Climate-related risks are dependent not only on the warming trend from GHGs, but also on the variability about the trend. However, assessment of the impacts of climate change tends to focus on the ultimate level of global warming1, only occasionally on the rate of global warming, and rarely on variability about the trend. Here we show that models that are more sensitive to GHGs emissions (that is, higher equilibrium climate sensitivity (ECS)) also have higher temperature variability on timescales of several years to several decades2. Counter-intuitively, high-sensitivity climates, as well as having a higher chance of rapid decadal warming, are also more likely to have had historical ‘hiatus’ periods than lower-sensitivity climates. Cooling or hiatus decades over the historical period, which have been relatively uncommon, are more than twice as likely in a high-ECS world (ECS = 4.5 K) compared with a low-ECS world (ECS = 1.5 K). As ECS also affects the background warming rate under future scenarios with unmitigated anthropogenic forcing, the probability of a hyper-warming decade—over ten times the mean rate of global warming for the twentieth century—is even more sensitive to ECS.
Access optionsAccess options
Subscribe to Journal
Get full journal access for 1 year
only $17.75 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
The datasets generated during the current study are available from the corresponding author on reasonable request.
United Nations Framework Convention on Climate Change (United Nations, 1992).
Lenton, T. M. Early warning of climate tipping points. Nat. Clim. Change 1, 201–209 (2011).
Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).
Stocker, T. F., Dahe, Q. & Plattner, G.-K. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 82–85 (IPCC, Cambridge Univ. Press, 2013).
Otto, A. et al. Energy budget constraints on climate response. Nat. Geosci. 6, 415–416 (2013).
Roe, G. Feedbacks, timescales, and seeing red. Annu. Rev. Earth Planet. Sci. 37, 93–115 (2009).
Strogatz, S. H. Nonlinear Dynamics and Chaos: with Applications to Physics, Biology, Chemistry, and Engineering (Westview, 2000).
Hasselmann, K. Stochastic models of climate extremes: theory and observations. Tellus 28, 473–485 (1976).
Wigley, T. M. L. & Raper, S. C. B. Natural variability of the climate system and detection of the greenhouse effect. Nature 344, 324–327 (1990).
Caldeira, K. & Myhrvold, N. P. Projections of the pace of warming following an abrupt increase in atmospheric carbon dioxide concentration. Environ. Res. Lett. 8, 34039–10 (2013).
Geoffroy, O. et al. Transient climate response in a two-layer energy-balance model. Part I: analytical solution and parameter calibration using CMIP5 AOGCM experiments. J. Clim. 26, 1841–1857 (2013).
Leith, C. E. Climate response and fluctuation dissipation. J. Atmos. Sci. 32, 2022–2026 (1975).
Gottwald, G. A., Wormell, J. P. & Wouters, J. On spurious detection of linear response and misuse of the fluctuation–dissipation theorem in finite time series. Phys. D 331, 89–101 (2016).
Kubo, R. The fluctuation–dissipation theorem. Rep. Prog. Phys. 29, 255–284 (1966).
Lutsko, N. J. & Takahashi, K. What can the internal variability of CMIP5 models tell us about their climate sensitivity? J. Clim. 31, 5051–5069 (2018).
Caldwell, P. M., Zelinka, M. D. & Klein, S. A. Evaluating emergent constraints on equilibrium climate sensitivity. J. Clim. 31, 3921–3942 (2018).
Schwartz, S. E. Heat capacity, time constant, and sensitivity of Earth’s climate system. J. Geophys. Res. 112, 24–25 (2007).
Colman, R. & Power, S. B. What can decadal variability tell us about climate feedbacks and sensitivity? Clim. Dynam. 51, 3815–3828 (2018).
Nijsse, F. J. M. M. & Dijkstra, H. A. A mathematical approach to understanding emergent constraints. Earth Syst. Dynam. 9, 999–1012 (2018).
Roberts, C. D., Palmer, M. D., McNeall, D. & Collins, M. Quantifying the likelihood of a continued hiatus in global warming. Nat. Clim. Change 5, 337–342 (2015).
Smith, D. M. et al. Role of volcanic and anthropogenic aerosols in the recent global surface warming slowdown. Nat. Clim. Change 6, 936–940 (2016).
Medhaug, I., Stolpe, M. B., Fischer, E. M. & Knutti, R. Reconciling controversies about the ‘global warming hiatus’. Nature 545, 41–47 (2017).
Cox, P. M., Huntingford, C. & Williamson, M. S. Emergent constraint on equilibrium climate sensitivity from global temperature variability. Nature 553, 319–322 (2018).
Brown, P. T. & Caldeira, K. Greater future global warming inferred from Earth’s recent energy budget. Nature 552, 45–50 (2017).
Sherwood, S. C., Bony, S. & Dufresne, J. L. Spread in model climate sensitivity traced to atmospheric convective mixing. Nature 505, 37–42 (2014).
Stan Modeling Language Users Guide and Reference Manual Version 2.18.0 (Stan Development Team, 2018).
Williamson, M. S., Cox, P. M. & Nijsse, F. J. M. M. Theoretical foundations of emergent constraints: relationships between climate sensitivity and global temperature variability in conceptual models. Dynam. Stat. Clim. Syst. 3, dzy006 (2018).
Nijsse, F. J. M. M., Cox, P. M., Huntingford, C. & Williamson, M. S. Decadal variability and climate sensitivity [Source Code]. (Code Ocean, 2019); https://doi.org/10.24433/CO.6887733.v1
This work was supported by the European Research Council ECCLES project, grant agreement number 742472 (F.J.M.M.N. and P.M.C.); the EU Horizon 2020 Research Programme CRESCENDO project, grant agreement number 641816 (P.M.C. and 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 Supplementary Table 1) for producing and making available their model output.
The authors declare no competing interests.
Peer review information: Nature Climate Change thanks Patrick Brown and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figs. 1–5, Table 1 and references.