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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. Secondly, 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 per cent 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 favour tremor activity. [ABSTRACT FROM AUTHOR]

This study presents an approach to better characterize the P‐wave and S‐wave velocity structure of the seafloor sediment layer using ocean bottom seismometers. The presence of low‐velocity seafloor sediment layers influences the observed seismic record at the seafloor over a broad frequency range, such that detailed knowledge of this sediment structure is essential to predict its effect on teleseismic records. We use the radial component of teleseismic P waves and autocorrelation functions of the radial, vertical, and pressure components of teleseismic P and S waves to obtain sediment layer models using the Markov chain Monte Carlo approach with parallel tempering. Synthetic tests show that the body waves constrain the P‐ and S‐wave impedances and travel times and the P‐ to S‐wave velocity ratio of the sediment layers. The proposed method resolves thin layers at a high resolution, including the uppermost thin (∼50 m to a few hundred meters) low S‐wave velocity layer. Real data applications at sites across the Pacific Ocean that are coincident with previous in situ studies demonstrate the effectiveness of this method in characterizing the seafloor sediment unit. The sediment models characterized by this new approach will allow us to more accurately predict and correct the effects of sediment layers in generating P‐ and S‐wave reverberations. Plain Language Summary: Ocean bottom seismometers are powerful tools for investigating the detailed structure of the oceanic mantle. However, most ocean bottom seismometers are placed above the low‐velocity water‐saturated sediment layer, such that their seismic records are inevitably affected by this seafloor sediment layer. Detailed constraints on the structure of the seafloor sediment layer allow us to accurately predict its effects on the observed seismic records. The seafloor sediment layer may consist of multiple discontinuities and vary regionally. This study proposes a new approach for characterizing the seismic properties of the seafloor sediment layer using teleseismic body waves recorded at ocean bottom seismometers. Synthetic tests show that the method can resolve thin sublayers within the sediment layer, such as a very thin low shear‐wave velocity layer and sharp seismic velocity jumps. Real data applications show that the sediment models obtained using this approach are in good agreement with those obtained from direct measurements and previous body‐wave analyses. Our proposed method will enable more detailed prediction and correction of the influence of the sediment layer on ocean bottom seismometer records, thereby providing more accurate constraints on deeper Earth structures. Key Points: The seismic properties of the seafloor sediment layer are characterized using ocean bottom seismometer teleseismic body‐wave recordsThe P‐ and S‐wave impedances and travel times and the VP/VS values of each sublayer within the sediment layer are resolvedIn situ seafloor sediment structure constraints will enable accurate correction and prediction of shallow structure effects [ABSTRACT FROM AUTHOR]

We derive the 3‐D S‐wave velocity structures of sediments and upper crust in the region off Ibaraki at Japan Trench subduction zone by applying ambient noise tomography to a dense array of short‐period ocean bottom seismometers (OBSs). The cross‐spectra were calculated using 27 or 142‐day continuous seismic data, and the phase velocities of the fundamental and the first‐higher Rayleigh wave modes are obtained in the frequency ranges of 0.1–0.25 Hz and 0.17–0.3 Hz, respectively. Our 1‐D S‐wave velocity inversion based on the trans‐dimensional Markov chain Monte Carlo method revealed multiple sedimentary layers above the acoustic basement and the upper crustal structure. The 1‐D structure was then used as a reference model to conduct ambient noise tomography and non‐linear inversion of the 3‐D S‐wave velocity structure by collecting data of the local 1‐D S‐wave velocity structure. Our 3‐D S‐wave velocity structure revealed three main points: (a) The acoustic basement is situated at a depth of ∼4 km depth; (b) the crustal structure is more complex than that of the sedimentary layers; and (c) the southern region has a complex crustal structure in which subducting seamounts were identified by previous P‐wave velocity tomographies. Plain Language Summary: Ambient noise tomography is a powerful tool to reveal seismic S‐wave velocity structure that provides important information for understanding the lithology, deformation, and earthquake processes of subduction zones. We applied the ambient noise tomography to a dense array of short‐period ocean bottom seismometers and obtained 3‐D S‐wave velocity structure of both the sediments and the upper crust in the region off Ibaraki at the Japan Trench subduction zone where a subducted seamount has been identified at 10–15 km depth. We obtained the phase velocities of the fundamental and the first‐higher Rayleigh wave modes in the frequency ranges of 0.1–0.25 Hz and 0.17–0.3 Hz, respectively. We performed inversion based on the trans‐dimensional Markov chain Monte Carlo method to obtain an initial averaged 1‐D S‐wave velocity structure with multiple sedimentary layers. The final 3‐D S‐wave velocity was obtained as the compilation of 1‐D structures adjusted for local heterogeneity through non‐linear inversion. Its structural features are summarized as (a) the acoustic basement is situated at ∼4 km depth, (b) the crustal structure is more complex than the sedimentary layers, and (c) the southern region has a complex crustal structure that may be caused by seamount subduction. Key Points: A 3‐D S‐wave velocity structure of sediments and upper crust is derived by applying ambient noise tomography using ocean bottom seismometers (OBS) data at 0.1–0.3 HzMulti‐mode Rayleigh wave analysis utilizing the Markov chain Monte Carlo method provides high‐resolution velocity structure of sediments and upper crustDense short‐period OBS array with station intervals of 6 km enables us to include high‐frequency components in the ambient noise analysis [ABSTRACT FROM AUTHOR]

Receiver functions, calculated by deconvolving P (or vertical) component records of teleseismic waveforms from the corresponding SV (or radial) components, have been widely used to obtain receiver‐side Green's functions in an approximate form. Conventional receiver function methods, however, often fail due to numerical instability of the deconvolution and strong multiples on the P components. These problems become severe when analyzing in high frequency and using data from ocean bottom seismometers (OBSs). We present a novel technique to estimate Green's functions of receiver‐side structure from teleseismic P waveforms. In this method, two components of Green's functions, which are assumed to form a series of pulses, are directly related in a single equation without explicit deconvolution. Based on the equation, we construct posterior probability distributions regarding the number of pulses, their timing, and amplitudes within a transdimensional Bayesian framework. A reversible‐jump Markov chain Monte Carlo method is used for this purpose, and we further utilize a parallel tempering method to achieve rapid convergence. Synthetic tests and application to an OBS installed at the Yamato Basin, the Sea of Japan, show that the proposed method can estimate radial‐component Green's functions more accurately than conventional receiver function methods. We suggest that the high‐frequency Green's functions estimated by the new method can be used to reveal fine‐scale (in order ~100 m) structure of the seafloor sediment. Plain Language Summary: The receiver function is a popular tool in geophysics. It extracts useful signals from the waves of distant earthquakes to investigate the Earth's subsurface structures. However, computing receiver functions is difficult under certain conditions; (1) when working with high‐frequency waves, the receiver function method becomes unstable; (2) when working with data from the ocean bottom or sedimentary basins, strong reverberations within the sediment or from the ocean surface are troublesome. This study provides a new technique that can clear these issues, making use of advanced statistical methods. We demonstrate its advantage over the conventional receiver function methods through both simulations and a real application to an ocean bottom seismometer. We suggest that the new method has the potential to reveal fine‐scale Earth structure even beneath the seafloor. Key Points: We propose a method that estimates Green's functions of receiver‐side structure from teleseismic waveforms by transdimensional inversionThe new method does not require deconvolution and is suited to the analysis of challenging (e.g., high frequency or offshore) data setsWe demonstrate the advantage of the new method through synthetic tests and the application to real offshore data [ABSTRACT FROM AUTHOR]