Articles | Volume 14, issue 9
https://doi.org/10.5194/tc-14-3017-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-3017-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Sep 2020
Research article |
| 15 Sep 2020
| 15 Sep 2020
Bayesian calibration of firn densification models
Vincent Verjans
CORRESPONDING AUTHOR
Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4QY, UK
Amber A. Leeson
Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4QY, UK
Christopher Nemeth
Department of Mathematics and Statistics, Lancaster University,
Lancaster LA1 4YF, UK
C. Max Stevens
Department of Earth and Space Sciences, University of Washington,
Seattle, WA, USA
Peter Kuipers Munneke
Institute for Marine and Atmospheric research Utrecht, Utrecht
University, Utrecht, the Netherlands
Brice Noël
Institute for Marine and Atmospheric research Utrecht, Utrecht
University, Utrecht, the Netherlands
Jan Melchior van Wessem
Institute for Marine and Atmospheric research Utrecht, Utrecht
University, Utrecht, the Netherlands
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Cited
12 citations as recorded by crossref.
- Firn on ice sheets C. Amory et al. 10.1038/s43017-023-00507-9
- Uncertainty in East Antarctic Firn Thickness Constrained Using a Model Ensemble Approach V. Verjans et al. 10.1029/2020GL092060
- Outlier accommodation with semiparametric density processes: A study of Antarctic snow density modelling D. Sheanshang et al. 10.1177/1471082X211043946
- Improving piecewise linear snow density models through hierarchical spatial and orthogonal functional smoothing P. White et al. 10.1002/env.2726
- An evaluation of a physics-based firn model and a semi-empirical firn model across the Greenland Ice Sheet (1980–2020) M. Thompson-Munson et al. 10.5194/tc-17-2185-2023
- More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM) A. Schneider et al. 10.1029/2021MS002542
- Machine learning of Antarctic firn density by combining radiometer and scatterometer remote-sensing data W. Li et al. 10.5194/tc-19-37-2025
- Inter-Annual Variability in the Antarctic Ice Sheets Using Geodetic Observations and a Climate Model A. Kaitheri et al. 10.3390/rs13112199
- Large interannual variability in supraglacial lakes around East Antarctica J. Arthur et al. 10.1038/s41467-022-29385-3
- Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer B. Groenke et al. 10.5194/tc-17-3505-2023
- Spatiotemporal distribution of seasonal snow density in the Northern Hemisphere based on in situ observation T. Che et al. 10.1016/j.rcar.2025.02.004
- Simulations of firn processes over the Greenland and Antarctic ice sheets: 1980–2021 B. Medley et al. 10.5194/tc-16-3971-2022
12 citations as recorded by crossref.
- Firn on ice sheets C. Amory et al. 10.1038/s43017-023-00507-9
- Uncertainty in East Antarctic Firn Thickness Constrained Using a Model Ensemble Approach V. Verjans et al. 10.1029/2020GL092060
- Outlier accommodation with semiparametric density processes: A study of Antarctic snow density modelling D. Sheanshang et al. 10.1177/1471082X211043946
- Improving piecewise linear snow density models through hierarchical spatial and orthogonal functional smoothing P. White et al. 10.1002/env.2726
- An evaluation of a physics-based firn model and a semi-empirical firn model across the Greenland Ice Sheet (1980–2020) M. Thompson-Munson et al. 10.5194/tc-17-2185-2023
- More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM) A. Schneider et al. 10.1029/2021MS002542
- Machine learning of Antarctic firn density by combining radiometer and scatterometer remote-sensing data W. Li et al. 10.5194/tc-19-37-2025
- Inter-Annual Variability in the Antarctic Ice Sheets Using Geodetic Observations and a Climate Model A. Kaitheri et al. 10.3390/rs13112199
- Large interannual variability in supraglacial lakes around East Antarctica J. Arthur et al. 10.1038/s41467-022-29385-3
- Investigating the thermal state of permafrost with Bayesian inverse modeling of heat transfer B. Groenke et al. 10.5194/tc-17-3505-2023
- Spatiotemporal distribution of seasonal snow density in the Northern Hemisphere based on in situ observation T. Che et al. 10.1016/j.rcar.2025.02.004
- Simulations of firn processes over the Greenland and Antarctic ice sheets: 1980–2021 B. Medley et al. 10.5194/tc-16-3971-2022
Latest update: 22 May 2025
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.
Ice sheets are covered by a firn layer, which is the transition stage between fresh snow and...
