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Climate constraint reflects forced signal

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Author information

All authors collaborated on the design of the study, the interpretation of the results and writing the manuscript. S.P. performed the analysis using CMIP5 data.

Competing interests

Declared none.

Correspondence to Stephen Po-Chedley.

Extended data figures and tables

  1. Extended Data Fig. 1 The strength of the \(\bar{{\boldsymbol{\Psi }}}\)–ECS relationship depends on the models considered.

    a, \(\bar{\Psi }\) versus ECS for the pre-industrial control experiment (as in Fig. 1a), but including six additional models listed in extended data table 1 of Cox et al.1 (grey) and five additional models not included in their original analysis (red; see Supplementary Information). The black line represents the regression obtained with the original 16-model subset of Cox et al.1, the grey line represents the regression with the 22-model subset (grey and black dots) and the red line represents the regression using all 27 models. The dotted grey lines connect models from a common modelling centre. The correlation coefficient is listed in parentheses for each set of models considered. b, As in a, but for the historical experiment. Using all models and the early historical period (1880–1962) to compute \(\bar{\Psi }\) (as in Fig. 1c), we arrive at a median ECS of 3.4 °C (95% confidence interval of 1.9–4.9 °C).

Supplementary information

  1. Supplementary Methods

    This file contains Supplementary Methods, References and Acknowledgements.

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Further reading

  • Cox et al. reply

    • Peter M. Cox
    • , Mark S. Williamson
    • , Femke J. M. M. Nijsse
    •  & Chris Huntingford

    Nature (2018)

Fig. 1: The ECS constraint depends on the underlying forcing.
Fig. 2: Forced temperature changes contaminate Ψ.
Extended Data Fig. 1: The strength of the \(\bar{{\boldsymbol{\Psi }}}\)–ECS relationship depends on the models considered.

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