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Probabilistic tsunami threat assessment of 10 recent earthquakes offshore Sumatra

  • Tsunami early warning (TEW) is a challenging task as a decision has to be made within few minutes on the basis of incomplete and error-prone data. Deterministic warning systems have difficulties in integrating and quantifying the intrinsic uncertainties. In contrast, probabilistic approaches provide a framework that handles uncertainties in a natural way. Recently, we have proposed a method using Bayesian networks (BNs) that takes into account the uncertainties of seismic source parameter estimates in TEW. In this follow-up study, the method is applied to 10 recent large earthquakes offshore Sumatra and tested for its performance. We have evaluated both the general model performance given the best knowledge we have today about the source parameters of the 10 events and the corresponding response on seismic source information evaluated in real-time. We find that the resulting site-specific warning level probabilities represent well the available tsunami wave measurements and observations. Difficulties occur in the real-time tsunamiTsunami early warning (TEW) is a challenging task as a decision has to be made within few minutes on the basis of incomplete and error-prone data. Deterministic warning systems have difficulties in integrating and quantifying the intrinsic uncertainties. In contrast, probabilistic approaches provide a framework that handles uncertainties in a natural way. Recently, we have proposed a method using Bayesian networks (BNs) that takes into account the uncertainties of seismic source parameter estimates in TEW. In this follow-up study, the method is applied to 10 recent large earthquakes offshore Sumatra and tested for its performance. We have evaluated both the general model performance given the best knowledge we have today about the source parameters of the 10 events and the corresponding response on seismic source information evaluated in real-time. We find that the resulting site-specific warning level probabilities represent well the available tsunami wave measurements and observations. Difficulties occur in the real-time tsunami assessment if the moment magnitude estimate is severely over- or underestimated. In general, the probabilistic analysis reveals a considerably large range of uncertainties in the near-field TEW. By quantifying the uncertainties the BN analysis provides important additional information to a decision maker in a warning centre to deal with the complexity in TEW and to reason under uncertainty.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Lilian Blaser, Matthias OhrnbergerORCiDGND, Frank KrügerGND, Frank ScherbaumORCiDGND
DOI:https://doi.org/10.1111/j.1365-246X.2011.05324.x
ISSN:0956-540X
Titel des übergeordneten Werks (Englisch):Geophysical journal international
Verlag:Wiley-Blackwell
Verlagsort:Malden
Publikationstyp:Wissenschaftlicher Artikel
Sprache:Englisch
Jahr der Erstveröffentlichung:2012
Erscheinungsjahr:2012
Datum der Freischaltung:26.03.2017
Freies Schlagwort / Tag:Early warning; Indian Ocean; Probabilistic forecasting; Tsunamis
Band:188
Ausgabe:3
Seitenanzahl:12
Erste Seite:1273
Letzte Seite:1284
Fördernde Institution:German Federal Ministry of Education and Research, Geotechnologien 'Fruhwarnsysteme' [03G0648D]
Organisationseinheiten:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
Peer Review:Referiert
Name der Einrichtung zum Zeitpunkt der Publikation:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
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