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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/tc-2019-111
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-111
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 03 Jun 2019

Submitted as: research article | 03 Jun 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

Surface Mass Balance of the Antarctic Ice Sheet and its link with surface temperature change in model simulations and reconstructions

Quentin Dalaiden1, Hugues Goosse1, François Klein1, Jan T. M. Lenaerts2, Max Holloway3,4, Louise Sime3, and Elizabeth R. Thomas3 Quentin Dalaiden et al.
  • 1Georges Lemaître Centre for Earth and Climate Research (TECLIM), Earth and Life Institute (ELI), Université catholique de Louvain (UCL), Louvain-la-Neuve Belgium
  • 2Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder CO, USA
  • 3British Antarctic Survey, Madingley Road, Cambridge, CB3 0ET, UK
  • 4Scottish Association for Marine Science, Oban, UK

Abstract. Improving our knowledge of the temporal and spatial variability of the Antarctic Ice Sheet (AIS) Surface Mass Balance (SMB) is crucial to reduce the uncertainties of past, present and future Antarctic contributions to sea level rise. Here, we show that Global Climate Models (GCMs) can reproduce the present-day (1979–2005) AIS SMB and the temporal variations over the last two centuries. An examination of the surface temperature–SMB relationship in model simulations demonstrates a strong link between the two. Reconstructions based on ice cores display a weaker relationship, indicating a model-data discrepancy that may be due to model biases or to the non-climatic noise present in the records. We find that, on the regional scale, the modelled temperature-SMB relationship is stronger than the relationship between δ18O-temperature. This suggests that SMB data can be used to reconstruct past surface temperatures. Using this finding, we assimilate isotope-enabled model SMB and δ18O output with ice-core observations, to generate a new surface temperature reconstruction. Although an independent evaluation of the skill is difficult because of the short observational time series, this new reconstruction outperforms the previous reconstructions for the continental-mean temperature that were based on δ18O alone with a linear correlation coefficient with the observed surface temperatures (1958–2010 CE) of 0.73. The improvement is largest for the East Antarctic region, where the uncertainties are particularly large. Finally, we provide a spatial SMB reconstruction of the AIS over the last two centuries showing 1) large variability in SMB trends at regional scale; and 2) a large SMB increase (0.82 Gt year−2) in West Antarctica over 1957–2000 while at the same time, East Antarctica has experienced a large SMB decrease (−3.3 Gt year−2), which is consistent with a recent reconstruction.

Quentin Dalaiden et al.
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Latest update: 18 Aug 2019
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Short summary
Large uncertainties remain in Antarctic surface temperature reconstructions over the last millennium. Here, the analysis of climate model outputs reveals that snow accumulation is a more relevant proxy for surface temperature reconstructions than δ18O. We use this finding in data assimilation experiments to compare to observed surface temperatures. We show that our continental temperature reconstruction outperforms reconstructions based on δ18O, especially for East Antarctica.
Large uncertainties remain in Antarctic surface temperature reconstructions over the last...
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