Letter | Published:

Robust spatially aggregated projections of climate extremes

Nature Climate Change volume 3, pages 10331038 (2013) | Download Citation

Abstract

Many climatic extremes are changing1,2,3,4,5, and decision-makers express a strong need for reliable information on further changes over the coming decades as a basis for adaptation strategies. Here, we demonstrate that for extremes stakeholders will have to deal with large irreducible uncertainties on local to regional scales as a result of internal variability, even if climate models improve rapidly. A multimember initial condition ensemble carried out with an Earth system model shows that trends towards more intense hot and less intense cold extremes may be masked or even reversed locally for the coming three to five decades even if greenhouse gas emissions rapidly increase. Likewise, despite a long-term trend towards more intense precipitation and longer dry spells, multidecadal trends of opposite sign cannot be excluded over many land points. However, extremes may dramatically change at a rate much larger than anticipated from the long-term signal. Despite these large irreducible uncertainties on the local scale, projections are remarkably consistent from an aggregated spatial probability perspective. Models agree that within only three decades about half of the land fraction will see significantly more intense hot extremes. We show that even in the short term the land fraction experiencing more intense precipitation events is larger than expected from internal variability. The proposed perspective yields valuable information for decision-makers and stakeholders at the international level.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    et al. Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset. J. Geophys. Res. Atmos. 118, 2098–2118 (2013).

  2. 2.

    , , , & Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U. S. Geophys. Res. Lett. 36, L23701 (2009).

  3. 3.

    , & Increasing frequency, intensity and duration of observed global heatwaves and warm spells. Geophys. Res. Lett. 39, L20714 (2012).

  4. 4.

    & Increase of extreme events in a warming world. Proc. Natl Acad. Sci. USA 108, 17905–17909 (2011).

  5. 5.

    , & Perception of climate change. Proc. Natl Acad. Sci. USA 109, E2415–E2423 (2012).

  6. 6.

    , & Human contribution to the European heatwave of 2003. Nature 432, 610–614 (2004).

  7. 7.

    , , , & Reconciling two approaches to attribution of the 2010 Russian heat wave. Geophys. Res. Lett. 39, L04702 (2012).

  8. 8.

    , , & Human contribution to more-intense precipitation extremes. Nature 470, 378–381 (2011).

  9. 9.

    Attribution of climate variations and trends to human influences and natural variability. WIREs Clim. Change 2, 925–930 (2011).

  10. 10.

    , , , & Detection of changes in temperature extremes during the second half of the twentieth century. Geophys. Res. Lett. 32, L20716 (2005).

  11. 11.

    , & Detectable changes in the frequency of temperature extremes. J. Clim. 26, 1561–1574 (2013).

  12. 12.

    , , , & Climate extremes indices in the CMIP5 multimodel ensemble: Part 2. Future climate projections. J. Geophys. Res. Atmos. 118, 2473–2493 (2013).

  13. 13.

    , , & Going to the extremes. Climatic Change 79, 185–211 (2006).

  14. 14.

    & Global changes in extreme events: Regional and seasonal dimension. Climatic Change 110, 669–696 (2012).

  15. 15.

    , , & Changes in temperature and precipitation extremes in the CMIP5 ensemble. Climatic Change 119, 345–357 (2013).

  16. 16.

    et al. in Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (eds Field, C. B. et al.) 109–230 (IPCC, Cambridge Univ. Press, 2011).

  17. 17.

    et al. Indices for monitoring changes in extremes based on daily temperature and precipitation data. WIREs Clim. Change 2, 851–870 (2011).

  18. 18.

    , , & Uncertainty in climate change projections: The role of internal variability. Clim. Dynam. 38, 527–546 (2012).

  19. 19.

    & Influence of modes of climate variability on global temperature extremes. J. Clim. 21, 3872–3889 (2008).

  20. 20.

    & Future changes in daily summer temperature variability: driving processes and role for temperature extremes. Clim. Dynam. 33, 917–935 (2009).

  21. 21.

    & The potential to narrow uncertainty in regional climate predictions. Bull. Am. Meteorol. Soc. 90, 1095–1107 (2009).

  22. 22.

    , , & Communication of the role of natural variability in future North American climate. Nature Clim. Change 2, 775–779 (2012).

  23. 23.

    , , & Robustness of future changes in local precipitation extremes. J. Clim. 21, 4280–4297 (2008).

  24. 24.

    , & Mapping model agreement on future climate projections. Geophys. Res. Lett. 38, L23701 (2011).

  25. 25.

    & Robustness and uncertainties in the new CMIP5 climate model projections. Nature Clim. Change 3, 369–373 (2013).

  26. 26.

    et al. When can we expect extremely high surface temperatures? Geophys. Res. Lett. 35, L14703 (2008).

  27. 27.

    , , , & Atmospheric blocking and mean biases in climate models. J. Clim. 23, 6143–6152 (2010).

  28. 28.

    et al. Can correcting feature location in simulated mean climate improve agreement on projected changes? Geophys. Res. Lett. 40, 354–358 (2013).

  29. 29.

    & Robust future precipitation declines in CMIP5 largely reflect the poleward expansion of model subtropical dry zones. Geophys. Res. Lett. 39, L18704 (2012).

  30. 30.

    et al. The community climate system model version 4. J. Clim. 24, 4973–4991 (2011).

Download references

Acknowledgements

This research was supported by the Swiss National Science Foundation.

Author information

Affiliations

  1. Institute for Atmospheric and Climate Science, ETH Zurich, Universitätstrasse 16, 8092 Zurich, Switzerland

    • E. M. Fischer
    • , U. Beyerle
    •  & R. Knutti

Authors

  1. Search for E. M. Fischer in:

  2. Search for U. Beyerle in:

  3. Search for R. Knutti in:

Contributions

E.M.F. carried out the analysis of the models, U.B. carried out the model experiment. All authors contributed extensively to the idea and the writing of this paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to E. M. Fischer.

Supplementary information

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nclimate2051

Further reading