Abstract
AbstractDescribing the relationship between a weather event and climate change—a science usually termedevent attribution—involves quantifying the extent to which human influence has affected the frequency or the strength of an observed event. In this study we show how event attribution can be implemented through the application of nonstationary statistics to transient simulations, typically covering the 1850–2100 period. The use of existing CMIP-style simulations has many advantages, including their availability for a large range of coupled models and the fact that they are not conditional to a given oceanic state. We develop a technique for providing a multimodel synthesis, consistent with the uncertainty analysis of long-term changes. Last, we describe how model estimates can be combined with historical observations to provide a single diagnosis accounting for both sources of information. The potential of this new method is illustrated using the 2003 European heat wave and under a Gaussian assumption. Results suggest that (i) it is feasible to perform event attribution using transient simulations and nonstationary statistics, even for a single model; (ii) the use of multimodel synthesis in event attribution is highly desirable given the spread in single-model estimates; and (iii) merging models and observations substantially reduces uncertainties in human-induced changes. Investigating transient simulations also enables us to derive insightful diagnostics of how the targeted event will be affected by climate change in the future.
Highlights
Describing the relationship between a given weather or climate event and anthropogenic climate change is a growing area of activity in the field of climate science (National Academies of Sciences, Engineering, and Medicine 2016)
Particular attention is paid to changes in probability of the event associated with human influence
To illustrate the method presented in this paper, we focus on the 2003 European heat wave (EHW03), an event that has long been scrutinized in event attribution studies (Stott et al 2004; Schär et al 2004; Christidis et al 2015a)
Summary
Describing the relationship between a given weather or climate event and anthropogenic climate change is a growing area of activity in the field of climate science (National Academies of Sciences, Engineering, and Medicine 2016). Since the pioneering studies of Allen (2003) and Stott et al (2004), the concept of event attribution has been applied to a wide variety of events, as synthesized in the annual special issues of the Bulletin of the American Meteorological Society. (BAMS) ‘‘Explaining Extreme Events from a Climate Perspective’’ (Peterson et al 2012, and subsequent issues).. Beyond issues related to the definition of the event of interest, the most commonly used approach is probabilistic and involves a comparison of the distributions of extreme events in the factual versus. Particular attention is paid to changes in probability of the event associated with human influence. This study will focus on the probabilistic approach and its statistical implementation, that is, how estimating changes in occurrence frequency and the corresponding uncertainty
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