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

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. An examination of the surface air temperature–SMB relationship i...

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Bibliographic Details
Main Authors: Dalaiden, Quentin, Goosse, Hugues, Klein, François, Lenaerts, Jan, Holloway, Max, Sime, Louis, Thomas, Elisabeth
Other Authors: UCL - SST/ELI/ELIC - Earth & Climate
Format: Article in Journal/Newspaper
Language:English
Published: European geosciences Union 2020
Subjects:
Online Access:http://hdl.handle.net/2078.1/229294
https://doi.org/10.5194/tc-2019-111
Description
Summary: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. An examination of the surface air 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 modeled relationship between surface air temperature and SMB is often stronger than between temperature and δ 18O. This suggests that SMB data can be used to reconstruct past surface air temperature. Using this finding, we assimilate isotope-enabled SMB and δ 18O model output with ice core observations to generate a new surface air 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 δ 18O alone. The improvement is most significant for the East Antarctic region, where the uncertainties are particularly large. Finally, using the same data assimilation method as for the surface air temperature reconstruction, we provide a spatial SMB reconstruction for the AIS over the last 2 centuries, showing large variability in SMB trends at a regional scale, with an increase (0.82 Gt yr−2 ) in West Antarctica over 1957–2000 and a decrease in East Antarctica during the same period (−0.13 Gt yr−2 ). As expected, this is consistent with the recent reconstruction used as a constraint in the data assimilation