Rapid estimation of source parameters for the 2022 Mw 6.6 Menyuan earthquake with combined high-rate GNSS and strong motion data in Northeastern Tibet.
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| Title: | Rapid estimation of source parameters for the 2022 Mw 6.6 Menyuan earthquake with combined high-rate GNSS and strong motion data in Northeastern Tibet. |
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| Authors: | Yang, Chen1 (AUTHOR), Su, Xiaoning1,2 (AUTHOR) suxiaoning_666@126.com, Gao, Zhiyu1,2 (AUTHOR), Kou, Ruixiong1,2 (AUTHOR) |
| Source: | Terrestrial, Atmospheric & Oceanic Sciences. 12/20/2024, Vol. 35 Issue 1, p1-12. 12p. |
| Subjects: | Global Positioning System, Magnitude estimation, Earthquakes, Parameter estimation, Emergency management |
| Abstract: | To investigate the reliability of high-rate GNSS in the rapid estimation of source parameters for the 2022 Menyuan Mw 6.6 earthquake, we collected high-rate GNSS and strong motion data within a 200 km radius of the epicenter. We performed high-precision calculations to obtain three-dimensional dynamic displacement waveforms for all stations and analyzed the reliability of source parameter estimation and coseismic deformation acquisition. The three-dimensional dynamic displacement waveforms show that the amplitude of displacement fluctuations at each station decreases with increasing distance from the epicenter. The station closest to the epicenter, C007, recorded a maximum east–west amplitude of 15 cm, a north–south amplitude of 10.8 cm, and a vertical amplitude of only 2.2 cm. The inverted epicenter location using displacement waveforms is (101.263°E, 37.802°N), with an origin time of 17:45:25.9 (UTC) and a magnitude of Mw 6.65. These results are generally consistent with those obtained from seismological methods using the seismic data. By combining high-rate GNSS and strong-motion data for magnitude estimation, an initial value of Mw 6.0 can be obtained 15 s after the earthquake, with stable convergence to Mw 6.6 within 40 s. The quality of magnitude estimation convergence is positively correlated with the number of stations. Based on the displacement waveforms 100 s before and after the earthquake, the coseismic deformation of this event can be quickly obtained. The results show opposite motion trends on the south and north sides of the seismogenic fault, with no significant vertical movement. Our results indicate that using near-field high-rate GNSS and strong motion data can rapidly and effectively estimate the source parameters and coseismic deformation of the strong earthquake, which can provide valuable reference for post-earthquake emergency response and rapid disaster assessment. [ABSTRACT FROM AUTHOR] |
| Copyright of Terrestrial, Atmospheric & Oceanic Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Header | DbId: egs DbLabel: Engineering Source An: 181826291 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Rapid estimation of source parameters for the 2022 Mw 6.6 Menyuan earthquake with combined high-rate GNSS and strong motion data in Northeastern Tibet. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yang%2C+Chen%22">Yang, Chen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Su%2C+Xiaoning%22">Su, Xiaoning</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> suxiaoning_666@126.com</i><br /><searchLink fieldCode="AR" term="%22Gao%2C+Zhiyu%22">Gao, Zhiyu</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kou%2C+Ruixiong%22">Kou, Ruixiong</searchLink><relatesTo>1,2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Terrestrial%2C+Atmospheric+%26+Oceanic+Sciences%22">Terrestrial, Atmospheric & Oceanic Sciences</searchLink>. 12/20/2024, Vol. 35 Issue 1, p1-12. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Global+Positioning+System%22">Global Positioning System</searchLink><br /><searchLink fieldCode="DE" term="%22Magnitude+estimation%22">Magnitude estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Earthquakes%22">Earthquakes</searchLink><br /><searchLink fieldCode="DE" term="%22Parameter+estimation%22">Parameter estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Emergency+management%22">Emergency management</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: To investigate the reliability of high-rate GNSS in the rapid estimation of source parameters for the 2022 Menyuan Mw 6.6 earthquake, we collected high-rate GNSS and strong motion data within a 200 km radius of the epicenter. We performed high-precision calculations to obtain three-dimensional dynamic displacement waveforms for all stations and analyzed the reliability of source parameter estimation and coseismic deformation acquisition. The three-dimensional dynamic displacement waveforms show that the amplitude of displacement fluctuations at each station decreases with increasing distance from the epicenter. The station closest to the epicenter, C007, recorded a maximum east–west amplitude of 15 cm, a north–south amplitude of 10.8 cm, and a vertical amplitude of only 2.2 cm. The inverted epicenter location using displacement waveforms is (101.263°E, 37.802°N), with an origin time of 17:45:25.9 (UTC) and a magnitude of Mw 6.65. These results are generally consistent with those obtained from seismological methods using the seismic data. By combining high-rate GNSS and strong-motion data for magnitude estimation, an initial value of Mw 6.0 can be obtained 15 s after the earthquake, with stable convergence to Mw 6.6 within 40 s. The quality of magnitude estimation convergence is positively correlated with the number of stations. Based on the displacement waveforms 100 s before and after the earthquake, the coseismic deformation of this event can be quickly obtained. The results show opposite motion trends on the south and north sides of the seismogenic fault, with no significant vertical movement. Our results indicate that using near-field high-rate GNSS and strong motion data can rapidly and effectively estimate the source parameters and coseismic deformation of the strong earthquake, which can provide valuable reference for post-earthquake emergency response and rapid disaster assessment. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Terrestrial, Atmospheric & Oceanic Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s44195-024-00083-5 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 1 Subjects: – SubjectFull: Global Positioning System Type: general – SubjectFull: Magnitude estimation Type: general – SubjectFull: Earthquakes Type: general – SubjectFull: Parameter estimation Type: general – SubjectFull: Emergency management Type: general Titles: – TitleFull: Rapid estimation of source parameters for the 2022 Mw 6.6 Menyuan earthquake with combined high-rate GNSS and strong motion data in Northeastern Tibet. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yang, Chen – PersonEntity: Name: NameFull: Su, Xiaoning – PersonEntity: Name: NameFull: Gao, Zhiyu – PersonEntity: Name: NameFull: Kou, Ruixiong IsPartOfRelationships: – BibEntity: Dates: – D: 20 M: 12 Text: 12/20/2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 10170839 Numbering: – Type: volume Value: 35 – Type: issue Value: 1 Titles: – TitleFull: Terrestrial, Atmospheric & Oceanic Sciences Type: main |
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