A Skillful Prediction Model for Winter NAO Based on Atlantic Sea Surface Temperature and Eurasian Snow Cover

Baoqiang Tian Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

Search for other papers by Baoqiang Tian in
Current site
Google Scholar
PubMed
Close
and
Ke Fan Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, and Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China

Search for other papers by Ke Fan in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

A new statistical forecast scheme, referred to as scheme 1, is developed using observed autumn Atlantic sea surface temperature (SST) and Eurasian snow cover in the preceding autumn to predict the upcoming winter North Atlantic Oscillation (NAO) using the year-to-year increment prediction approach (i.e., DY approach). Two predictors for the year-to-year increment are identified that are available in the preceding autumn. Cross-validation tests for the period 1950–2011 and independent hindcasts for the period 1990–2011 are performed to validate the prediction ability of the proposed technique. The cross-validation test results for 1950–2011 reveal a high correlation coefficient of 0.52 (0.58) between the predicted and observed NAO indices (DY of the NAO). The model also successfully predicts the independent hindcasts for the period 1990–2011 with a correlation coefficient of 0.55 (0.74). In addition, scheme 0 (i.e., anomaly approach) is established using the SST and snow cover anomalies during the preceding autumn. Compared with scheme 0, this new prediction model has higher predictive skill in reproducing the interdecadal variability of NAO. Therefore, this study provides an effective climate prediction scheme for the interannual and interdecadal variability of NAO in boreal winter.

Corresponding author address: Baoqiang Tian, Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Building 40, Beijing 100029, China. E-mail: tianbq@mail.iap.ac.cn

Abstract

A new statistical forecast scheme, referred to as scheme 1, is developed using observed autumn Atlantic sea surface temperature (SST) and Eurasian snow cover in the preceding autumn to predict the upcoming winter North Atlantic Oscillation (NAO) using the year-to-year increment prediction approach (i.e., DY approach). Two predictors for the year-to-year increment are identified that are available in the preceding autumn. Cross-validation tests for the period 1950–2011 and independent hindcasts for the period 1990–2011 are performed to validate the prediction ability of the proposed technique. The cross-validation test results for 1950–2011 reveal a high correlation coefficient of 0.52 (0.58) between the predicted and observed NAO indices (DY of the NAO). The model also successfully predicts the independent hindcasts for the period 1990–2011 with a correlation coefficient of 0.55 (0.74). In addition, scheme 0 (i.e., anomaly approach) is established using the SST and snow cover anomalies during the preceding autumn. Compared with scheme 0, this new prediction model has higher predictive skill in reproducing the interdecadal variability of NAO. Therefore, this study provides an effective climate prediction scheme for the interannual and interdecadal variability of NAO in boreal winter.

Corresponding author address: Baoqiang Tian, Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Building 40, Beijing 100029, China. E-mail: tianbq@mail.iap.ac.cn
Save
  • Bojariu, R., and Gimeno L. , 2003a: Predictability and numerical modelling of the North Atlantic Oscillation. Earth Sci. Rev., 63, 145168, doi:10.1016/S0012-8252(03)00036-9.

    • Search Google Scholar
    • Export Citation
  • Bojariu, R., and Gimeno L. , 2003b: The role of snow cover fluctuations in multiannual NAO persistence. Geophys. Res. Lett., 30, 1156, doi:10.1029/2002GL015651.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and Entekhabi D. , 1999: Eurasian snow cover variability and Northern Hemisphere climate predictability. Geophys. Res. Lett., 26, 345348, doi:10.1029/1998GL900321.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and Entekhabi D. , 2001: The influence of snow cover on Northern Hemisphere climate variability. Atmos.–Ocean, 39, 3553, doi:10.1080/07055900.2001.9649665.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., and Fletcher C. , 2007: Improved skill of Northern Hemisphere winter surface temperature predictions based on land–atmosphere fall anomalies. J. Climate, 20, 41184132, doi:10.1175/JCLI4241.1.

    • Search Google Scholar
    • Export Citation
  • Cohen, J., Barlow M. , Kushner P. J. , and Saito K. , 2007: Stratosphere–troposphere coupling and links with Eurasian land surface variability. J. Climate, 20, 53355343, doi:10.1175/2007JCLI1725.1.

    • Search Google Scholar
    • Export Citation
  • Compo, G. P., and Coauthors, 2011: The Twentieth Century Reanalysis Project. Quart. J. Roy. Meteor. Soc., 137, 128, doi:10.1002/qj.776.

    • Search Google Scholar
    • Export Citation
  • Czaja, A., and Frankignoul C. , 1999: Influence of the North Atlantic SST on the atmospheric circulation. Geophys. Res. Lett., 26, 29692972, doi:10.1029/1999GL900613.

    • Search Google Scholar
    • Export Citation
  • Czaja, A., and Frankignoul C. , 2002: Observed impact of Atlantic SST anomalies on the North Atlantic Oscillation. J. Climate, 15, 606623, doi:10.1175/1520-0442(2002)015<0606:OIOASA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Doblas-Reyes, F. J., Pavan V. , and Stephenson D. B. , 2003: The skill of multi-model seasonal forecasts of the wintertime North Atlantic Oscillation. Climate Dyn., 21, 501514, doi:10.1007/s00382-003-0350-4.

    • Search Google Scholar
    • Export Citation
  • Falarz, M., 2004: Variability and trends in the duration and depth of snow cover in Poland in the 20th century. Int. J. Climatol., 24, 17131727, doi:10.1002/joc.1093.

    • Search Google Scholar
    • Export Citation
  • Fan, K., and Tian B. Q. , 2013: Prediction of wintertime heavy snow activity in northeast China. Chin. Sci. Bull.,58, 1420–1426, doi:10.1007/s11434-012-5502-7.

  • Fan, K., Wang H. , and Choi Y. J. , 2008: A physically-based statistical forecast model for the middle-lower reaches of the Yangtze River Valley summer rainfall. Chin. Sci. Bull., 53, 602609, doi:10.1007/s11434-008-0083-1.

    • Search Google Scholar
    • Export Citation
  • Fan, K., Liu Y. , and Chen H. , 2012: Improving the prediction of the East Asian summer monsoon: New approaches. Wea. Forecasting, 27, 10171030, doi:10.1175/WAF-D-11-00092.1.

    • Search Google Scholar
    • Export Citation
  • Feddersen, H., 2003: Impact of tropical SST variations on the linear predictability of the atmospheric circulation in the Atlantic/European region. Ann. Geophys., 46, 109124, doi:10.4401/ag-3381.

    • Search Google Scholar
    • Export Citation
  • Gong, G., Entekhabi D. , and Cohen J. , 2003: Modeled Northern Hemisphere winter climate response to realistic Siberian snow anomalies. J. Climate, 16, 39173931, doi:10.1175/1520-0442(2003)016<3917:MNHWCR>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Hurrell, J. W, 1995: Decadal trends in the North Atlantic Oscillation: Regional temperatures and precipitation. Science,269, 676–679, doi:10.1126/science.269.5224.676.

  • Kim, Y., Kim K. Y. , and Kim B. M. , 2013: Physical mechanisms of European winter snow cover variability and its relationship to the NAO. Climate Dyn., 40, 16571669, doi:10.1007/s00382-012-1365-5.

    • Search Google Scholar
    • Export Citation
  • Marshall, J., and Coauthors, 2001: North Atlantic climate variability: Phenomena, impacts and mechanisms. Int. J. Climatol., 21, 18631898, doi:10.1002/joc.693.

    • Search Google Scholar
    • Export Citation
  • Michaelsen, J., 1987: Cross-validation in statistical climate forecast models. J. Climate Appl. Meteor., 26, 15891600, doi:10.1175/1520-0450(1987)026<1589:CVISCF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Müller, W. A., Appenzeller C. , and Schär C. , 2005: Probabilistic seasonal prediction of the winter North Atlantic Oscillation and its impact on near surface temperature. Climate Dyn., 24, 213226, doi:10.1007/s00382-004-0492-z.

    • Search Google Scholar
    • Export Citation
  • Peings, Y., Brun E. , Mauvais V. , and Douville H. , 2013: How stationary is the relationship between Siberian snow and Arctic Oscillation over the 20th century? Geophys. Res. Lett.,40, 183–188, doi:10.1029/2012gl054083.

  • Rodwell, M. J., and Folland C. K. , 2002: Atlantic air–sea interaction and seasonal predictability. Quart. J. Roy. Meteor. Soc., 128, 14131443, doi:10.1002/qj.200212858302.

    • Search Google Scholar
    • Export Citation
  • Rodwell, M. J., Rowell D. , and Folland C. , 1999: Oceanic forcing of the wintertime North Atlantic Oscillation and European climate. Nature, 398, 320323, doi:10.1038/18648.

    • Search Google Scholar
    • Export Citation
  • Saito, K., and Cohen J. , 2003: The potential role of snow cover in forcing interannual variability of the major Northern Hemisphere mode. Geophys. Res. Lett., 30, 1302, doi:10.1029/2002GL016341.

    • Search Google Scholar
    • Export Citation
  • Saito, K., Cohen J. , and Entekhabi D. , 2001: Evolution of atmospheric response to early-season Eurasian snow cover anomalies. Mon. Wea. Rev., 129, 27462760, doi:10.1175/1520-0493(2001)129<2746:EOARTE>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Saunders, M. A., and Qian B. D. , 2002: Seasonal predictability of the winter NAO from North Atlantic sea surface temperatures. Geophys. Res. Lett., 29, 2043, doi:10.1029/2002GL014952.

    • Search Google Scholar
    • Export Citation
  • Scaife, A. A., and Coauthors, 2014: Skillful long-range prediction of European and North American winters. Geophys. Res. Lett.,41, doi:10.1002/2014GL059637.

  • Smith, T. M., Reynolds R. W. , Peterson T. C. , and Lawrimore J. , 2008: Improvements to NOAA’s historical merged land–ocean surface temperature analysis (1880–2006). J. Climate, 21, 22832296, doi:10.1175/2007JCLI2100.1.

    • Search Google Scholar
    • Export Citation
  • Stephenson, D. B., Pavan V. , and Bojariu R. , 2000: Is the North Atlantic Oscillation a random walk? Int. J. Climatol., 20, 118, doi:10.1002/(SICI)1097-0088(200001)20:1<1::AID-JOC456>3.0.CO;2-P.

    • Search Google Scholar
    • Export Citation
  • Sun, J., and Wang H. , 2012: Changes of the connection between the summer North Atlantic Oscillation and the East Asian summer rainfall. J. Geophys. Res., 117, D08110, doi:10.1029/2012JD017482.

    • Search Google Scholar
    • Export Citation
  • Sun, J., Wang H. , and Yuan W. , 2008: Decadal variations of the relationship between the summer North Atlantic Oscillation and middle East Asian air temperature. J. Geophys. Res., 113, D15107, doi:10.1029/2007JD009626.

    • Search Google Scholar
    • Export Citation
  • Tian, B., and Fan K. , 2012: Relationship between the late spring NAO and summer extreme precipitation frequency in the middle and lower reaches of the Yangtze River. Atmos. Oceanic Sci. Lett., 5, 455460.

    • Search Google Scholar
    • Export Citation
  • Wang, H. J., and Chen H. P. , 2012: Climate control for southeastern China moisture and precipitation: Indian or East Asian monsoon? J. Geophys. Res., 117, D12109, doi:10.1029/2012JD017734.

    • Search Google Scholar
    • Export Citation
  • Wang, H. J., Zhang Y. , and Lang X. M. , 2010: On the predictand of short-term climate prediction (in Chinese). Climate Environ. Res, 15, 225228.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 731 346 10
PDF Downloads 301 74 5