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Precalibrating an intermediate complexity climate model

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Abstract

Credible climate predictions require a rational quantification of uncertainty, but full Bayesian calibration requires detailed estimates of prior probability distributions and covariances, which are difficult to obtain in practice. We describe a simplified procedure, termed precalibration, which provides an approximate quantification of uncertainty in climate prediction, and requires only that uncontroversially implausible values of certain inputs and outputs are identified. The method is applied to intermediate-complexity model simulations of the Atlantic meridional overturning circulation (AMOC) and confirms the existence of a cliff-edge catastrophe in freshwater-forcing input space. When uncertainty in 14 further parameters is taken into account, an implausible, AMOC-off, region remains as a robust feature of the model dynamics, but its location is found to depend strongly on values of the other parameters.

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Acknowledgments

The authors gratefully acknowledge the help of Andrew Price in performing large ensemble simulations, as well as support from the UK Natural Environment Research Council (NERC) RAPID climate change programme (via the THCMIP project), the NERC QUEST programme and the UK Department for Environment, Food and Rural Affairs (via the UK Met Office). Part of this work was completed while Rougier was a Duke University Fellow at the Statistical and Applied Mathematical Sciences Institute (SAMSI), Durham NC.

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Authors and Affiliations

  1. Earth and Environmental Sciences, The Open University, Milton Keynes, MK7 6AA, UK

    Neil R. Edwards

  2. Centre for Ecology and Hydrology, Edinburgh, UK

    David Cameron

  3. Department of Mathematics, University of Bristol, Bristol, BS8 1TW, UK

    Jonathan Rougier

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  1. Neil R. Edwards
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  2. David Cameron
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  3. Jonathan Rougier
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Correspondence to Neil R. Edwards.

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Edwards, N.R., Cameron, D. & Rougier, J. Precalibrating an intermediate complexity climate model. Clim Dyn 37, 1469–1482 (2011). https://doi.org/10.1007/s00382-010-0921-0

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  • DOI: https://doi.org/10.1007/s00382-010-0921-0

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