An Improved Pattern Informatics Method for Extracting Ionospheric Disturbances Related to Seismicity Based on CSES Data: A Case Study of the Mw 7.3 Maduo Earthquake

Abstract

The exploration of multi-layer coupling mechanisms between earthquakes and the ionosphere is crucial for utilizing ionospheric precursors in earthquake prediction. A significant research task involves continuously tracking the spatio-temporal changes in ionospheric parameters, acquiring comprehensive seismic anomaly information, and capturing “deterministic” precursor anomalies. Building upon previous research on seismic ionospheric signal characteristics and data from the China Seismo-Electromagnetic Satellite (CSES), we have enhanced the Pattern Informatics(PI) Method and proposed an Improved Pattern Informatics(IPI) Method. The IPI method enables the calculation of the spatio-temporal dynamics of electronic density anomalies detected by the CSES satellite. Taking the 2021 Maduo Mw7.3 earthquake as a case study, we analyzed the seismic signals potentially contained in the electronic density anomaly disturbances. The results show that: 1) Compared to original electronic density images, the IPI method-derived models extracted distinct electronic density anomaly signals, regardless of the data collected whether during descending (daytime) or ascending (nighttime) orbits, or across different time scales of change window. 2) The electronic density anomalies appeared about 40 days prior to the Maduo Mw7.3 earthquake. The evolution of these anomalies followed a pattern of appearance, persistence, disappearance, re-emergence, and final disappearance. Moreover, the evolution trends of the IPI hotspot images calculated from descending and ascending orbit data were similar. These results suggest that the IPI method can capture the spatio-temporal trends of ionospheric parameters and effectively extract electronic precursors related to strong earthquakes.