EGU23-5082, updated on 22 Feb 2023
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Representing storylines with causal networks to support decision making

Taro Kunimitsu1, Marina Baldissera Pacchetti2, Alessio Ciullo3, Jana Sillmann1,4, Theodore G. Shepherd5, Ümit Taner6, and Bart van den Hurk6,7
Taro Kunimitsu et al.
  • 1CICERO Center for International Climate Research, Oslo, Norway
  • 2Sustainability Research Institute, University of Leeds, Leeds, United Kingdom
  • 3Institute for Environmental Decisions, ETH Zurich, Zurich, Switzerland
  • 4Research Unit for Sustainability and Climate Risks, University of Hamburg, Hamburg, Germany
  • 5Department of Meteorology, University of Reading, Reading, United Kingdom
  • 6Deltares, Delft, The Netherlands
  • 7Institute for Environmental Studies, VU Amsterdam, Amsterdam, The Netherlands

Physical climate storylines, which are physically self-consistent unfoldings of events, have been powerful tools in understanding regional climate impacts. We show how embedding physical climate storylines into a causal network framework allows user value judgments to be incorporated into the storyline in the form of probabilistic Bayesian priors, and can support decision making through inspection of the causal network outputs.

We exemplify this through a specific storyline, namely a storyline on the impacts of tropical cyclones on the European Union Solidarity Fund. We outline how the constructed causal network can incorporate value judgments, particularly the prospects on climate change and its impact on cyclone intensity increase, and on economic growth. We also explore how the causal network responds to policy options chosen by the user. The resulting output from the network leads to individualized policy recommendations, allowing the causal network to be used as a possible interface for policy exploration in stakeholder engagements. 

How to cite: Kunimitsu, T., Baldissera Pacchetti, M., Ciullo, A., Sillmann, J., Shepherd, T. G., Taner, Ü., and van den Hurk, B.: Representing storylines with causal networks to support decision making, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5082,, 2023.