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Bayesian seismic source inversion with a 3-D Earth model of the Japanese Islands
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  • Saule Simute,
  • Christian Boehm,
  • Lion Krischer,
  • Alexey Gokhberg,
  • Martin Vallée,
  • Andreas Fichtner
Saule Simute
ETH Zurich

Corresponding Author:[email protected]

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Christian Boehm
Department of Earth Sciences, Institute of Geophysics, ETH Zürich
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Lion Krischer
Mondaic AG
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Alexey Gokhberg
Fragata Computer Systems AG
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Martin Vallée
Institut De Physique Du Globe De Paris
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Andreas Fichtner
ETH Zurich
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We present probabilistic centroid-moment tensor solutions inferred from the combination of Hamiltonian Monte Carlo sampling and a 3-D full-waveform inversion Earth model of the Japanese archipelago. While the former provides complete posterior probability densities, the latter allows us to exploit waveform data with periods as low as 15 s. For the computation of Green’s functions, we employ spectral-element simulations through the radially anisotropic and visco-elastic model, leading to substantial improvements of data fit compared to layered models. Focusing on Mw 4.8 - Mw 5.3 offshore earthquakes with a significant non-double-couple component, we simultaneously infer the centroid location, time and moment tensor without any a priori constraints on the faulting mechanism. Furthermore, we perform the inversions across several period bands, varying the minimum period between 15 s and 50 s. Accounting for 3-D Earth structure at shorter periods can increase the double-couple component of an event, compared to the GCMT solution, by tens of percent. This suggests that at least some of the non-double-couple events in the GCMT catalog might result from unmodeled Earth structure. We also observe that significant changes in source parameters, and the double-couple component in particular, may be related to only small waveform changes, thereby accentuating the importance of a reliable Earth model. Posterior probability density distributions become increasingly multimodal for shorter-period data that provide tighter constraints on source parameters. This implies, in our specific case, that stochastic approaches to the source inversion problem are required for periods below ~ 20 s to avoid trapping in local minima.