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Probabilistic inversion of expert assessments to inform projections about Antarctic ice sheet responses

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  • Robert William Fuller
  • Tony E Wong
  • Klaus Keller

Abstract

The response of the Antarctic ice sheet (AIS) to changing global temperatures is a key component of sea-level projections. Current projections of the AIS contribution to sea-level changes are deeply uncertain. This deep uncertainty stems, in part, from (i) the inability of current models to fully resolve key processes and scales, (ii) the relatively sparse available data, and (iii) divergent expert assessments. One promising approach to characterizing the deep uncertainty stemming from divergent expert assessments is to combine expert assessments, observations, and simple models by coupling probabilistic inversion and Bayesian inversion. Here, we present a proof-of-concept study that uses probabilistic inversion to fuse a simple AIS model and diverse expert assessments. We demonstrate the ability of probabilistic inversion to infer joint prior probability distributions of model parameters that are consistent with expert assessments. We then confront these inferred expert priors with instrumental and paleoclimatic observational data in a Bayesian inversion. These additional constraints yield tighter hindcasts and projections. We use this approach to quantify how the deep uncertainty surrounding expert assessments affects the joint probability distributions of model parameters and future projections.

Suggested Citation

  • Robert William Fuller & Tony E Wong & Klaus Keller, 2017. "Probabilistic inversion of expert assessments to inform projections about Antarctic ice sheet responses," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-13, December.
  • Handle: RePEc:plo:pone00:0190115
    DOI: 10.1371/journal.pone.0190115
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    References listed on IDEAS

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    1. Michael Oppenheimer & Christopher M. Little & Roger M. Cooke, 2016. "Expert judgement and uncertainty quantification for climate change," Nature Climate Change, Nature, vol. 6(5), pages 445-451, May.
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    Cited by:

    1. Vivek Srikrishnan & Yawen Guan & Richard S. J. Tol & Klaus Keller, 2022. "Probabilistic projections of baseline twenty-first century CO2 emissions using a simple calibrated integrated assessment model," Climatic Change, Springer, vol. 170(3), pages 1-20, February.
    2. Ioanna Ioannou & Jaime E. Cadena & Willy Aspinall & David Lange & Daniel Honfi & Tiziana Rossetto, 2022. "Prioritization of hazards for risk and resilience management through elicitation of expert judgement," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 2773-2795, July.
    3. 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.
    4. Jérémy Rohmer & Gonéri Cozannet & Jean-Charles Manceau, 2019. "Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions," Climatic Change, Springer, vol. 155(1), pages 95-109, July.

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