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Abstract <p>Typhoon formation and development in the ocean area, leading to a major challenge in the study of ionospheric response to typhoon is the sparse distribution of observation sites. To address this limitation, this study proposes a ground and space based (G/SBased) joint ionospheric detection technique that integrates data from ground-based Global Navigation Satellite System (GNSS) receivers and Low Earth Orbit (LEO) satellites. The approach combines LEO-derived Total Electron Content (TEC) with ground-based GNSS-TEC for unified ionospheric modeling. Prior to integration, the LEO-TEC is adjusted using the Chapman function to ensure consistency with the vertical sensing altitude of the ground-based GNSS-TEC. This innovative approach was applied to examine ionospheric anomalies during Super Typhoon Hagibis (1919). The results demonstrate that the G/SBased joint detection method effectively addresses the spatial sparsity of ground based GNSS sites over oceans, substantially increasing both the quantity and spatial homogeneity of ionospheric piercing points (IPPs). This approach resolves the issue of TEC overfitting associated with uneven IPP distribution in ground based GNSS monitoring. Comparative analysis reveals that the G/SBased technique significantly enhances TEC retrieval accuracy in the typhoon’s core region, reducing the mean error (ME) from –3.98 to –0.67 TECU and the root mean square error (RMSE) from 5.83 to 5.16&#xa0;TECU compared to standalone ground based GNSS measurements. Furthermore, the study identifies distinct ionospheric TEC anomalies in the typhoon center as it approached landfall. The G/SBased joint detection technique exhibits superior capabilities for monitoring typhoon-related ionospheric disturbances. By incorporating LEO satellite constellations, it overcomes the challenge of insufficient direct observation data over ocean areas, which otherwise hinders the use of GNSS observation data to detect typhoon induced ionospheric disturbances in remote seas.</p>

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Ionospheric Disturbance Monitoring during Typhoon Hagibis Based on GNSS G/SBased Joint Technology

  • 期刊论文

  • 发表日期：

    2026年2月1日

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  • Jianfeng Li,
  • Fang Wang,
  • Ding Yang,
  • Yunhui Xiang

摘要

Abstract

Typhoon formation and development in the ocean area, leading to a major challenge in the study of ionospheric response to typhoon is the sparse distribution of observation sites. To address this limitation, this study proposes a ground and space based (G/SBased) joint ionospheric detection technique that integrates data from ground-based Global Navigation Satellite System (GNSS) receivers and Low Earth Orbit (LEO) satellites. The approach combines LEO-derived Total Electron Content (TEC) with ground-based GNSS-TEC for unified ionospheric modeling. Prior to integration, the LEO-TEC is adjusted using the Chapman function to ensure consistency with the vertical sensing altitude of the ground-based GNSS-TEC. This innovative approach was applied to examine ionospheric anomalies during Super Typhoon Hagibis (1919). The results demonstrate that the G/SBased joint detection method effectively addresses the spatial sparsity of ground based GNSS sites over oceans, substantially increasing both the quantity and spatial homogeneity of ionospheric piercing points (IPPs). This approach resolves the issue of TEC overfitting associated with uneven IPP distribution in ground based GNSS monitoring. Comparative analysis reveals that the G/SBased technique significantly enhances TEC retrieval accuracy in the typhoon’s core region, reducing the mean error (ME) from –3.98 to –0.67 TECU and the root mean square error (RMSE) from 5.83 to 5.16 TECU compared to standalone ground based GNSS measurements. Furthermore, the study identifies distinct ionospheric TEC anomalies in the typhoon center as it approached landfall. The G/SBased joint detection technique exhibits superior capabilities for monitoring typhoon-related ionospheric disturbances. By incorporating LEO satellite constellations, it overcomes the challenge of insufficient direct observation data over ocean areas, which otherwise hinders the use of GNSS observation data to detect typhoon induced ionospheric disturbances in remote seas.