Singular Spectrum Analysis of the Total Electron Content Changes Prior to M ≥ 6.0 Earthquakes in the Chinese Mainland During 1998–2013

Abstract

Early studies have shown evidence of the seismo-ionospheric perturbations prior to large earthquakes. Due to dynamic complexity in the ionosphere, the identification of precursory ionospheric changes is quite challenging. In this study, we analyze the total electron content (TEC) in the global ionosphere map and investigate the TEC changes prior to M ≥ 6.0 earthquakes in the Chinese Mainland during 1998–2013 to identify possible seismo-ionospheric precursors. Singular spectrum analysis is applied to extract the trend and periodic variations including diurnal and semi-diurnal components, which are dominated by solar activities. The residual ΔTEC which is mainly composed of errors and possible perturbations induced by earthquakes and geomagnetic activities is further investigated, and the root-mean-square error is employed to detect anomalous changes. The F10.7 and Dst index is also used as criterion to rule out the anomalies when intense solar or geomagnetic activities occur. Our results are consistent with those of previous studies. It is confirmed that the negative anomalies are dominant 1–5 days before the earthquakes at the fixed point (35°N, 90°E) during 0600–1000 LT. The anomalies are more obvious near the epicenter area. The singular spectrum analysis method help to establish a more reliable variation background of TEC and thus may improve the identification of precursory ionospheric changes.

Investigating short-term earthquake precursors detection through monitoring of total electron content variation in ionosphere

“…The variability of ionospheric variations makes it difficult to distinguish the anomalies caused by enhanced pre-seismic activity The number of earthquakes with precursors in relationship with the earliest time it was detected before earthquake, and size of magnitude based on previous studies (Naaman et al, 2001;Pulinets et al, 2007;Afraimovich and Astafyeva, 2008;Sharma et al, 2010;Zhao et al, 2010;Akhoondzadeh and Saradjian, 2011;Hasbi et al, 2011;Kon et al, 2011;Saradjian and Akhoondzadeh, 2011;Xu et al, 2011;Zolotov et al, 2011;Akhoondzadeh, 2012;Choi et al, 2012;Zhu et al, 2013;Lin, 2014;Tang et al, 2015;Daneshvar and Freund, 2016;Oikonomou et al, 2016;Jiang et al, 2017;Sharma et al, 2017;Tao et al, 2017;Akpan et al, 2019;Li et al, 2019;Shi et al, 2019;Yang et al, 2019;Simha et al, 2020;Tachema and Nadji, 2020;Chen et al, 2021;Mahmoudian and Ghayour, 2021;Mehdi et al, 2021;Sasmal et al, 2021;Dong et al, 2022).…”

GNSS TEC-Based Earthquake Ionospheric Perturbation Detection Using a Novel Deep Learning Framework

“…In addition to these seismic case-based studies, seismologists have also extensively conducted statistics-based studies on TEC anomalies prior to large earthquakes. In such research, Chen et al [17] analyzed the TEC of the global ionospheric map using singular spectrum analysis to establish reliable background variability and determine the root-mean-square error (RMSE) of detected anomalies prior to M s ≥ 6.0 earthquakes in mainland China from 1998 to 2013. They found that the anomalies were concentrated 1-5 days before the earthquakes and that the anomalies were most obvious near the epicenter.…”

Assessing Earthquake Forecasting Performance Based on Annual Mobile Geomagnetic Observations in Southwest China

“…Field studies show that various seismo-geomagnetic signals can be generated at the different stages of earthquake formation and occurrence [18,[23][24][25]. These include the mid-and long-term resistivity changes before the earthquake [26][27][28], mid-and short-term ultra-low-frequency (ULF) [14,[29][30][31][32][33] and very low frequency (VLF) geomagnetic field changes [34][35][36][37], and changes in the total electron content (TEC) over a short period of hours/minutes [38][39][40][41]. Annual mobile geomagnetic observation is one of the observed methods for the geomagnetic field, which carries out periodic and repeated mobile observations on many geomagnetic observation sites in a specific area.…”