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Assumptions for emergent constraints

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

The Original Article was published on 18 January 2018

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Fig. 1: Analysis of simulated and observed time series using three methods to isolate unforced variability.
Fig. 2: Comparison of the central estimate and likely range of ECS for various methods and for four observational datasets.


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Authors and Affiliations



P.T.B. and M.B.S. performed the analysis. P.T.B. wrote an initial draft of the manuscript. All authors contributed to interpreting the results and refining the manuscript.

Corresponding author

Correspondence to Patrick T. Brown.

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Competing interests

Declared none.

Extended data figures and tables

Extended Data Fig. 1 Ψ metric of temperature variability versus time.

This figure is analogous to figure 2a in Cox et al.1, but without data from ACCESS1-0, inmcm4, IPSL-CM5B-LR, MPI-ESM-LR, GFDL-ESM2G, MIROC5 and bcc-csm1-1-m because not all required simulations were available for these models. Black lines correspond to Ψ calculated from the historical experiment, which includes all forcings. Blue lines correspond to Ψ calculated from the historical–natural experiment (‘historicalNat’), which includes only forcings from changes in incoming solar radiation and volcanic aerosols. Red lines correspond to Ψ calculated from the historical greenhouse gas experiment (‘historicalGHG’), which includes only forcing from well-mixed greenhouse gases (and ozone in some models). Thin lines are individual model-ensemble members (r1i1p1) and thick lines are multi-model means (MMMs). The data show that Ψ (as calculated by Cox et al.1) is non-stationary and inflated towards the end of the record, even in the case where models are forced by only greenhouse gases.

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Supplementary Material

This file contains assumptions for emergent constraints.

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Brown, P.T., Stolpe, M.B. & Caldeira, K. Assumptions for emergent constraints. Nature 563, E1–E3 (2018).

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