Representing storylines with causal networks to support decision making: Framework and example

Physical climate storylines, which are physically self-consistent unfoldings of events or pathways, have been powerful tools in understanding regional impacts. We show how embedding physical storylines into a causal network framework allows user value judgments to be incorporated the storyline form probabilistic Bayesian priors, and can support decision making through inspection outputs. exemplify this specific storyline, namely on impacts tropical cyclones European Union Solidarity Fund. outline constructed incorporate judgments, particularly prospects change its impact cyclone intensity increase, economic growth. also explore responds policy options chosen by user. The resulting output from leads individualized recommendations, allowing used as possible interface for exploration stakeholder engagements.