Seismo Ionospheric Anomalies around and over the Epicenters of Pakistan Earthquakes

Abstract

Global Navigation Satellite System (GNSS)-based ionospheric anomalies are nowadays used to identify a possible earthquake (EQ) precursor and hence a new research topic in seismic studies. The current study also aims to provide an investigation of ionospheric anomalies associated to EQs. In order to study possible pre-and post-seismic perturbations during the preparation phase of large-magnitude EQs, statistical and machine learning algorithms are applied to Total Electron Content (TEC) from the Global Positioning System (GPS) and Global Ionosphere Maps (GIMs). We observed TEC perturbation from the Sukkur (27.8° N, 68.9° E) GNSS station near the epicenter of Mw 5.4 Mirpur EQ within 5–10 days before the main shock day by implementing machine learning and statistical analysis. However, no TEC anomaly occurred in GIM-TEC over the Mirpur EQ epicenter. Furthermore, machine learning and statistical techniques are also implemented on GIM TEC data before and after the Mw 7.7 Awaran, where TEC anomalies can be clearly seen within 5–10 days before the seismic day and the subsequent rise in TEC during the 2 days after the main shock. These variations are also evident in GIM maps over the Awaran EQ epicenter. The findings point towards a large emission of EQ energy before and after the main shock during quiet storm days, which aid in the development of lithosphere ionosphere coupling. However, the entire analysis can be expanded to more satellite and ground-based measurements in Pakistan and other countries to reveal the pattern of air ionization from the epicenter through the atmosphere to the ionosphere.

Keywords

• GPS VTEC
• deep learning
• earthquakes
• GIM-TEC
• Pakistan