Can knowledge of the state of the stratosphere be used to improve statistical forecasts of the troposphere?

• Published in: Quarterly journal of the Royal Meteorological Society Vol. 129; no. 595; pp. 3205 - 3224
• Main Authors: Charlton, A. J., O'Neill, A., Stephenson, D. B., Lahoz, W. A., Baldwin, M. P.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.10.2003; Wiley
• Subjects: Arctic Oscillation; Earth, ocean, space; Exact sciences and technology; External geophysics; Meteorology; Multiple regression; meteorology; Predictor; Time series; Arctic oscillation; Arctic Oscillation Multiple regression; ocean-atmosphere interaction; troposphere; Variance; Winter; Predictability; Statistical model; statistical analysis; stratosphere
• ISSN: 0035-9009; 1477-870X
• DOI: 10.1256/qj.02.232

Recent analysis of the Arctic Oscillation (AO) in the stratosphere and troposphere has suggested that predictability of the state of the tropospheric AO may be obtained from the state of the stratospheric AO. However, much of this research has been of a purely qualitative nature. We present a more thorough statistical analysis of a long AO amplitude dataset which seeks to establish the magnitude of such a link. A relationship between the AO in the lower stratosphere and on the 1000 hPa surface on a 10–45 day time‐scale is revealed. The relationship accounts for ∼5% of the variance of the 1000 hPa time series at its peak value and is significant at the 5% level. Over a similar time‐scale the 1000 hPa time series accounts for ≤1% of itself and is not significant at the 5% level. Further investigation of the relationship reveals that it is only present during the winter season and in particular during February and March. It is also demonstrated that using stratospheric AO amplitude data as a predictor in a simple statistical model results in a gain of skill of ∼5% over a troposphere‐only statistical model. This gain in skill is not repeated if an unrelated time series is included as a predictor in the model. Copyright © 2003 Royal Meteorological Society