When the fraction of attributable risk does not inform the impact associated with anthropogenic climate change

Abstract

Weather and climate phenomena have outsized impacts on society when they are particularly extreme. Extreme Event Attribution (EEA) seeks to quantify the extent to which extreme weather and climate phenomena are the result of anthropogenic climate change (ACC), and thus it has implications for many pertinent climate change discussions, including those on potential legal claims of loss and damages and calculations of the social cost of carbon. The Fraction of Attributable Risk (FAR) is one metric that is used to quantify the proportion of an extreme weather or climate “event” associated with ACC. The FAR is typically applied to changes in the likelihood of exceeding some geophysical value chosen, post hoc, to represent the “event” (e.g., i.e., rainfall amounts, flood depths, drought measures, temperature values, etc.). The FAR has further been used to estimate the fraction of observed impacts (e.g., lives lost or economic damage) that can be associated with ACC by multiplying realized impacts by the FAR (IFAR = Impact×FAR). Here, we illustrate with a few stylized examples that this IFAR calculation only produces reliably useful results when the weather or climate phenomena in question can be easily conceived of as a discrete binary “event” (i.e., the entirety of the event either occurs or it does not). We show that the IFAR calculation can produce misleading results when the weather or climate phenomena in question are on a continuum, and ACC can be thought of as altering the intensity of the geophysical value that is used in the eventhood definition. Specifically, we show that the IFAR calculation inflates the impacts associated with ACC in these circumstances because it inaccurately assumes that there would have been zero impact had the geophysical value chosen to define eventhood not been exceeded. We illustrate that for weather and climate phenomena on a continuum (e.g., floods, droughts, temperatures, etc.), a clearer way of conceptualizing the impacts associated with ACC is to compare the expected value of the impact between the ACC and preindustrial conditions across the full continuum.