Abstract
Abstract Extreme event attribution answers the question of whether and by how much anthropogenic climate change has contributed to the occurrence or magnitude of an extreme weather event. It is also used to link extreme event impacts to climate change. Impacts, however, are often related to multiple compounding climate drivers. Because extreme event attribution typically focuses on univariate assessments, these assessments might only provide a partial answer to the question of anthropogenic influence to a high-impact event. We present a theoretical extension to classical extreme event attribution for certain types of compound events. Based on synthetic data, we illustrate how the bivariate fraction of attributable risk (FAR) differs from the univariate FAR depending on the extremeness of the event as well as the trends in and dependence between the contributing variables. Overall, the bivariate FAR is similar in magnitude or smaller than the univariate FAR if the trend in the second variable is comparably weak and the dependence between both variables is moderate or high, a typical situation for temporally co-occurring heat waves and droughts. If both variables have similarly large trends or the dependence between both variables is weak, bivariate FARs are larger and are likely to provide a more adequate quantification of the anthropogenic influence. Using multiple climate model large ensembles, we apply the framework to two case studies, a recent sequence of hot and dry years in the Western Cape region of South Africa and two spatially co-occurring droughts in crop-producing regions in South Africa and Lesotho.
Highlights
Whether and by how much anthropogenic climate change influences the occurrence of climate extremes is an important question to address for informing adaptation and supporting mitigation efforts
We present an extension of the classical event attribution approach to compound events with multiple drivers and apply it to two case studies
Extreme event attribution has developed into a mature field of research (National Academies of Sciences, Engineering and Medicine 2016), being able to provide rapid answers to the question of how much of the magnitude or frequency of a recently experienced extreme event can be attributed to anthropogenic climate change after such an event has occurred (Van Der Wiel et al 2017; Otto et al 2018a; Philip et al 2018; van Oldenborgh et al 2021b)
Summary
Herring et al (2021)) Those studies focus predominantly on univariate quantities even though there is growing evidence that extreme event impacts are often related to anomalies in multiple climate variables, called compound events (Zscheischler et al 2014, 2018; Pan et al 2020; Tschumi and Zscheischler 2020; Van Der Wiel et al 2020). Multivariate hazard indicators do not always exist, for instance for compound drought-heatwave events or spatially compounding events It is not clear how univariate assessments should be combined, as the combined assessment critically depends on the correlation between the different drivers. We apply our new compound event attribution framework to two case studies: years with concurrent extremely low precipitation and extremely high temperature in the Western Cape region (Section 3), and two co-occurring meteorological droughts in crop-producing regions in Lesotho and in the north-eastern part of South Africa (Section 4)
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call