Uncertain Numbers, Clear Causes: Lessons on uncertainty from 10 years of attributing extreme weather events to climate change

Extreme event attribution studies are becoming increasingly prominent, with nearly 1,000 analyses conducted to date and many more expected as operational attribution services are being launched. While the field is growing rapidly, this proliferation raises an important question: how can we ensure that each study meaningfully contributes to our understanding of climate change impacts, rather than merely adding to a growing volume of isolated results? Just as in broader climate science, it is essential to understand how different lines of evidence combine, to translate this surge of activity into robust, cumulative knowledge.

This keynote examines what causal links climate scientists can legitimately make, how these links are established, and how uncertainty shapes—but does not preclude—robust conclusions. Drawing on more than a decade of experience from World Weather Attribution (WWA), it uses event attribution studies as a central example of scientific causal reasoning. Event attribution assesses whether and to what extent human-induced climate change has
altered the likelihood or severity of specific extreme weather events. Such studies have become routine, with heatwaves dominating in Europe and globally and heavy rainfall studies concentrated in parts of Asia and North America, while major gaps remain in the rest of the world.

Recent findings highlight that often, differences between datasets explain more variance than the precise definition of an event. This has implications for the added value of further quantitative attribution in well-studied regions and for identifying when new analyses are scientifically necessary, and in general for the meaningfulness of granular climate information.