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Emergent constraint on equilibrium climate sensitivity from global temperature variability

A Brief Communications Arising to this article was published on 31 October 2018

A Brief Communications Arising to this article was published on 31 October 2018

A Brief Communications Arising to this article was published on 31 October 2018


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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Figure 1: Historical global warming.
Figure 2: Metric of global mean temperature variability.
Figure 3: Emergent constraint on ECS.
Figure 4: Sensitivity of the emergent constraint on ECS to window width.

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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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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.

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Correspondence to Peter M. Cox.

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The authors declare no competing financial interests.

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

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Extended data figures and tables

Extended Data Figure 1 Test of emergent relationship against models not used in the calibration.

The test set includes additional models from some climate centres (labelled ‘f x’, ‘f y’ and so on), and initial condition ensembles with particular models (labelled ‘c2’, ‘c3’ and so on). The black dot-dashed line shows the best-fit linear regression across the model ensemble, with the prediction error for the fit given by the black dashed lines (see Methods). The vertical blue lines show the observational constraint from the HadCRUT4 observations: the mean (dot-dashed line) and the mean plus and minus one standard deviation (dashed lines). Individual CMIP5 model runs are denoted by the letters listed in Extended Data Table 1.

Extended Data Figure 2 Comparison of Ψ statistics for the 16 CMIP5 models from ‘filtered-mean’ temperature and global-mean temperature.

The filtered model output calculates area-mean values of temperature using only the points where there are observations in the HadCRUT4 dataset. All cases analyse 1880–2016 and use a 55-yr window width. The dotted line is the 1:1 line.

Extended Data Figure 3 Gradient of emergent relationship between ECS and Ψ as a function of window width.

The dotted line shows the gradient predicted with equation (2) using the ensemble-mean value of Q2×CO2/σN. Note that the theory (dot-dashed line) fits best at the optimal window width of 55 yr. All cases here analyse 1880–2016 and use the 16-model ensemble.

Extended Data Table 1 Earth system models used in this study, as provided by the CMIP5 project19
Extended Data Table 2 Robustness of the emergent constraint to the choice of observational dataset and model ensemble

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Cox, P., Huntingford, C. & Williamson, M. Emergent constraint on equilibrium climate sensitivity from global temperature variability. Nature 553, 319–322 (2018).

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