The Impact of Stratospheric Circulation Extremes on Minimum Arctic Sea Ice Extent

Karen L. Smith Lamont-Doherty Earth Observatory, Palisades, New York

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Lorenzo M. Polvani Department of Applied Physics and Applied Mathematics, and Department of Earth and Environmental Sciences, Columbia University, New York, New York

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L. Bruno Tremblay Department of Atmospheric and Oceanic Sciences, McGill University, Montreal, Quebec, Canada

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Abstract

Given the rapidly changing Arctic climate, there is an urgent need for improved seasonal predictions of Arctic sea ice. Yet, Arctic sea ice prediction is inherently complex. Among other factors, wintertime atmospheric circulation has been shown to be predictive of summertime Arctic sea ice extent. Specifically, many studies have shown that the interannual variability of summertime Arctic sea ice extent (SIE) is anticorrelated with the leading mode of extratropical atmospheric variability, the Arctic Oscillation (AO), in the preceding winter. Given this relationship, the potential predictive role of stratospheric circulation extremes and stratosphere–troposphere coupling in linking the AO and Arctic SIE variability is examined. It is shown that extremes in the stratospheric circulation during the winter season, namely, stratospheric sudden warming (SSW) and strong polar vortex (SPV) events, are associated with significant anomalies in sea ice concentration in the Barents Sea in spring and along the Eurasian coastline in summer in both observations and a fully coupled, stratosphere-resolving general circulation model. Consistent with previous work on the AO, it is shown that SSWs, which are followed by the negative phase of the AO at the surface, result in sea ice growth, whereas SPVs, which are followed by the positive phase of the AO at the surface, result in sea ice loss, although the mechanisms in the Barents Sea and along the Eurasian coastline are different. The analysis suggests that the presence or absence of stratospheric circulation extremes in winter may play a nontrivial role in determining total September Arctic SIE when combined with other factors.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-17-0495.s1.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Current affiliation: Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada.

Corresponding author: Karen L. Smith, karen.smith@utoronto.ca

Abstract

Given the rapidly changing Arctic climate, there is an urgent need for improved seasonal predictions of Arctic sea ice. Yet, Arctic sea ice prediction is inherently complex. Among other factors, wintertime atmospheric circulation has been shown to be predictive of summertime Arctic sea ice extent. Specifically, many studies have shown that the interannual variability of summertime Arctic sea ice extent (SIE) is anticorrelated with the leading mode of extratropical atmospheric variability, the Arctic Oscillation (AO), in the preceding winter. Given this relationship, the potential predictive role of stratospheric circulation extremes and stratosphere–troposphere coupling in linking the AO and Arctic SIE variability is examined. It is shown that extremes in the stratospheric circulation during the winter season, namely, stratospheric sudden warming (SSW) and strong polar vortex (SPV) events, are associated with significant anomalies in sea ice concentration in the Barents Sea in spring and along the Eurasian coastline in summer in both observations and a fully coupled, stratosphere-resolving general circulation model. Consistent with previous work on the AO, it is shown that SSWs, which are followed by the negative phase of the AO at the surface, result in sea ice growth, whereas SPVs, which are followed by the positive phase of the AO at the surface, result in sea ice loss, although the mechanisms in the Barents Sea and along the Eurasian coastline are different. The analysis suggests that the presence or absence of stratospheric circulation extremes in winter may play a nontrivial role in determining total September Arctic SIE when combined with other factors.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-17-0495.s1.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Current affiliation: Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada.

Corresponding author: Karen L. Smith, karen.smith@utoronto.ca

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  • Arthun, M., T. Eldevik, L. H. Smedsrud, O. Skagseth, and R. B. Ingvaldsen, 2012: Quantifying the influence of Atlantic heat on Barents sea ice variability and retreat. J. Climate, 25, 47364743, https://doi.org/10.1175/JCLI-D-11-00466.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baldwin, M., and T. Dunkerton, 2001: Stratospheric harbingers of anomalous weather regimes. Science, 294, 581584, https://doi.org/10.1126/science.1063315.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bitz, C. M., M. M. Holland, E. C. Hunke, and R. E. Moritz, 2005: Maintenance of the sea-ice edge. J. Climate, 18, 29032921, https://doi.org/10.1175/JCLI3428.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bushuk, M., R. Msadek, M. Winton, G. A. Vecchi, R. Gudgel, A. Rosati, and X. Yang, 2017: Skillful regional prediction of Arctic sea ice on seasonal timescales. Geophys. Res. Lett., 44, 49534964, https://doi.org/10.1002/2017GL073155.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Butler, A. H., D. J. Seidel, S. C. Hardiman, N. Butchart, T. Birner, and A. Match, 2015: Defining sudden stratospheric warmings. Bull. Amer. Meteor. Soc., 96, 19131928, https://doi.org/10.1175/BAMS-D-13-00173.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cai, D., M. Dameris, H. Garny, and T. Runde, 2012: Implications of all season Arctic sea-ice anomalies on the stratosphere. Atmos. Chem. Phys., 12, 11 81911 831, https://doi.org/10.5194/acp-12-11819-2012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charlton-Perez, A. J., and L. Polvani, 2007: A new look at stratospheric sudden warmings. Part I: Climatology and modeling benchmarks. J. Climate, 20, 449469, https://doi.org/10.1175/JCLI3996.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charlton-Perez, A. J., and Coauthors, 2013: On the lack of stratospheric dynamical variability in low-top versions of the CMIP5 models. J. Geophys. Res. Atmos., 118, 24942505, https://doi.org/10.1002/jgrd.50125.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, Z., J. Liu, M. Song, Q. Yang, and S. Xu, 2017: Impacts of assimilating satellite sea ice concentration and thickness on Arctic sea ice prediction in the NCEP Climate Forecast System. J. Climate, 30, 84298446, https://doi.org/10.1175/JCLI-D-17-0093.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chevallier, M., and D. Salas-Mélia, 2012: The role of sea ice thickness distribution in the Arctic sea ice potential predictability: A diagnostic approach with a coupled GCM. J. Climate, 25, 30253038, https://doi.org/10.1175/JCLI-D-11-00209.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Comiso, J., 2000: Bootstrap sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS, version 2. National Snow and Ice Data Center Distributed Active Archive Center. Subset used: Northern Hemisphere daily data (updated yearly), accessed 9 September 2016, https://doi.org/10.5067/J6JQLS9EJ5HU.

    • Crossref
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, https://doi.org/10.1002/qj.828.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Douville, H., 2009: Stratospheric polar vortex influence on Northern Hemisphere winter climate variability. Geophys. Res. Lett., 36, L18703, https://doi.org/10.1029/2009GL039334.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Feldstein, S. B., and S. Lee, 2014: Intraseasonal and interdecadal jet shifts in the Northern Hemisphere: The role of warm pool tropical convection and sea ice. J. Climate, 27, 64976518, https://doi.org/10.1175/JCLI-D-14-00057.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Garfinkel, C. I., A. H. Butler, D. W. Waugh, M. M. Hurwitz, and L. M. Polvani, 2012: Why might stratospheric sudden warmings occur with similar frequency in El Niño and La Niña winters? J. Geophys. Res., 117, D19106, https://doi.org/10.1029/2012JD017777.

    • Search Google Scholar
    • Export Citation
  • Holland, M. M., and J. Stroeve, 2011: Changing seasonal sea ice predictor relationships in a changing Arctic climate. Geophys. Res. Lett., 38, L18501, https://doi.org/10.1029/2011GL049303.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hunke, E. C., and W. H. Lipscomb, 2008: CICE: The Los Alamos sea ice model, documentation and software, version 4.0. Los Alamos National Laboratory Tech. Rep. LA-CC-06-012, 76 pp.

  • Itkin, P., and T. Krumpen, 2017: Winter sea ice export from the Laptev Sea preconditions the local summer sea ice cover and fast ice decay. Cryosphere, 11, 23832391, https://doi.org/10.5194/tc-11-2383-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jung, T., and Coauthors, 2016: Advancing polar prediction capabilities on daily to seasonal time scales. Bull. Amer. Meteor. Soc., 97, 16311647, https://doi.org/10.1175/BAMS-D-14-00246.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kim, B.-M., S.-W. Son, S.-K. Min, J.-H. Jeong, S.-J. Kim, X. Zhang, T. Shim, and J.-H. Yoon, 2014: Weakening of the stratospheric polar vortex by Arctic sea-ice loss. Nat. Commun., 5, 4646, https://doi.org/10.1038/ncomms5646.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kimura, N., A. Nishimura, Y. Tanaka, and H. Yamaguchi, 2013: Influence of winter sea-ice motion on summer ice cover in the Arctic. Polar Res., 32, 20193, https://doi.org/10.3402/polar.v32i0.20193.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koenigk, T., U. Mikolajewicz, J. H. Jungclaus, and A. Kroll, 2009: Sea ice in the Barents Sea: Seasonal to interannual variability and climate feedbacks in a global coupled model. Climate Dyn., 32, 11191138, https://doi.org/10.1007/s00382-008-0450-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landrum, L., M. M. Holland, D. P. Schneider, and E. Hunke, 2012: Antarctic sea ice climatology, variability, and late twentieth-century change in CCSM4. J. Climate, 25, 48174838, https://doi.org/10.1175/JCLI-D-11-00289.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Marsh, D. R., M. J. Mills, D. E. Kinnison, J.-F. Lamarque, N. Calvo, and L. M. Polvani, 2013: Climate change from 1850 to 2005 simulated in CESM1(WACCM). J. Climate, 26, 73727391, https://doi.org/10.1175/JCLI-D-12-00558.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ogi, M., K. Yamazaki, and J. M. Wallace, 2010: Influence of winter and summer surface wind anomalies on summer Arctic sea ice extent. Geophys. Res. Lett., 37, L07701, https://doi.org/10.1029/2009GL042356.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peings, Y., and G. Magnusdottir, 2014: Response of the wintertime Northern Hemisphere atmospheric circulation to current and projected Arctic sea ice decline: A numerical study with CAM5. J. Climate, 27, 244264, https://doi.org/10.1175/JCLI-D-13-00272.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Petty, A. A., D. Schroder, J. C. Stroeve, T. Markus, J. Miller, N. T. Kurtz, D. L. Feltman, and D. Flocco, 2017: Skillful spring forecasts of September Arctic sea ice extent using passive microwave sea ice observations. Earth’s Future, 5, 254263, https://doi.org/10.1002/2016EF000495.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polvani, L. M., L. Sun, A. H. Butler, J. H. Richter, and C. Deser, 2017: Distinguishing stratospheric sudden warmings from ENSO as key drivers of wintertime climate variability over the North Atlantic and Eurasia. J. Climate, 30, 19591969, https://doi.org/10.1175/JCLI-D-16-0277.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rigor, I. G., and J. M. Wallace, 2004: Variations in the age of Arctic sea-ice and summer sea-ice extent. Geophys. Res. Lett., 31, L09401, https://doi.org/10.1029/2004GL019492.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rigor, I. G., J. M. Wallace, and R. L. Colony, 2002: Response of sea ice to the Arctic Oscillation. J. Climate, 15, 26482663, https://doi.org/10.1175/1520-0442(2002)015<2648:ROSITT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scaife, A. A., J. R. Knight, G. K. Vallis, and C. K. Folland, 2005: A stratospheric influence on the winter NAO and North Atlantic surface climate. Geophys. Res. Lett., 32, L18715, https://doi.org/10.1029/2005GL023226.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scaife, A. A., and Coauthors, 2016: Seasonal winter forecasts and the stratosphere. Atmos. Sci. Lett., 17, 5156, https://doi.org/10.1002/asl.598.

  • Schröder, D., D. L. Feltham, D. Flocco, and M. Tsamados, 2014: September Arctic sea-ice minimum predicted by spring melt-pond fraction. Nat. Climate Change, 4, 353357, https://doi.org/10.1038/nclimate2203.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scinocca, J. F., M. C. Reader, D. A. Plummer, M. Sigmond, P. J. Kushner, T. G. Shepherd, and R. Ravishankara, 2009: Impact of sudden Arctic sea-ice loss on stratospheric polar ozone recovery. Geophys. Res. Lett., 36, L24701, https://doi.org/10.1029/2009GL041239.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shu, Q., Z. Song, and F. Qiao, 2015: Assessment of sea ice simulations in the CMIP5 models. Cryosphere, 9, 399409, https://doi.org/10.5194/tc-9-399-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sigmond, M., J. F. Scinocca, V. V. Kharin, and T. G. Shepherd, 2013: Enhanced seasonal forecast skill following stratospheric sudden warmings. Nat. Geosci., 6, 98102, https://doi.org/10.1038/ngeo1698.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sorteberg, A., and B. Kvingedal, 2006: Atmospheric forcing on the Barents Sea winter ice extent. J. Climate, 19, 47724784, https://doi.org/10.1175/JCLI3885.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., J. Maslanik, M. C. Serreze, I. Rigor, W. Meier, and C. Fowler, 2011: Sea ice response to an extreme negative phase of the Arctic Oscillation during winter 2009/2010. Geophys. Res. Lett., 38, L02502, https://doi.org/10.1029/2010GL045662.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., V. Kattsov, A. Barrett, M. Serreze, T. Pavlova, M. Holland, and W. N. Meier, 2012: Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations. Geophys. Res. Lett., 39, L16502, https://doi.org/10.1029/2012GL052676.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., A. Barrett, M. Serreze, and A. Schweiger, 2014a: Using records from submarine, aircraft and satellites to evaluate climate model simulations of Arctic sea ice thickness. Cryosphere, 8, 18391854, https://doi.org/10.5194/tc-8-1839-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., L. C. Hamilton, C. M. Bitz, and E. Blanchard-Wrigglesworth, 2014b: Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008–2013. Geophys. Res. Lett., 41, 24112418, https://doi.org/10.1002/2014GL059388.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stroeve, J. C., E. Blanchard-Wrigglesworth, V. Guemas, S. Howell, F. Massonnet, and S. Tietsche, 2015: Improving predictions of Arctic sea ice extent. Eos, Earth and Space Science News, No. 96, 10–15, https://doi.org/10.1029/2015EO031431.

    • Crossref
    • Export Citation
  • Strong, C., and G. Magnusdottir, 2010: Modeled winter sea ice variability and the North Atlantic Oscillation: A multi-century perspective. Climate Dyn., 34, 515525, https://doi.org/10.1007/s00382-009-0550-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Strong, C., and K. M. Golden, 2016: Filling the polar data gap in sea ice concentration fields using partial differential equations. Remote Sens., 8, 442, https://doi.org/10.3390/rs8060442.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Strong, C., G. Magnusdottir, and H. Stern, 2009: Observed feedback between winter sea ice and the North Atlantic Oscillation. J. Climate, 22, 60216032, https://doi.org/10.1175/2009JCLI3100.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, L., C. Deser, L. Polvani, and R. Tomas, 2014: Influence of projected Arctic sea ice loss on polar stratospheric ozone and circulation in spring. Environ. Res. Lett., 9, 084016, https://doi.org/10.1088/1748-9326/9/8/084016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, L., C. Deser, and R. A. Tomas, 2015: Mechanisms of stratospheric and tropospheric circulation response to projected Arctic sea ice loss. J. Climate, 28, 78247845, https://doi.org/10.1175/JCLI-D-15-0169.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thorndike, A. S., D. A. Rothrock, G. A. Maykut, and R. Colony, 1975: The thickness distribution of sea ice. J. Geophys. Res., 80, 45014513, https://doi.org/10.1029/JC080i033p04501.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tietsche, S., D. Notz, J. H. Jungclaus, and J. Marotzke, 2013: Predictability of large interannual Arctic sea-ice anomalies. Climate Dyn., 41, 25112526, https://doi.org/10.1007/s00382-013-1698-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wettstein, J. J., and C. Deser, 2014: Internal variability in projections of twenty-first-century Arctic sea ice loss: Role of the large-scale atmospheric circulation. J. Climate, 27, 527550, https://doi.org/10.1175/JCLI-D-12-00839.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, J., B. Tremblay, R. Newton, and R. Allard, 2016: Dynamic preconditioning of the minimum September sea-ice extent. J. Climate, 29, 58795891, https://doi.org/10.1175/JCLI-D-15-0515.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, Q., and X. Zhang, 2010: Observed forcing feedback processes between Northern Hemisphere atmospheric circulation and Arctic sea ice coverage. Geophys. Res. Lett., 115, D14119, https://doi.org/10.1029/2009JD013574.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, Y., and K. L. Smith, 2016: Response of Northern Hemisphere midlatitude circulation to Arctic amplification in a simple atmospheric general circulation model. J. Climate, 29, 20412058, https://doi.org/10.1175/JCLI-D-15-0602.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, X. Y., X. Yuan, and M. Ting, 2016: Dynamical link between the Barents–Kara Sea ice and the Arctic Oscillation. J. Climate, 29, 51035122, https://doi.org/10.1175/JCLI-D-15-0669.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, J., and D. A. Rothrock, 2003: Modeling global sea ice with a thickness and enthalpy distribution model in generalized curvilinear coordinates. Mon. Wea. Rev., 131, 845861, https://doi.org/10.1175/1520-0493(2003)131<0845:MGSIWA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, P., Y. Wu, and K. Smith, 2018: Prolonged effect of the stratospheric pathway in linking Barents–Kara Sea sea ice variability to the midlatitude circulation in a simplified model. Climate Dyn., 50, 527539, https://doi.org/10.1007/s00382-017-3624-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
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