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Spatiotemporal dependence of Antarctic sea ice variability to dynamic and thermodynamic forcing: a coupled ocean–sea ice model study

  • Kazuya Kusahara
  • Guy D. Williams
  • Robert Massom
  • Philip Reid
  • Hiroyasu Hasumi
Article

Abstract

Satellite-derived Antarctic sea ice extent has displayed a slight upward since 1979, but with strong temporal and regional variability—the drivers of which are poorly understood. Here, we conduct numerical experiments with a circum-Antarctic ocean–sea ice–ice shelf model driven by realistic atmospheric surface boundary conditions to examine the factors responsible for the temporal and spatial patterns in observed Antarctic sea ice variability. The model successfully reproduces observed seasonal and interannual variability in total sea ice extent and the temporal/spatial patterns of sea ice concentration and seasonality (days of advance and retreat and actual ice days) for 1979–2014. Sensitivity experiments are performed, in which the interannual variability in wind stress or thermodynamic surface forcing is ignored, to delineate their contributions to Antarctic sea ice fields. The results demonstrate that: (1) thermodynamic forcing plays a key role in driving interannual variability in sea ice extent and seasonality in most Antarctic sectors; (2) only in the Ross Sea the wind stress does become the main driver of sea ice extent variability; (3) thermodynamic forcing largely regulates interannual variability in the timing of sea ice advance, while wind stress largely controls the timing of the sea ice retreat; and (4) although both wind stress and thermodynamic forcing contribute to variability in total sea ice volume, the wind stress plays a dominant role in regulating sea ice volume variability in the near-coastal zone.

Keywords

Antarctic sea ice variability An ocean–sea ice model Wind stress Thermodynamic forcing 

Notes

Acknowledgements

This research was supported by the Australian Government’s Business Cooperative Research Centres Programme through the Antarctic Climate an Ecosystems Cooperative Research Centre (ACE CRC), and contributes to AAS 4116. GW was supported by the Australian Research Council’s Future Fellowship program. HH was supported by Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number JP26247080. We thank two anonymous reviewers for their helpful and constructive comments on the manuscript.

References

  1. Allison I, Worby A (1994) Seasonal changes of sea–ice characteristics off east Antarctica. Ann Glaciol 20:195–201.  https://doi.org/10.3189/172756494794587096 doiCrossRefGoogle Scholar
  2. Arzel O, Fichefet T, Goosse H (2006) Sea ice evolution over the 20th and 21st centuries as simulated by current AOGCMs. Ocean Model 12:401–415.  https://doi.org/10.1016/j.ocemod.2005.08.002 CrossRefGoogle Scholar
  3. Bitz CM, Lipscomb WH (1999) An energy-conserving thermodynamic model of sea ice. J Geophys Res 104:15669–15677.  https://doi.org/10.1029/1999JC900100 CrossRefGoogle Scholar
  4. Cavalieri DJ, Gloersen P, Campbell WJ (1984) Determination of sea ice parameters with the NIMBUS 7 SMMR. J Geophys Res Atmos 89:5355–5369.  https://doi.org/10.1029/JD089iD04p05355 CrossRefGoogle Scholar
  5. Comiso JC, Kwok R, Martin S, Gordon AL (2011) Variability and trends in sea ice extent and ice production in the Ross Sea. J Geophys Res Ocean 116:1–19.  https://doi.org/10.1029/2010JC006391 CrossRefGoogle Scholar
  6. Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597.  https://doi.org/10.1002/qj.828 CrossRefGoogle Scholar
  7. Hasumi H (2006) CCSR ocean component model (COCO) version 4.0. CCSR Rep. No. 25Google Scholar
  8. Hibler WD (1979) A dynamic thermodynamic sea ice model. J Phys Oceanogr 9:815–846.  https://doi.org/10.1175/1520-0485(1979)009%3C0815:ADTSIM%3E2.0.CO;2 CrossRefGoogle Scholar
  9. Hobbs WR, Massom R, Stammerjohn S et al (2016) A review of recent changes in Southern Ocean sea ice, their drivers and forcings. Glob Planet Change 143:228–250.  https://doi.org/10.1016/j.gloplacha.2016.06.008 CrossRefGoogle Scholar
  10. Holland PR, Bruneau N, Enright C et al (2014) Modeled trends in Antarctic sea ice thickness. J Clim 27:3784–3801.  https://doi.org/10.1175/JCLI-D-13-00301.1 CrossRefGoogle Scholar
  11. Hosking JS, Orr A, Marshall GJ et al (2013) The influence of the Amundsen–Bellingshausen Seas Low on the climate of West Antarctica and its representation in coupled climate model simulations. J Clim 26:6633–6648.  https://doi.org/10.1175/JCLI-D-12-00813.1 CrossRefGoogle Scholar
  12. Hunke EC, Dukowicz JK (1997) An elastic-viscous-plastic model for sea ice dynamics. J Phys Oceanogr 27:1849–1867.  https://doi.org/10.1175/1520-0485(1997)027%3C1849:AEVPMF%3E2.0.CO;2 CrossRefGoogle Scholar
  13. Jeffries MO, Worby AP, Morris K, Eweeks W (1997) Seasonal variations in the properties and structural composition of sea ice and snow cover in the Bellingshausen and Amundsen Seas, Antarctica. J Glaciol 43:138–151.  https://doi.org/10.1017/S0022143000002902 CrossRefGoogle Scholar
  14. Jones JM, Gille ST, Goosse H et al (2016) Assessing recent trends in high-latitude Southern Hemisphere surface climate. Nat Clim Chang 6:917–926.  https://doi.org/10.1038/nclimate3103 CrossRefGoogle Scholar
  15. Kimura N (2007) Mechanisms controlling the temporal variation of the sea ice edge in the Southern Ocean. J Oceanogr 63:685–694.  https://doi.org/10.1007/s10872-007-0060-3 CrossRefGoogle Scholar
  16. Kimura N, Wakatsuchi M (2011) Large-scale processes governing the seasonal variability of the Antarctic sea ice. Tellus. Ser A Dyn Meteorol Oceanogr 63:828–840.  https://doi.org/10.1111/j.1600-0870.2011.00526.x CrossRefGoogle Scholar
  17. Koopmans LH (1974) The spectral analysis of time series. Academic Press, New YorkGoogle Scholar
  18. Kurtz NT, Markus T (2012) Satellite observations of Antarctic sea ice thickness and volume. J Geophys Res 117:C08025.  https://doi.org/10.1029/2012JC008141 CrossRefGoogle Scholar
  19. Kusahara K, Hasumi H (2013) Modeling Antarctic ice shelf responses to future climate changes and impacts on the ocean. J Geophys Res Ocean 118:2454–2475.  https://doi.org/10.1002/jgrc.20166 CrossRefGoogle Scholar
  20. Kusahara K, Hasumi H (2014) Pathways of basal meltwater from Antarctic ice shelves: a model study. J Geophys Res Ocean 119:5690–5704.  https://doi.org/10.1002/2014JC009915 CrossRefGoogle Scholar
  21. Kusahara K, Williams GD, Massom R et al (2017) Roles of wind stress and thermodynamic forcing in recent trends in Antarctic sea ice and Southern Ocean SST: an ocean–sea ice model study. Glob Planet Change 158:103–118.  https://doi.org/10.1016/j.gloplacha.2017.09.012 CrossRefGoogle Scholar
  22. Leppäranta M (2005) The drift of sea ice. Springer, ChichesterGoogle Scholar
  23. Maksym T, Stammerjohn S, Ackley S, Massom R (2012) Antarctic sea ice—a polar opposite? Oceanography 25:140–151.  https://doi.org/10.5670/oceanog.2012.88 CrossRefGoogle Scholar
  24. Massom R, Reid P, Stammerjohn S et al (2013) Change and variability in East Antarctic sea ice seasonality, 1979/80–2009/10. PLoS ONE.  https://doi.org/10.1371/journal.pone.0064756 Google Scholar
  25. Mellor GL, Kantha L (1989) An ice–ocean coupled model. J Geophys Res 94:10937–10954Google Scholar
  26. Nuncio M, Luis AJ, Yuan X (2011) Topographic meandering of Antarctic Circumpolar Current and Antarctic Circumpolar Wave in the ice–ocean–atmosphere system. Geophys Res Lett.  https://doi.org/10.1029/2011GL046898 Google Scholar
  27. Parkinson CL, Cavalieri DJ (2012) Antarctic sea ice variability and trends, 1979–2010. Cryosphere 6:871–880.  https://doi.org/10.5194/tc-6-871-2012 CrossRefGoogle Scholar
  28. Raphael MN, Marshall GJ, Turner J et al (2016) The Amundsen sea low: variability, change, and impact on Antarctic climate. Bull Am Meteorol Soc 97:111–121.  https://doi.org/10.1175/BAMS-D-14-00018.1 CrossRefGoogle Scholar
  29. Raphael MN, Holland MM, Landrum L, Hobbs WR (2018) Links between the Amundsen Sea Low and sea ice in the Ross Sea: seasonal and interannual relationships. Clim Dyn.  https://doi.org/10.1007/s00382-018-4258-4 Google Scholar
  30. Röske F (2006) A global heat and freshwater forcing dataset for ocean models. Ocean Model 11:235–297.  https://doi.org/10.1016/j.ocemod.2004.12.005 CrossRefGoogle Scholar
  31. Shu Q, Song Z, Qiao F (2015) Assessment of sea ice simulations in the CMIP5 models. Cryosphere 9:399–409.  https://doi.org/10.5194/tc-9-399-2015 CrossRefGoogle Scholar
  32. Simpkins GR, Ciasto LM, England MH (2013) Observed variations in multidecadal Antarctic sea ice trends during 1979–2012. Geophys Res Lett 40:3643–3648.  https://doi.org/10.1002/grl.50715 CrossRefGoogle Scholar
  33. Stammerjohn SE, Martinson DG, Smith RC et al (2008) Trends in Antarctic annual sea ice retreat and advance and their relation to El Niño–Southern Oscillation and Southern Annular Mode variability. J Geophys Res 113:1–20.  https://doi.org/10.1029/2007JC004269 CrossRefGoogle Scholar
  34. Stammerjohn S, Massom R, Rind D, Martinson D (2012) Regions of rapid sea ice change: an inter-hemispheric seasonal comparison. Geophys Res Lett.  https://doi.org/10.1029/2012GL050874 Google Scholar
  35. Steele M, Steele M, Morley R et al (2001) PHC: a global ocean hydrography with a high quality Arctic Ocean. J Clim 14:2079–2087.  https://doi.org/10.1175/1520-0442 CrossRefGoogle Scholar
  36. Swift CT, Cavalieri DJ (1985) Passive microwave remote sensing for sea ice research. EOS Trans Am Geophys Union 66:1210–1212.  https://doi.org/10.1029/EO066i049p01210 CrossRefGoogle Scholar
  37. Thomas D (2016) Sea ice, 3rd edn. Wiley-Blackwell, HobokenGoogle Scholar
  38. Thompson RORY (1979) Coherence significance levels. J Atmos Sci 36:2020–2021.  https://doi.org/10.1175/1520-0469(1979)036%3C2020:CSL%3E2.0.CO;2 CrossRefGoogle Scholar
  39. Timmermann R, Le Brocq A, Deen T et al (2010) A consistent dataset of Antarctic ice sheet topography, cavity geometry, and global bathymetry. Earth Syst Sci Data Discuss 3:231–257.  https://doi.org/10.5194/essdd-3-231-2010 CrossRefGoogle Scholar
  40. Turner J, Hosking JS, Marshall GJ et al (2016) Antarctic sea ice increase consistent with intrinsic variability of the Amundsen Sea Low. Clim Dyn 46:2391–2402.  https://doi.org/10.1007/s00382-015-2708-9 CrossRefGoogle Scholar
  41. Wadhams P, Lange MA, Ackley SF (1987) The ice thickness distribution across the Atlantic sector of the Antarctic Ocean in midwinter. J Geophys Res 92:14535.  https://doi.org/10.1029/JC092iC13p14535 CrossRefGoogle Scholar
  42. White WB, Peterson RG (1996) An Antarctic circumpolar wave in surface pressure, wind, temperature and sea–ice extent. Nature 380:699–702.  https://doi.org/10.1038/380699a0 CrossRefGoogle Scholar
  43. Working Group I/IPCC (2013) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, New York.  https://doi.org/10.1017/CBO9781107415324
  44. Yuan X, Martinson DG (2000) Antarctic sea ice extent variability and its global connectivity. J Clim 13:1697–1717.  https://doi.org/10.1175/1520-0442(2000)013%3C1697:ASIEVA%3E2.0.CO;2 CrossRefGoogle Scholar
  45. Yuan X, Martinson DG (2001) The Antarctic dipole and its predictability. Geophys Res Lett 28:3609–3612.  https://doi.org/10.1029/2001GL012969 CrossRefGoogle Scholar
  46. Zhang J (2014) Modeling the impact of wind intensification on Antarctic sea ice volume. J Clim 27:202–214.  https://doi.org/10.1175/JCLI-D-12-00139.1 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Japan Agency for Marine-Earth Science and Technology (JAMSTEC)Yokohama-cityJapan
  2. 2.Antarctic Climate and Ecosystems Research CentreUniversity of TasmaniaHobartAustralia
  3. 3.Institute of Marine and Antarctic StudiesUniversity of TasmaniaHobartAustralia
  4. 4.Australian Antarctic DivisionKingstonAustralia
  5. 5.Australian Bureau of MeteorologyHobartAustralia
  6. 6.Atmosphere and Ocean Research InstituteThe University of TokyoChibaJapan

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