The Prediction of Non-stationary Climate Series Based on Empirical Mode Decomposition

• Published in: Advances in atmospheric sciences Vol. 27; no. 4; pp. 845 - 854
• Main Author: 杨培才 王革丽 卞建春 周秀骥
• Format: Journal Article
• Language: English
• Published: Heidelberg SP Science Press 01.07.2010; Springer Nature B.V
• Subjects: Accuracy; Atmospheric Sciences; Decomposition; Earth and Environmental Science; Earth Sciences; Geophysics/Geodesy; Meteorology; Nonlinear systems; Research methodology; Time series; Weather forecasting; 序列预测; 模式分解法; 气候预测; 经验模式分解; 隔离元件; 非平稳性; 非平稳时间序列; 非线性相互作用; climate prediction; time series prediction; nonlinear system; nonstationarity; EMD
• ISSN: 0256-1530; 1861-9533
• DOI: 10.1007/s00376-009-9128-x

This paper proposes a new approach which we refer to as ＂segregated prediction＂ to predict climate time series which are nonstationary. This approach is based on the empirical mode decomposition method （EMD）, which can decompose a time signal into a finite and usually small number of basic oscillatory components. To test the capabilities of this approach, some prediction experiments are carried out for several climate time series. The experimental results show that this approach can decompose the nonstationarity of the climate time series and segregate nonlinear interactions between the different mode components, which thereby is able to improve prediction accuracy of these original climate time series.