Nonlinear Prediction of ENSO

Abstract

Abstract: Nonlinear time-sequence analysis is used to study the time evolution of El Nino-Southern Oscillation (ENSO) by combining the method of global function approximation with lyapunov exponent analysis. The method includes phase-space reconstruction, lyapunov exponent analysis, global function approximation, principal components analysis and least-square estimation. The data used here is monthly sea surface temperature anomalies (SSTA) from CZ (Cane & Zebiak) model. It differs from traditional time-sequence analysis methods in which nonlinear chaotic time-sequence prediction is used. The present method is proved to be a successful one with lesser data, and it provides an alternative method for ENSO prediction.

Key words: phase-space reconstruction, lyapunov exponents, global function approximation monthly, sea surface temperature anomaly (SSTA), El Nino-Southern Oscillation (ENSO), prediction

摘要： 运用非线性时间序列分析方法，结合全局函数拟合和lyapunov指数分析对厄尔尼诺-南方涛动（ENSO）的时间演变进行研究。方法包括：相空间重构，lyapunov指数分析，全局函数拟合，主分量分析，最小二乘拟合。资料为CZ (Cane & Zebiak)模式产生的月平均海表温度异常（SSTA）场。采用非线性混沌时间序列预报，不同于传统的时间序列分析方法。相比其他模式，它能用较少的资料得到较好的预报结果，为今后的ENSO预报提供了一个可供参考的方法。

关键词: 相空间重构, lyapunov指数, 全局函数拟合, 月平均海表温度异常, 厄尔尼诺-南方涛动, 预报

CLC Number:

P456

LI Kunyu,LI Xiaodong. Nonlinear Prediction of ENSO[J]. Acta Scientiarum Naturalium Universitatis Pekinensis.

李坤玉, 李晓东. ENSO非线性预报[J]. 北京大学学报（自然科学版）.

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URL: https://xbna.pku.edu.cn/EN/

https://xbna.pku.edu.cn/EN/Y2007/V43/I1/30

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Nonlinear Prediction of ENSO

ENSO非线性预报

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