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Emergent constraint on equilibrium climate sensitivity from global temperature variability

Author

Listed:
  • Peter M. Cox

    (College of Engineering, Mathematics and Physical Science, University of Exeter)

  • Chris Huntingford

    (Centre for Ecology and Hydrology)

  • Mark S. Williamson

    (College of Engineering, Mathematics and Physical Science, University of Exeter)

Abstract

Equilibrium climate sensitivity—which remains the largest uncertainty in climate projections—is constrained to a ‘likely’ range of 2.2–3.4 K by taking into account the variability of global temperature about long-term historical warming.

Suggested Citation

  • Peter M. Cox & Chris Huntingford & Mark S. Williamson, 2018. "Emergent constraint on equilibrium climate sensitivity from global temperature variability," Nature, Nature, vol. 553(7688), pages 319-322, January.
    • Handle: RePEc:nat:nature:v:553:y:2018:i:7688:d:10.1038_nature25450
    DOI: 10.1038/nature25450
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    Cited by:

    1. Yan Yu & Jiafu Mao & Stan D. Wullschleger & Anping Chen & Xiaoying Shi & Yaoping Wang & Forrest M. Hoffman & Yulong Zhang & Eric Pierce, 2022. "Machine learning–based observation-constrained projections reveal elevated global socioeconomic risks from wildfire," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    2. Roxana Dumitrescu & Marcos Leutscher & Peter Tankov, 2024. "Energy transition under scenario uncertainty: a mean-field game of stopping with common noise," Mathematics and Financial Economics, Springer, volume 18, number 4, December.
    3. Wagner, Gernot & Weitzman, Martin L., 2018. "Potentially large equilibrium climate sensitivity tail uncertainty," Economics Letters, Elsevier, vol. 168(C), pages 144-146.
    4. Bruns, Stephan B. & Csereklyei, Zsuzsanna & Stern, David I., 2020. "A multicointegration model of global climate change," Journal of Econometrics, Elsevier, vol. 214(1), pages 175-197.
    5. Dilger, Alexander, 2020. "Wirtschaftsethische Überlegungen zum Klimawandel," Discussion Papers of the Institute for Organisational Economics 5/2020, University of Münster, Institute for Organisational Economics.
    6. Ziming Chen & Tianjun Zhou & Xiaolong Chen & Wenxia Zhang & Lixia Zhang & Mingna Wu & Liwei Zou, 2022. "Observationally constrained projection of Afro-Asian monsoon precipitation," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    7. Wenyu Zhou & L. Ruby Leung & Nicholas Siler & Jian Lu, 2023. "Future precipitation increase constrained by climatological pattern of cloud effect," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    8. Michel Damian & Luigi De Paoli, 2017. "Climate change: Back to development," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2017(3), pages 5-24.
    9. Lucile Ricard & Fabrizio Falasca & Jakob Runge & Athanasios Nenes, 2024. "network-based constraint to evaluate climate sensitivity," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    10. Carlos A. Sierra & Holger Metzler & Markus Müller & Eurika Kaiser, 2021. "Closed-loop and congestion control of the global carbon-climate system," Climatic Change, Springer, vol. 165(1), pages 1-24, March.
    11. Dipu, Sudhakar & Quaas, Johannes & Quaas, Martin & Rickels, Wilfried & Mülmenstädt, Johannes & Boucher, Olivier, 2021. "Substantial Climate Response outside the Target Area in an Idealized Experiment of Regional Radiation Management," Open Access Publications from Kiel Institute for the World Economy 240193, Kiel Institute for the World Economy (IfW Kiel).
    12. Francisco Estrada & Oscar Calder'on-Bustamante & Wouter Botzen & Juli'an A. Velasco & Richard S. J. Tol, 2021. "AIRCC-Clim: a user-friendly tool for generating regional probabilistic climate change scenarios and risk measures," Papers 2111.01762, arXiv.org.
    13. Roman Olson & Soon-Il An & Yanan Fan & Jason P Evans, 2019. "Accounting for skill in trend, variability, and autocorrelation facilitates better multi-model projections: Application to the AMOC and temperature time series," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-24, April.
    14. David B. Stephenson & Alemtsehai A. Turasie & Donald P. Cummins, 2023. "More Accurate Climate Trend Attribution by Using Cointegrating Vector Time Series Models," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    15. Chris Huntingford & Mark S. Williamson & Femke J. M. M. Nijsse, 2020. "CMIP6 climate models imply high committed warming," Climatic Change, Springer, vol. 162(3), pages 1515-1520, October.
    16. Sergei Soldatenko & Alexey Bogomolov & Andrey Ronzhin, 2021. "Mathematical Modelling of Climate Change and Variability in the Context of Outdoor Ergonomics," Mathematics, MDPI, vol. 9(22), pages 1-25, November.
    17. Yuanfang Chai & Yao Yue & Louise J. Slater & Jiabo Yin & Alistair G. L. Borthwick & Tiexi Chen & Guojie Wang, 2022. "Constrained CMIP6 projections indicate less warming and a slower increase in water availability across Asia," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    18. Michel Damian & Luigi de Paoli, 2018. "Climate change: Back to development," Post-Print hal-01870974, HAL.

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