大气科学2017，Vol.41Issue(3)：501-514,14.DOI:10.3878/j.issn.1006-9895.1608.16135
基于幅频分离的气候时间序列预测试验
A Predicting Test on Climatic Time Series Based on Amplitude-Frequency Separation
摘要
Abstract
From the perspective of the instantaneous frequency and amplitude of climatic wave series and by virtue of the technique of least square support vector machine (LS-SVM),a new prediction method of climatic series is proposed based on the separation of amplitude and frequency.A 30-pentad prediction test on Nanjing precipitation is conducted using this method.The results show that,the new prediction method based on the amplitude-frequency separation presents good prediction accuracies on both the amplitudes of all modes and the frequencies of higher frequency modes.The accumulated errors of predicted instantaneous frequencies have highly sensitive impacts on the anomaly correlations of modes.This method can distinctly improve the prediction of higher frequency modes.For the lower frequency modes,the boundary effect of ensemble empirical mode decomposition (EEMD) causes remarkable errors on the calculation of instantaneous frequency,which subsequently leads to inaccurate argument and eventually results in unsatisfactory prediction on modes of lower frequencies.Thereby,implementing both amplitude-frequency separation and LS-SVM for the prediction of higher frequency modes of climatic series while merely using LS-SVM for the prediction of lower frequency modes can give perfect predictions on components of both higher and lower frequencies,and ultimately improve the prediction of the whole climatic series.The test implementing this frequency-based prediction method on prediction of precipitation in Nanjing shows that the anomaly correlation remains greater than 0.4 in its 30-pentad prediction.关键词
幅频分离/高频分量/瞬时频率/最小二乘支持向量机/经验模态分解Key words
Amplitude-frequency separation/High frequency/Instantaneous frequency/Least-square support vector machine/Ensemble empirical mode decomposition分类
天文与地球科学引用本文复制引用
张舰齐,王丽琼,左瑞亭,叶晶,马秋丽,叶成志..基于幅频分离的气候时间序列预测试验[J].大气科学,2017,41(3):501-514,14.基金项目
国家自然科学基金资助项目41475071,国家青年科学基金资助项目41305018,财政部/科技部公益类行业专项GYHY201306016 （）
National Natural Science Foundation of China (Grant 41475071),National Youth Science Funds (Grant 41305018),Ministry of Finance/ Ministry of Science and Technology of the Public Sector Special (Grant GYHY201306016) （Grant 41475071）
