Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength
The effects of anthropogenic climate change are most drastic in the Arctic. This amplification of climate change signals is strongly connected to the sea ice in the Arctic Ocean. This thesis presents an analysis of the sea ice cover in numerical ocean – sea ice models with a focus on two different p...
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ftawi:oai:epic.awi.de:51461 2023-05-15T14:24:50+02:00 Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength Ungermann, Mischa 2017 application/pdf https://epic.awi.de/id/eprint/51461/ https://epic.awi.de/id/eprint/51461/1/thesis_MUngermann.pdf http://nbn-resolving.de/urn:nbn:de:gbv:46-00106414-11 https://hdl.handle.net/10013/epic.8f97bc8d-1355-434e-87ef-0a2bb434cf34 https://hdl.handle.net/ unknown https://epic.awi.de/id/eprint/51461/1/thesis_MUngermann.pdf https://hdl.handle.net/ Ungermann, M. orcid:0000-0002-2437-4221 (2017) Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength PhD thesis, hdl:10013/epic.8f97bc8d-1355-434e-87ef-0a2bb434cf34 EPIC3 Thesis notRev 2017 ftawi 2021-12-24T15:45:20Z The effects of anthropogenic climate change are most drastic in the Arctic. This amplification of climate change signals is strongly connected to the sea ice in the Arctic Ocean. This thesis presents an analysis of the sea ice cover in numerical ocean – sea ice models with a focus on two different parameter- izations: an active ice thickness distribution and an ice strength parameter- ization that is based on this additional thickness information. The research questions are: (1) can the parameterizations improve the reproduction of Arctic-wide sea ice observations? (2) Do the parameterizations actually re- produce physically observed behavior? (3) How can the parameterizations and their use in basin-scale models be improved further? In a first step, model quality is assessed by a quantitative measure of the reproduction of satellite observations of sea ice concentration, thickness and drift. Including a full ice thickness distribution in each grid cell instead of only two ice categories clearly improves the model results. At the same time, a strength parameterization based on a two-category approach produces better model results than a multi-category strength parameterization. In a next step, the two parameterizations are evaluated in more detail. The ice thickness distribution parameterization reproduces local observations in the Arctic to a large degree and simulates faithfully regional and seasonal differences found in observed distributions. The poor performance of the multi-category ice strength parameterization is explained by the physical assumptions that were made in its original derivation and that do not agree with the current understanding of the ice cover. In conclusion, using an ice thickness distribution improves model performance, but a multi-category parameterization of the ice strength should be avoided. In future work, a new ice strength parameterization could be derived from the physical properties of the ice pack that are demonstrated in this work. Thesis Arctic Arctic Arctic Ocean Climate change ice pack Sea ice Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Arctic Arctic Ocean |
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Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) |
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ftawi |
language |
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description |
The effects of anthropogenic climate change are most drastic in the Arctic. This amplification of climate change signals is strongly connected to the sea ice in the Arctic Ocean. This thesis presents an analysis of the sea ice cover in numerical ocean – sea ice models with a focus on two different parameter- izations: an active ice thickness distribution and an ice strength parameter- ization that is based on this additional thickness information. The research questions are: (1) can the parameterizations improve the reproduction of Arctic-wide sea ice observations? (2) Do the parameterizations actually re- produce physically observed behavior? (3) How can the parameterizations and their use in basin-scale models be improved further? In a first step, model quality is assessed by a quantitative measure of the reproduction of satellite observations of sea ice concentration, thickness and drift. Including a full ice thickness distribution in each grid cell instead of only two ice categories clearly improves the model results. At the same time, a strength parameterization based on a two-category approach produces better model results than a multi-category strength parameterization. In a next step, the two parameterizations are evaluated in more detail. The ice thickness distribution parameterization reproduces local observations in the Arctic to a large degree and simulates faithfully regional and seasonal differences found in observed distributions. The poor performance of the multi-category ice strength parameterization is explained by the physical assumptions that were made in its original derivation and that do not agree with the current understanding of the ice cover. In conclusion, using an ice thickness distribution improves model performance, but a multi-category parameterization of the ice strength should be avoided. In future work, a new ice strength parameterization could be derived from the physical properties of the ice pack that are demonstrated in this work. |
format |
Thesis |
author |
Ungermann, Mischa |
spellingShingle |
Ungermann, Mischa Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength |
author_facet |
Ungermann, Mischa |
author_sort |
Ungermann, Mischa |
title |
Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength |
title_short |
Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength |
title_full |
Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength |
title_fullStr |
Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength |
title_full_unstemmed |
Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength |
title_sort |
modelling arctic sea ice: on the relationship between ice thickness distributions and the ice strength |
publishDate |
2017 |
url |
https://epic.awi.de/id/eprint/51461/ https://epic.awi.de/id/eprint/51461/1/thesis_MUngermann.pdf http://nbn-resolving.de/urn:nbn:de:gbv:46-00106414-11 https://hdl.handle.net/10013/epic.8f97bc8d-1355-434e-87ef-0a2bb434cf34 https://hdl.handle.net/ |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Arctic Ocean Climate change ice pack Sea ice |
genre_facet |
Arctic Arctic Arctic Ocean Climate change ice pack Sea ice |
op_source |
EPIC3 |
op_relation |
https://epic.awi.de/id/eprint/51461/1/thesis_MUngermann.pdf https://hdl.handle.net/ Ungermann, M. orcid:0000-0002-2437-4221 (2017) Modelling Arctic Sea Ice: On the Relationship between Ice Thickness Distributions and the Ice Strength PhD thesis, hdl:10013/epic.8f97bc8d-1355-434e-87ef-0a2bb434cf34 |
_version_ |
1766297287135330304 |