Letter | Published:

Emergent constraint on equilibrium climate sensitivity from global temperature variability

Nature volume 553, pages 319322 (18 January 2018) | Download Citation


Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5–4.5 degrees Celsius for more than 25 years1. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2–3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship2 between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming3, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

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This work was supported by the European Research Council (ERC) ECCLES project, grant agreement number 742472 (P.M.C.); the EU Horizon 2020 Research Programme CRESCENDO project, grant agreement number 641816 (P.M.C. and M.S.W.); the EPSRC-funded ReCoVER project (M.S.W.); and the NERC CEH National Capability fund (C.H.). We also acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups (listed in Extended Data Table 1 of this paper) for producing and making available their model output.

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  1. College of Engineering, Mathematics and Physical Science, University of Exeter, Exeter EX4 4QF, UK

    • Peter M. Cox
    •  & Mark S. Williamson
  2. Centre for Ecology and Hydrology, Wallingford OX10 8BB, UK

    • Chris Huntingford


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All authors collaboratively designed the study and contributed to the manuscript. P.M.C. led the study and drafted the manuscript. C.H. was the lead on the time-series data for the CMIP5 models. M.S.W. led on the theoretical analysis.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Peter M. Cox.

Reviewer Information Nature thanks P. Forster and T. Mauritsen for their contribution to the peer review of this work.

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