Accessibility navigation


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

Kunimitsu, T., Baldissera Pacchetti, M., Ciullo, A., Sillmann, J., Shepherd, T. G. ORCID: https://orcid.org/0000-0002-6631-9968, Taner, M. Ü. and van den Hurk, B. (2023) Representing storylines with causal networks to support decision making: framework and example. Climate Risk Management, 40. 100496. ISSN 2212-0963

[img] Text (Open Access) - Published Version
· Restricted to Repository staff only
· The Copyright of this document has not been checked yet. This may affect its availability.
· Available under License Creative Commons Attribution.

2MB
[img] Text - Accepted Version
· Restricted to Repository staff only
· The Copyright of this document has not been checked yet. This may affect its availability.
· Available under License Creative Commons Attribution Non-commercial No Derivatives.

912kB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1016/j.crm.2023.100496

Abstract/Summary

Physical climate storylines, which are physically self-consistent unfoldings of events or pathways, 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.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:111036
Publisher:Elsevier

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation