Scholarlink

<p>Seismic noise in the frequency band from approximately 0.003–1.0&#xa0;Hz is primarily composed of three main components: the primary microseism, secondary microseisms, and the hum. These signals dominate the monthly averages of seismic noise. However, temporary additional signals in the same frequency band can occur, such as those generated by tropical cyclones in the ocean. In the present study, we investigate one such instance: Biparjoy, an extremely severe tropical cyclone that formed over the central-east Arabian Sea. We identified an increase in amplitude in a continuous seismic record from 6 June 2023 to 17 June 2023, during which ground displacements of up to 300 nm were observed. Furthermore, we extracted the path travelled by the cyclone using three-component waveform data, which closely matched the daily results published by the India Meteorological Department (IMD). These findings demonstrate the potential of using seismic data to monitor and track cyclone activity.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Seismological signatures of Biparjoy Cyclone recorded by GSNet stations in Gujarat, India

  • 期刊论文

  • 发表日期：

    2025年7月11日

查看全文
  • D Pragnath,
  • G Srijayanthi,
  • Santosh Kumar,
  • Sumer Chopra

摘要

Seismic noise in the frequency band from approximately 0.003–1.0 Hz is primarily composed of three main components: the primary microseism, secondary microseisms, and the hum. These signals dominate the monthly averages of seismic noise. However, temporary additional signals in the same frequency band can occur, such as those generated by tropical cyclones in the ocean. In the present study, we investigate one such instance: Biparjoy, an extremely severe tropical cyclone that formed over the central-east Arabian Sea. We identified an increase in amplitude in a continuous seismic record from 6 June 2023 to 17 June 2023, during which ground displacements of up to 300 nm were observed. Furthermore, we extracted the path travelled by the cyclone using three-component waveform data, which closely matched the daily results published by the India Meteorological Department (IMD). These findings demonstrate the potential of using seismic data to monitor and track cyclone activity.