Royal Dutch Meteorological Institute; Ministery Of Infrastructure And The Environment

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A protocol for probabilistic extreme event attribution analyses
by S.Y. Philip (KNMI), S.F. Kew (KNMI), G.J. van Oldenborgh (KNMI), F.E.L. Otto (Environmental Change Institute, University of Oxford), R. Vautard (LSCE/IPSL)K. van der Wiel (KNMI)A. King (University of Melbourne)F. Lott (UK Met Office)J. Arrighi (Red Cross Red Crescent Climate Centre)R. Singh (Red Cross Red Crescent Climate Centre)M. van Aalst (Red Cross Red Crescent Climate Centre)

Over the last few years, methods have been developed to answer questions on the effect of global warming on recent extreme events. Many “event attribution” studies have now been performed, a sizeable fraction even within a few weeks of the event, to increase the usefulness of the results. In doing these analyses, it has become apparent that the attribution itself is only one step of an extended process that leads from the observation of an extreme event to a successfully communicated attribution statement. In this paper we detail the protocol that was developed by the World Weather Attribution group over the course of the last 4 years and about two dozen rapid and slow attribution studies covering warm, cold, wet, dry, and stormy extremes. It starts from the choice of which events to analyse and proceeds with the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis and ends with the communication procedures. This article documents this protocol. It is hoped that our protocol will be useful in designing future event attribution studies and as a starting point of a protocol for an operational attribution service.

Bibliographic data
Philip, S.Y., S.F. Kew, G.J. van Oldenborgh, F.E.L. Otto, R. Vautard, K. van der Wiel, A. King, F. Lott, J. Arrighi, R. Singh and M. van Aalst, A protocol for probabilistic extreme event attribution analyses
Adv in Statistical Climat., Meteor. and Ocean., 2020, 6, 177-203, doi:10.5194/ascmo-6-177-2020.
Abstract (html)  Complete text (pdf: 4 MB)