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A robust empirical seasonal prediction of winter NAO and surface climate
Wang, L.; Ting, M.; Kushner, P.J. (2017). A robust empirical seasonal prediction of winter NAO and surface climate. NPG Scientific Reports 7(279): 9 pp. https://hdl.handle.net/10.1038/s41598-017-00353-y
In: Scientific Reports (Nature Publishing Group). Nature Publishing Group: London. ISSN 2045-2322, more
Peer reviewed article  

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Authors  Top 
  • Wang, L.
  • Ting, M.
  • Kushner, P.J.

Abstract
    A key determinant of winter weather and climate in Europe and North America is the North Atlantic Oscillation (NAO), the dominant mode of atmospheric variability in the Atlantic domain. Skilful seasonal forecasting of the surface climate in both Europe and North America is reflected largely in how accurately models can predict the NAO. Most dynamical models, however, have limited skill in seasonal forecasts of the winter NAO. A new empirical model is proposed for the seasonal forecast of the winter NAO that exhibits higher skill than current dynamical models. The empirical model provides robust and skilful prediction of the December-January-February (DJF) mean NAO index using a multiple linear regression (MLR) technique with autumn conditions of sea-ice concentration, stratospheric circulation, and sea-surface temperature. The predictability is, for the most part, derived from the relatively long persistence of sea ice in the autumn. The lower stratospheric circulation and sea-surface temperature appear to play more indirect roles through a series of feedbacks among systems driving NAO evolution. This MLR model also provides skilful seasonal outlooks of winter surface temperature and precipitation over many regions of Eurasia and eastern North America.

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