Abstract
AbstractExtreme event attribution studies attempt to quantify the role of human influences in observed weather and climate extremes. These studies are of broad scientific and public interest, although quantitative results (e.g., that a specific event was made a specific number of times more likely because of anthropogenic forcings) can be difficult to communicate accurately to a variety of audiences and difficult for audiences to interpret. Here, we focus on how results of these studies can be effectively communicated using standardized language and propose, for the first time, a set of calibrated terms to describe event attribution results. Using these terms and an accompanying visual guide, results are presented in terms of likelihood of event changes and the associated uncertainties. This standardized language will allow clearer communication and interpretation of probabilities by the public and stakeholders.
Highlights
In the years since the first extreme event attribution (EEA) studies provided a quantification of the role of anthropogenic influence in the occurrence of a specific extreme (Stott et al, 2004), many such attribution studies have been conducted
For EEA studies that have quantified the human influence in temperature extremes using an attribution framework, there is a general trend toward a greater degree of confidence in the results of these studies
We argue that the publication, communication, and dissemination of single, specific fraction of attributable risk (FAR), or risk ratio (RR) value for extreme events, even where explicit uncertainty estimation has been undertaken, does not enhance the ability of EEA studies to provide scientific information to the public or policymakers about climate change, risk, and adaption
Summary
In the years since the first extreme event attribution (EEA) studies provided a quantification of the role of anthropogenic influence in the occurrence of a specific extreme (Stott et al, 2004), many such attribution studies have been conducted (see Herring et al, 2014, 2015, 2016). In our scientific experiences, the focus on a single RR or FAR number, confounds rather than clarifies EEA results and implications We highlight one such example in which a rapid coupled climate model‐based analysis was conducted of the anomalously hot sea surface temperatures (SSTs) in the Coral Sea in 2016 that coincided with significant bleaching of the Great Barrier Reef (GBR). This analysis estimated that there was at least 175 times increase in the likelihood of such hot conditions occurring during March due to anthropogenic greenhouse gases (King et al, 2016). A comprehensive treatment of EEA language has been identified as an important issue for event attribution (National Academies of Sciences, Engineering, and Medicine, 2016)
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