Bayesian Seismic Source Inversion With a 3‐D Earth Model of the Japanese Islands. Issue 1 (28th December 2022)

• Record Type: Journal Article
• Authors: Simutė, Saulė; Boehm, Christian; Krischer, Lion; Gokhberg, Alexey; Vallée, Martin; Fichtner, Andreas
• Is Part Of: Journal of geophysical research. Volume 128:Issue 1(2023)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-28
• Subjects: source inversion -- centroid‐moment tensor -- seismic tomography -- Bayesian inference -- Hamiltonian Monte Carlo -- non‐double‐couple components; Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1029/2022JB024231
• Languages: English
• ISSNs: 2169-9313

Abstract

Abstract: 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 islands. 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 13 M w 4.8– M w 5.3 offshore earthquakes with a significant non‐double‐couple (non‐DC) 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 and 50 s. Accounting for 3‐D Earth structure at shorter periods can increase the double‐couple (DC) component of an event, compared to the GCMT solution, by tens of percent. This suggests that non‐DC events in the GCMT catalog may result from unmodeled Earth structure and the related limitation to longer‐period data. We also observe that significant changes in source parameters, and the DC 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. Plain Language Summary: In the majority of global earthquake catalogs, the earthquake solution, that is, centroid location, time and a rupture mechanism, is typically inferred assuming a 1‐D Earth model. However, both earthquake source and Earth structure contribute to seismic recordings, meaning that unaccounted structure might map into and pollute the source solution. In this study we use a 3‐D Earth structure of the Japanese islands to model the waveforms and infer earthquake parameters of 13 small‐to‐moderate magnitude offshore events. We do not put any a priori constraints on the faulting mechanism and let it be determined by the data. We perform stochastic inversions, which provide us with a collection of all plausible models ranked by their respective probability. When a 3‐D Earth structure at shorter periods is taken into account, the earthquake mechanisms, investigated in this study, can be largely explained by a slip on the fault. We also observe that significant changes in source parameters may be related to tiny waveform changes, thereby accentuating the importance of a reliable Earth model. Key Points: Full‐waveform inversion models enable the use of shorter‐period data in earthquake source inversion Using regional waveforms at 15 s period may reduce non‐double‐couple components by tens of percent Probability densities of source parameters below 20 s are non‐Gaussian, thus demanding stochastic inversion approaches