Articles | Volume 3, issue 1
https://doi.org/10.5194/ascmo-3-17-2017
https://doi.org/10.5194/ascmo-3-17-2017
18 Apr 2017
 | 18 Apr 2017

A statistical framework for conditional extreme event attribution

Pascal Yiou, Aglaé Jézéquel, Philippe Naveau, Frederike E. L. Otto, Robert Vautard, and Mathieu Vrac

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Cited articles

Allen, M.: Liability for climate change, Nature, 421, 891–892, 2003.
Bindoff, N., Stott, P., AchutaRao, K., Allen, M., Gillett, N., Gutzler, D., Hansingo, K., Hegerl, G., Hu, Y., Jain, S., Mokhov, I., Overland, J., Perlwitz, J., Sebbari, R., and Zhang, X.: Detection and Attribution of Climate Change: from Global to Regional, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 867–952, 2013.
Cattiaux, J., Vautard, R., Cassou, C., Yiou, P., Masson-Delmotte, V., and Codron, F.: Winter 2010 in Europe: A cold extreme in a warming climate, Geophys. Res. Lett., 37, L20704, https://doi.org/10.1029/2010gl044613, 2010.
Christidis, N. and Stott, P.: Extreme rainfall in the United Kingdom during winter 2013/14: The role of atmospheric circulation and climate change, B. Am. Meteorol. Soc., 96, S46–S50, https://doi.org/10.1175/BAMS-D-15-00094.1, 2015.
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The attribution of classes of extreme events, such as heavy precipitation or heatwaves, relies on the estimate of small probabilities (with and without climate change). Such events are connected to the large-scale atmospheric circulation. This paper links such probabilities with properties of the atmospheric circulation by using a Bayesian decomposition. We test this decomposition on a case of extreme precipitation in the UK, in January 2014.