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Revisiting Antarctic ice loss due to marine ice-cliff instability

Naturevolume 566pages5864 (2019) | Download Citation

Abstract

Predictions for sea-level rise this century due to melt from Antarctica range from zero to more than one metre. The highest predictions are driven by the controversial marine ice-cliff instability (MICI) hypothesis, which assumes that coastal ice cliffs can rapidly collapse after ice shelves disintegrate, as a result of surface and sub-shelf melting caused by global warming. But MICI has not been observed in the modern era and it remains unclear whether it is required to reproduce sea-level variations in the geological past. Here we quantify ice-sheet modelling uncertainties for the original MICI study and show that the probability distributions are skewed towards lower values (under very high greenhouse gas concentrations, the most likely value is 45 centimetres). However, MICI is not required to reproduce sea-level changes due to Antarctic ice loss in the mid-Pliocene epoch, the last interglacial period or 1992–2017; without it we find that the projections agree with previous studies (all 95th percentiles are less than 43 centimetres). We conclude that previous interpretations of these MICI projections over-estimate sea-level rise this century; because the MICI hypothesis is not well constrained, confidence in projections with MICI would require a greater range of observationally constrained models of ice-shelf vulnerability and ice-cliff collapse.

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Data availability

All projections from this study are available from the corresponding author on request. Simulations of the last interglacial, Pliocene and 1992–2017 and 2000–2100 sea-level contributions for all DP16 ensemble members are available on Code Ocean (https://doi.org/10.24433/CO.4ebd8cda-35c0-4d8f-9b7c-d1b064109437). Simulations at 2500 for the subset of the DP16 ensemble that pass their calibration are available in the supplementary information of DP16.

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Acknowledgements

T.L.E., N.R.E. and P.B.H. were supported by EPSRC Research on Changes of Variability and Environmental Risk (ReCoVER: EP/M008495/1) under the Quantifying Uncertainty in Antarctic Ice Sheet Instability (QUAntIS) project (RFFLP 006). T.L.E. was also supported by the EPSRC-funded Past Earth Network (EP/M008363/1) and the Université Joseph Fourier–Grenoble International visitor fund ‘Campagne INVITES’. N.R.G. is supported by contract VUW1501 from the Royal Society Te Aparangi. I.J.N. was supported by the NERC iSTAR-C project Dynamical control on the response of Pine Island Glacier (NE/J005738/1) and now by the NASA Sea Level Change programme. A.W. is supported by the Open University Faculty of Science, Technology, Engineering and Mathematics. We thank R. DeConto for running additional simulations necessary for the analysis, suggestions and discussions, and K. Ruckert and A. Levermann for providing data. We thank the statisticians who attended the Past Earth Network events ‘Assessing Palaeoclimate Uncertainty’ (held jointly with the Environmental Statistics Section of the Royal Statistics Society, Cambridge, August 2016), ‘Emulators workshop’ (Leeds, June 2017) and writing retreat (Callow Hall, August 2017) for advice, particularly I. Vernon, P. Challenor and J. Rougier. We thank D. Le Bars, D. McNeall, D. Demeritt and the King’s Geography Hazards, Risk and Regulation reading group (G. Adamson, F. Liu, A. Razli, L. Ball and A. Heilbron) for comments on the manuscript. We also thank K.-K. Shiu and D. Campbell for supporting T.L.E. in this work.

Author information

Affiliations

  1. Department of Geography, King’s College London, London, UK

    • Tamsin L. Edwards
  2. School of Environment, Earth and Ecosystem Sciences, Faculty of Science, Technology, Engineering and Mathematics, Open University, Milton Keynes, UK

    • Mark A. Brandon
    • , Neil R. Edwards
    • , Philip B. Holden
    •  & Andreas Wernecke
  3. Université Grenoble Alpes, CNRS, IRD, IGE, Grenoble, France

    • Gael Durand
    •  & Catherine Ritz
  4. Antarctic Research Centre, Victoria University of Wellington, Wellington, New Zealand

    • Nicholas R. Golledge
  5. GNS Science, Avalon, Lower Hutt, New Zealand

    • Nicholas R. Golledge
  6. Earth System Science Interdisciplinary Center, College Park, MD, USA

    • Isabel J. Nias
  7. Centre for Polar Observation and Modelling, School of Geographical Sciences, University of Bristol, Bristol, UK

    • Antony J. Payne

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Contributions

T.L.E. conceived the idea, carried out the analysis, produced the figures and wrote the manuscript. A.W. and P.B.H. performed preliminary analyses. A.J.P., A.W., C.R., G.D., I.J.N., M.A.B. and N.R.G. contributed ideas on glaciological and oceanic aspects; A.W., N.R.E. and P.B.H. contributed ideas on statistical aspects. All authors contributed to writing the manuscript.

Conflict of interest

The authors declare no competing interests.

Corresponding author

Correspondence to Tamsin L. Edwards.

Extended data figures and tables

  1. Extended Data Fig. 1 Sensitivity of DP16 RCP8.5 projections to the lower bound of the Pliocene data.

    a, b, Bias-uncorrected (a) and bias-corrected (b) DP16 projections6 for Antarctic sea-level contribution by 2100 under RCP8.5 as a function of the lower bound of the Pliocene data range. The solid red line and pink shading show the mean ± 1 s.d.; the dotted lines indicate ±2 s.d. c, Sensitivity of our emulated projections for RCP8.5 at 2100 with MICI: lines show 5th, 25th, 50th, 75th and 95th percentiles; asterisks indicate the mode.

  2. Extended Data Fig. 2 DP16 RCP8.5 projection distributions.

    ad, DP16 ensemble projections6 for Antarctic sea-level contribution by 2100 under RCP8.5 for their four variants—low-Pliocene bias-uncorrected (a), low-Pliocene bias-corrected (b), high-Pliocene bias-uncorrected (c) and high-Pliocene bias-corrected (d)—showing the full 64-member ensemble (grey) and the subset selected by calibrating with Pliocene and last interglacial sea-level reconstructions (red). The solid red lines and pink shading show the mean ± 1 s.d.; the horizontal black lines indicate the ≥68% probability interval (see main text and Methods for more details).

  3. Extended Data Fig. 3 Relationships between RCP8.5 projections at 2100 and past sea-level changes.

    ac, Sea-level contribution at 2100 under RCP8.5 versus sea-level contribution during the Pliocene (a), last interglacial (b) and from 1992 to 2017 (c), for the emulator (small grey dots) and DP16 simulator (large open circles; ref. 6 and R. DeConto, personal communication), with ocean bias correction off (blue) and on (red). Grey shading indicates the DP16 palaeodata range (a, b) or observational mean ± 3 s.d.25 (c); the dashed lines additionally include model error.

  4. Extended Data Fig. 4 Relationship between past and future sea-level changes with and without MICI.

    a, b, Simulator ensemble (large circles; ref. 6 and R. DeConto, personal communication) and emulated ensembles (small circles) with (a) and without (b) MICI, showing Pliocene versus last interglacial sea-level changes, with the colour scale indicating the sea-level equivalent (SLE) contribution at 2100 under RCP8.5. Large emulator points and filled simulator points are those that pass the 1992–2017 calibration25. The shaded rectangle indicates the bounds of the DP16 low-Pliocene and last interglacial palaeodata constraints; the dashed rectangle shows constraints in this study (which include model error).

  5. Extended Data Fig. 5 Sensitivity of RCP8.5 projections to MICI and calibration choices.

    Projections for RCP8.5 at 2100 are shown with and without MICI, for different combinations of calibration eras (‘palaeo’, Pliocene and last interglacial; present, 1992–2017) and model discrepancy (with, without or double). Box and whiskers show the 5th, 25th, 50th, 75th and 95th percentiles; asterisks show the mode. Numbers alongside each plot indicate the median, the 5%–95% probability interval and the mode (in parentheses and asterisked).

  6. Extended Data Fig. 6 Emulator validation.

    Left column, emulator prediction versus simulation for each ensemble member, with the emulator fitted to the other ensemble members, for each of the outputs used for building and validating emulator structure: RCP8.5, RCP4.5 and RCP2.6 sea-level contribution at 2100; 1992–2017 contribution; last interglacial; and Pliocene. Vertical error bars show 95% credibility intervals. Right column, difference between emulator predictions and simulations, standardized by emulator error, for the same six outputs. Values falling mostly between ±2 indicate that the emulator has adequate uncertainty estimates. Simulation data from ref. 6 and R. DeConto (personal communication).

  7. Extended Data Fig. 7 Sensitivity of RCP8.5 projections to model parameters.

    ac, Sea-level contribution at 2100 under RCP8.5 versus VCLIF (a), CREVLIQ (b) and OCFAC (c) parameters for the emulator (small grey dots with error bars) and simulator (large open circles; blue, bias-uncorrected; red, bias-corrected). Simulation data from ref. 6 and R. DeConto (personal communication).

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