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).