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  • Author or Editor: Julien Cattiaux x
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Julien Cattiaux
and
Aurélien Ribes

Abstract

Weather extremes are the showcase of climate variability. Given their societal and environmental impacts, they are of great public interest. The prevention of natural hazards, the monitoring of single events, and, more recently, their attribution to anthropogenic climate change constitute key challenges for both weather services and scientific communities. Before a single event can be scrutinized, it must be properly defined; in particular, its spatiotemporal characteristics must be chosen. So far, this definition is made with some degree of arbitrariness, yet it might affect conclusions when explaining an extreme weather event from a climate perspective. Here, we propose a generic road map for defining single events as objectively as possible. In particular, as extreme events are inherently characterized by a small probability of occurrence, we suggest selecting the space–time characteristics that minimize this probability. In this way, we are able to automatically identify the spatiotemporal scale at which the event has been the most extreme. According to our methodology, the European heat wave of summer 2003 would be defined as a 2-week event over France and Spain and the Boulder, Colorado, intense rainfall of September 2013 a 5-day local event. Importantly, we show that in both cases, maximizing the rarity of the event does not maximize (or minimize) its fraction of attributable risk to anthropogenic climate change.

Full access
Julien Cattiaux
,
Aurélien Ribes
, and
Vikki Thompson

Abstract

Because they are rare, extreme weather events have critical impacts on societies and ecosystems and attract public and scientific attention. The most unusual events are regularly documented as part of routine climate monitoring by meteorological services. A growing number of attribution studies also aim at quantifying how their probability has evolved under human-induced climate change. However, it is often recognized that (i) the selection of studied events is geographically uneven, and (ii) the definition of a given event, in particular, its spatiotemporal scale, is subjective, which may impact attribution statements. Here we present an original method that objectively selects, defines, and compares extreme events that have occurred worldwide in the recent years. Building on previous work, the event definition consists of automatically selecting the spatiotemporal scale that maximizes the event rarity, accounting for the nonstationary context of climate change. We then explore all years, seasons, and regions and search for the most extreme events. We demonstrate how our searching procedure can be both useful for climate monitoring over a given territory, and resolve the geographical selection bias of attribution studies. Ultimately, we provide a selection of the most exceptional hot and cold events in the recent past, among which are iconic heatwaves such as those seen in 2021 in Canada and in 2003 in Europe.

Open access
Pascal Yiou
,
Julien Cattiaux
,
Davide Faranda
,
Nikolay Kadygrov
,
Aglae Jézéquel
,
Philippe Naveau
,
Aurelien Ribes
,
Yoann Robin
,
Soulivanh Thao
,
Geert Jan van Oldenborgh
, and
Mathieu Vrac
Free access