Paper
2 January 2025 TEC anomaly detection in ionosphere of super typhoon Meranti
Honghao Shu, Ning Li, Ling Huang, Wenwen Li, Xu Liu, Caishenglong Han, Xiaoxuan Wei, Chuang Qian
Author Affiliations +
Proceedings Volume 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024); 135140I (2025) https://doi.org/10.1117/12.3059033
Event: 2024 International Conference on Remote Sensing and Digital Earth, 2024, Chengdu, China
Abstract
Typhoons, originating from tropical ocean surfaces, are among the most severe natural disasters worldwide, often leading to significant loss of life and property. Research indicates that the Total Electron Content (TEC) of the ionosphere experiences various disturbances before and after a typhoon event. This study utilizes global ionospheric data provided by the Chinese Academy of Sciences (CAS) to analyze the anomalies in TEC during a 15-day period surrounding Super Typhoon "Meranti" (No. 14) in 2016, employing Singular Spectrum Analysis (SSA) and the Sliding Interquartile Range (SIQR) method to detect perturbations. The results show that the anomalies detected by the SSA method are smaller than those detected by the SIQR method, but the number of detected abnormal periods increases significantly, indicating that the SSA method is more sensitive to anomaly detection of ionospheric TEC. Taken together, the SSA method shows significant advantages in detecting ionospheric TEC disturbances along the typhoon path. It can identify abnormal periods more comprehensively, highlight the abnormal characteristics of the ionosphere, and provides an effective tool for understanding the impact of typhoons on the ionosphere.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Honghao Shu, Ning Li, Ling Huang, Wenwen Li, Xu Liu, Caishenglong Han, Xiaoxuan Wei, and Chuang Qian "TEC anomaly detection in ionosphere of super typhoon Meranti", Proc. SPIE 13514, International Conference on Remote Sensing and Digital Earth (RSDE 2024), 135140I (2 January 2025); https://doi.org/10.1117/12.3059033
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KEYWORDS
Matrices

Analytical research

Interpolation

Singular value decomposition

Environmental sensing

Wind speed

Natural disasters

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