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Uncertainty analysis comes to integrated assessment models for climate change…and conversely

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  • Roger Cooke

Abstract

This article traces the development of uncertainty analysis through three generations punctuated by large methodology investments in the nuclear sector. Driven by a very high perceived legitimation burden, these investments aimed at strengthening the scientific basis of uncertainty quantification. The first generation building off the Reactor Safety Study introduced structured expert judgment in uncertainty propagation and distinguished variability and uncertainty. The second generation emerged in modeling the physical processes inside the reactor containment building after breach of the reactor vessel. Operational definitions and expert judgment for uncertainty quantification were elaborated. The third generation developed in modeling the consequences of release of radioactivity and transport through the biosphere. Expert performance assessment, dependence elicitation and probabilistic inversion are among the hallmarks. Third generation methods may be profitably employed in current Integrated Assessment Models (IAMs) of climate change. Possible applications of dependence modeling and probabilistic inversion are sketched. It is unlikely that these methods will be fully adequate for quantitative uncertainty analyses of the impacts of climate change, and a penultimate section looks ahead to fourth generation methods. Copyright The Author(s) 2013

Suggested Citation

  • Roger Cooke, 2013. "Uncertainty analysis comes to integrated assessment models for climate change…and conversely," Climatic Change, Springer, vol. 117(3), pages 467-479, April.
  • Handle: RePEc:spr:climat:v:117:y:2013:i:3:p:467-479
    DOI: 10.1007/s10584-012-0634-y
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    References listed on IDEAS

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    Cited by:

    1. Werner, Christoph & Bedford, Tim & Cooke, Roger M. & Hanea, Anca M. & Morales-Nápoles, Oswaldo, 2017. "Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions," European Journal of Operational Research, Elsevier, vol. 258(3), pages 801-819.
    2. Bistline, John E., 2014. "Energy technology expert elicitations: An application to natural gas turbine efficiencies," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 177-187.
    3. Peter Harrison Howard & Derek Sylvan, 2020. "Wisdom of the experts: Using survey responses to address positive and normative uncertainties in climate-economic models," Climatic Change, Springer, vol. 162(2), pages 213-232, September.
    4. Howard, Peter H. & Derek, Sylvan, 2016. "The Wisdom of the Economic Crowd: Calibrating Integrated Assessment Models Using Consensus," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235639, Agricultural and Applied Economics Association.
    5. Peter H. Howard & Thomas Sterner, 2017. "Few and Not So Far Between: A Meta-analysis of Climate Damage Estimates," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(1), pages 197-225, September.
    6. Terje Aven & Ortwin Renn, 2015. "An Evaluation of the Treatment of Risk and Uncertainties in the IPCC Reports on Climate Change," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 701-712, April.
    7. Colson, Abigail R. & Cooke, Roger M., 2017. "Cross validation for the classical model of structured expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 109-120.
    8. Cooke, Roger M., 2014. "Deep and Shallow Uncertainty in Messaging Climate Change," RFF Working Paper Series dp-14-11, Resources for the Future.

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