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\begin{document}

\title{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}



\author[1]{Weixi Tian}%
\author[2]{Yongxian Zhang}%
\author[3]{Changhui Ju}%
\author[3]{Shengfeng Zhang}%
\author[3]{Maoning Feng}%
\author[4]{Fengli Liu}%
\affil[1]{Institute of geophysics ,China Earthquake Administration}%
\affil[2]{Institute of Earthquake Forecasting, China Earthquake Administration}%
\affil[3]{Institute of Earthquake Forcasting,China Earthquake Administration}%
\affil[4]{Department of Earth and Space Sciences, Southern University of Science and Technology}%


\vspace{-1em}



  
  \date{May 25, 2024}


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\begin{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.%
\end{abstract}%



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