Climatic Change

, Volume 119, Issue 2, pp 345–357 | Cite as

Changes in temperature and precipitation extremes in the CMIP5 ensemble

  • V. V. KharinEmail author
  • F. W. Zwiers
  • X. Zhang
  • M. Wehner


Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.


Return Period Precipitation Extreme Generalize Extreme Value Generalize Extreme Value Distribution Cold Extreme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Supplementary material

10584_2013_705_MOESM1_ESM.pdf (58.8 mb)
(PDF 58.8 MB)


  1. Alexander LV et al (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111. doi: 10.1029/2005JD006290 Google Scholar
  2. Allen MR, Ingram WJ (2002) Constraints on future changes in climate and the hydrologic cycle. Nature 419:224–232. doi: 10.1038/nature01092 CrossRefGoogle Scholar
  3. Boer GJ (1993) Climate change and the regulation of the surface moisture and energy budgets. Clim Dyn 8:225–239. doi: 10.1007/BF00198617 CrossRefGoogle Scholar
  4. Dee DP et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. doi: 10.1002/qj.828 CrossRefGoogle Scholar
  5. Dupuis DJ, Tsao M (1998) A hybrid estimator for the generalized Pareto and extreme-value distributions. Commun Stat, Theory Methods 27:925–941. doi: 10.1080/03610929808832136 CrossRefGoogle Scholar
  6. Hosking JRM (1990) L-moments: analysis and estimation of distributions using linear combinations of order statistics. J R Stat Soc 52:105–124Google Scholar
  7. Kharin VV, Zwiers FW (2005) Estimating extremes in transient climate change simulations. J Climate 18:1156–1173CrossRefGoogle Scholar
  8. Kharin VV, Zwiers FW, Zhang X (2005) Intercomparison of near surface temperature and precipitation extremes in AMIP–2 simulations, reanalyses, and observations. J Climate 18:5201–5223CrossRefGoogle Scholar
  9. Kharin VV, Zwiers FW, Zhang X, Hegerl GC (2007) Changes in temperature and precipitation extremes in the IPCC ensemble of global coupled model simulations. J Climate 20:1419–1444CrossRefGoogle Scholar
  10. Klein Tank AMG, Zwiers FW, Zhang X (2009) Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation. Climate data and monitoring WCDMP-No 72, WMO-TD No 1500, 56 ppGoogle Scholar
  11. Min SK, Zhang X, Zwiers FW, Hegerl GC (2011) Human contribution to more-intense precipitation extremes. Nature 470:378–381CrossRefGoogle Scholar
  12. Moss RH et al (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756CrossRefGoogle Scholar
  13. Mueller B, Seneviratne SI (2012) Hot days induced by precipitation deficits at the global scale. PNAS. doi: 10.1073/pnas.1204330109 Google Scholar
  14. Nakicenovic N, Swart R (2000) IPCC special report on emission scenarios. Cambridge University Press, Cambridge. ISBN 0521804930, 612 ppGoogle Scholar
  15. Seneviratne SI et al (2012) Changes in climate extremes and their impacts on the natural physical environment. In: Managing the risks of extreme events and disasters to advance climate change adaptation. A special report of working groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 109–230Google Scholar
  16. Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013a) Climate extremes indices in the CMIP5 multi-model ensemble. Part 1: model evaluation in the present climate. J Geophys Res, in press. doi: 10.1002/jgrd.50203 Google Scholar
  17. Sillmann J, Kharin VV, Zwiers FW, Zhang X, Bronaugh D (2013b) Climate extremes indices in the CMIP5 multi-model ensemble. Part 2: Future projections. J Geophys Res, in press. doi: 10.1002/jgrd.50188 Google Scholar
  18. Solomon S et al (2007) Climate change 2007: the physical science basis, contribution of working group I to the fourth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge. ISBN 978-0-521-88009-1Google Scholar
  19. Tebaldi C, Hayhoe K, Arblaster JM, Meehl GA (2006) Going to the extremes: an intercomparison of model-simulated historical and future changes in extreme events. Clim Change 79:185–211. doi: 10.1007/s10584-006-9051-4 CrossRefGoogle Scholar
  20. von Storch H, Zwiers FW (2012) Testing ensembles of climate change scenarios for “statistical significance”. Clim Change. doi: 10.1007/s10584-012-0551-0 Google Scholar

Copyright information

© Crown Copyright 2013

Authors and Affiliations

  • V. V. Kharin
    • 1
    Email author
  • F. W. Zwiers
    • 2
  • X. Zhang
    • 3
  • M. Wehner
    • 4
  1. 1.Canadian Centre for Climate Modelling and AnalysisEnvironment CanadaVictoriaCanada
  2. 2.Pacific Climate Impacts ConsortiumUniversity of VictoriaVictoriaCanada
  3. 3.Climate Data and Analysis SectionEnvironment CanadaTorontoCanada
  4. 4.Lawrence Berkeley National LaboratoryBerkeleyUSA

Personalised recommendations