This paper develops a self-parametrized Bayesian inversion to infer the spatio-temporal evolution of tsunami sources (initial sea state) due to megathrust earthquakes. To date, tsunami-source uncertainties are poorly understood, and the effect of choices such as discretization have not been studied. The approach developed here is based on a trans-dimensional self-parametrization of the sea surface, avoids regularization constraints and provides rigorous uncertainty estimation that accounts for model-selection ambiguity associated with the source discretization. The sea surface is parametrized using self-adapting irregular grids, which match the local resolving power of the data and provide parsimonious solutions for complex source characteristics. Source causality is ensured by including rupture-velocity and obtaining delay times from the Eikonal equation. The data are recorded on ocean-bottom pressure and coastal wave gauges and predictions are based on Green-function libraries computed from ocean-basin scale tsunami models for cases that include/exclude dispersion effects. The inversion is applied to tsunami waveforms from the great 2011 Tohoku-Oki (Japan) earthquake. The tsunami source is strongest near the Japan trench with posterior mean amplitudes of ~5 m. In addition, the data appear sensitive to rupture velocity, which is part of our kinematic source model.
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October 2014
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October 01 2014
Bayesian tsunami-waveform inversion with trans-dimensional tsunami-source models
Jan Dettmer;
Jan Dettmer
Res. School of Earth Sci., Australian National Univ., 3800 Finnerty Rd., Victoria, Br. Columbia V8W 3P6, Canada, [email protected]
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Jakir Hossen;
Jakir Hossen
Res. School of Earth Sci., Australian National Univ., Canberra, ACT, Australia
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Phil R. Cummins;
Phil R. Cummins
Res. School of Earth Sci., Australian National Univ., Canberra, ACT, Australia
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Stan E. Dosso
Stan E. Dosso
School of Earth and Ocean Sci., Univ. of Victoria, Victoria, BC, Canada
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J. Acoust. Soc. Am. 136, 2085 (2014)
Citation
Jan Dettmer, Jakir Hossen, Phil R. Cummins, Stan E. Dosso; Bayesian tsunami-waveform inversion with trans-dimensional tsunami-source models. J. Acoust. Soc. Am. 1 October 2014; 136 (4_Supplement): 2085. https://doi.org/10.1121/1.4899490
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