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

Viewed

Total article views: 3,450 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,150 1,089 211 3,450 174 158
  • HTML: 2,150
  • PDF: 1,089
  • XML: 211
  • Total: 3,450
  • BibTeX: 174
  • EndNote: 158
Views and downloads (calculated since 18 Apr 2017)
Cumulative views and downloads (calculated since 18 Apr 2017)

Viewed (geographical distribution)

Total article views: 3,344 (including HTML, PDF, and XML) Thereof 3,339 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
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.