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Scenarios that illuminate vulnerabilities and robust responses

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  • Robert Lempert

Abstract

Scenarios exist so that decision makers and those who provide them with information can make statements about the future that claim less confidence than do predictions, projections, and forecasts. Despite their prevalence, fundamental questions remain about how scenarios should best be developed and used. This paper proposes a particular conceptualization of scenarios that aims to address many of the challenges faced when using scenarios to inform contentious policy debates. The concept envisions scenarios as illuminating the vulnerabilities of proposed policies, that is, as concise summaries of the future states of the world in which a proposed policy would fail to meet its goals. Such scenarios emerge from a decision support process that begins with a proposed policy, seeks to understand the conditions under which it would fail, and then uses this information to identify and evaluate potential alternative policies that are robust over a wide range of future conditions. Statistical cluster analyses applied to databases of simulation model results can help identify scenarios as part of this process. Drawing on themes from the decision support literature, this paper first reviews difficulties faced when using scenarios to inform climate-related decisions, describes the proposed approach to address these challenges, illustrates the approach with applications for three different types of users, and concludes with some thoughts on implications for the provision of climate information and for future scenario processes. Copyright RAND Corporation 2013

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  • Robert Lempert, 2013. "Scenarios that illuminate vulnerabilities and robust responses," Climatic Change, Springer, vol. 117(4), pages 627-646, April.
    • Handle: RePEc:spr:climat:v:117:y:2013:i:4:p:627-646
    DOI: 10.1007/s10584-012-0574-6
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    1. Christine M. Albano & Maureen I. McCarthy & Michael D. Dettinger & Stephanie A. McAfee, 2021. "Techniques for constructing climate scenarios for stress test applications," Climatic Change, Springer, vol. 164(3), pages 1-25, February.
    2. Evelina Trutnevyte & Céline Guivarch & Robert Lempert & Neil Strachan, 2016. "Reinvigorating the scenario technique to expand uncertainty consideration," Climatic Change, Springer, vol. 135(3), pages 373-379, April.
    3. Mark Howden & Katharine L. Jacobs, 2016. "Innovations in assessment and adaptation: building on the US National Climate Assessment," Climatic Change, Springer, vol. 135(1), pages 157-171, March.
    4. Theodore G. Shepherd & Emily Boyd & Raphael A. Calel & Sandra C. Chapman & Suraje Dessai & Ioana M. Dima-West & Hayley J. Fowler & Rachel James & Douglas Maraun & Olivia Martius & Catherine A. Senior , 2018. "Storylines: an alternative approach to representing uncertainty in physical aspects of climate change," Climatic Change, Springer, vol. 151(3), pages 555-571, December.
    5. Abdul Tariq & Robert Jay Lempert & John Riverson & Marla Schwartz & Neil Berg, 2017. "A climate stress test of Los Angeles’ water quality plans," Climatic Change, Springer, vol. 144(4), pages 625-639, October.
    6. Richard Moss, 2016. "Assessing decision support systems and levels of confidence to narrow the climate information “usability gap”," Climatic Change, Springer, vol. 135(1), pages 143-155, March.
    7. Marzena Kramarz & Katarzyna Dohn & Edyta Przybylska & Lilla Knop, 2020. "Scenarios for the Development of Multimodal Transport in the TRITIA Cross-Border Area," Sustainability, MDPI, vol. 12(17), pages 1-41, August.
    8. Densing, M. & Panos, E. & Hirschberg, S., 2016. "Meta-analysis of energy scenario studies: Example of electricity scenarios for Switzerland," Energy, Elsevier, vol. 109(C), pages 998-1015.
    9. Xexakis, Georgios & Hansmann, Ralph & Volken, Sandra P. & Trutnevyte, Evelina, 2020. "Models on the wrong track: Model-based electricity supply scenarios in Switzerland are not aligned with the perspectives of energy experts and the public," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    10. Trutnevyte, Evelina & McDowall, Will & Tomei, Julia & Keppo, Ilkka, 2016. "Energy scenario choices: Insights from a retrospective review of UK energy futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 326-337.
    11. Mark Howden & Katharine Jacobs, 2016. "Innovations in assessment and adaptation: building on the US National Climate Assessment," Climatic Change, Springer, vol. 135(1), pages 157-171, March.
    12. Maria da Conceição Cunha, 2023. "Water and Environmental Systems Management Under Uncertainty: From Scenario Construction to Robust Solutions and Adaptation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2271-2285, May.
    13. Lempert Robert J., 2014. "Embedding (some) benefit-cost concepts into decision support processes with deep uncertainty," Journal of Benefit-Cost Analysis, De Gruyter, vol. 5(3), pages 487-514, December.
    14. Bhave, Ajay Gajanan & Conway, Declan & Dessai, Suraje & Stainforth, David A., 2017. "Barriers and opportunities for robust decision making approaches to support climate change adaptation in the developing world," LSE Research Online Documents on Economics 68318, London School of Economics and Political Science, LSE Library.
    15. Yilmaz, Hasan Ümitcan & Kimbrough, Steven O. & van Dinther, Clemens & Keles, Dogan, 2022. "Power-to-gas: Decarbonization of the European electricity system with synthetic methane," Applied Energy, Elsevier, vol. 323(C).
    16. Parker, Andrew M. & Srinivasan, Sinduja V. & Lempert, Robert J. & Berry, Sandra H., 2015. "Evaluating simulation-derived scenarios for effective decision support," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 64-77.
    17. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 175(C), pages 3-24.
    18. Shortridge, Julie & Aven, Terje & Guikema, Seth, 2017. "Risk assessment under deep uncertainty: A methodological comparison," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 12-23.
    19. Jairo Quirós-Tortós & Guido Godínez- Zamora & Daniel Gerardo de La Torre Ugarte & Carlos Heros & Juan Lazo Lazo & Elías Ruiz & Berioska Quispe & Daniella Diez Canseco & Freddy Garro & Jimena Mora & Lo, 2021. "Costos y beneficios de la carbono-neutralidad en Perú: Una evaluación robusta," Post-Print halshs-03318133, HAL.
    20. Vanesa Valiño & Adnan Rasheed & Ana Tarquis & Alicia Perdigones, 2014. "Effect of increasing temperatures on cooling systems. A case of study: European greenhouse sector," Climatic Change, Springer, vol. 123(2), pages 175-187, March.
    21. Priess, Joerg A. & Hauck, Jennifer & Haines-Young, Roy & Alkemade, Rob & Mandryk, Maryia & Veerkamp, Clara & Gyorgyi, Bela & Dunford, Rob & Berry, Pam & Harrison, Paula & Dick, Jan & Keune, Hans & Kok, 2018. "New EU-scale environmental scenarios until 2050 – Scenario process and initial scenario applications," Ecosystem Services, Elsevier, vol. 29(PC), pages 542-551.
    22. Richard H. Moss, 2016. "Assessing decision support systems and levels of confidence to narrow the climate information “usability gap”," Climatic Change, Springer, vol. 135(1), pages 143-155, March.
    23. Dittrich, Ruth & Wreford, Anita & Moran, Dominic, 2016. "A survey of decision-making approaches for climate change adaptation: Are robust methods the way forward?," Ecological Economics, Elsevier, vol. 122(C), pages 79-89.
    24. Julie E. Shortridge & Seth D. Guikema, 2016. "Scenario Discovery with Multiple Criteria: An Evaluation of the Robust Decision‐Making Framework for Climate Change Adaptation," Risk Analysis, John Wiley & Sons, vol. 36(12), pages 2298-2312, December.

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