Validation of a rapid attribution of the May/June 2016 flood-inducing precipitation in France to climate change

Sjoukje Philip*, Sarah F. Kew, Geert Jan van Oldenborgh, Emma Aalbers, Robert Vautard, Friederike Otto, Karsten Haustein, Florence Habets, Roop Singh

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The extreme precipitation that resulted in historic flooding in central-northern France began 26 May 2016 and was linked to a large cutoff low. The floods caused some casualties and over a billion euros in damage. To objectively answer the question of whether anthropogenic climate change played a role, a near-real-time "rapid" attribution analysis was performed, using well-established event attribution methods, best available observational data, and as many climate simulations as possible within that time frame. This study confirms the results of the rapid attribution study. We estimate how anthropogenic climate change has affected the likelihood of exceedance of the observed amount of 3-day precipitation in April-June for the Seine and Loire basins. We find that the observed precipitation in the Seine basin was very rare, with a return period of hundreds of years. It was less rare on the Loire-roughly 1 in 20 years. We evaluated five climate model ensembles for 3-day basin-averaged precipitation extremes in April-June. The four ensembles that simulated the statistics agree well. Combining the results reduces the uncertainty and indicates that the probability of such rainfall has increased over the last century by about a factor of 2.2 ( > 1.4) on the Seine and 1.9 ( > 1.5) on the Loire due to anthropogenic emissions. These numbers are virtually the same as those in the near-real-time attribution study by van Oldenborgh et al. Together with the evaluation of the attribution of Storm Desmond by Otto et al., this shows that, for these types of events, near-real-time attribution studies are now possible.

Original languageEnglish
Pages (from-to)1881-1898
Number of pages18
JournalJournal of Hydrometeorology
Volume19
Issue number11
DOIs
Publication statusPublished - 1 Nov 2018

Keywords

  • Climate change
  • Climate models

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