Skilful predictions of the winter North Atlantic Oscillation one year ahead


The winter North Atlantic Oscillation is the primary mode of atmospheric variability in the North Atlantic region and has a profound influence on European and North American winter climate. Until recently, seasonal variability of the North Atlantic Oscillation was thought to be largely driven by chaotic and inherently unpredictable processes1,2. However, latest generation seasonal forecasting systems have demonstrated significant skill in predicting the North Atlantic Oscillation when initialized a month before the onset of winter3,4,5. Here we extend skilful dynamical model predictions to more than a year ahead. The skill increases greatly with ensemble size due to a spuriously small signal-to-noise ratio in the model, and consequently larger ensembles are projected to further increase the skill in predicting the North Atlantic Oscillation. We identify two sources of skill for second-winter forecasts of the North Atlantic Oscillation: climate variability in the tropical Pacific region and predictable effects of solar forcing on the stratospheric polar vortex strength. We also identify model biases in Arctic sea ice that, if reduced, may further increase skill. Our results open possibilities for a range of new climate services, including for the transport6,7, energy, water management8 and insurance sectors.

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Figure 1: First- and second-winter NAO skill.
Figure 2: The signal-to-noise paradox.
Figure 3: Potential sources of winter NAO skill.
Figure 4: Multiple linear regression analysis.


  1. 1

    Johansson, A. Prediction skill of the NAO and PNA from daily to seasonal time scales. J. Clim. 20, 1957–1975 (2007).

    Article  Google Scholar 

  2. 2

    Kim, H.-M., Webster, P. & Curry, J. Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere winter. Clim. Dynam. 23, 2957–2973 (2012).

    Article  Google Scholar 

  3. 3

    Scaife, A. A. et al. Skillful long-range prediction of European and North American winters. Geophys. Res. Lett. 41, 2514–2519 (2014).

    Article  Google Scholar 

  4. 4

    Riddle, E. E., Butler, A. H., Furtado, J. C., Cohen, J. L. & Kumar, K. CFSv2 ensemble prediction of the wintertime Arctic Oscillation. Clim. Dynam. 41, 1099–1116 (2013).

    Article  Google Scholar 

  5. 5

    Stockdale, T. N., Molenti, F. & Ferranti, L. Atmospheric initial conditions and the predictability of the Arctic Oscillation. Geophys. Res. Lett. 42, 1173–1179 (2015).

    Article  Google Scholar 

  6. 6

    Palin, E. et al. Skilful seasonal forecasts of winter disruption to the UK transport system. J. Appl. Meteorol. Clim. 55, 325–344 (2016).

    Article  Google Scholar 

  7. 7

    Karpechko, A. Y., Peterson, K. A., Scaife, A. A., Vainio, J. & Gregow, H. Skilful seasonal predictions of Baltic Sea ice cover. Environ. Res. Lett. 10, 044007 (2015).

    Article  Google Scholar 

  8. 8

    Svensson, C. et al. Long-range forecasts of UK winter hydrology. Environ. Res. Lett. 10, 064006 (2015).

    Article  Google Scholar 

  9. 9

    Athanasiadis, P. J. et al. The representation of atmospheric blocking and the associated low-frequency variability in two seasonal prediction systems. J. Clim. 27, 9082–9100 (2014).

    Article  Google Scholar 

  10. 10

    Sun, J. & Ahn, J.-B. Dynamical seasonal predictability of the Arctic Oscillation using a CGCM. Int. J. Climatol. 35, 1342–1353 (2015).

    Article  Google Scholar 

  11. 11

    Kang, D. et al. Prediction of the Arctic Oscillation in boreal winter by dynamical seasonal forecasting systems. Geophys. Res. Lett. 41, 3577–3585 (2014).

    Article  Google Scholar 

  12. 12

    Eade, R. et al. Do seasonal-to-decadal climate predictions underestimate the predictability of the real world? Geophys. Res. Lett. 41, 5620–5628 (2014).

    Article  Google Scholar 

  13. 13

    Siegert, S. et al. A Bayesian framework for verification and recalibration of ensemble forecasts: how uncertain is NAO predictability? J. Clim. 29, 995–1012 (2016).

    Article  Google Scholar 

  14. 14

    MacLachlan, C. et al. Global seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Q. J. R. Meteorol. Soc. 141, 1072–1084 (2015).

    Article  Google Scholar 

  15. 15

    Murphy, J. M. Assessment of the practical utility of extended range ensemble forecasts. Q. J. R. Meteorol. Soc. 116, 89–125 (1990).

    Article  Google Scholar 

  16. 16

    Shi, W., Schaller, N., MacLeod, D., Palmer, T. N. & Weisheimer, A. Impact of hindcast length on estimates of seasonal climate predictability. Geophys. Res. Lett. 42, L1554 (2015).

    Article  Google Scholar 

  17. 17

    Brönnimann, S., Xoplaki, E., Casty, C., Pauling, A. & Luterbacher, J. ENSO influence on Europe during the last centuries. Clim. Dynam. 28, 181–197 (2007).

    Article  Google Scholar 

  18. 18

    Bell, C. J., Gray, L. J., Charlton-Perez, A. J., Joshi, M. & Scaife, A. A. Stratospheric communication of El Niño teleconnections to European winter. J. Clim. 22, 4083–4096 (2009).

    Article  Google Scholar 

  19. 19

    Ineson, S. & Scaife, A. A. The role of the stratosphere in the European climate response to El Niño. Nat. Geosci. 2, 32–36 (2009).

    Article  Google Scholar 

  20. 20

    Rodwell, M. J., Rowell, D. P. & Folland, C. K. Oceanic forcing of the wintertime North Atlantic Oscillation and European climate. Nature 398, 320–323 (1999).

    Article  Google Scholar 

  21. 21

    Yang, S. & Christensen, J. H. Arctic sea ice reduction and European cold winters in CMIP5 climate change experiments. Geophys. Res. Lett. 39, L20707 (2012).

    Google Scholar 

  22. 22

    Kidston, J. et al. Stratospheric influence on tropospheric jet streams, storm tracks and surface weather. Nat. Geosci. 8, 433–330 (2015).

    Article  Google Scholar 

  23. 23

    Luo, J.-J., Masson, S., Behera, S. K. & Yamagata, T. Extended ENSO predictions using a fully coupled ocean–atmosphere model. J. Clim. 21, 84–93 (2008).

    Article  Google Scholar 

  24. 24

    Kodera, K. & Kuroda, Y. Dynamical response to the solar cycle. J. Geophys. Res. 107, 4749 (2002).

    Article  Google Scholar 

  25. 25

    Ineson, S. et al. Solar forcing of winter climate variability in the Northern Hemisphere. Nat. Geosci. 4, 753–757 (2011).

    Article  Google Scholar 

  26. 26

    Williams, K. et al. The Met office global coupled model 2.0 (GC2) configuration. Geosci. Model Dev. 88, 1509–1524 (2015).

    Article  Google Scholar 

  27. 27

    Knight, J. F. et al. Predictions of climate several years ahead using an improved decadal prediction system. J. Clim. 27, 7550–7567 (2014).

    Article  Google Scholar 

  28. 28

    Smith, D. M. & Murphy, J. M. An objective ocean temperature and salinity analysis using covariances from a global climate model. J. Geophys. Res. 112, C02022 (2007).

    Article  Google Scholar 

  29. 29

    Rayner, N. A. et al. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407 (2003).

    Article  Google Scholar 

  30. 30

    Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–507 (2011).

    Article  Google Scholar 

  31. 31

    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

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This work was supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101), the EU FP7 SPECS project and the UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund.

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N.D. led the analysis. N.D., D.S. and A.S. wrote the paper with comments from all other authors.

Corresponding author

Correspondence to Nick Dunstone.

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The authors declare no competing financial interests.

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Dunstone, N., Smith, D., Scaife, A. et al. Skilful predictions of the winter North Atlantic Oscillation one year ahead. Nature Geosci 9, 809–814 (2016).

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