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Climatic Change

, Volume 137, Issue 1–2, pp 187–200 | Cite as

Investigating the pace of temperature change and its implications over the twenty-first century

  • Yann ChavaillazEmail author
  • Sylvie Joussaume
  • Amaury Dehecq
  • Pascale Braconnot
  • Robert Vautard
Article

Abstract

Most climatological studies characterize the future climate change as the evolution between a fixed current baseline and the future. However, as climate continues to change, ecosystems and societies will need to continuously adapt to a moving target. Here, we consider indicators of the pace of temperature change estimated from CMIP5 projections of an ensemble of climate models. We define the pace as a difference in relevant metrics between two successive 20-year periods, i.e. with a continually moving baseline. Under the strongest emission pathway (RCP8.5), the warming rate strongly increases, and peaks before 2080. All latitudes experience at least a doubling in the warming rate compared to the current period. Significant shifts in temperature distributions above twice the standard deviation between two successive 20-year periods expand from 9 % of continents on average currently to 41 % by 2060 onwards. In these regions, a warm year with a return period of about 50 years would become quite common 20 years later. The fraction of the world population exposed to such shifts will grow from 8 % to about 60 % on average, i.e. 6 billion people. Tropical areas are strongly affected, especially West Africa and South-East Asia. Low mitigation (RCP6.0) limits the warming rate to current values. Medium mitigation (RCP4.5) even reduces population exposure to significant shifts in temperature distributions to negligible values by the end of the century. Strong mitigation (RCP2.6) is the only option that generates a return to values similar to the historical period for all our indicators related to the pace of temperature change. This alternative way to analyze climate projections can yield new insights for the climate impacts and adaptation communities.

Keywords

Land Surface World Population Historical Period Current Period Equilibrium Climate Sensitivity 
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.

Notes

Acknowledgments

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is in charge of the fifth Coupled Model Intercomparison Project, and we thank the climate modeling groups for producing and making available their model output. To analyze the CMIP5 data, this study benefited from the IPSL Prodiguer-Ciclad facility which is supported by CNRS, UPMC, and Labex L-IPSL, which is funded by the ANR (Grant #ANR-10-LABX-0018) and by the European FP7 IS-ENES2 project (Grant #312979). We especially thank S. Denvil and J. Raciazek for supervising data fetching. We also warmly acknowledge R. Knutti at ETH Zürich, C. Nangini at LSCE-IPSL and L. Terray at CERFACS for their comments and useful advice on our work. This study was accomplished as part of a PhD thesis funded by the French Alternative Energies and Atomic Energy Commission (CEA) and the French Ministry of Defense (DGA). We thus acknowledge both organizations for making this work possible.

Supplementary material

10584_2016_1659_MOESM1_ESM.pdf (1.4 mb)
(PDF 1.37 MB)

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Yann Chavaillaz
    • 1
    Email author
  • Sylvie Joussaume
    • 1
  • Amaury Dehecq
    • 1
    • 2
  • Pascale Braconnot
    • 1
  • Robert Vautard
    • 1
  1. 1.Laboratoire des Sciences du Climat et de l’Environnement LSCE/IPSL, CEA-CNRS-UVSQUniversité Paris-SaclayGif-sur-Yvette CedexFrance
  2. 2.Laboratoire LISTICUniversité Savoie Mont Blanc, Polytech Annecy-ChambéryAnnecy-le-Vieux CedexFrance

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