地球物理学进展 ›› 2021, Vol. 36 ›› Issue (1): 112-118.doi: 10.6038/pg2021DD0536

• 固体地球物理及空间物理学(大气、行星、地球动力学、重磁电及地震学、地热学) • 上一篇    下一篇

日长变化中长周期信号的提取及其特征分析

张欣峰1,2(), 刘根友1,*()   

  1. 1.中国科学院测量与地球物理研究所大地测量与地球动力学国家重点实验室,武汉 430077
    2.中国科学院大学,北京 100049
  • 收稿日期:2020-03-13 修回日期:2020-08-21 出版日期:2021-02-20 发布日期:2021-03-11
  • 通讯作者: 刘根友 E-mail:zhangxinfeng@whigg.ac.cn;liugy@whigg.ac.cn
  • 作者简介:张欣峰,男,1994年出生,硕士研究生,主要从事地球自转参数的时间序列分析研究.E-mail: zhangxinfeng@whigg.ac.cn
  • 基金资助:
    国家自然科学基金(41774017);国家自然科学基金(41621091);国家重点研发计划(2016YFB0501900)

Extraction and feature analysis of long-period signals in the length-of-day variations

ZHANG XinFeng1,2(), LIU GenYou1,*()   

  1. 1. State Key Laboratory of Geodesy and Earth’s Dynamics, Institute of Geodesy and Geophysics,Wuhan 430077, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2020-03-13 Revised:2020-08-21 Online:2021-02-20 Published:2021-03-11
  • Contact: LIU GenYou E-mail:zhangxinfeng@whigg.ac.cn;liugy@whigg.ac.cn

摘要:

地核与固体地球之间角动量的交换虽然可以明显引起十年尺度的日长变化,但两者之间的耦合机制尚不明确.为了对日长年代际变化进行更深入的分析,有必要对其中主要的周期信号进行识别和提取.为此,本文利用标准Morlet小波变换方法,对精度相对较差的长期日长数据(1760—2018)进行处理,识别和提取出了7个频率稳定的长周期信号,周期分别为11.7年、13.5年、15.6年、19.4年、22.5年、32.4年和67.4年.此外,基于信号的时域提取结果,计算获得了相应信号的平均振幅,分别为0.07 ms、0.11 ms、0.10 ms、0.21 ms、0.36 ms、0.49 ms 和0.96 ms,并对信号的时域变化特征做了初步分析,可以为进一步研究与日长年代际变化相关的的物理机制提供一定的参考.

关键词: 日长变化, 标准Morlet小波变换, 长周期信号, 特征分析

Abstract:

Although the exchange of angular momentum between the core and the solid earth can obviously cause decadal variations in the length of day (LOD), the coupling mechanism between the two is not clear. In order to conduct a more in-depth analysis of the decadal LOD variations, it is necessary to identify and extract the main periodic signals. To this end, this paper uses the normal Morlet wavelet transform method to process the long-term time series (1760-2018), which precision is relatively poor. Seven stable periodic signals are recognized and extracted, which are 11.7 a, 13.5 a, 15.6 a, 19.4 a, 22.5 a, 32.4 a and 67.4 a signals, respectively. Furthermore, based on the time-domain extracted result, the average amplitudes of corresponding signal are calculated, which are 0.07 ms, 0.11 ms, 0.10 ms, 0.21 ms, 0.36 ms, 0.49 ms and 0.96 ms, respectively. Finally, this paper makes preliminary analysis of the time-domain characteristic of the signal, which can provide certain references for further research on the geophysical mechanism of decadal variations in length of day.

Key words: Length of day, NMWT method, Long-period signals, Feature analysis

中图分类号: