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<p>Earthquakes are natural spectacles that occur when accumulated stress within the Earth’s crust is suddenly released, producing vibrations that travel through the ground. When a large earthquake releases energy, it generates acoustic waves and gravity waves that travel upward through the atmosphere. As these waves propagate, they disturb the density of the ionospheric plasma, leading to variations in Total Electron Content (TEC). This study investigates how ionospheric TEC responds before, after and during five major earthquakes in Japan and evaluates the ability of a Universal Kriging (UK) model to predict TEC variations. Five significant earthquakes that occurred between 2004 and 2024 were analyzed using True TEC data taken from USUD station, along with geomagnetic and solar parameters such as F10.7, Dst, Ap, and solar wind speed. TEC behavior during earthquakes was compared with the 30 days Median TEC values prior to each event was utilized to identify whether the ionospheric disturbances potentially linked to seismic or solar activity. Four statistical indicators were used to assess the performance of the UK, Median and IRI-2020 model. Performance evaluation parameters show that the Median TEC provides lower absolute error and bias, the UK model captures TEC variability effectively, especially during disturbed ionospheric conditions. Across the five events, noticeable TEC deviations were observed during the Kamaishi Earthquake where the solar and geomagnetic indices were quiet indicating possible seismo-ionospheric coupling. Both the Median and predicted values aligned close with the True TEC when compared to the IRI-2020 model. For the remaining four earthquakes the TEC variations were happened due to the solar and geomagnetic activity, but the Median and UK model performed well with less error metrics during those periods also. The findings highlight the potential of integrating TEC analysis with solar &amp; geomagnetic indices along with geophysical parameters for understanding ionospheric precursors for improved earthquake monitoring strategies.</p>

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Analysis and prediction of ionospheric TEC during five earthquakes in Japan using Universal Kriging and comparison with median/IRI-2020 TEC

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月1日

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  • R. Mukesh,
  • S. Kiruthiga,
  • Sarat C. Dass,
  • M. Vijay

摘要

Earthquakes are natural spectacles that occur when accumulated stress within the Earth’s crust is suddenly released, producing vibrations that travel through the ground. When a large earthquake releases energy, it generates acoustic waves and gravity waves that travel upward through the atmosphere. As these waves propagate, they disturb the density of the ionospheric plasma, leading to variations in Total Electron Content (TEC). This study investigates how ionospheric TEC responds before, after and during five major earthquakes in Japan and evaluates the ability of a Universal Kriging (UK) model to predict TEC variations. Five significant earthquakes that occurred between 2004 and 2024 were analyzed using True TEC data taken from USUD station, along with geomagnetic and solar parameters such as F10.7, Dst, Ap, and solar wind speed. TEC behavior during earthquakes was compared with the 30 days Median TEC values prior to each event was utilized to identify whether the ionospheric disturbances potentially linked to seismic or solar activity. Four statistical indicators were used to assess the performance of the UK, Median and IRI-2020 model. Performance evaluation parameters show that the Median TEC provides lower absolute error and bias, the UK model captures TEC variability effectively, especially during disturbed ionospheric conditions. Across the five events, noticeable TEC deviations were observed during the Kamaishi Earthquake where the solar and geomagnetic indices were quiet indicating possible seismo-ionospheric coupling. Both the Median and predicted values aligned close with the True TEC when compared to the IRI-2020 model. For the remaining four earthquakes the TEC variations were happened due to the solar and geomagnetic activity, but the Median and UK model performed well with less error metrics during those periods also. The findings highlight the potential of integrating TEC analysis with solar & geomagnetic indices along with geophysical parameters for understanding ionospheric precursors for improved earthquake monitoring strategies.