Seasonal prediction skill for surface winter climate in the Euro-Atlantic sector has been limited so far. In particular, the predictability of the winter North Atlantic Oscillation, the mode that largely dominates regional atmospheric and climate variability, remains a hurdle for present dynamical prediction systems. Statistical forecasts have also been largely elusive, but October Eurasian snow cover has been shown to be a robust source of regional predictability. Here we use maximum covariance analysis to show that Arctic sea-ice variability represents another good predictor of the winter Euro-Atlantic climate at lead times of as much as three months. Cross-validated hindcasts of the winter North Atlantic Oscillation index using September sea-ice anomalies yield a correlation skill of 0.59 for the period 1979/1980-2012/2013, suggesting that 35% of its variance could be predicted three months in advance. This skill can be further enhanced, at the expense of a shorter lead time, by using October Eurasian snow cover as an additional predictor. Skilful predictions of winter European surface air temperature and precipitation are also obtained with September sea ice as the only predictor. We conclude that it is important to incorporate Arctic sea-ice variability in seasonal prediction systems. © 2014 Macmillan Publishers Limited.
CITATION STYLE
García-Serrano, J., & Frankignoul, C. (2014). High predictability of the winter Euro-Atlantic climate from cryospheric variability. Nature Geoscience, 7(6), 1–5. https://doi.org/10.1038/ngeo2118
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