Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates
A parallel ocean and ice model (POIM) in generalized orthogonal curvilinear coordinates has been developed for global climate studies. The POIM couples the Parallel Ocean Program (POP) with a 12-category thickness and enthalpy distribution (TED) sea ice model. Although the POIM aims at modeling the...
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ftciteseerx:oai:CiteSeerX.psu:10.1.1.167.1046 2023-05-15T14:59:12+02:00 Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates Jinlun Zhang D. A. Rothrock The Pennsylvania State University CiteSeerX Archives 2002 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.1046 http://psc.apl.washington.edu/zhang/Pubs/POIM.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.1046 http://psc.apl.washington.edu/zhang/Pubs/POIM.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://psc.apl.washington.edu/zhang/Pubs/POIM.pdf text 2002 ftciteseerx 2016-01-07T15:52:26Z A parallel ocean and ice model (POIM) in generalized orthogonal curvilinear coordinates has been developed for global climate studies. The POIM couples the Parallel Ocean Program (POP) with a 12-category thickness and enthalpy distribution (TED) sea ice model. Although the POIM aims at modeling the global ocean and sea ice system, the focus of this study is on the presentation, implementation, and evaluation of the TED sea ice model in a generalized coordinate system. The TED sea ice model is a dynamic thermodynamic model that also explicitly simulates sea ice ridging. Using a viscous plastic rheology, the TED model is formulated such that all the metric terms in generalized curvilinear coordinates are retained. Following the POP’s structure for parallel computation, the TED model is designed to be run on a variety of computer architectures: parallel, serial, or vector. When run on a computer cluster with 10 parallel processors, the parallel performance of the POIM is close to that of a corresponding POP ocean-only model. Model results show that the POIM captures the major features of sea ice motion, concentration, extent, and thickness in both polar oceans. The results are in reasonably good agreement with buoy observations of ice motion, satellite observations of ice extent, and submarine observations of ice thickness. The model biases are within 8 % in Arctic ice motion, within 9 % in Arctic ice thickness, and within 14 % in ice extent in both hemispheres. The model captures 56 % of the variance of ice Text Arctic Sea ice Unknown Arctic |
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A parallel ocean and ice model (POIM) in generalized orthogonal curvilinear coordinates has been developed for global climate studies. The POIM couples the Parallel Ocean Program (POP) with a 12-category thickness and enthalpy distribution (TED) sea ice model. Although the POIM aims at modeling the global ocean and sea ice system, the focus of this study is on the presentation, implementation, and evaluation of the TED sea ice model in a generalized coordinate system. The TED sea ice model is a dynamic thermodynamic model that also explicitly simulates sea ice ridging. Using a viscous plastic rheology, the TED model is formulated such that all the metric terms in generalized curvilinear coordinates are retained. Following the POP’s structure for parallel computation, the TED model is designed to be run on a variety of computer architectures: parallel, serial, or vector. When run on a computer cluster with 10 parallel processors, the parallel performance of the POIM is close to that of a corresponding POP ocean-only model. Model results show that the POIM captures the major features of sea ice motion, concentration, extent, and thickness in both polar oceans. The results are in reasonably good agreement with buoy observations of ice motion, satellite observations of ice extent, and submarine observations of ice thickness. The model biases are within 8 % in Arctic ice motion, within 9 % in Arctic ice thickness, and within 14 % in ice extent in both hemispheres. The model captures 56 % of the variance of ice |
author2 |
The Pennsylvania State University CiteSeerX Archives |
format |
Text |
author |
Jinlun Zhang D. A. Rothrock |
spellingShingle |
Jinlun Zhang D. A. Rothrock Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates |
author_facet |
Jinlun Zhang D. A. Rothrock |
author_sort |
Jinlun Zhang |
title |
Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates |
title_short |
Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates |
title_full |
Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates |
title_fullStr |
Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates |
title_full_unstemmed |
Modeling Global Sea Ice with a Thickness and Enthalpy Distribution Model in Generalized Curvilinear Coordinates |
title_sort |
modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates |
publishDate |
2002 |
url |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.1046 http://psc.apl.washington.edu/zhang/Pubs/POIM.pdf |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
http://psc.apl.washington.edu/zhang/Pubs/POIM.pdf |
op_relation |
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.167.1046 http://psc.apl.washington.edu/zhang/Pubs/POIM.pdf |
op_rights |
Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
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1766331335248445440 |