The Cryosphere
The Cryosphere
TC
Articles | Volume 17, issue 11
Articles | Volume 17, issue 11
https://doi.org/10.5194/tc-17-4661-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-4661-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 11
Research article
 | 
07 Nov 2023
Research article |  | 07 Nov 2023

Choice of observation type affects Bayesian calibration of Greenland Ice Sheet model simulations

Denis Felikson, Sophie Nowicki, Isabel Nias, Beata Csatho, Anton Schenk, Michael J. Croteau, and Bryant Loomis

Supplement

https://doi.org/10.5194/tc-17-4661-2023-supplement

Data sets

MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data I. Joughin, B. Smith, I. Howat, and T. Scambos https://doi.org/10.5067/OC7B04ZM9G6Q

GRACE High-Resolution Trend Mascons - Greenland Ice Sheet (2007-2015) B. Loomis, D. Felikson, T. Sabaka, and B. Medley https://doi.org/10.5281/zenodo.10037961

Annual Dynamic Ice Thickness Change Rate, Greenland 1993-2017 (v1) B. Csatho, T. Schenk, and D. Felikson https://doi.org/10.5281/zenodo.7324429

Model code and software

Release v3.0 of greenland-and-antarctica-projection-calibration code repository Denis Felikson https://doi.org/10.5281/zenodo.10038131

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Short summary
We narrow the spread in model simulations of the Greenland Ice Sheet using velocity change, dynamic thickness change, and mass change observations. We find that the type of observation chosen can lead to significantly different calibrated probability distributions. Further work is required to understand how to best calibrate ensembles of ice sheet simulations because this will improve probability distributions of projected sea-level rise, which is crucial for coastal planning and adaptation.
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