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Ensemble prediction of transitions of the North Atlantic eddy-driven jet

Frame, T. H. A., Ambaum, M. H. P., Gray, S. L. J. and Methven, J. (2011) Ensemble prediction of transitions of the North Atlantic eddy-driven jet. Quarterly Journal of the Royal Meteorological Society, 137 (658). pp. 1288-1297. ISSN 1477-870X

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To link to this article DOI: 10.1002/qj.829

Abstract/Summary

The consistency of ensemble forecasts from three global medium-range prediction systems with the observed transition behaviour of a three-cluster model of the North Atlantic eddy-driven jet is examined. The three clusters consist of a mid jet cluster taken to represent an undisturbed jet and south and north jet clusters representing southward and northward shifts of the jet. The ensemble forecasts span a period of three extended winters (October–February) from October 2007–February 2010. The mean probabilities of transitions between the clusters calculated from the ensemble forecasts are compared with those calculated from a 23-extended-winter climatology taken from the European Centre for Medium-Range Weather Forecasts 40-Year Re-analysis (ERA40) dataset. No evidence of a drift with increasing lead time of the ensemble forecast transition probabilities towards values inconsistent with the 23-extended-winter climatology is found. The ensemble forecasts of transition probabilities are found to have positive Brier Skill at 15 day lead times. It is found that for the three-extended-winter forecast set, probabilistic forecasts initialized in the north jet cluster are generally less skilful than those initialized in the other clusters. This is consistent with the shorter persistence time-scale of the north jet cluster observed in the ERA40 23-extended-winter climatology. Copyright © 2011 Royal Meteorological Society

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical and Physical Sciences > Department of Meteorology
Faculty of Science > School of Mathematical and Physical Sciences > NCAS
ID Code:22350
Uncontrolled Keywords:TIGGE;weather regimes;clustering
Publisher:Royal Meteorological Society

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