Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/146103
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dc.contributor.authorManta, Fabioen_US
dc.contributor.authorOcchipinti, Giovannien_US
dc.contributor.authorFeng, Lujiaen_US
dc.contributor.authorHill, Emma M.en_US
dc.date.accessioned2021-01-26T08:32:43Z-
dc.date.available2021-01-26T08:32:43Z-
dc.date.issued2020-
dc.identifier.citationManta, F., Occhipinti, G., Feng, L., & Hill, E. M. (2020). Rapid identification of tsunamigenic earthquakes using GNSS ionospheric sounding. Scientific Reports, 10(1), 11054-. doi:10.1038/s41598-020-68097-wen_US
dc.identifier.issn2045-2322en_US
dc.identifier.other0000-0001-9323-3185-
dc.identifier.other0000-0002-3736-5025-
dc.identifier.other0000-0003-0231-5818-
dc.identifier.urihttps://hdl.handle.net/10356/146103-
dc.description.abstractThe largest tsunamis are generated by seafloor uplift resulting from rupture of offshore subduction-zone megathrusts. The rupture of the shallowest part of a megathrust often produces unexpected outsize tsunami relative to their seismic magnitude. These are so called ‘tsunami earthquakes’, which are difficult to identify rapidly using the current tsunami warning systems, even though, they produce some of the deadliest tsunami. We here introduce a new method to evaluate the tsunami risk by measuring ionospheric total electron content (TEC). We examine two Mw 7.8 earthquakes (one is a tsunami earthquake and the other is not) generated in 2010 by the Sunda megathrust, offshore Sumatra, to demonstrate for the first time that observations of ionospheric sounding from Global Navigation Satellite System (GNSS) can be used to evaluate the tsunamigenic potential of earthquakes as early as 8 min after the mainshock.en_US
dc.description.sponsorshipMinistry of Education (MOE)en_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.language.isoenen_US
dc.relationNRF-NRFI05-2019-0009en_US
dc.relation.ispartofScientific Reportsen_US
dc.relation.uri10.21979/N9/3KUEM5en_US
dc.rights© 2020 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.subjectEngineering::Environmental engineeringen_US
dc.titleRapid identification of tsunamigenic earthquakes using GNSS ionospheric soundingen_US
dc.typeJournal Articleen
dc.contributor.schoolAsian School of the Environmenten_US
dc.contributor.researchEarth Observatory of Singaporeen_US
dc.identifier.doi10.1038/s41598-020-68097-w-
dc.description.versionPublished versionen_US
dc.identifier.pmid32632250-
dc.identifier.scopus2-s2.0-85087482564-
dc.identifier.issue1en_US
dc.identifier.volume10en_US
dc.subject.keywordsNatural Hazardsen_US
dc.subject.keywordsSeismologyen_US
dc.description.acknowledgementSome of the results presented here are reported in the PhD thesis of Dr. Fabio Manta (https://hdl.handle.net/10356/107577), archived by Nanyang Technological University, Singapore. We are grateful to the many scientists and field technicians who have kept the SuGAr network in operation. These include Paramesh Banerjee, Iwan Hermawan, Danny Natawidjaja, Jeffrey Encillo, Imam Suprihanto, Dudi Prayudi, and Bambang Suwargadi. SuGAr GPS data are available for download from ftp://ftp.earthobservatory.sg/SugarData. This research was supported by the National Research Foundation Singapore under its Singapore NRF Investigatorship scheme (Award No. NRF-NRFI05-2019-0009) and by the EOS and the National Research Foundation Singapore and the Singapore Ministry of Education under the Research Centres of Excellence initiative. G.O. is supported by Programme National de Télédétection Spatiale (PNTS), grant n PNTS-2014-07; by the CNES, grant GISnet&Back; and by the Institut Universitaire de France (IUF). We thank Benoit Taisne for useful discussions, and the reviewers for constructive comments. This is EOS contribution 300 and IPGP contribution 4054.en_US
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