Abstract
Time of emergence, which characterizes when significant signals of climate change will emerge from existing variability, is a useful and increasingly common metric1,2,3. However, a more useful metric for understanding future climate change in the context of past experience may be the ratio of climate signal to noise (S/N)—a measure of the amplitude of change expressed in terms of units of existing variability3. Here, we present S/N projections in the context of emergent climates (termed ‘unusual’, ‘unfamiliar’ and ‘unknown’ by reference to an individual’s lifetime), highlighting sensitivity to future emissions scenarios and geographical and human groupings. We show how for large sections of the world’s population, and for several geopolitical international groupings, mitigation can delay the onset of ‘unknown’ or ‘unfamiliar’ climates by decades, and perhaps even beyond 2100. Our results demonstrate that the benefits of mitigation accumulate over several decades, a key metric of which is reducing S/N, or keeping climate as familiar as possible. A relationship is also identified between cumulative emissions and patterns of emergent climate signals. Timely mitigation will therefore provide the greatest benefits to those facing the earliest impacts, many of whom are alive now.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Quantifying generational and geographical inequality of climate change
Scientific Reports Open Access 25 May 2023
-
Climate change and the global redistribution of biodiversity: substantial variation in empirical support for expected range shifts
Environmental Evidence Open Access 11 April 2023
-
Extreme heat in New Zealand: a synthesis
Climatic Change Open Access 02 September 2022
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Get just this article for as long as you need it
$39.95
Prices may be subject to local taxes which are calculated during checkout




References
Giorgi, F. & Bi, X. Time of emergence (TOE) of GHG-forced precipitation change hot-spots. Geophys. Res. Lett. 36, L06709 (2009).
Mahlstein, I., Knutti, R., Solomon, S. & Portmann, R. W. Early onset of significant local warming in low latitude countries. Environ. Res. Lett. 6, 034009 (2011).
Hawkins, E. & Sutton, R. Time of emergence of climate signals. Geophys. Res. Lett. 39, L01702 (2012).
Lehner, F. & Stocker, T. F. From local perception to global perspective. Nat. Clim. Change 5, 731–734 (2015).
Coumou, D. & Robinson, A. Historic and future increase in the global land area affected by monthly heat extremes. Environ. Res. Lett. 8, 034018 (2013).
Weitzman, M. L. Fat-tailed uncertainty in the economics of catastrophic climate change. Rev. Environ. Econ. Policy 5, 275–292 (2011).
Stern, N. The Economics of Climate Change: The Stern Review (HM Treasury, 2007).
Nordhaus, W. D. & Boyer, J. Roll the DICE Again: Economic Models of Global Warming (MIT Press, 1999).
Tol, R. S. J. Estimates of the damage costs of climate change. Part 2: dynamic estimates. Environ. Res. Econ. 21, 135–160 (2002).
IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) 1–32 (Cambridge Univ. Press, 2014).
Ricke, K. L., Moreno-Cruz, J. B., Schewe, J., Levermann, A. & Caldeira, K. Policy thresholds in mitigation. Nat. Geosci. 9, 5–6 (2016).
Gastner, M. T. & Newman, M. E. J. Diffusion-based method for producing density-equalizing maps. Proc. Natl Acad. Sci. USA 101, 7499–7504 (2004).
Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (IPCC, Cambridge Univ. Press, 2013).
Leduc, M., Matthews, H. D. & de Elia, R. Regional estimates of the transient climate response to cumulative CO2 emissions. Nat. Clim. Change 6, 474–478 (2016).
Collier, P. Wars, Guns, and Votes: Democracy in Dangerous Places (Bodley Head, 2009).
Collier, P. The Bottom Billion: Why the Poorest Countries are Failing and What Can Be Done About It (Oxford Univ. Press, 2007).
Frame, D. J. & Hepburn, C. J. in Climate Change and Common Sense: Essays in Honour of Tom Schelling (eds Hahn, R. W. & Ulph, A.) (Oxford Univ. Press, 2011).
Lazarus, R. J. Super wicked problems and climate change: restraining the present to liberate the future. Cornell Law Rev. 94, 1153–1234 (2009).
IPCC Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge Univ. Press, 2013).
Acknowledgements
D.F., L.J.H. and M.J. acknowledge support from Victoria University of Wellington. E.H. and M.J. acknowledge support from NCAS Climate. D.F. and L.J.H. acknowledge support from the Deep South National Science Challenge. E.H. is funded by a UK NERC Research Fellowship. The authors thank S. Dean and S. Rosier for informative discussions.
Author information
Authors and Affiliations
Contributions
M.J. and D.F. conceived the project. D.F., E.H. and L.J.H. performed the analysis, and M.d.R. produced the cartograms and maps. All authors wrote the paper.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Supplementary information
Supplementary Information
Supplementary Information (PDF 1392 kb)
Rights and permissions
About this article
Cite this article
Frame, D., Joshi, M., Hawkins, E. et al. Population-based emergence of unfamiliar climates. Nature Clim Change 7, 407–411 (2017). https://doi.org/10.1038/nclimate3297
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/nclimate3297
This article is cited by
-
Climate change and the global redistribution of biodiversity: substantial variation in empirical support for expected range shifts
Environmental Evidence (2023)
-
Quantifying generational and geographical inequality of climate change
Scientific Reports (2023)
-
Extreme heat in New Zealand: a synthesis
Climatic Change (2022)
-
Signals in temperature extremes emerge in China during the last millennium based on CMIP5 simulations
Climatic Change (2022)
-
Emerging new climate extremes over Europe
Climate Dynamics (2022)