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COP21 climate negotiators’ responses to climate model forecasts

Author

Listed:
  • Valentina Bosetti

    (Bocconi University
    Fondazione Eni Enrico Mattei)

  • Elke Weber

    (Princeton University)

  • Loïc Berger

    (Fondazione Eni Enrico Mattei
    IESEG School of Management)

  • David V. Budescu

    (Fordham University)

  • Ning Liu

    (Bocconi University
    Fondazione Eni Enrico Mattei)

  • Massimo Tavoni

    (Fondazione Eni Enrico Mattei
    Economics and Industrial Engineering, Politecnico di Milano)

Abstract

Communicating climate science requires depicting uncertainty. This study shows that the tendency for COP21 policymakers to assign model forecasts less weight than their prior beliefs when making predictions is mitigated by presenting individual model forecasts with the statistical range.

Suggested Citation

  • Valentina Bosetti & Elke Weber & Loïc Berger & David V. Budescu & Ning Liu & Massimo Tavoni, 2017. "COP21 climate negotiators’ responses to climate model forecasts," Nature Climate Change, Nature, vol. 7(3), pages 185-190, March.
    • Handle: RePEc:nat:natcli:v:7:y:2017:i:3:d:10.1038_nclimate3208
    DOI: 10.1038/nclimate3208
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    Cited by:

    1. Jordan Harold & Irene Lorenzoni & Thomas F. Shipley & Kenny R. Coventry, 2020. "Communication of IPCC visuals: IPCC authors’ views and assessments of visual complexity," Climatic Change, Springer, vol. 158(2), pages 255-270, January.
    2. Angela Morelli & Tom Gabriel Johansen & Rosalind Pidcock & Jordan Harold & Anna Pirani & Melissa Gomis & Irene Lorenzoni & Eamon Haughey & Kenny Coventry, 2021. "Co-designing engaging and accessible data visualisations: a case study of the IPCC reports," Climatic Change, Springer, vol. 168(3), pages 1-11, October.
    3. Loïc Berger & Massimo Marinacci, 2020. "Model Uncertainty in Climate Change Economics: A Review and Proposed Framework for Future Research," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 77(3), pages 475-501, November.
    4. Emily Ho & David V. Budescu & Valentina Bosetti & Detlef P. Vuuren & Klaus Keller, 2019. "Not all carbon dioxide emission scenarios are equally likely: a subjective expert assessment," Climatic Change, Springer, vol. 155(4), pages 545-561, August.
    5. Watanabe, Masahide & Fujimi, Toshio, 2022. "Ambiguity of scientific probability predictions and willingness-to-pay for climate change mitigation policies," Research in Economics, Elsevier, vol. 76(4), pages 386-402.
    6. Foucart, Renaud & Schmidt, Robert C., 2019. "(Almost) efficient information transmission in elections," European Economic Review, Elsevier, vol. 119(C), pages 147-165.
    7. Loïc Berger & Valentina Bosetti, 2020. "Are Policymakers Ambiguity Averse?," The Economic Journal, Royal Economic Society, vol. 130(626), pages 331-355.
    8. Loic Berger & Massimo Marinacci, 2017. "Model Uncertainty in Climate Change Economics," Working Papers 616, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    9. Astrid Kause & Wändi Bruine de Bruin & Fai Fung & Andrea Taylor & Jason Lowe, 2020. "Visualizations of Projected Rainfall Change in the United Kingdom: An Interview Study about User Perceptions," Sustainability, MDPI, vol. 12(7), pages 1-21, April.
    10. Toshio Fujimi & Masahide Watanabe & Hirokazu Tatano, 2021. "Public trust, perceived accuracy, perceived likelihood, and concern on multi-model climate projections communicated with different formats," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 26(5), pages 1-20, June.

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