Locating tectonic tremors with uncertainty estimates: time- and amplitude-difference optimization, wave propagation-based quality control and Bayesian inversion

Abstract

Summary The accurate location of tectonic tremors helps improve understanding of their underlying physical processes. However, current location methods often do not statistically evaluate uncertainties to a satisfactory degree and do not account for potential biases due to subsurface structures not included in the model. To address these issues, we propose a novel three-step process for locating tectonic tremors. First, the measured time- and amplitude differences between station pairs are optimized to obtain station-specific relative time and amplitude measurements with uncertainty estimates. Second, the time– and amplitude–distance relationships in the optimized data are used to roughly estimate the propagation speed (i.e., shear wave velocity) and attenuation strength. Linear regression is applied to each event, and the resulting velocity and attenuation strength are used for quality control. Finally, the tremor location problem is formulated within a Bayesian framework where the model parameters include the source locations, local site delay/amplification factors, shear wave velocity, and attenuation strength. The Markov chain Monte Carlo algorithm is used to sample the posterior probability and is augmented by a parallel tempering scheme for an efficient global search. We tested the proposed method on ocean-bottom data indicating an intense episode of tectonic tremors in Kumano-nada within the Nankai Trough subduction zone. The results show that the range of the 95% confidence interval is typically <7 km horizontally and <10 km vertically. A series of experiments with different inversion settings reveals that adopting amplitude data and site correction factors help reduce random error and systematic bias, respectively. Probabilistic sampling allows us to spatially map the probability of a tremor occurring at a given location. The probability map is used to identify lineaments of tremor sources, which provides insights into structural factors that favor tremor activity.

Revisiting Seismic Energy of Shallow Tremors: Amplifications Due To Site and Propagation Path Effects Near the Nankai Trough

“…The seismic waves from a shallow tremor source were effectively trapped within thick sedimentary layers (Takemura, Yabe, et al, 2020); consequently, the onset of the P-and S-waves became unclear, and strong envelope broadening occurred (Figure 4a). The group velocity of traces at distances ≥20 km fluctuated around 2.3 km/s, which was typically within the velocity range for shallow tremors in this region ( Akuhara et al, 2023). Reverberations within the sedimentary and seawater layers cause unclear onsets of individual phases (Movie S1).…”

Frontal Thrust Ramp‐Up and Slow Earthquakes Due To Underthrusting of Basement High in the Nankai Trough

“…The slow earthquake distribution (mainly tremors) is dense in area IV but gradually decreases westward in area III (Figure 5b). A tremor cluster in 2021 January started around the western margin of this profile after the westward propagation of VLFE and tremors in December 2020 (Akuhara et al., 2023).…”

“…They suggested that the slow earthquakes were caused by the impingement of high relief on the subducting basement, as is inferred in the Hikurangi margin (Saffer & Wallace, 2015). Akuhara et al (2023) analyzed the probability of the location of a new slow earthquake cluster in 2021 January off Kumano Takemura et al, 2022;Tamaribuchi et al, 2022) and suggested that the cluster was located near the deformation front of the accretionary wedge.…”

“…Episodic slow earthquakes take place in the Nankai forearc off‐Kumano, but epicenters of the events, especially their focal depths, are not precise because ocean‐bottom‐seismometer (OBS) deployments are biased on the upper slope with scarce locations outside the trench (e.g., Akuhara et al., 2023; Takemura et al., 2022). Such uncertainty of the focal depth of the slow earthquake makes it difficult to understand their mechanical cause, even though possible factors have been suggested from other indirect information, such as the décollement geometry and the reflective properties of the décollement.…”

“…Akuhara et al. (2023) analyzed the probability of the location of a new slow earthquake cluster in 2021 January off Kumano (Ogiso & Tamaribuchi, 2022; Takemura et al., 2022; Tamaribuchi et al., 2022) and suggested that the cluster was located near the deformation front of the accretionary wedge.…”