Climate Dynamics

, Volume 49, Issue 9–10, pp 3051–3073 | Cite as

Quantifying the effect of interannual ocean variability on the attribution of extreme climate events to human influence

  • Mark D. Risser
  • Dáithí A. Stone
  • Christopher J. Paciorek
  • Michael F. Wehner
  • Oliver Angélil
Article

Abstract

In recent years, the climate change research community has become highly interested in describing the anthropogenic influence on extreme weather events, commonly termed “event attribution.” Limitations in the observational record and in computational resources motivate the use of uncoupled, atmosphere/land-only climate models with prescribed ocean conditions run over a short period, leading up to and including an event of interest. In this approach, large ensembles of high-resolution simulations can be generated under factual observed conditions and counterfactual conditions that might have been observed in the absence of human interference; these can be used to estimate the change in probability of the given event due to anthropogenic influence. However, using a prescribed ocean state ignores the possibility that estimates of attributable risk might be a function of the ocean state. Thus, the uncertainty in attributable risk is likely underestimated, implying an over-confidence in anthropogenic influence. In this work, we estimate the year-to-year variability in calculations of the anthropogenic contribution to extreme weather based on large ensembles of atmospheric model simulations. Our results both quantify the magnitude of year-to-year variability and categorize the degree to which conclusions of attributable risk are qualitatively affected. The methodology is illustrated by exploring extreme temperature and precipitation events for the northwest coast of South America and northern-central Siberia; we also provides results for regions around the globe. While it remains preferable to perform a full multi-year analysis, the results presented here can serve as an indication of where and when attribution researchers should be concerned about the use of atmosphere-only simulations.

Keywords

Climate change Anthropogenic Event attribution Extreme weather Risk ratio 

Notes

Acknowledgements

This work was supported by the Regional and Global Climate Modeling Program of the Office of Biological and Environmental Research in the Department of Energy Office of Science under contract number DE-AC02-05CH11231. This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.

Supplementary material

382_2016_3492_MOESM1_ESM.pdf (209 kb)
Supplementary material 1 (PDF 210 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Mark D. Risser
    • 1
  • Dáithí A. Stone
    • 2
  • Christopher J. Paciorek
    • 3
  • Michael F. Wehner
    • 2
  • Oliver Angélil
    • 4
  1. 1.Climate and Ecosystem Sciences DivisionLawrence Berkeley National LaboratoryBerkeleyUSA
  2. 2.Computational Research DivisionLawrence Berkeley National LaboratoryBerkeleyUSA
  3. 3.Department of StatisticsUniversity of California BerkeleyBerkeleyUSA
  4. 4.Climate Change Research CentreUniversity of New South WalesKensingtonUSA

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