A coupled regional Arctic sea ice-ocean model: configuration and application

A regional sea ice-ocean coupled model for the Arctic Ocean was developed, based on the MITgcm ocean circulation model and classical Hibler79 type two category thermodynamics-dynamics sea ice model. The sea ice dynamics and thermodynamics were considered based on Viscous-Plastic (VP) and Winton thre...

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Main Authors: Qun, Li, Lu, Zhang, Huiding, Wu
Format: Article in Journal/Newspaper
Language:English
Published: Polar Research Institute of China - PRIC 2010
Subjects:
Online Access:http://library.arcticportal.org/2403/
http://library.arcticportal.org/2403/1/A2010-017.pdf
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spelling ftarcticportal:oai:generic.eprints.org:2403 2023-10-09T21:44:09+02:00 A coupled regional Arctic sea ice-ocean model: configuration and application Qun, Li Lu, Zhang Huiding, Wu 2010-12 application/pdf http://library.arcticportal.org/2403/ http://library.arcticportal.org/2403/1/A2010-017.pdf en eng Polar Research Institute of China - PRIC http://library.arcticportal.org/2403/1/A2010-017.pdf Qun, Li and Lu, Zhang and Huiding, Wu (2010) A coupled regional Arctic sea ice-ocean model: configuration and application. Advances in Polar Science, 21 (2). pp. 180-192. Oceans Article PeerReviewed 2010 ftarcticportal 2023-09-13T22:54:14Z A regional sea ice-ocean coupled model for the Arctic Ocean was developed, based on the MITgcm ocean circulation model and classical Hibler79 type two category thermodynamics-dynamics sea ice model. The sea ice dynamics and thermodynamics were considered based on Viscous-Plastic (VP) and Winton three-layer models, respectively. A detailed configuration of coupled model has been introduced. Special attention has been paid to the model grid setup, subgrid paramerization, ice-ocean coupling and open boundary treatment. The coupled model was then applied and two test run examples were presented. The first model run was a climatology simulation with 10 years(1992—2002) averaged NCAR/NCEP reanalysis data as atmospheric forcing. The second model run was a seasonal simulation for the period of 1992—2007. The atmospheric forcing was daily NCAR/NCEP reanalysis. The climatology simulation captured the general pattern of the sea ice thickness distribution of the Arctic, i.e., the thickest sea ice is situated around the Canada Archipelago and the north coast of the Greenland. For the second model run, the modeled September Sea ice extent anomaly from 1992—2007 was highly correlated with the observations, with a linear correlation coefficient of 0.88. The minimum of the Arctic sea ice area in the September of 2007 was unprecedented. The modeled sea ice area and extent for this minimum was overestimated relative to the observations. However, it captured the general pattern of the sea ice retreat. Article in Journal/Newspaper Advances in Polar Science Arctic Arctic Arctic Ocean Greenland Polar Science Polar Science Sea ice Arctic Portal Library Arctic Arctic Ocean Canada Greenland
institution Open Polar
collection Arctic Portal Library
op_collection_id ftarcticportal
language English
topic Oceans
spellingShingle Oceans
Qun, Li
Lu, Zhang
Huiding, Wu
A coupled regional Arctic sea ice-ocean model: configuration and application
topic_facet Oceans
description A regional sea ice-ocean coupled model for the Arctic Ocean was developed, based on the MITgcm ocean circulation model and classical Hibler79 type two category thermodynamics-dynamics sea ice model. The sea ice dynamics and thermodynamics were considered based on Viscous-Plastic (VP) and Winton three-layer models, respectively. A detailed configuration of coupled model has been introduced. Special attention has been paid to the model grid setup, subgrid paramerization, ice-ocean coupling and open boundary treatment. The coupled model was then applied and two test run examples were presented. The first model run was a climatology simulation with 10 years(1992—2002) averaged NCAR/NCEP reanalysis data as atmospheric forcing. The second model run was a seasonal simulation for the period of 1992—2007. The atmospheric forcing was daily NCAR/NCEP reanalysis. The climatology simulation captured the general pattern of the sea ice thickness distribution of the Arctic, i.e., the thickest sea ice is situated around the Canada Archipelago and the north coast of the Greenland. For the second model run, the modeled September Sea ice extent anomaly from 1992—2007 was highly correlated with the observations, with a linear correlation coefficient of 0.88. The minimum of the Arctic sea ice area in the September of 2007 was unprecedented. The modeled sea ice area and extent for this minimum was overestimated relative to the observations. However, it captured the general pattern of the sea ice retreat.
format Article in Journal/Newspaper
author Qun, Li
Lu, Zhang
Huiding, Wu
author_facet Qun, Li
Lu, Zhang
Huiding, Wu
author_sort Qun, Li
title A coupled regional Arctic sea ice-ocean model: configuration and application
title_short A coupled regional Arctic sea ice-ocean model: configuration and application
title_full A coupled regional Arctic sea ice-ocean model: configuration and application
title_fullStr A coupled regional Arctic sea ice-ocean model: configuration and application
title_full_unstemmed A coupled regional Arctic sea ice-ocean model: configuration and application
title_sort coupled regional arctic sea ice-ocean model: configuration and application
publisher Polar Research Institute of China - PRIC
publishDate 2010
url http://library.arcticportal.org/2403/
http://library.arcticportal.org/2403/1/A2010-017.pdf
geographic Arctic
Arctic Ocean
Canada
Greenland
geographic_facet Arctic
Arctic Ocean
Canada
Greenland
genre Advances in Polar Science
Arctic
Arctic
Arctic Ocean
Greenland
Polar Science
Polar Science
Sea ice
genre_facet Advances in Polar Science
Arctic
Arctic
Arctic Ocean
Greenland
Polar Science
Polar Science
Sea ice
op_relation http://library.arcticportal.org/2403/1/A2010-017.pdf
Qun, Li and Lu, Zhang and Huiding, Wu (2010) A coupled regional Arctic sea ice-ocean model: configuration and application. Advances in Polar Science, 21 (2). pp. 180-192.
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