Bayesian calibration of firn densification models
Firn densification modelling is key to understanding ice sheet mass balance, ice sheet surface elevation change, and the age difference between ice and the air in enclosed air bubbles. This has resulted in the development of many firn models, all relying to a certain degree on parameter calibration...
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ftdoajarticles:oai:doaj.org/article:29fa14b54f554ed195d5b64a307706a0 2023-05-15T13:41:36+02:00 Bayesian calibration of firn densification models V. Verjans A. A. Leeson C. Nemeth C. M. Stevens P. Kuipers Munneke B. Noël J. M. van Wessem 2020-09-01T00:00:00Z https://doi.org/10.5194/tc-14-3017-2020 https://doaj.org/article/29fa14b54f554ed195d5b64a307706a0 EN eng Copernicus Publications https://tc.copernicus.org/articles/14/3017/2020/tc-14-3017-2020.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-14-3017-2020 1994-0416 1994-0424 https://doaj.org/article/29fa14b54f554ed195d5b64a307706a0 The Cryosphere, Vol 14, Pp 3017-3032 (2020) Environmental sciences GE1-350 Geology QE1-996.5 article 2020 ftdoajarticles https://doi.org/10.5194/tc-14-3017-2020 2022-12-31T09:03:33Z Firn densification modelling is key to understanding ice sheet mass balance, ice sheet surface elevation change, and the age difference between ice and the air in enclosed air bubbles. This has resulted in the development of many firn models, all relying to a certain degree on parameter calibration against observed data. We present a novel Bayesian calibration method for these parameters and apply it to three existing firn models. Using an extensive dataset of firn cores from Greenland and Antarctica, we reach optimal parameter estimates applicable to both ice sheets. We then use these to simulate firn density and evaluate against independent observations. Our simulations show a significant decrease (24 % and 56 %) in observation–model discrepancy for two models and a smaller increase (15 %) for the third. As opposed to current methods, the Bayesian framework allows for robust uncertainty analysis related to parameter values. Based on our results, we review some inherent model assumptions and demonstrate how firn model choice and uncertainties in parameter values cause spread in key model outputs. Article in Journal/Newspaper Antarc* Antarctica Greenland Ice Sheet The Cryosphere Directory of Open Access Journals: DOAJ Articles Greenland The Cryosphere 14 9 3017 3032 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 V. Verjans A. A. Leeson C. Nemeth C. M. Stevens P. Kuipers Munneke B. Noël J. M. van Wessem Bayesian calibration of firn densification models |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Firn densification modelling is key to understanding ice sheet mass balance, ice sheet surface elevation change, and the age difference between ice and the air in enclosed air bubbles. This has resulted in the development of many firn models, all relying to a certain degree on parameter calibration against observed data. We present a novel Bayesian calibration method for these parameters and apply it to three existing firn models. Using an extensive dataset of firn cores from Greenland and Antarctica, we reach optimal parameter estimates applicable to both ice sheets. We then use these to simulate firn density and evaluate against independent observations. Our simulations show a significant decrease (24 % and 56 %) in observation–model discrepancy for two models and a smaller increase (15 %) for the third. As opposed to current methods, the Bayesian framework allows for robust uncertainty analysis related to parameter values. Based on our results, we review some inherent model assumptions and demonstrate how firn model choice and uncertainties in parameter values cause spread in key model outputs. |
format |
Article in Journal/Newspaper |
author |
V. Verjans A. A. Leeson C. Nemeth C. M. Stevens P. Kuipers Munneke B. Noël J. M. van Wessem |
author_facet |
V. Verjans A. A. Leeson C. Nemeth C. M. Stevens P. Kuipers Munneke B. Noël J. M. van Wessem |
author_sort |
V. Verjans |
title |
Bayesian calibration of firn densification models |
title_short |
Bayesian calibration of firn densification models |
title_full |
Bayesian calibration of firn densification models |
title_fullStr |
Bayesian calibration of firn densification models |
title_full_unstemmed |
Bayesian calibration of firn densification models |
title_sort |
bayesian calibration of firn densification models |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/tc-14-3017-2020 https://doaj.org/article/29fa14b54f554ed195d5b64a307706a0 |
geographic |
Greenland |
geographic_facet |
Greenland |
genre |
Antarc* Antarctica Greenland Ice Sheet The Cryosphere |
genre_facet |
Antarc* Antarctica Greenland Ice Sheet The Cryosphere |
op_source |
The Cryosphere, Vol 14, Pp 3017-3032 (2020) |
op_relation |
https://tc.copernicus.org/articles/14/3017/2020/tc-14-3017-2020.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-14-3017-2020 1994-0416 1994-0424 https://doaj.org/article/29fa14b54f554ed195d5b64a307706a0 |
op_doi |
https://doi.org/10.5194/tc-14-3017-2020 |
container_title |
The Cryosphere |
container_volume |
14 |
container_issue |
9 |
container_start_page |
3017 |
op_container_end_page |
3032 |
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1766152930878029824 |