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Attribution of extreme weather and climate‐related events

Author

Listed:
  • Peter A. Stott
  • Nikolaos Christidis
  • Friederike E. L. Otto
  • Ying Sun
  • Jean‐Paul Vanderlinden
  • Geert Jan van Oldenborgh
  • Robert Vautard
  • Hans von Storch
  • Peter Walton
  • Pascal Yiou
  • Francis W. Zwiers

Abstract

Extreme weather and climate‐related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human‐induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers. WIREs Clim Change 2016, 7:23–41. doi: 10.1002/wcc.380 This article is categorized under: Paleoclimates and Current Trends > Detection and Attribution Climate Models and Modeling > Knowledge Generation with Models

Suggested Citation

  • Peter A. Stott & Nikolaos Christidis & Friederike E. L. Otto & Ying Sun & Jean‐Paul Vanderlinden & Geert Jan van Oldenborgh & Robert Vautard & Hans von Storch & Peter Walton & Pascal Yiou & Francis W., 2016. "Attribution of extreme weather and climate‐related events," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 7(1), pages 23-41, January.
  • Handle: RePEc:wly:wirecc:v:7:y:2016:i:1:p:23-41
    DOI: 10.1002/wcc.380
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    Cited by:

    1. Harry Haupt & Markus Fritsch, 2022. "Quantile Trend Regression and Its Application to Central England Temperature," Mathematics, MDPI, vol. 10(3), pages 1-20, January.
    2. Chloe H. Lucas & Kate I. Booth, 2020. "Privatizing climate adaptation: How insurance weakens solidaristic and collective disaster recovery," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 11(6), November.
    3. Salvatore Martelli & Valerio Martini & Francesco Mocera & Aurelio Soma’, 2024. "Life Cycle Assessment Comparison of Orchard Tractors Powered by Diesel and Hydrogen Fuel Cell," Energies, MDPI, vol. 17(18), pages 1-29, September.
    4. Kumar, Nikhil & Poonia, Vikas & Gupta, B.B. & Goyal, Manish Kumar, 2021. "A novel framework for risk assessment and resilience of critical infrastructure towards climate change," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    5. Timothy Wilson & Ilan Noy, 2023. "Fifty years of peril: A comprehensive comparison of the impact of terrorism and disasters linked to natural hazards (1970–2019)," Global Policy, London School of Economics and Political Science, vol. 14(5), pages 647-662, November.
    6. Pretis, Felix, 2021. "Exogeneity in climate econometrics," Energy Economics, Elsevier, vol. 96(C).

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