Ocean Dynamics

, Volume 64, Issue 12, pp 1693–1717 | Cite as

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

  • Linghan LiEmail author
  • Arthur J. Miller
  • Julie L. McClean
  • Ian Eisenman
  • Myrl C. Hendershott


A fine-resolution (1/10°) ocean/sea ice model configured in the Community Earth System Model framework is compared with observations and studied to determine the basin-scale and local balances controlling the variability of sea ice anomalies from the mean seasonal cycle in the Bering Sea for the time period 1980–1989. The model produces variations in total Bering Sea ice area anomalies that are highly correlated with observations. Surface air temperature, which is specified from reanalysis atmospheric forcing, strongly controls the ice volume variability in this simulation. The thermodynamic ice volume change is dominated by surface energy flux via atmosphere-ice sensible heat flux, except near the southern ice edge where it is largely controlled by ocean-ice heat flux. While thermodynamic processes dominate the variations in ice volume in the Bering Sea on the large scale, dynamic processes are important on the local scale near ice margins (both oceanic and land), where dynamic and thermodynamic ice volume changes have opposite signs and nearly cancel each other. Ice motion is generally consistent with winds driving the flow, except near certain straits in the north where ice motion largely follows ocean currents. Two key climate events, strong ice growth with cold air temperature and northerly wind anomalies in February 1984 and weak ice growth with warm air temperature and southerly wind anomalies in February 1989, are studied here in detail. While the processes controlling the ice changes are generally similar to those in other years, these large events help reveal the characteristic spatial patterns of ice growth/melt and transport anomalies.


Sea ice Bering Sea Interannual variability Ice growth/melt Sea ice motion Climate dynamics 



This study formed a portion of the Ph.D. dissertation of LL at Scripps Institution of Oceanography. Funding was provided by National Science Foundation grants OCE-0960770, OCE-1419306, and ARC-1107795. JLM was supported by the US Department of Energy’s Office of Biological and Environmental Research in the Office of Science as part of a project named “Ultra High Resolution Global Climate Simulation to Explore and Quantify Predictive Skill for Climate Means, Variability and Extremes” and DOE DE-FG0205ER64119. The SIO Department generously provided salary support for LL during her final year at Scripps. The ocean/sea-ice simulation was conducted using computer resources (Yellowstone; ark:/85065/d7wd3xhc) provided by the Climate Simulation Laboratory at NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation and other agencies. Computer resources were also provided by the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy. Caroline Papadopoulos (SIO) carried out the ocean sea ice simulation. Elena Yulaeva (SIO) is thanked for extracting the Bering Sea ocean and sea-ice model fields and transferring them from the NSF computing facility at Yellowstone to SIO.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Linghan Li
    • 1
    Email author
  • Arthur J. Miller
    • 1
  • Julie L. McClean
    • 1
  • Ian Eisenman
    • 1
  • Myrl C. Hendershott
    • 1
  1. 1.Scripps Institution of OceanographyUniversity of California, San DiegoLa JollaUSA

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