Climatic Change

, Volume 144, Issue 2, pp 131–142 | Cite as

Assessing climate change impacts on extreme weather events: the case for an alternative (Bayesian) approach

  • Michael E. MannEmail author
  • Elisabeth A. Lloyd
  • Naomi Oreskes


The conventional approach to detecting and attributing climate change impacts on extreme weather events is generally based on frequentist statistical inference wherein a null hypothesis of no influence is assumed, and the alternative hypothesis of an influence is accepted only when the null hypothesis can be rejected at a sufficiently high (e.g., 95% or “p = 0.05”) level of confidence. Using a simple conceptual model for the occurrence of extreme weather events, we show that if the objective is to minimize forecast error, an alternative approach wherein likelihoods of impact are continually updated as data become available is preferable. Using a simple “proof-of-concept,” we show that such an approach will, under rather general assumptions, yield more accurate forecasts. We also argue that such an approach will better serve society, in providing a more effective means to alert decision-makers to potential and unfolding harms and avoid opportunity costs. In short, a Bayesian approach is preferable, both empirically and ethically.



We thank James V. Stone, Psychology Department, Sheffield University, Sheffield, England for kindly posting the Bayesian coin flipping routine (MatLab code version 7.5. downloaded from We thank two anonymous reviewers for the helpful comments on the initial draft of this article.

Supplementary material

10584_2017_2048_MOESM1_ESM.docx (73 kb)
Fig. S1 (DOCX 73 kb)


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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  • Michael E. Mann
    • 1
    Email author
  • Elisabeth A. Lloyd
    • 2
  • Naomi Oreskes
    • 3
  1. 1.Department of Meteorology and Atmospheric SciencePenn State UniversityUniversity ParkUSA
  2. 2.History and Philosophy of Science DepartmentIndiana UniversityBloomingtonUSA
  3. 3.History of Science DepartmentHarvard UniversityCambridgeUSA

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