On the role of moderator and mediator variables in conditional event attribution of heatwaves over Europe

Abstract

This study examines how a risk-based attribution analysis of European heat wave events under climate change varies when explanatory variables are included in the analysis. Instead of relying solely on temperature statistics, the analysis is conducted while conditioning on large-scale circulation or pre-existing climate anomalies. Using the hot European summers of 2006 and 2007 as examples, we observe several systematic effects. Controlling for the presence of atmospheric blocking explains much of the natural temperature variability and greatly improves the separation of present and pre-industrial distributions in both years. In 2006, the predominant strong blocking raised the expected temperatures, so that, by comparison, the observed anomaly no longer appeared unusually hot, even in a pre-industrial climate. More complex effects occur when the conditions are part of the causal chain of climate change, for example, acting as moderators or mediators. By conditioning on such variables, we may remove part of the climate change signal and thus fundamentally alter the outcome of the attribution study. Using a simplified model we demonstrate why attribution studies with different kinds of conditions can reach different, seemingly contradictory conclusions.