| 基于奇异谱分析的南方涛动指数短期气候预测试验 |
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| 作者姓名： | Liu Jianwen Dong Peiming |
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| 作者单位： | Liu Jianwen and Dong Peiming Beijing Aviation Institute of Meteorology,Beijing 100085 |
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| 基金项目： | This work was supported by the" National Key Project Studies on Short-Range Climate Prediction
System in China" (96-908-04-02). |
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| 摘 要： | The Southern Oscillation Index (SOI) time series is analyzed by means of the singular spectrum analysis (SSA) method with 60-month window length. Two major oscillatory pairs are found in the series whose pe riods are quasi-four and quasi-two years respectively. The auto-regressive model, which is developed on the basis of the Maximum Entropy Spectrum Analy sis, is fitted to each of the 9 leading components including the oscillatory pairs. The prediction of SOI with the 36-month lead is obtained from the reconstruction of these extrapolated series. Correlation coefficient between predicted series and 5 months running mean of observed series is up to 0.8. The model can successfully predict the peak and duration of the strong ENSO event from 1997 to 1998. It＇s also shown that the proper choice of reconstructed components is the key to improve the model prediction.
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| 关 键 词： | 南方涛动指数 奇异谱分析 振荡分量 重构 |
Short-range Climate Prediction Experiment of the Southern Oscillation Index Based on the Singular Spectrum Analysis |
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| Liu Jianwen,Dong Peiming.Short-range Climate Prediction Experiment of the Southern Oscillation Index Based on the Singular Spectrum Analysis[J].Advances in Atmospheric Sciences,2001,18(5):873-881. |
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| Authors: | Liu Jianwen and Dong Peiming |
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| Institution: | Beijing Aviation Institute of Meteorology, Beijing 100085,Beijing Aviation Institute of Meteorology, Beijing 100085 |
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| Abstract: | The Southern Oscillation Index (SOI) time series is analyzed by means of the singular spectrum analysis (SSA) method with 60-month window length. Two major oscillatory pairs are found in the series whose pe- riods are quasi-four and quasi-two years respectively. The auto-regressive model, which is developed on the basis of the Maximum Entropy Spectrum Analy- sis. is fitted to each of the 9 leading components including the oscillatory pairs. The prediction of SOI with the 36-month lead is obtained from the reconstruction of these extrapolated series. Correlation coeffcient between predicted series and 5 months running mean of observed series is up to 0.8. The model can successfully predict the peak and duration of the strong ENSO event from 1997 to 1998. It's also shown that the proper choice of reconstructed components is the key to improve the model prediction. |
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| Keywords: | Southern Oscillation Index Singular Spectrum Analysis Principal component Reconstruction |
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