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| 基于EMD 和集合预报技术的气候预测方法 | |
| 引用本文： | 毕硕本,陈譞,覃志年,徐寅,王必强.基于EMD 和集合预报技术的气候预测方法[J].热带气象学报,2012(2):283-288. |
| 作者姓名： | 毕硕本 陈譞 覃志年 徐寅 王必强 |
| 作者单位： | 1. 南京信息工程大学遥感学院,江苏 南京 210044 2. 广西壮族自治区气候中心,广西 南宁 530022 3. 南京信息工程大学信息与控制学院,江苏 南京 210044 |
| 基金项目： | 中国气象局新技术推广项目(CMATG2009MS19(2));国家自然科学基金项目(41071253)共同资助 |
| 摘 要： | 气候系统是典型的非平稳性系统,然而对于气候观测数据的处理通常是在时间序列平稳的假定下完成的,比如气温和降水的多步预报,这通常会导致预报准确度较低。为改进该缺陷,首先将非平稳数据序列分解成平稳的、多尺度特征的本征模态函数分量(IMF),再使用数值集合预报与逐步回归分析相结合的方式对每一个IMF分量构建不同的预报模型,最后线性拟合成预报结果。通过Visual Studio 2008开发平台使用上述方法建立了一个短期气候预报系统,采用广西区88个气象站1957—2005年的2月距平气温数据进行实际验证。结果表明,相对于普通预测和单一预测方法,加入了EMD和集合预报技术的方法在仅用历史资料进行多步预测的情况下,对于气候的变化趋势以及突发性气候具有更好的预报能力。 |
| 关 键 词： | 短期气候预测 经验模态分解(EMD) 集合预报 均生函数逐步回归模型 时间序列 |
| 收稿时间： | 2010/6/16 0:00:00 |
| 修稿时间： | 2011/3/10 0:00:00 |
STUDY OF CLIMATE PREDICTION METHOD BASED ON EMD AND ENSEMBLE PREDICTION TECHNIQUE |
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| BI Shuo-ben,CHEN Xuan,QIN Zhi-nian,XU Yin and WANG Bi-qiang.STUDY OF CLIMATE PREDICTION METHOD BASED ON EMD AND ENSEMBLE PREDICTION TECHNIQUE[J].Journal of Tropical Meteorology,2012(2):283-288. | |
| Authors: | BI Shuo-ben CHEN Xuan QIN Zhi-nian XU Yin and WANG Bi-qiang |
| Institution: | School of Remote Sensing, NUIST, Nanjing 210044, China;School of Remote Sensing, NUIST, Nanjing 210044, China;Guangxi Zhuang Autonomous Region Climate Center, Nanning 530022, China;School of Information and Control Technologies, NUIST, Nanjing 210044, China;School of Remote Sensing, NUIST, Nanjing 210044, China |
| Abstract: | Climate systems are generally non-stationary.The data processing of climate observations,e.g.multi-step prediction of temperature and precipitation,is usually performed under an assumption that the time series is stationary.This may lead to unsatisfied accuracy in the prediction.In this paper,we study on a new method integrating an ensemble prediction technique and a stepwise regression model based on Mean-Valued Generated Function.By using the Empirical Mode Decomposition(EMD),we decomposed a non-stationary time series into a series of Intrinsic Mode Function(IMF) components and a trend component which is preliminary stable.Then a prediction model was built for each IMF component using an ensemble prediction technique and a stepwise regression analysis.The final results can be obtained by linear fitting.Using this method and the Visual Studio 2008,we developed a short-term climate prediction system which is calibrated by the temperature anomaly from 88 meteorological observation stations in Guangxi Zhuang Autonomous Region during the Februarys of 1957—2005.Compared to the normal and single prediction,the new method involving the EMD and the ensemble prediction technique has better performance in the prediction of climate change trend and abrupt climate changes when the multi-step prediction is made using historical data. |
| Keywords: | short term climate prediction Empirical Mode Decomposition(EMD) ensemble prediction technique stepwise regression model based on mean-valued generated function time series |
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