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地震 ›› 2021, Vol. 41 ›› Issue (3): 171-191.doi: 10.12196/j.issn.1000-3274.2021.03.013

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2019年四川长宁MS6.0地震前电离层TEC异常分析

翟笃林1,2,3, 林剑1,2,3, 张学民4, 宋锐5, 熊攀4   

  1. 1.中国地震局地震研究所, 湖北 武汉 430071;
    2.中国地震局地震大地测量重点实验室, 湖北 武汉 430071;
    3.湖北省地震局, 湖北 武汉 430071;
    4.中国地震局地震预测研究所, 北京 100036;
    5.Chiba University, Inage 263-8522, Japan
  • 收稿日期:2019-11-28 修回日期:2020-11-23 出版日期:2021-07-31 发布日期:2021-11-02
  • 通讯作者: 张学民, 研究员。 E-mail: zhangxm96@126.com
  • 作者简介:翟笃林(1992-), 男, 安徽芜湖人, 研究实习员, 主要从事空间电离层TEC数据处理方法研究。
  • 基金资助:
    中国地震科学实验场项目(2018CSES0203); 国家重点研发计划项目(2018YFC1503506, 2018YFC1503505)

Analysis of Ionospheric TEC Anomalies before the 2019 MS6.0 Earthquake in Changning, Sichuan Province

ZHAI Du-lin1,2,3, LIN Jian1,2,3, ZHANG Xue-min4, SONG Rui5, XIONG Pan4   

  1. 1. Institute of Seismology, CEA, Wuhan 430071, China;
    2. Key Laboratory of Earthquake Geodesy, CEA, Wuhan 430071, China;
    3. Hubei Earthquake Administration, Wuhan 430071, China;
    4. Institute of Earthquake Forecasting, China Earthquake Administration, Beijing 100036;
    5. Chiba University, Inage 263-8522, Japan
  • Received:2019-11-28 Revised:2020-11-23 Online:2021-07-31 Published:2021-11-02

摘要: 2019年6月17日四川宜宾市长宁县发生MS6.0地震。 为了检测地震电离层电子浓度总含量(TEC)异常变化, 采用自回归滑动平均模型(ARIMA)和先知(Prophet)两种方法来描述TEC时间序列, 检测长宁地震前后TEC异常变化。 地磁指数Kp, Dst, Ap和F10.7用于区分与太阳—地磁活动等空间因素相关的其他异常。 结果显示, 使用ARIMA方法, 除了在地震发生前13天5:45 UTC检测到TEC数据时间序列中的显著电离层异常外, 其他电离层异常变化全部发生在震后2~6 d; 而使用Prophet方法在地震发生前16天7:45 UTC、 13天9:30 UTC、 5天8:30 UTC以及3天09:30 UTC检测到多处异常现象。 综合分析表明, 使用Prophet方法比ARIMA更易检测出震前异常。 同时, Prophet由于其非线性学习的能力相对较强可作为地震电离层异常检测的鲁棒预测工具。

关键词: Prophet, ARIMA, 电离层异常, TEC, 地震

Abstract: On 17 June 2019, an earthquake with MS6.0 occurred near Changning, Yibin, Sichuan Province. In order to detect the anomalous changes of Total Electron Content (TEC) seismic ionospheric, Autoregressive Integrated Moving Average Model (ARIMA) and prophet are used to describe the TEC time series and detect TEC anomalies variations before and after the Changning earthquake. In this study, geomagnetic indices (i.e. Kp, Dst, Ap and F10.7) are used to distinguish pre-earthquake anomalies from the other anomalies related to the geomagnetic and solar activities. The result of ARIMA shows that apart from the significant ionospheric anomalies in TEC time series detected at 5:45 UTC, 13 days before the earthquake, all the other ionospheric anomalies occurred 2~6 days after the event. While using Prophet method, multiple pre-earthquake anomalies are detected at 7:45 UTC before 16 days, 9:30 UTC before 13 days, 8:30 UTC before 5 days, and 09:30 UTC before 3 days. A comprehensive analysis indicates that the Prophet method is more likely to manifest anomalous states than traditional methods such as ARIMA. Meanwhile, due to its promising ability of nonlinearly learning, Prophet method is worthy of attention as a robust predictive tool for seismic ionospheric anomaly detection.

Key words: Prophet, ARIMA, Ionospheric anomalies, TEC, Earthquake

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