Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

作者：Theodore G. Shepherd, Emily Boyd, Raphael Calel, S. C. Chapman, Suraje Dessai, Ioana Dima-West, Hayley J. Fowler, Rachel James, Douglas Maraun, Olivia Martius, C. A. Senior, Adam H. Sobel, David A. Stainforth, Simon F. B. Tett, Kevin E. Trenberth, Bart van den Hurk, N. W. Watkins, Robert L. Wilby, Dimitri Zenghelis · 发表于：Climatic Change · 年份：2018 · DOI：10.1007/s10584-018-2317-9 · 被引用次数：779 · 研究领域：Sustainability and Climate Change Governance、Climate Change Communication and Perception、Climate variability and models

As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a 'storyline' approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a con...