2014年
Month-to-Month Predictability Variations of the Winter-Time Stratospheric Polar Vortex in an Operational One-month Ensemble Prediction System
JOURNAL OF THE METEOROLOGICAL SOCIETY OF JAPAN
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- 巻
- 92
- 号
- 6
- 開始ページ
- 543
- 終了ページ
- 558
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.2151/jmsj.2014-603
- 出版者・発行元
- METEOROLOGICAL SOC JAPAN
Month-to-month variation in the predictability of the stratospheric polar vortex in the Northern Hemisphere winter is examined on the basis of the systematic error and the ensemble spread of the North Pole temperature using a seven-year archive of the operational ensemble one-month forecast dataset provided by the Japan Meteorological Agency.The systematic error defined by the ensemble mean error averaged over forecasts starting from each calendar month shows the following intraseasonal variability. In early winter, it has significantly large positive values of the North Pole temperature in the stratosphere, whereas in late winter, there is a significant negative bias in the upper stratosphere. The Eliassen-Palm (E-P) flux diagnosis reveals that the significant underestimation of the equatorward propagation of planetary waves in the stratosphere is related to the positive bias in early winter. On the other hand, the negative bias in late winter is not attributable to any systematic error of E-P flux. Hence, it is suggested that inadequate parameterization schemes for physical processes are responsible for the negative bias.An upper bound of the predictable period of the North Pole temperature is also assessed on the basis of monthly averaged ensemble spread using the logistic equation that describes the time evolution of small initial errors proposed by Lorenz. The estimated predictable period in the stratosphere attains a maximum value of 35 days in early winter, and gradually decreases with the seasonal march to 20 days in late winter, which is considerably longer than that in the troposphere (14 days).
- リンク情報
- ID情報
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- DOI : 10.2151/jmsj.2014-603
- ISSN : 0026-1165
- eISSN : 2186-9057
- Web of Science ID : WOS:000348588700004