Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle

The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model co...

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Main Authors: Li, L, McClean, JL, Miller, AJ, Eisenman, I, Hendershott, MC, Papadopoulos, CA
Format: Article in Journal/Newspaper
Language:unknown
Published: eScholarship, University of California 2014
Subjects:
Online Access:https://escholarship.org/uc/item/63t7g573
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spelling ftcdlib:oai:escholarship.org/ark:/13030/qt63t7g573 2023-05-15T15:43:19+02:00 Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle Li, L McClean, JL Miller, AJ Eisenman, I Hendershott, MC Papadopoulos, CA 2014-12-01 application/pdf https://escholarship.org/uc/item/63t7g573 unknown eScholarship, University of California qt63t7g573 https://escholarship.org/uc/item/63t7g573 public Sea ice Ice growth/melt Sea ice motion Heat flux Climate dynamics Bering Sea Oceanography Maritime Engineering article 2014 ftcdlib 2021-03-28T08:18:54Z The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic patterns occur in the model, but with typically smaller magnitudes and with season-specific geographical and directional differences. Article in Journal/Newspaper Bering Sea Sea ice St Lawrence Island University of California: eScholarship Bering Sea Lawrence Island ENVELOPE(-103.718,-103.718,56.967,56.967)
institution Open Polar
collection University of California: eScholarship
op_collection_id ftcdlib
language unknown
topic Sea ice
Ice growth/melt
Sea ice motion
Heat flux
Climate dynamics
Bering Sea
Oceanography
Maritime Engineering
spellingShingle Sea ice
Ice growth/melt
Sea ice motion
Heat flux
Climate dynamics
Bering Sea
Oceanography
Maritime Engineering
Li, L
McClean, JL
Miller, AJ
Eisenman, I
Hendershott, MC
Papadopoulos, CA
Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle
topic_facet Sea ice
Ice growth/melt
Sea ice motion
Heat flux
Climate dynamics
Bering Sea
Oceanography
Maritime Engineering
description The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic patterns occur in the model, but with typically smaller magnitudes and with season-specific geographical and directional differences.
format Article in Journal/Newspaper
author Li, L
McClean, JL
Miller, AJ
Eisenman, I
Hendershott, MC
Papadopoulos, CA
author_facet Li, L
McClean, JL
Miller, AJ
Eisenman, I
Hendershott, MC
Papadopoulos, CA
author_sort Li, L
title Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle
title_short Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle
title_full Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle
title_fullStr Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle
title_full_unstemmed Processes driving sea ice variability in the Bering Sea in an eddying ocean/sea ice model: Mean seasonal cycle
title_sort processes driving sea ice variability in the bering sea in an eddying ocean/sea ice model: mean seasonal cycle
publisher eScholarship, University of California
publishDate 2014
url https://escholarship.org/uc/item/63t7g573
long_lat ENVELOPE(-103.718,-103.718,56.967,56.967)
geographic Bering Sea
Lawrence Island
geographic_facet Bering Sea
Lawrence Island
genre Bering Sea
Sea ice
St Lawrence Island
genre_facet Bering Sea
Sea ice
St Lawrence Island
op_relation qt63t7g573
https://escholarship.org/uc/item/63t7g573
op_rights public
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