ENSO非线性预报

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。

Nonlinear Prediction of ENSO

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.