Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic
The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end, different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated an...
Published in: | Journal of Geophysical Research: Oceans |
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Online Access: | https://oceanrep.geomar.de/id/eprint/37342/ https://oceanrep.geomar.de/id/eprint/37342/1/jgrc22169.pdf https://doi.org/10.1002/2016JC012128 |
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ftoceanrep:oai:oceanrep.geomar.de:37342 2023-05-15T14:26:51+02:00 Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic Ungermann, Mischa Tremblay, L. Bruno Martin, Torge Losch, Martin 2017-03-16 text https://oceanrep.geomar.de/id/eprint/37342/ https://oceanrep.geomar.de/id/eprint/37342/1/jgrc22169.pdf https://doi.org/10.1002/2016JC012128 en eng AGU (American Geophysical Union) Wiley https://oceanrep.geomar.de/id/eprint/37342/1/jgrc22169.pdf Ungermann, M., Tremblay, L. B., Martin, T. and Losch, M. (2017) Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic. Open Access Journal of Geophysical Research: Oceans, 122 (3). pp. 2090-2107. DOI 10.1002/2016JC012128 <https://doi.org/10.1002/2016JC012128>. doi:10.1002/2016JC012128 info:eu-repo/semantics/openAccess Article PeerReviewed 2017 ftoceanrep https://doi.org/10.1002/2016JC012128 2023-04-07T15:32:19Z The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end, different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness, and drift speed with an semiautomatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed. Article in Journal/Newspaper Arctic Arctic Sea ice OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel) Arctic Journal of Geophysical Research: Oceans 122 3 2090 2107 |
institution |
Open Polar |
collection |
OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel) |
op_collection_id |
ftoceanrep |
language |
English |
description |
The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end, different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness, and drift speed with an semiautomatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed. |
format |
Article in Journal/Newspaper |
author |
Ungermann, Mischa Tremblay, L. Bruno Martin, Torge Losch, Martin |
spellingShingle |
Ungermann, Mischa Tremblay, L. Bruno Martin, Torge Losch, Martin Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic |
author_facet |
Ungermann, Mischa Tremblay, L. Bruno Martin, Torge Losch, Martin |
author_sort |
Ungermann, Mischa |
title |
Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic |
title_short |
Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic |
title_full |
Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic |
title_fullStr |
Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic |
title_full_unstemmed |
Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic |
title_sort |
impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the arctic |
publisher |
AGU (American Geophysical Union) |
publishDate |
2017 |
url |
https://oceanrep.geomar.de/id/eprint/37342/ https://oceanrep.geomar.de/id/eprint/37342/1/jgrc22169.pdf https://doi.org/10.1002/2016JC012128 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic Sea ice |
genre_facet |
Arctic Arctic Sea ice |
op_relation |
https://oceanrep.geomar.de/id/eprint/37342/1/jgrc22169.pdf Ungermann, M., Tremblay, L. B., Martin, T. and Losch, M. (2017) Impact of the ice strength formulation on the performance of a sea ice thickness distribution model in the Arctic. Open Access Journal of Geophysical Research: Oceans, 122 (3). pp. 2090-2107. DOI 10.1002/2016JC012128 <https://doi.org/10.1002/2016JC012128>. doi:10.1002/2016JC012128 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1002/2016JC012128 |
container_title |
Journal of Geophysical Research: Oceans |
container_volume |
122 |
container_issue |
3 |
container_start_page |
2090 |
op_container_end_page |
2107 |
_version_ |
1766300293376507904 |