The concept of spectrally nudged storylines for extreme event attribution

Abstract Spectrally nudged storylines (constraining the large-scale atmospheric circulation to follow that of a particular weather event) represent a relatively new attribution method. They differ from conventional, probabilistic attribution approaches which consider a class of similar, generally univariate, extremes. Instead, their focus is on particular, historic extreme events of large impact which are still vividly anchored in collective memory. The innovation of the method is the feasibility to quantify the role of anthropogenic climate change for specific extreme events of the recent past, and it draws on experience from regional climate downscaling. Spectrally nudged storylines thus offer a new, easily implemented and easily understandable way of communicating climate change to the general public and decision-makers, as well as a pathway for detailed attribution of climate impacts. The technique offers great potential as an addition to the established attribution methods by answering different questions and providing new attribution results.