Nonstationary Time Series Prediction by Incorporating External Forces

Almost all climate time series have some degree of nonstationarity due to external forces of the observed system. Therefore, these external forces should be taken into account when reconstructing the climate dy- namics. This paper presents a novel technique in predicting nonstationary time series. T...

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Bibliographic Details
Published in:Advances in atmospheric sciences 2013-11, Vol.30 (6), p.1601-1607
Main Author: 王革丽 杨培才 周秀骥
Format: Article
Language:English
Subjects:
Atmospheric models
Atmospheric Sciences
Atmospherics
Climate
Climate models
Dynamical systems
Dynamics
Earth and Environmental Science
Earth Sciences
Geophysics/Geodesy
Mathematical models
Meteorology
Prediction models
Skills
Time series
技术
整合
时间序列预测
模型生成
气候模式
非平稳时间序列
预测能力
驱动力
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Summary:Almost all climate time series have some degree of nonstationarity due to external forces of the observed system. Therefore, these external forces should be taken into account when reconstructing the climate dy- namics. This paper presents a novel technique in predicting nonstationary time series. The main difference of this new technique from some previous methods is that it incorporates the driving forces in the pre- diction model. To appraise its effectiveness, three prediction experiments were carried out using the data generated from some known classical dynamical models and a climate model with multiple external forces. Experimental results indicate that this technique is able to improve the prediction skill effectively.
ISSN:0256-1530
1861-9533
DOI:10.1007/s00376-013-2134-z