基于EEMD-CES的单站地面气温资料质量控制方法研究

为了去除或减少我国地面气温观测资料中含有的噪声成分,提高观测资料质量,提出了一种新的单站质量控制算法。该算法融合了集合经验模态分解法(Ensemble Empirical Mode Decomposition,EEMD)和三次指数平滑法(Cubic Exponential Smooth,CES)。利用EEMD方法将气温观测资料分解为一系列相对平稳的本征模分量,并基于能量密度和相关性准则从中分析筛选出目标分量,以完成资料重构;利用CES方法对重构资料建立单站质量控制模型,形成了一种基于EEMD-CES的地面观测资料质量控制算法。为检验该方法的可行性与适用性,选取2008年全国9个观测站地面逐时气温观测资料进行质量控制,并对比传统的单站质量控制法、经验模态分解法和三次指数平滑法的质量控制效果。试验结果表明,基于EEMD-CES的质量控制方法能有效地标记出数据的可疑值,相比传统方法,具有更高的检错率和更强的适应性。

A quality control method of surface temperature observations based on the EEMD-CES algorithm for a single station

In this paper,in order to reduce or remove the noise components included in observations of surface temperature in China as much as possible and improve the quality of observations,a new single station quality control algorithm is proposed.The algorithm combines Ensemble Empirical Mode Decomposition (EEMD) and Cubic Exponential Smooth (CES).First,the EEMD method is used to decompose the temperature observations into a series of relatively stable intrinsic mode functions.Next,based on the energy density and the correlation criterion,the target component is analyzed and screened out to complete the data reconstruction.Finally,the CES method is used to establish a single station quality control model with the reconstructed data,and form an EEMD-CES quality control model.In order to test the feasibility and applicability of this method,this paper selects the surface hourly temperature observations from nine stations throughout the country for quality control in 2008.The results are then compared with the quality control effects of the traditional single station quality control method,empirical mode decomposition method,and cubic exponential smoothing method.The experimental results show that the quality control method based on EEMD-CES can effectively mark the suspicious value of data,and has a higher error detection rate and stronger adaptability than the traditional method.