1. Introduction

A warming climate affects precipitation extremes, through both thermodynamic and dynamic processes (Eden et al., 2016). At two thirds of global weather stations, annual precipitation maxima have increased since 1950 (Sun et al., 2021; Westra et al., 2013), and record-breaking daily extremes have significantly increased, especially since the 1980s (Lehmann et al., 2015). These increases are broadly consistent with the thermodynamic effect prescribed by the Clausius-Clapeyron relationship (Fischer & Knutti, 2016). Besides extreme precipitation, peak river discharge is also changing around the globe (Do et al., 2017; Slater et al., 2021), raising questions on the role of anthropogenic climate change in the occurrence of floods (Blöschl et al., 2017; Kundzewicz et al., 2014).
To address questions about the effect of climate change on specific extreme weather events, a research line has emerged in the last two decades, called extreme event attribution. This field evolved from detection and attribution of the so-called “fingerprints” of anthropogenic global warming (Stone & Allen, 2005; Stott et al., 2004). Several methods have been proposed (Uhe et al., 2016). The key concepts underlying these methods are: 1) to detect trends in the observed historical occurrence of events as the one in question, or more extreme; and 2) if a trend emerges, to assess the potential influence of climate change on the probability of the event, by comparing results from climate models of the factual climate (i.e., with anthropogenic greenhouse forcing) and of the counterfactual climate (i.e., with pre-industrial levels of greenhouse forcing) (NASEM, 2016). This is sometimes referred to as ‘probabilistic’ extreme event attribution, as it allows to make probabilistic attribution statements. A main motivation behind this research is to address the pressing societal and policy questions about the cause of the disaster. Reflecting the urgency of the questions, these studies are frequently and prominently featured in the media (Osaka et al., 2020). For example, the popular website Carbon Brief maintains an inventory of attribution studies, in an interactive global map (Fig. 1). Out of 504 attribution studies, including both peer-reviewed and ‘rapid’ studies, 126 concern the attribution of “rain and flooding” events. Most of these studies found that the likelihood of the event was significantly altered by climate change (red markers).