Arctic Ocean Ice Thickness: Modes of Variability and the Best Locations from Which to Monitor Them

R. W. Lindsay Polar Science Center, University of Washington, Seattle, Washington

Search for other papers by R. W. Lindsay in
Current site
Google Scholar
PubMed
Close
and
J. Zhang Polar Science Center, University of Washington, Seattle, Washington

Search for other papers by J. Zhang in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Model simulations of Arctic sea ice and ocean systems are used to determine the major spatial and temporal modes of variability in the ice thickness. A coupled ice–ocean model is forced with daily NCEP–NCAR reanalysis surface air pressure and surface air temperature fields for the period 1951–2003 with the analysis of the results performed for the 51-yr period 1953–2003. Ice concentration data and ice velocity data (beginning in 1979) are assimilated to further constrain the simulations to match the observed conditions. The simulated ice thins over the study period with the area of greatest thinning in a band from the Laptev Sea across the Pole to Fram Strait. The thinning rate is greatest since 1988. The major spatial modes of variability were determined with empirical orthogonal functions (EOFs) for the ice thickness within the Arctic Ocean. The first three EOFs account for 30%, 18%, and 15%, respectively, of the annual mean ice thickness variance. The first EOF is a nearly basinwide pattern, and the next two are orthogonal lateral modes. Because of the nonstationary nature of the ice thickness time series, significant changes in the modes are found if a shorter period is analyzed. The second and third principal components are well correlated with the Arctic Oscillation. The model results are also used to simulate an observation system and to then determine optimal mooring locations to monitor the basinwide mean ice thickness as well as the spatial and temporal patterns represented in the EOF analysis. The nonstationary aspect of the ice thickness limits the strength of the conclusions that can be drawn.

Corresponding author address: Dr. R. Lindsay, Polar Science Center, University of Washington, 1013 N.E. 40th St., Seattle, WA 98105. Email: lindsay@apl.washington.edu

Abstract

Model simulations of Arctic sea ice and ocean systems are used to determine the major spatial and temporal modes of variability in the ice thickness. A coupled ice–ocean model is forced with daily NCEP–NCAR reanalysis surface air pressure and surface air temperature fields for the period 1951–2003 with the analysis of the results performed for the 51-yr period 1953–2003. Ice concentration data and ice velocity data (beginning in 1979) are assimilated to further constrain the simulations to match the observed conditions. The simulated ice thins over the study period with the area of greatest thinning in a band from the Laptev Sea across the Pole to Fram Strait. The thinning rate is greatest since 1988. The major spatial modes of variability were determined with empirical orthogonal functions (EOFs) for the ice thickness within the Arctic Ocean. The first three EOFs account for 30%, 18%, and 15%, respectively, of the annual mean ice thickness variance. The first EOF is a nearly basinwide pattern, and the next two are orthogonal lateral modes. Because of the nonstationary nature of the ice thickness time series, significant changes in the modes are found if a shorter period is analyzed. The second and third principal components are well correlated with the Arctic Oscillation. The model results are also used to simulate an observation system and to then determine optimal mooring locations to monitor the basinwide mean ice thickness as well as the spatial and temporal patterns represented in the EOF analysis. The nonstationary aspect of the ice thickness limits the strength of the conclusions that can be drawn.

Corresponding author address: Dr. R. Lindsay, Polar Science Center, University of Washington, 1013 N.E. 40th St., Seattle, WA 98105. Email: lindsay@apl.washington.edu

Save
  • Bryan, K., 1969: A numerical method for the study of the circulation of the world oceans. J. Comput. Phys, 4 , 347376.

  • Chapman, W. L., and J. E. Walsh, 1993: Recent variations of sea ice and air temperatures in high latitudes. Bull. Amer. Meteor. Soc, 74 , 3347.

    • Search Google Scholar
    • Export Citation
  • Cox, M. D., 1984: A primitive equation, three-dimensional model of the oceans. GFDL Ocean Group Tech. Rep. 1, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton University, Princeton, NJ, 250 pp.

  • Flato, G. M., and W. D. Hibler III, 1995: Ridging and strength in modeling the thickness distribution of Arctic sea ice. J. Geophys. Res, 100 , C9. 1861118626.

    • Search Google Scholar
    • Export Citation
  • Hibler III, W. D., 1979: A dynamic thermodynamic sea ice model. J. Phys. Oceanogr, 9 , 817846.

  • Hibler III, W. D., and K. Bryan, 1987: A diagnostic ice–ocean model. J. Phys. Oceanogr, 17 , 9871015.

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc, 77 , 437471.

  • Kraus, E. B., and J. S. Turner, 1967: A one-dimensional model of the seasonal thermocline: II. The general theory and its consequences. Tellus, 19 , 98106.

    • Search Google Scholar
    • Export Citation
  • Lindsay, R. W., and J. Zhang, 2005: The thinning of Arctic sea ice, 1988–2003: Have we passed a tipping point? J. Climate, 18 , 48794894.

    • Search Google Scholar
    • Export Citation
  • Lindsay, R. W., and J. Zhang, 2006: Assimilation of ice concentration in an ice–ocean model. J. Atmos. Oceanic Technol, in press.

  • Morison, J. H., and Coauthors, 2002: North Pole Environmental Observatory delivers early results. Eos, Trans. Amer. Geophys. Union, 83 , 357. 360361.

    • Search Google Scholar
    • Export Citation
  • Parkinson, C. L., and W. M. Washington, 1979: A large scale numerical model of sea ice. J. Geophys. Res, 84 , 311337.

  • Partington, K., T. Flynn, D. Lamb, C. Bertoia, and K. Dedrick, 2003: Late twentieth century Northern Hemisphere sea-ice record from U.S. National Ice Center ice charts. J. Geophys. Res, 108 .3343, doi:10.01029/2002JC001623.

    • Search Google Scholar
    • Export Citation
  • Rayner, N. A., E. B. Horton, D. E. Parker, C. K. Folland, and R. B. Hacket, 1996: Version 2.2 of the global sea-ice and sea surface temperature data set, 1903–1994. Hadley Centre for Climate Prediction and Research, Climate Research Tech. Note 74, 21 pp.

  • Rigor, I. G., J. M. Wallace, and R. L. Colony, 2002: Response of sea ice to the Arctic Oscillation. J. Climate, 15 , 26482663.

  • Rothrock, D. A., Y. Yu, and G. A. Maykut, 1999: Thinning of the Arctic sea-ice cover. Geophys. Res. Lett, 26 , 34693472.

  • Rothrock, D. A., J. Zhang, and Y. Yu, 2003: The Arctic ice thickness anomaly of the 1990s: A consistent view from observations and models. J. Geophys. Res, 108 .3083, doi:10.1029/2001JC001208.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., and Coauthors, 2003: A record minimum Arctic sea ice extent and area in 2002. Geophys. Res. Lett, 30 .1110, doi:10.1029/2002GL016406.

    • Search Google Scholar
    • Export Citation
  • Singarayer, J. S., and J. L. Bamber, 2003: EOF analysis of three records of sea-ice concentration spanning the last thirty years. Geophys. Res. Lett, 30 .1251, doi:10.1029/2002GL016640.

    • Search Google Scholar
    • Export Citation
  • Thompson, D. W. J., and J. M. Wallace, 1998: The Arctic Oscillation signature in the wintertime geopotential height and temperature fields. Geophys. Res. Lett, 25 , 12971300.

    • Search Google Scholar
    • Export Citation
  • Winton, M., 2000: A reformulated three-layer sea ice model. J. Atmos. Oceanic Technol, 17 , 525531.

  • Zhang, J., and W. D. Hibler III, 1997: On an efficient numerical method for modeling sea ice dynamics. J. Geophys. Res, 102 , 86918702.

    • Search Google Scholar
    • Export Citation
  • Zhang, J., W. D. Hibler III, M. Steele, and D. A. Rothrock, 1998: Arctic ice-ocean modeling with and without climate restoring. J. Phys. Oceanogr, 28 , 191217.

    • Search Google Scholar
    • Export Citation
  • Zhang, J., D. A. Rothrock, and M. Steele, 2000: Recent changes in Arctic sea ice: The interplay between ice dynamics and thermodynamics. J. Climate, 13 , 30993114.

    • Search Google Scholar
    • Export Citation
  • Zhang, J., D. R. Thomas, D. A. Rothrock, R. W. Lindsay, Y. Yu, and R. Kwok, 2003: Assimilation of ice motion observations and comparisons with submarine ice thickness data. J. Geophys. Res, 108 .3170, doi:10.1029/2001JC001041.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 932 538 76
PDF Downloads 197 41 8