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Shrivastava MN, Sunil AS, Maurya AK, Aguilera F, Orrego S, Sunil PS, Cienfuegos R, Moreno M. Tracking tsunami propagation and Island's collapse after the Hunga Tonga Hunga Ha'apai 2022 volcanic eruption from multi-space observations. Sci Rep 2023; 13:20109. [PMID: 37978308 PMCID: PMC10656493 DOI: 10.1038/s41598-023-46397-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 10/31/2023] [Indexed: 11/19/2023] Open
Abstract
The quantity and accuracy of satellite-geodetic measurements have increased over time, revolutionizing the monitoring of tectonic processes. Global Navigation Satellite System (GNSS) and satellite radar signals provide observations beyond ground deformation, including how earthquake and tsunami processes affect variations in the ionosphere. Here, we study the Hunga Tonga Hunga Ha'apai (HTHH) volcanic eruption 2022 and its associated tsunami propagation with the analysis GNSS derived Total Electron Content (TEC), Synthetic Aperture Radar (SAR) Sentinel-1 data, complemented with tide gauge observations. We utilize GNSS sites data within a ~ 5000 km radius from the volcanic eruption for estimating the ionospheric perturbation as Vertical TEC. We give evidence on the detection of acoustic gravity, internal gravity, and atmospheric Lamb waves signatures in the TEC perturbation. In particular, the internal gravity waves that concentrated in the southwest of Tonga, directly correlates with the observed tsunami propagation direction as accounted by the tide gauge measurements. However, the acoustic gravity wave signature in the TEC is dominant in the north direction suggesting a surface deformation, which could be verified using Sentinel-1A SAR amplitude data. The analysis presented herein shows that within 5 h of the volcanic eruption, the central part of the HTHH island landscape disappeared with the biggest explosion. The unprecedented detail resolved by integrating satellite data yields previously unknown details of the deformation of the 2022 HTHH volcano eruption.
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Affiliation(s)
- Mahesh N Shrivastava
- Departamento de Ciencias Geologicas, Universidad Católica del Norte, Antofagasta, Chile.
- Millenium Institute on Volcanic Risk Research - Ckelar Volcanoes, Antofagasta, Chile.
- Centro de Investigación para la Gestión Integrada del Riesgo de Desastres, Santiago, Chile.
| | - A S Sunil
- Department of Marine Geology and Geophysics, School of Marine Sciences, Cochin University of Science and Technology, Kochi, India
| | - Ajeet K Maurya
- Department of Physics, Babasaheb Bhimrao Ambedkar University, Lucknow, India
| | - Felipe Aguilera
- Departamento de Ciencias Geologicas, Universidad Católica del Norte, Antofagasta, Chile
- Millenium Institute on Volcanic Risk Research - Ckelar Volcanoes, Antofagasta, Chile
| | - Simón Orrego
- Departamento de Ciencias Geologicas, Universidad Católica del Norte, Antofagasta, Chile
| | - P S Sunil
- Department of Marine Geology and Geophysics, School of Marine Sciences, Cochin University of Science and Technology, Kochi, India
| | - Rodrigo Cienfuegos
- Centro de Investigación para la Gestión Integrada del Riesgo de Desastres, Santiago, Chile
- Departamento de Ingeniería Hidráulica y Ambiental, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Marcos Moreno
- Centro de Investigación para la Gestión Integrada del Riesgo de Desastres, Santiago, Chile
- Departmento de Ingeniería Estructural y Geotécnica, Pontificia Universidad Católica de Chile, Santiago, Chile
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Determining spatio-temporal characteristics of coseismic travelling ionospheric disturbances (CTID) in near real-time. Sci Rep 2021; 11:20783. [PMID: 34675366 PMCID: PMC8531289 DOI: 10.1038/s41598-021-99906-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 09/30/2021] [Indexed: 11/20/2022] Open
Abstract
Earthquakes are known to generate ionospheric disturbances that are commonly referred to as co-seismic travelling ionospheric disturbances (CTID). In this work, for the first time, we present a novel method that enables to automatically detect CTID in ionospheric GNSS-data, and to determine their spatio-temporal characteristics (velocity and azimuth of propagation) in near-real time (NRT), i.e., less than 15 min after an earthquake. The obtained instantaneous velocities allow us to understand the evolution of CTID and to estimate the location of the CTID source in NRT. Furthermore, also for the first time, we developed a concept of real-time travel-time diagrams that aid to verify the correlation with the source and to estimate additionally the propagation speed of the observed CTID. We apply our methods to the Mw7.4 Sanriku earthquake of 09/03/2011 and the Mw9.0 Tohoku earthquake of 11/03/2011, and we make a NRT analysis of the dynamics of CTID driven by these seismic events. We show that the best results are achieved with high-rate 1 Hz data. While the first tests are made on CTID, our method is also applicable for detection and determining of spatio-temporal characteristics of other travelling ionospheric disturbances that often occur in the ionosphere driven by many geophysical phenomena.
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Tsunami detection by GPS-derived ionospheric total electron content. Sci Rep 2021; 11:12978. [PMID: 34155312 PMCID: PMC8217264 DOI: 10.1038/s41598-021-92479-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 06/04/2021] [Indexed: 02/05/2023] Open
Abstract
To unravel the relationship between earthquake and tsunami using ionospheric total electron content (TEC) changes, we analyzed two Chilean tsunamigenic subduction earthquakes: the 2014 Pisagua Mw 8.1 and the 2015 Illapel Mw 8.3. During the Pisagua earthquake, the TEC changes were detected at the GPS sites located to the north and south of the earthquake epicenter, whereas during the Illapel earthquake, we registered the changes only in the northward direction. Tide-gauge sites mimicked the propagation direction of tsunami waves similar to the TEC change pattern during both earthquakes. The TEC changes were represented by three signals. The initial weaker signal correlated well with Acoustic Rayleigh wave (AWRayleigh), while the following stronger perturbation was interpreted to be caused by Acoustic Gravity wave (AGWepi) and Internal Gravity wave (IGWtsuna) induced by earthquakes and subsequent tsunamis respectively. Inevitably, TEC changes can be utilized to evaluate earthquake occurrence and tsunami propagation within a framework of multi-parameter early warning systems.
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