Abstract

The China Seismo-Electromagnetic Satellite (CSES), with a sun-synchronous orbit at 507 km altitude, was launched on 2 February 2018 to investigate pre-earthquake ionospheric anomalies (PEIAs) and ionospheric space weather. The CSES probes manifest longitudinal features of four-peak plasma density and three plasma depletions in the equatorial/low-latitudes as well as mid-latitude troughs. CSES plasma and the total electron content (TEC) of the global ionosphere map (GIM) are used to study PEIAs associated with a destructive M7.0 earthquake and its followed M6.5 and M6.3/M6.9 earthquakes in Lombok, Indonesia, on 5, 17, and 19 August 2018, respectively, as well as to examine ionospheric disturbances induced by an intense storm with the Dst index of − 175 nT on 26 August 2018. Anomalous increases (decreases) in the GIM TEC and CSES plasma density (temperature) frequently appear specifically over the epicenter days 1–5 before the M7.0 earthquake and followed earthquakes, when the geomagnetic conditions of these PEIA periods are relatively quiet, Dst: − 37 to 19 nT. In contrast, TEC and CSES plasma parameter anomalies occur globally in the southern hemisphere during the storm days of 26–28 August 2018. The CSES ion velocity shows that the electric fields of PEIAs associated with the M7.0 earthquake are 0.21/0.06 mV/m eastward and 0.11/0.10 mV/m downward at post-midnight/post-noon on 1–3 August 2018, while the penetration electric fields during the storm periods of 26–28 August 2018 are 0.17/0.45 mV/m westward/downward at post-midnight of 02:00 LT and 0.26/0.26 mV/m eastward/upward at post-noon of 14:00 LT. Spatial analyses on CSES plasma discriminate PEIAs from global effects and locate the epicenter of possible forthcoming large earthquakes. CSES ion velocities are useful to derive PEIA- and storm-related electric fields in the ionosphere.

Key points

Spatial analyses are essential to find pre-earthquake ionospheric anomalies (PEIAs).

PEIA-related electric fields can be estimated by using the ion velocity in the ionosphere.

China seismo-electromagnetic satellite is used to detect PEIAs and study ionospheric space weather.

Details

Title
Spatial analyses on pre-earthquake ionospheric anomalies and magnetic storms observed by China seismo-electromagnetic satellite in August 2018
Author
Liu, Jann-Yenq Tiger 1   VIAFID ORCID Logo  ; Shen, Xuhui 2 ; Chang, Fu-Yuan 3 ; Chen, Yuh-Ing 4 ; Sun, Yang-Yi 5 ; Chen, Chieh-Hung 5 ; Pulinets, Sergey 6 ; Hattori, Katsumi 7 ; Ouzounov, Dimitar 8 ; Tramutoli, Valerio 9 ; Parrot, Michel 10 ; Chen, Wei-Sheng 11 ; Liu, Cheng-Yan 11 ; Zhang, Fei 11 ; Liu, Dapeng 12 ; Zhang, Xue-Min 13 ; Yan, Rui 12 ; Wang, Qiao 14 

1  National Central University, Center for Astronautical Physics and Engineering (CAPE), Taoyuan City, Taiwan (GRID:grid.37589.30) (ISNI:0000 0004 0532 3167); National Central University, Department of Space Science and Engineering, Taoyuan City, Taiwan (GRID:grid.37589.30) (ISNI:0000 0004 0532 3167); National Central University, Center for Space and Remote Sensing Research, Taoyuan City, Taiwan (GRID:grid.37589.30) (ISNI:0000 0004 0532 3167) 
2  National Space Science Center, CAS, Beijing, China (GRID:grid.454733.2) (ISNI:0000 0004 0596 2874) 
3  National Central University, Center for Astronautical Physics and Engineering (CAPE), Taoyuan City, Taiwan (GRID:grid.37589.30) (ISNI:0000 0004 0532 3167) 
4  National Central University, Graduate Institute of Statistics, Taoyuan City, Taiwan (GRID:grid.37589.30) (ISNI:0000 0004 0532 3167) 
5  China University of Geosciences, Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, Wuhan, China (GRID:grid.503241.1) (ISNI:0000 0004 1760 9015) 
6  Russian Academy of Sciences, Space Research Institute, Moscow, Russia (GRID:grid.4886.2) (ISNI:0000 0001 2192 9124) 
7  Chiba University, Department of Earth Sciences, Graduate School of Science, Chiba, Japan (GRID:grid.136304.3) (ISNI:0000 0004 0370 1101) 
8  Chapman University, Center of Excellence in Earth Systems Modeling & Observations, Schmid College of Science & Technology, Orange, USA (GRID:grid.254024.5) (ISNI:0000 0000 9006 1798) 
9  University of Basilicata, School of Engineering, Potenza, Italy (GRID:grid.7367.5) (ISNI:0000 0001 1939 1302) 
10  LPCE/CNRS, Orleans, France (GRID:grid.7367.5) 
11  China Earthquake Administration, Institute of Engineering Mechanics, Beijing, China (GRID:grid.450296.c) (ISNI:0000 0000 9558 2971) 
12  Ministry of Emergency Management, National Institute of Natural Hazards, Beijing, China (GRID:grid.450296.c) (ISNI:0000 0000 9558 2971) 
13  Beijing University of Technology, Institute of Earthquake Prediction, Beijing, China (GRID:grid.28703.3e) (ISNI:0000 0000 9040 3743) 
14  China Earthquake Administration, Institute of Geophysics, Beijing, China (GRID:grid.450296.c) (ISNI:0000 0000 9558 2971) 
Pages
4
Publication year
2024
Publication date
Dec 2024
Publisher
Springer Nature B.V.
e-ISSN
21964092
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1186/s40562-024-00320-2
ProQuest document ID
2916738234
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.