An Improved Pattern Informatics Method for Extracting Ionospheric Disturbances Related to Seismicity Based on CSES Data: A Case Study of the <i>M</i>w7.3 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. Based on data from the China Seismo‐Electromagnetic Satellite (CSES), we enhance the Pattern Informatics (PI) Method and propose an Improved Pattern Informatics (IPI) Method. The IPI method enables the calculation of the spatio‐temporal dynamics of electron density anomalies detected by the CSES satellite. The seismic signals in the electron density during earthquake on 2021 at Maduo are investigated in this work. The results show that: (a) Compared to original electron density images, the IPI method‐derived models extract distinct electron density anomaly signals, regardless of the data whether are collected during descending (daytime) or ascending (nighttime) orbits, or across different time scales of change window. (b) The electron density anomalies appear about 40 days prior to the Maduo M w7.3 earthquake. The evolution of these anomalies follows a pattern of appearance, persistence, disappearance, re‐emergence, and final disappearance. Moreover, the evolution trends of the IPI hotspot images at daytime and nighttime are 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.