Articles | Volume 17, issue 11
https://doi.org/10.5194/tc-17-4661-2023
https://doi.org/10.5194/tc-17-4661-2023
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

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Latest update: 08 May 2024
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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.