Climatic Change

, Volume 128, Issue 3–4, pp 187–200 | Cite as

European participatory scenario development: strengthening the link between stories and models

  • Kasper KokEmail author
  • Ilona Bärlund
  • Martina Flörke
  • Ian Holman
  • Marc Gramberger
  • Jan Sendzimir
  • Benjamin Stuch
  • Katharina Zellmer


Scenario development methods get to grips with taking a long-term view on complex issues such as climate change through involvement of stakeholders. Many of the recent (global) scenario exercises have been structured according to a Story-and-Simulation approach. Although elaborately studied, conceptual and practical issues remain in linking qualitative stories and quantitative models. In this paper, we show how stakeholders can directly estimate model parameter values using a three-step approach called Fuzzy Set Theory. We focus on the effect of multiple iterations between stories and models. Results show that we were successful in quickly delivering stakeholder-based quantification of key model parameters, with full consistency between linguistic terms used in stories and numeric values. Yet, values changed strongly from one iteration to the next. A minimum of two and preferably at least three iterations is needed to harmonise stories and models. We conclude that the application of Fuzzy Set Theory enabled a highly valuable, structured and reproducible process to increase consistency between stories and models, but that future work is needed to show its true potential, particularly related to the effect of iterations. Additionally, the number of tools that need to be applied in a short period of time to execute a Story-And-Simulation approach introduces drawbacks that need to be studied. However, an approach such as Story-And-Simulation is indispensable and effective in marrying the perspectives of scientists and other stakeholders when studying complex systems and complex problems.


Linguistic Term Fuzzy Membership Function Group Model Building Qualitative Scenario Iteration Round 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research was funded by SCENES (EC-funded FP6, contract number 036822) and CLIMAVE (EC-funded FP7, contract number 244031). We wish to thank also all stakeholders that were involved in the process of scenario development.

Supplementary material

10584_2014_1143_MOESM1_ESM.docx (8.7 mb)
ESM 1 (DOCX 8.72 kb)


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Kasper Kok
    • 1
    Email author
  • Ilona Bärlund
    • 2
  • Martina Flörke
    • 3
  • Ian Holman
    • 4
  • Marc Gramberger
    • 5
  • Jan Sendzimir
    • 6
  • Benjamin Stuch
    • 3
  • Katharina Zellmer
    • 5
  1. 1.Soil Geography and Landscape GroupWageningen UniversityWageningenThe Netherlands
  2. 2.Helmholtz Centre for Environmental Research (UFZ)MagdeburgGermany
  3. 3.Center for Environmental Systems ResearchUniversity of KasselKasselGermany
  4. 4.Cranfield Water Science InstituteCranfield UniversityBedfordUK
  5. 5.Prospex bvbaKeerbergenBelgium
  6. 6.International Institute for Applied Systems AnalysisLaxenburgAustria

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