A comparison of storyline attribution methods for a midlatitude cyclone

Since 2004, methods for event attribution have been developed across many groups. Early studies showed that answers to attribution questions are sensitively dependent on the framing of the study used but recently developed methods for storyline attribution have not been compared in detail.

Here, we compare three common methods for storyline attribution, alongside the probabilistic method, based on the midlatitude cyclone Babet. This storm caused flooding in the UK and Ireland in October 2023. The three storyline methods are flow analogues, pseudo-global warming, and forecast-based attribution. We discuss four questions that might be asked of attribution studies by the public: (1) Has climate change impacted the event? (2) How has climate change impacted the frequency of the event? (3) How has climate change impacted the event severity? (4) Were the dynamics of the event influenced by climate change and if yes, how?

We argue that storyline methods are better suited to answer questions about severity changes in events but that probabilistic methods are needed to determine changes in frequency of the event. Limitations and opportunities of the methods need to be clearly communicated to the public when publishing event attribution studies.

Finally, we compare the framing of storyline attribution to that of probabilistic attribution. To the best of our knowledge, this comparison of methods is the first study discussing the differences in the framing and the quantitative results of storyline attribution methods. We hope it represents a basis for future systematic comparisons.