Articles | Volume 14, issue 9
https://doi.org/10.5194/tc-14-3017-2020
https://doi.org/10.5194/tc-14-3017-2020
Research article
 | 
15 Sep 2020
Research article |  | 15 Sep 2020

Bayesian calibration of firn densification models

Vincent Verjans, Amber A. Leeson, Christopher Nemeth, C. Max Stevens, Peter Kuipers Munneke, Brice Noël, and Jan Melchior van Wessem

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Latest update: 19 Jun 2024
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Short summary
Ice sheets are covered by a firn layer, which is the transition stage between fresh snow and ice. Accurate modelling of firn density properties is important in many glaciological aspects. Current models show disagreements, are mostly calibrated to match specific observations of firn density and lack thorough uncertainty analysis. We use a novel calibration method for firn models based on a Bayesian statistical framework, which results in improved model accuracy and in uncertainty evaluation.