouse gas concentrations are high.

Entities:  

Keywords:  Paleocene–Eocene Thermal Maximum; climate sensitivity; data assimilation; greenhouse climates; hydrological cycle

Mesh:

Substances:

Year:  2022        PMID: 36215472      PMCID: PMC9586325          DOI: 10.1073/pnas.2205326119

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   12.779


  21 in total

1.  A blast of gas in the latest Paleocene: simulating first-order effects of massive dissociation of oceanic methane hydrate.

Authors:  G R Dickens; M M Castillo; J C Walker
Journal:  Geology       Date:  1997-03       Impact factor: 5.399

2.  State-dependent climate sensitivity in past warm climates and its implications for future climate projections.

Authors:  Rodrigo Caballero; Matthew Huber
Journal:  Proc Natl Acad Sci U S A       Date:  2013-08-05       Impact factor: 11.205

3.  Large-scale ocean deoxygenation during the Paleocene-Eocene Thermal Maximum.

Authors:  Weiqi Yao; Adina Paytan; Ulrich G Wortmann
Journal:  Science       Date:  2018-07-19       Impact factor: 47.728

4.  Fluvial response to abrupt global warming at the Palaeocene/Eocene boundary.

Authors:  Brady Z Foreman; Paul L Heller; Mark T Clementz
Journal:  Nature       Date:  2012-10-24       Impact factor: 49.962

Review 5.  Past climates inform our future.

Authors:  Jessica E Tierney; Christopher J Poulsen; Isabel P Montañez; Tripti Bhattacharya; Ran Feng; Heather L Ford; Bärbel Hönisch; Gordon N Inglis; Sierra V Petersen; Navjit Sagoo; Clay R Tabor; Kaustubh Thirumalai; Jiang Zhu; Natalie J Burls; Gavin L Foster; Yves Goddéris; Brian T Huber; Linda C Ivany; Sandra Kirtland Turner; Daniel J Lunt; Jennifer C McElwain; Benjamin J W Mills; Bette L Otto-Bliesner; Andy Ridgwell; Yi Ge Zhang
Journal:  Science       Date:  2020-11-06       Impact factor: 47.728

6.  Arctic hydrology during global warming at the Palaeocene/Eocene thermal maximum.

Authors:  Mark Pagani; Nikolai Pedentchouk; Matthew Huber; Appy Sluijs; Stefan Schouten; Henk Brinkhuis; Jaap S Sinninghe Damsté; Gerald R Dickens
Journal:  Nature       Date:  2006-08-10       Impact factor: 49.962

7.  Robust Hadley Circulation changes and increasing global dryness due to CO2 warming from CMIP5 model projections.

Authors:  William K M Lau; Kyu-Myong Kim
Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-23       Impact factor: 11.205

8.  The seawater carbon inventory at the Paleocene-Eocene Thermal Maximum.

Authors:  Laura L Haynes; Bärbel Hönisch
Journal:  Proc Natl Acad Sci U S A       Date:  2020-09-14       Impact factor: 11.205

9.  Extreme warmth and heat-stressed plankton in the tropics during the Paleocene-Eocene Thermal Maximum.

Authors:  Joost Frieling; Holger Gebhardt; Matthew Huber; Olabisi A Adekeye; Samuel O Akande; Gert-Jan Reichart; Jack J Middelburg; Stefan Schouten; Appy Sluijs
Journal:  Sci Adv       Date:  2017-03-03       Impact factor: 14.136

10.  Simulation of Eocene extreme warmth and high climate sensitivity through cloud feedbacks.

Authors:  Jiang Zhu; Christopher J Poulsen; Jessica E Tierney
Journal:  Sci Adv       Date:  2019-09-18       Impact factor: 14.136

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