| 日长年际信号提取及其与大气相关性分析 |
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| 引用本文： | 张欣峰,刘根友.日长年际信号提取及其与大气相关性分析[J].大地测量与地球动力学,2020,40(11):1188-1193. |
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| 作者姓名： | 张欣峰 刘根友 |
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| 摘 要： | 为对日长年际变化进行更细致分析，利用标准Morlet小波变换方法，从日长变化序列中识别和提取出6个主要的年际信号，周期分别为2.3 a（2.4 a）、3.3 a、3.7 a、4.8 a、6.1 a和8.1 a，并基于信号的时域提取结果，计算获得相应信号的平均振幅，依次为0.08 ms、0.05 ms、0.05 ms、0.07 ms、0.10 ms和0.07 ms。仿照提取出的6个日长年际信号，对大气角动量序列中相应的信号进行提取，并对两者进行相关性分析。结果显示，大气和日长对应的4个高频年际信号（2.3 a（2.4 a）、3.3 a、3.7 a和4.8 a信号）存在强相关，相关系数分别为0.99、0.93、0.99和0.91，且大气的激发贡献率依次为99.7%、63.1%、94.7%和69.3%，表明日长2.3 a（2.4 a）和3.7 a信号几乎完全可由大气解释，而大气也为其余2个日长信号的主要激发源；大气6.0 a、8.5 a信号与日长对应的6.1 a、8.1 a信号不相关或弱相关，相关系数分别为-0.11和-0.56。
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| 关 键 词： | 日长变化 标准Morlet小波变换 年际信号 平均振幅 特征分析 |
Extraction of Interannual Signals in the Length-of-Day Variation and Correlation Analysis with the Atmosphere |
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| ZHANG Xinfeng,LIU Genyou.Extraction of Interannual Signals in the Length-of-Day Variation and Correlation Analysis with the Atmosphere[J].Journal of Geodesy and Geodynamics,2020,40(11):1188-1193. |
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| Authors: | ZHANG Xinfeng LIU Genyou |
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| Abstract: | In order to conduct a more detailed analysis of the length-of-day (LOD) interannual variation, we use the normal Morlet wavelet transform method to identify and extract six main interannual signals from the LOD time series, which are 2.3 a (2.4 a), 3.3 a, 3.7 a, 4.8 a, 6.1 a and 8.1 a signals, respectively. Then, based on the time-domain extracted result, we acquire corresponding average amplitudes, which are 0.08 ms, 0.05 ms, 0.05 ms, 0.07 ms, 0.10 ms and 0.07 ms, respectively. Refer to the method of extracting interannual signals of the LOD, we extract the corresponding signals in the atmospheric angular momentum series, and perform correlation analysis between them. The results show that the atmosphere is closely related to four high frequency interannual signals (2.3 a (2.4 a), 3.3 a, 3.7 a and 4.8 a) corresponding to the LOD, and the correlation coefficients are 0.99, 0.93, 0.99, 0.91, respectively. The contribution rates of the atmosphere to the 2.3 a (2.4 a), 3.3 a, 3.7 a and 4.8 a signals of LOD are about 99.7%, 63.1%, 94.7% and 69.3%, which indicates that 2.3 a (2.4 a) and 3.7 a signals of the LOD can be almost completely explained by atmosphere, and the other two signals are also mainly affected by atmosphere. The 6.0 a and 8.5 a atmospheric signals are irrelevant or weakly related with the 6.1 a and 8.1 a signals corresponding to the LOD, and the correlation coefficients are -0.11 and -0.56, respectively. |
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| Keywords: | length-of-day variation normal Morlet wavelet transform interannual signals average amplitude characteristic analysis |
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