A Multi-System View of Wintertime NAO Seasonal Predictions.

Wednesday, 16 December 2015
Poster Hall (Moscone South)
Panagiotis Athanasiadis1, Silvio Gualdi1, Adam A Scaife2, Alessio Bellucci1, Leon Hermanson2 and Enrico Scoccimarro3, (1)CMCC - Bologna, Bologna, Italy, (2)Met Office Hadley center for Climate Change, Exeter, United Kingdom, (3)National Institute of Geophysics and Volcanology, BOLOGNA, Italy
In the mid-latitudes the seasonal predictability has been known to be low to moderate. However, significant predictive skill for the mean winter North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) has been recently reported for a number of different seasonal forecasting systems [e.g., Riddle et al. (2013), Scaife et al. (2014), Stockdale et al. (2015)]. Here we present results from a multi-system analysis, including CFSv2 (24 members), UKMO (24 members) and CMCC (9 members) seasonal prediction systems. For their common hindcast period (19972011) the skill for the NAO/AO reaches as high as +0.85 for the multi-system ensemble mean. Certainly, part of the skill increase in respect to the individual systems is related to the larger size of the multi-system ensemble, though blending different systems together may bring additional improvements since each system benefits differently from the various sources of natural seasonal predictability. Therefore, initiatives similar to the North American Multi-Model Ensemble can bring added value to seasonal predictions even if individual systems sooner or later exploit all their potential skill by increasing their ensemble size. Furthermore, it is demonstrated that the NAO skill actually translates to better predictions of near-surface air temperature and precipitation anomalies in the domain influenced by the NAO (lower root-mean square errors and higher spatial correlation in respect to the corresponding observed anomalies).