Climate Dynamics

, Volume 45, Issue 5–6, pp 1547–1564 | Cite as

Fast-track attribution assessments based on pre-computed estimates of changes in the odds of warm extremes

  • Nikolaos ChristidisEmail author
  • Peter A. Stott
  • Francis W. Zwiers


Regional warming due to anthropogenic influence on the climate is expected to increase the frequency of very warm years and seasons. The growing research area of extreme event attribution has provided pertinent scientific evidence for a number of such warm events for which the forced climate response rises above internal climatic variability. Although the demand for attribution assessments is higher shortly after an event occurs, most scientific studies become available several months later. A formal attribution methodology is employed here to pre-compute the changing odds of very warm years and seasons in regions across the world. Events are defined based on the exceedence of temperature thresholds and their changing odds are measured over a range of pre-specified thresholds, which means assessments can be made as soon as a new event happens. Optimal fingerprinting provides observationally constrained estimates of the global temperature response to external forcings from which regional information is extracted. This information is combined with estimates of internal variability to construct temperature distributions with and without the effect of anthropogenic influence. The likelihood of an event is computed for each distribution and the change in the odds estimated. Analyses are conducted with seven climate models to explore the model dependency of the results. Apart from colder regions and seasons, characterised by greater internal climate variability, the odds of warm events are found to have significantly increased and temperatures above the threshold of 1-in-10 year events during 1961–1990 have become at least twice as likely to occur.


Detection and attribution Regional temperature extremes Anthropogenic forcings 



We thank the two reviewers for their constructive comments. NC and PAS were supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101) and the EUCLEIA project funded by the European Union’s Seventh Framework Programme [FP7/2007-2013] under Grant Agreement No. 607085.


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Copyright information

© Crown Copyright 2014

Authors and Affiliations

  • Nikolaos Christidis
    • 1
    Email author
  • Peter A. Stott
    • 1
  • Francis W. Zwiers
    • 2
  1. 1.Met Office Hadley CentreExeterUK
  2. 2.Pacific Climate Impacts Consortium, Sedgewick C183University of VictoriaVictoriaCanada

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