Study of the ionospheric precursors associated with M w ≥6.0EQ from Ionosonde Stations and GIM TEC

• Published in: Journal of atmospheric and solar-terrestrial physics 2024-03, Vol.256, p.106205, Article 106205
• Main Authors: Ahmed, Junaid, Shah, Munawar, Iqbal, Talat, Shah, Muhammad Ali, Amin, Ayaz
• Format: Article
• Language: English
• Subjects: GIM-TEC; Ionospheric critical frequency (foF2); Lithospheric-ionospheric coupling; Seismic precursors; Seismogenic zone
• ISSN: 1364-6826; 1879-1824
• DOI: 10.1016/j.jastp.2024.106205

To study the coupling mechanism between lithosphere, atmosphere and ionosphere, the ionosonde based earthquake (EQ) anomalies provide clear indications for the future events. The Lithospheric-Atmosphere-Ionospheric coupling (LAIC) provides information about pre and post seismic precursors over the seismogenic zone. This study presents the variations in ionospheric critical frequency (foF2) of the F2 layer and Total Electron Content (TEC) from Global Ionospheric Maps (GIMs) associated with the two Mw ≥ 6.0 EQs at Pakistan-Iran border (here-in-after, Saravan EQ) and Afghanistan. The ionosonde stations data located at Islamabad and Sonmiani provided significant foF2 variation for the April 16, 2013 (Mw7.7) and June 22, 2022 (Mw6.0) EQs in Saravan and Afghanistan, respectively. Furthermore, the foF2 values showed significant variations before the main shocks of both the events. Moreover, the TEC maps over the epicenter supported the variations of ionosonde data with maximum variations beyond the bound of the statistical method as anomalous positive variations before the two events. Moreover, prominent variations occur before both the EQs in ionosonde and TEC data but the Afghanistan event showed more pronounced variations than Saravan EQ. Additionally, it has been observed that more prominent variation occurs in both the stations within 5–10 days before the main shocks to aid another development in LAIC hypothesis. •Seismoionospheric anomalies have been studied for Mw ≥ 6.0 EQ.•Ionosonde and GIM-TEC data showed variations near epicenter.•Anomalies became more significant near the epicenters.•Storms time ionospheric are also prominent in the data.