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This paper presents empirical models for the frequency content parameters of offshore ground motions in the Japan Trench area based on the S-net dataset, comprising 6,436 recordings from 496 events. Significant variations in frequency content among shallow crustal, upper-mantle, subduction interface and subducting slab are revealed. Empirical models for To, Tavg, and Tm are proposed, considering moment magnitude, source distance, focal depth, and tectonic types. A comparative analysis with four existing land models highlights differences. Total residual results indicate that land models, based on shallow crustal datasets, tend to overestimate observed frequency content parameters in the Japan Trench area. [ABSTRACT FROM AUTHOR]

S-net is a large-scale seafloor observation network for earthquakes and tsunamis around the Japan Trench, consisting of 150 observatories equipped with seismometers and pressure gauges. The sensors have been set up inside cylindrical pressure vessels, which have been buried in the shallow-water regions (water depth <1,500 m), while the vessels have been laid freely on the seafloor in the deeper-water regions. Previous studies showed that the cylindrical pressure vessels rotate during strong shakings due to poor coupling with the seabed sediments, thus making it difficult to retrieve the actual ground motions. We investigated the static changes in the orientations of S-net accelerometers due to shakings from 1,878 earthquakes of Mj greater than 4 that occurred around the network, and found that rotations as large values as 16° were observed during the 2022,Mj 7.4, off-Fukushima Prefecture earthquake. We estimated the threshold acceleration levels after which the sensors are likely to rotate at all S-net stations separately and found that the threshold values lie mostly between 5 and 50 cm/s². Finally, we discussed the observed peak accelerations and velocities at the S-net stations with those recorded on land, where high-quality records were obtained, during the 2022, Mj 7.4 earthquake, which was also the largest magnitude earthquake to occur in the region after the network commenced operation. The results presented herein complement several previous studies and form the basis for more comprehensive future investigations. [ABSTRACT FROM AUTHOR]

Abstract The 2022 eruption of the Hunga Tonga-Hunga Ha'apai volcano excited an atmospheric Lamb wave, which induced a fast-traveling tsunami. This tsunami was driven by the pressure-forced wave traveling at the speed of the Lamb wave and, thus, was much faster than conventional tsunamis. This was the first case in which ocean bottom monitoring systems widely observed an air pressure-induced tsunami. We found that the pressure-forced waves split and generated ocean gravity waves after passing the Japan Trench based on the S-net data. Our simulations show that changes in water depth can amplify or decrease the pressure-forced wave. Simultaneously, an ocean gravity wave is generated due to the conservation of water volume. Because the ocean gravity wave was slower than the pressure-forced wave near Japan, it was separated from, and traveled behind, the pressure-forced wave. We explained the wave separation phenomenon and reproduced the waveforms of different splitting stages observed by the stations near the Japan Trench. Graphical Abstract

Abstract S-net is a large-scale ocean bottom (OB) network in the Japan Trench area, consisting of inline-type 150 observatories equipped with seismometers and pressure gauges. Among them, 41 observatories have been buried about one meter beneath the seafloors in the shallow water regions (water depth

Abstract Long-term continuous observation of seafloor pressure is effective for detecting seafloor vertical deformations that are associated with transient tectonic phenomena such as slow slip events. Since the aseismic slip event prior to the 2011 Tohoku earthquake, several discoveries have been made on spontaneous slow slip events and various other types of slow earthquake along the Japan and Kuril Trenches. Seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net) is expected to provide invaluable information on slow slip activities via geodetic signals that are detected by pressure observation. This study inspects the quality of the S-net pressure data in view of seafloor geodesy by comparison with records obtained by more than 100 autonomous ocean bottom pressure recorders (OBPRs) deployed along the Japan Trench. OBPRs have long been standard tools in seafloor geodesy, and the data collected are considered a benchmark in terms of quality. Most of the S-net stations showed noise levels that are considerably higher than those of the OBPRs over periods of more than 2 d. We speculate that a strong correlation between pressure and temperature accounts for much of the long-term noise. In this study, the temperature-dependent fluctuation component was estimated by prediction filtering and removed from the original data, leading to a significant reduction in the noise level at 51 stations, which reached levels almost equivalent to those of OBPRs. Although no significant pressure changes have been identified as associated with the 2018 Boso SSE or repeated tremor bursts in the northern Japan Trench thus far, our findings indicate that these stations are sufficiently sensitive to detect slow slip events occurring nearby.

The 2022 eruption of the Hunga Tonga-Hunga Ha'apai volcano excited an atmospheric Lamb wave, which induced a fast-traveling tsunami. This tsunami was driven by the pressure-forced wave traveling at the speed of the Lamb wave and, thus, was much faster than conventional tsunamis. This was the first case in which ocean bottom monitoring systems widely observed an air pressure-induced tsunami. We found that the pressure-forced waves split and generated ocean gravity waves after passing the Japan Trench based on the S-net data. Our simulations show that changes in water depth can amplify or decrease the pressure-forced wave. Simultaneously, an ocean gravity wave is generated due to the conservation of water volume. Because the ocean gravity wave was slower than the pressure-forced wave near Japan, it was separated from, and traveled behind, the pressure-forced wave. We explained the wave separation phenomenon and reproduced the waveforms of different splitting stages observed by the stations near the Japan Trench. [ABSTRACT FROM AUTHOR]

S-net is a large-scale ocean bottom (OB) network in the Japan Trench area, consisting of inline-type 150 observatories equipped with seismometers and pressure gauges. Among them, 41 observatories have been buried about one meter beneath the seafloors in the shallow water regions (water depth <1500 m). We analyzed the strong-motion data recorded at the S-net sites from earthquakes with magnitudes 3.5 < Mw ≤ 7 and focal depths < 70 km to understand the site amplification effect on the recorded motions. We used the spectral inversion technique and obtained some fundamental properties of the earthquake source spectra, path attenuation, and site factors from the horizontal-component S-wave portions of the recordings. We obtained that the source spectra followed the ω - 2 source model generally well, and the estimated magnitudes were mostly within ± 0.3 magnitude units of the catalog magnitudes. The stress drops increased systematically with the focal depths, and the values for the shallow earthquakes in the Pacific Plate were higher than those for the interplate earthquakes with comparable focal depths. The path-averaged quality factors were generally frequency-dependent and were somewhat larger than those in the past studies. The peak site frequencies ranged between about 0.2 and 10 Hz, while the peak amplification factors ranged between 10 and 50. Even though the peak frequencies and amplification factors differed from site to site, the peak frequencies were mostly higher than 2 Hz at the outer trench stations, while they were lower than 2 Hz at many inner trench stations. The amplification factors at a few OB sites in the shallow water regions were comparable with the theoretical ones computed from the 1-D subsea model. The amplification factors at intermediate frequencies (~ 0.3 to 2 Hz) generally increased with P-wave travel time in the sediments estimated from the multi-channel seismic survey. At about 20% of the sites (mainly at the unburied stations), spurious site spectra were recognized at frequencies higher than about 4 Hz. If the site spectra between 4 and 10 Hz are required, using only the X-component records is recommended. [ABSTRACT FROM AUTHOR]

Rupture directions and directivity effects of moderate‐sized intraslab and interplate earthquakes off the coast of Fukushima Prefecture were estimated using seafloor S‐net records and onshore K‐NET and KiK‐net records. The azimuthal dependance of the source spectral ratio of each earthquake relative to a reference earthquake observed at the same station was modeled based on a ω−2 model assuming unilateral rupture. The azimuthal dependance of the source spectral ratio observed for most earthquakes reached a maximum at 2–3 Hz and weakened at higher and lower frequencies. The rupture directivity effect contributes to stations located up to the maximum hypocentral distance of 150 km used in this study. All four down‐dip compressional intraslab earthquakes were estimated to rupture toward the up‐dip, i.e., the land. In addition, the six interplate earthquakes were estimated to rupture either up‐dip or in the opposite direction of the strikes, i.e., between south and southeast directions. Only one interplate earthquake was estimated to rupture down‐dip, i.e., toward the land. In the case of intraslab earthquakes, the regions of large radiation patterns and large rupture directivity overlap in the onshore coastal area. Therefore, when only onshore records were used, the estimates of short‐period spectral levels were biased. [ABSTRACT FROM AUTHOR]

In this paper, we investigated the characteristics of nonlinear site response (NLSR) at 23 S-net seafloor sites using strong-motion records obtained during three Mw 7 class earthquakes that occurred directly beneath the network. During the earthquakes, horizontal peak accelerations as large values as 1,400 and 1700 cm/s2 were recorded at the land (KiK-net) and S-net stations, respectively. The S-net is a large-scale inline-type seafloor observation network for earthquake and tsunami in the Japan Trench area. Characterization of NLSR is important because, in most common cases, it can cause a reduction of higher frequency components and a shift of predominant site frequency to lower one. Obtaining high-quality strong-motion records at seafloor sites is extremely difficult and expensive. Some of the records from the three earthquakes used in this study were contaminated by the rotations of the sensor houses, resulting in the ramps and offsets after the arrival of strong S-wave phases. We used a time window of 10 s starting from the S-wave onset, that avoided the ramps and offsets mostly. Using the horizontal-to-vertical spectral ratio (HVSR) technique, we found that the selected S-net sites might have experienced substantial degrees of NLSR during the three earthquakes with peak accelerations greater than about 60 cm/s2. To investigate that the obtained features of NLSR were realistic or not at the S-net sites, we examined the NLSR at nine KiK-net sites on land where high-quality strong-motion records were obtained. We found that the KiK-net sites experienced various degrees of NLSR during the three earthquakes, and the obtained characteristics of NLSR at the KiK-net and S-net sites were comparable. We found that the NLSR affected the ground motions at frequencies mainly higher than 1 Hz at both Kik-net and S-net sites. Despite these similarities, by analyzing the spectral ratios between two horizontal component records, we suspected that the induced rotations contributed to some extent in exaggerating the degree of NLSR at the S-net sites, primarily when the components perpendicular to the cable axes were used. We concluded that consideration of induced rotational effects is necessary to understand the NLSR at the S-net sites better.

Abstract Rupture directions and directivity effects of moderate‐sized intraslab and interplate earthquakes off the coast of Fukushima Prefecture were estimated using seafloor S‐net records and onshore K‐NET and KiK‐net records. The azimuthal dependance of the source spectral ratio of each earthquake relative to a reference earthquake observed at the same station was modeled based on a ω−2 model assuming unilateral rupture. The azimuthal dependance of the source spectral ratio observed for most earthquakes reached a maximum at 2–3 Hz and weakened at higher and lower frequencies. The rupture directivity effect contributes to stations located up to the maximum hypocentral distance of 150 km used in this study. All four down‐dip compressional intraslab earthquakes were estimated to rupture toward the up‐dip, i.e., the land. In addition, the six interplate earthquakes were estimated to rupture either up‐dip or in the opposite direction of the strikes, i.e., between south and southeast directions. Only one interplate earthquake was estimated to rupture down‐dip, i.e., toward the land. In the case of intraslab earthquakes, the regions of large radiation patterns and large rupture directivity overlap in the onshore coastal area. Therefore, when only onshore records were used, the estimates of short‐period spectral levels were biased.

Long-term continuous observation of seafloor pressure is effective for detecting seafloor vertical deformations that are associated with transient tectonic phenomena such as slow slip events. Since the aseismic slip event prior to the 2011 Tohoku earthquake, several discoveries have been made on spontaneous slow slip events and various other types of slow earthquake along the Japan and Kuril Trenches. Seafloor observation network for earthquakes and tsunamis along the Japan Trench (S-net) is expected to provide invaluable information on slow slip activities via geodetic signals that are detected by pressure observation. This study inspects the quality of the S-net pressure data in view of seafloor geodesy by comparison with records obtained by more than 100 autonomous ocean bottom pressure recorders (OBPRs) deployed along the Japan Trench. OBPRs have long been standard tools in seafloor geodesy, and the data collected are considered a benchmark in terms of quality. Most of the S-net stations showed noise levels that are considerably higher than those of the OBPRs over periods of more than 2 d. We speculate that a strong correlation between pressure and temperature accounts for much of the long-term noise. In this study, the temperature-dependent fluctuation component was estimated by prediction filtering and removed from the original data, leading to a significant reduction in the noise level at 51 stations, which reached levels almost equivalent to those of OBPRs. Although no significant pressure changes have been identified as associated with the 2018 Boso SSE or repeated tremor bursts in the northern Japan Trench thus far, our findings indicate that these stations are sufficiently sensitive to detect slow slip events occurring nearby. [ABSTRACT FROM AUTHOR]

Abstract Low-frequency tremors have been widely detected in many tectonic zones, and are often located adjacent to megathrust zones, indicating that their spatiotemporal evolution provides important insights into megathrust events. The envelope correlation method (ECM) is commonly used to detect tremors. However, the ECM also detects regular earthquakes, which requires the separation of these two signals after the initial detection. In addition, signals of tremors are weak, so classifying tremors from noises is also an essential problem. We develop a convolutional neural network (CNN)-based method using a single S-net station located off Sanriku region, Northeast Japan, to classify local earthquakes, tremors, and noise. Along the Japan Trench, especially in a region focused in this study, local earthquakes and tremors occurred in coexistence within a small region, so detection, location, and discrimination of these events are the key to understand the relationship between slow and regular earthquakes. The spectrograms of the three-component velocity waveforms that were recorded during 16 August 2016 to 14 August 2018 are used as the training and test datasets for the CNN. The CNN successfully classified 100%, 96%, and 98% of the earthquakes, tremors, and noise, respectively. We also showed a successful application of our method to continuous waveform data including a tremor to explore the feasibility of the proposed method in classifying tremors and noise in continuous streaming data. The output probabilities for the true classifications decrease with increasing epicentral distance and/or decreasing event magnitude. This highlights the need to train the CNN using tremors proximal to the seismic stations for detecting tremors using multiple stations.

Abstract The Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench (S-net) is presently the world’s largest network of ocean bottom pressure sensors for real-time tsunami monitoring. This paper analyzes the efficacy of such a vast system in tsunami forecasting through exhaustive synthetic experiments. We consider 1500 hypothetical tsunami scenarios from megathrust earthquakes with magnitudes ranging from Mw 7.7–9.1. We employ a stochastic slip model to emulate heterogeneous slip patterns on specified 240 subfaults over the plate interface of the Japan Trench subduction zone and its vicinity. Subsequently, the associated tsunamis in terms of maximum coastal tsunami heights are evaluated along the 50-m isobath by means of a Green’s function summation. To produce tsunami forecasts, we utilize a tsunami inversion from virtually observed waveforms at the S-net stations. Remarkably, forecasts accuracy of approximately 99% can be achieved using tsunami data within an interval of 3 to 5 min after the earthquake (2-min length), owing to the exceedingly dense observation points. Additionally, we apply an optimization technique to determine the optimal combination of stations with respect to earthquake magnitudes. The results show that the minimum requisite number of stations to maintain the accuracy attained by the existing network configuration decreases from 130 to 90 when the earthquake size increases from Mw 7.7 to 9.1.

This study reports an ocean‐bottom pressure gauge (OBP) network, S‐net, which captured meteotsunamis with amplitudes as small as a few cm, and investigates its validity and limitation for meteotsunami research studies through data analyses and numerical simulations. On July 1, 2020, S‐net recorded tsunami‐like signals, although no earthquake was reported. These waves, propagating northward with a velocity of ∼110 m/s, were explained by an atmospheric low pressure with a maximum amplitude of −0.5 ± 0.1 hPa moving northeastward at a speed of 45–50 m/s. The maximum amplitudes of the sea‐surface height during the low‐pressure passing were up to twice larger than those directly converted from the ocean‐bottom pressure without considering the effect of the atmospheric pressure. Our results suggest that the S‐net with numerical simulations can detect the generation and propagation of meteotsunamis, which could not be achieved in the past when dense OBP networks were not available. Plain Language Summary: Recent developments in deep‐ocean tsunami observation networks using ocean‐bottom pressure gauge sensors have been remarkable, which have an advantage of continuously monitoring the ocean. On July 1, 2020, a deep‐ocean observation network off eastern Japan, S‐net, recorded small tsunami‐like ocean waves. Although tsunamis are often excited by earthquakes, no earthquake was reported at that time. We investigated the observed feature of these waves, which suggests that the waves were meteorological tsunamis, or meteotsunamis, originating from an atmospheric pressure disturbance. To investigate the behavior of these waves in detail, we conducted numerical meteotsunami simulations. The maximum amplitudes of the sea‐surface height during the atmospheric low‐pressure passing were up to twice larger than those expected from the observed seafloor pressure change without considering the contribution of the atmospheric pressure disturbance. We demonstrated that analyzing the data from the wide and dense array of S‐net made it possible to understand the behavior of the meteotsunamis in detail, which could not be achieved in the past when only a few pressure gauges were available. The S‐net's continuous monitoring of the seafloor pressure in the deep ocean will contribute to deepening our understanding of oceanography and meteorology. Key Points: Deep‐ocean pressure gauge array observation off NE Japan detected nonseismic tsunami‐like pressure signals with amplitudes of several hPaA numerical simulation revealed that the signals were meteotsunamis related to a northeastward‐moving atmospheric low pressureIt is necessary to consider the effects of the atmospheric pressure to appropriately estimate sea‐surface height from seafloor pressure gauge [ABSTRACT FROM AUTHOR]

Low-frequency tremors have been widely detected in many tectonic zones, and are often located adjacent to megathrust zones, indicating that their spatiotemporal evolution provides important insights into megathrust events. The envelope correlation method (ECM) is commonly used to detect tremors. However, the ECM also detects regular earthquakes, which requires the separation of these two signals after the initial detection. In addition, signals of tremors are weak, so classifying tremors from noises is also an essential problem. We develop a convolutional neural network (CNN)-based method using a single S-net station located off Sanriku region, Northeast Japan, to classify local earthquakes, tremors, and noise. Along the Japan Trench, especially in a region focused in this study, local earthquakes and tremors occurred in coexistence within a small region, so detection, location, and discrimination of these events are the key to understand the relationship between slow and regular earthquakes. The spectrograms of the three-component velocity waveforms that were recorded during 16 August 2016 to 14 August 2018 are used as the training and test datasets for the CNN. The CNN successfully classified 100%, 96%, and 98% of the earthquakes, tremors, and noise, respectively. We also showed a successful application of our method to continuous waveform data including a tremor to explore the feasibility of the proposed method in classifying tremors and noise in continuous streaming data. The output probabilities for the true classifications decrease with increasing epicentral distance and/or decreasing event magnitude. This highlights the need to train the CNN using tremors proximal to the seismic stations for detecting tremors using multiple stations. [ABSTRACT FROM AUTHOR]

Tsunamis with amplitudes of up to 40 cm, related to the Mw 7.1 normal‐faulting earthquake off Fukushima, Japan, on November 21, 2016, were clearly recorded by a new offshore wide and dense ocean‐bottom pressure gauge network, S‐net, with high azimuthal coverage located closer to the focal area. We processed the S‐net data and found some stations included the tsunami‐irrelevant drift and step signals. We analyzed the S‐net data to infer the tsunami source distribution. A subsidence region with a narrow spatial extent (∼40 km) and a large peak (∼200 cm) was obtained. The other near‐coastal waveforms not used for the inversion analysis were also reproduced very well. Our fault model suggests the maximum stress drop across the fault plane of >∼10 MPa and the average of 4.2 MPa, whereas the shear stress increase along the fault caused by the 2011 Tohoku earthquake was only ∼2 MPa. Past studies have suggested that horizontal compressional stress around this region switched to horizontal extensional stress after the Tohoku earthquake due to its stress perturbation. The present result, however, suggests that the horizontal extensional stress was locally predominant at the shallowest surface around the focal area even before 2011. The present study demonstrates that the S‐net high‐azimuthal‐coverage pressure data provide a significant constraint on the fault modeling, which enables us to discuss the stress regime within the overriding plate at the offshore. Our analysis provides an implication for crustal stress states, which is important for understanding generation mechanisms of intraplate earthquakes. Plain Language Summary: On November 21, 2016 (UTC), a large earthquake occurred within the continental plate off Fukushima, Japan, and a new seafloor tsunami network, S‐net, recorded its tsunamis with much higher azimuthal coverage and with shorter epicentral distance than any of the previous networks. We analyzed the S‐net data to reveal the rupture process of this earthquake. Our result explained all of the S‐net data and the other tsunami network data very well. According to past studies, the continental plate in northeastern Japan was under horizontal compression before the 2011 Tohoku earthquake due to the pushing force by the subducting oceanic plate. However, our rupture modeling result suggested that the plate around the earthquake rupture area was horizontally stretched even before the Tohoku earthquake, so that the off‐Fukushima earthquake occurred. Our study demonstrated that the S‐net, which has high spatial coverage, makes it possible to reveal the rupture model of offshore earthquakes, which was difficult in the past before S‐net became available. The S‐net will also enable us to discuss the impact of the Tohoku earthquake on the crustal stress, which is necessary for understanding the earthquake generation mechanics. Key Points: Tsunamis due to the 2016 off‐Fukushima shallow normal‐faulting earthquake were observed by the S‐net wide and dense pressure gauge networkUse of the near field and the high‐coverage array significantly improved the constraint of the fault modeling of the 2016 earthquakeHorizontal extensional stress predominant even before the 2011 Tohoku earthquake should be the main cause of the earthquake and tsunami [ABSTRACT FROM AUTHOR]

Abstract We have identified “N”-shaped Y/X amplitude spectral ratios in S-coda records from a significant number of OBSs (ocean bottom seismometers) belonging to in-line-type ocean bottom networks of S-net and ETMC deployed around the Japan Trench and Sagami Trough, respectively. The “N”-shape reflects a sharp peak and notch at approximately 5–13 Hz and 10–23 Hz, respectively. This shape does not characterize OBSs belonging to node-type ocean bottom network of DONET deployed near the Nankai Trough. For S-net stations, the “N”-shape is not clearly formed for stations installed within grooves dug in the seafloor. We interpret the “N”-shaped Y/X amplitude spectral ratio is caused by the natural vibrations of a cylindrical pressure vessel that is placed sideways (long-axis lies in the horizontal plane) on the seafloor. The notch and peak frequencies in the Y/X amplitude spectral ratio likely correspond to natural frequencies of longitudinal (X-direction) and torsional and/or bending (Y-direction) vibrations, respectively. These natural vibrations are not observed for buried OBSs or those installed within grooves in the seafloor probably because they are better coupled to the seafloor. We propose a simple model to evaluate the extent to which the peak and notch have formed, which depends on the natural frequencies and coupling of the pressure vessel. We suggest users of in-line-type OBSs carefully examine if there are different responses between the X and Y components when frequencies about > 3 Hz are used. When installing OBS networks in the future, installing OBSs and cables within grooves dug in the seafloor or by burial will be effective in suppressing such natural vibrations.

We analyzed strong-motion records at the ground and borehole in and around the Kanto Basin and the seafloor in the Japan Trench area from three nearby offshore earthquakes of similar magnitudes (Mw 5.8–5.9). The seafloor strong-motion records were obtained from S-net, which was established to enhance tsunami and earthquake early warnings after the 2011 great Tohoku-oki earthquake disaster. The borehole records were obtained from MeSO-net, a dense network of seismometers installed at a depth of 20 m in the Tokyo metropolitan area. The ground records were obtained from the K-NET and KiK-net networks, established after the 1995 great Hanshin-Awaji earthquake disaster. The MeSO-net and S-net stations record the shakings continuously, while the K-NET and KiK-net records are based on triggering thresholds. It is crucial to evaluate the properties of strong motions recorded by the S-net for earthquake early warning (EEW). This paper compared the peak ground accelerations (PGAs) and peak ground velocities (PGVs) between the S-net and K-NET/KiK-net stations. Because the MeSO-net records were from the borehole, we compared the PGAs and significant durations of the low-frequency motions (0.1–0.5 Hz) between the S-net and MeSO-net stations from identical record lengths. We found that the horizontal PGAs and PGVs at the S-net sites were similar to or larger than the K-NET/KiK-net sites for the S wave. In contrast, the vertical PGAs and PGVs at the S-net sites were similar to or smaller than those at the K-NET/KiK-net sites for the S wave. Particularly, the PGAs and PGVs for the P-wave parts on the vertical-component records of S-net were, on average, much smaller than those of K-NET/KiK-net records. The difference was more evident in the PGAs. The average ratios of S-wave horizontal to vertical PGAs were about 2.5 and 5 for the land and S-net sites, respectively. The low-frequency PGAs at the S-net sites were similar to or larger than those of the MeSO-net borehole records. The significant durations between the two-networks low-frequency records were generally comparable. Quantification of the results from a larger dataset may contribute to ground-motion prediction for EEW and the design of the offshore facilities.

The Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench (S-net) is presently the world's largest network of ocean bottom pressure sensors for real-time tsunami monitoring. This paper analyzes the efficacy of such a vast system in tsunami forecasting through exhaustive synthetic experiments. We consider 1500 hypothetical tsunami scenarios from megathrust earthquakes with magnitudes ranging from Mw 7.7–9.1. We employ a stochastic slip model to emulate heterogeneous slip patterns on specified 240 subfaults over the plate interface of the Japan Trench subduction zone and its vicinity. Subsequently, the associated tsunamis in terms of maximum coastal tsunami heights are evaluated along the 50-m isobath by means of a Green's function summation. To produce tsunami forecasts, we utilize a tsunami inversion from virtually observed waveforms at the S-net stations. Remarkably, forecasts accuracy of approximately 99% can be achieved using tsunami data within an interval of 3 to 5 min after the earthquake (2-min length), owing to the exceedingly dense observation points. Additionally, we apply an optimization technique to determine the optimal combination of stations with respect to earthquake magnitudes. The results show that the minimum requisite number of stations to maintain the accuracy attained by the existing network configuration decreases from 130 to 90 when the earthquake size increases from Mw 7.7 to 9.1. [ABSTRACT FROM AUTHOR]

Abstract A new dense and widely distributed tsunami observation network installed off northeast Japan detected millimeter‐scale tsunamis from an Mw 6.0 shallow interplate earthquake on 20 August 2016. Based on the fault model deduced from this data set, we obtained a stress drop of 1.5 MPa for this event, similar to those associated with typical interplate earthquakes. The rupture area was unlikely to overlap with regions where slow earthquakes occur, such as low‐frequency‐tremors and very‐low‐frequency‐earthquakes. The results demonstrated that this new network has dramatically increased the detectability of millimeter‐scale tsunamis. Some near‐source stations were contaminated by large pressure offset signals irrelevant to tsunami, and we must therefore be careful when analyzing these data. Nonetheless, the new array enables estimations of the stress drops of moderate offshore earthquakes and can be used to elucidate the spatial variation of mechanical properties along the plate interface with much higher resolution than previously possible.

A new dense and widely distributed tsunami observation network installed off northeast Japan detected millimeter‐scale tsunamis from an Mw 6.0 shallow interplate earthquake on 20 August 2016. Based on the fault model deduced from this data set, we obtained a stress drop of 1.5 MPa for this event, similar to those associated with typical interplate earthquakes. The rupture area was unlikely to overlap with regions where slow earthquakes occur, such as low‐frequency‐tremors and very‐low‐frequency‐earthquakes. The results demonstrated that this new network has dramatically increased the detectability of millimeter‐scale tsunamis. Some near‐source stations were contaminated by large pressure offset signals irrelevant to tsunami, and we must therefore be careful when analyzing these data. Nonetheless, the new array enables estimations of the stress drops of moderate offshore earthquakes and can be used to elucidate the spatial variation of mechanical properties along the plate interface with much higher resolution than previously possible. Plain Language Summary: Tsunamis are generated when an earthquake occurs beneath the seafloor. Far fewer tsunami observations have been recorded from moderate earthquakes than large to giant earthquakes because tsunamis created by moderate earthquakes have been too small to be observed. On 20 August 2016, a moderate earthquake occurred off Sanriku, in northeastern Japan, and a tsunami with a height of less than 1 cm was recorded by a new seafloor tsunami observation network. This network has many tsunami sensors distributed much closer to each other and over a much wider area than any other previous network in the world. Using these data, this study estimated the source location and size, and the slip amount of the 2016 earthquake with higher accuracy, which was impossible to achieve from past observations because they were too far away from the earthquake and the signals were too small. Using this source information, we could estimate the stress drop associated with the earthquake, which is important because the stress drop information deepens our understanding of how and why earthquakes happen. Key Points: Millimeter‐scale tsunamis from an Mw 6.0 earthquake were captured by the S‐net, a new nationwide pressure gauge array off Sanriku, JapanTsunami signals were identified from the pressure data adjacent to the source, which were contaminated by signals irrelevant to tsunamisWe inferred the stress drop of the earthquake from the tsunami data more reliably than could be done from seismogram analysis [ABSTRACT FROM AUTHOR]

With increasing resource exploitation and engineering construction offshore, the seismic safety of offshore structures has received attention from researchers and designers, and an offshore ground motion prediction model (GMPM) can be used to estimate the possible earthquake response of structures and provide the foundation for seismic fortification of structures. Because there are few strong motion records recorded by offshore stations, there are insufficient empirical data in the magnitude-distance range to directly develop a GMPM using empirical regression techniques. To develop a reliable GMPM for data-poor offshore regions, we used a referenced empirical approach based on an onshore empirical prediction model. We collected 2605 records from 138 crustal earthquake events, 2669 records from 125 slab earthquake events and 5693 records from 267 interface earthquake events recorded by S-net stations. We used the existing Japanese onshore GMPM as a reference model. Then, we analyzed the residuals of the reference model for offshore data and calculated its adjustment factors. Finally, we developed a GMPM for the Japan Trench area and compared it with the existing onshore models. The proposed model fit the data subsets at hypocentral distances of 20–300 km reasonably well. There were different spectral accelerations (SAs) for different source types, with considerably larger SAs for short periods of offshore motions from crustal events than for the motions from the other two types, and the difference becomes more obvious with the increase of magnitude. At short periods, the SAs of the offshore motions from slab events were slightly larger than those of the motions from the interface events. The discrepancy of the offshore and onshore GMPM was significant, and the peak ground accelerations (PGAs) and SAs of the offshore ground motions were apparently greater than those of onshore ground motions of the same magnitude and distance. The offshore GMPM established by the reference empirical approach contribute to studying the characteristics of offshore strong ground motions, and this approach can be applied to data-poor regions. • A regional offshore ground motion prediction model is established based on the referenced empirical approach. • The PGA and spectral accelerations between the offshore and onshore regions are different. • Referenced empirical approach can provide reference for establishing ground motion prediction model in data-poor regions. [ABSTRACT FROM AUTHOR]

We found offshore shallow low‐frequency tremor in the northern Japan Trench subduction zone, using records from the Seafloor Observation Network for Earthquakes and Tsunamis along the Japan Trench. The tremor aligned with a narrow zone, which follows the 10‐ to 25‐km depth contours of the plate interface and occurred in two distinct areas, off Tokachi and Sanriku, separated by a gap. In the 1.75 years examined, two episodes lasting for a few weeks were identified off Tokachi. During these episodes, tremor occurred concurrently with swarms of very low frequency earthquakes and migrated laterally about 120 km along the trench strike. In contrast, tremor off Sanriku lasted shorter (half a day to 5 days) and repeated at shorter intervals (1–4 months). The variation in tremor behavior such as duration, recurrence, migration, and the association with very low frequency earthquakes suggests along‐strike heterogeneities in frictional properties at the shallow plate interface. Plain Language Summary: Low‐frequency tremor has been widely recognized at many subduction zones yet has not been directly measured in the Japan Trench subduction zone in northeastern Japan. Using a newly installed seafloor seismic network, we report for the first time observations of tremor occurring at the shallow subduction plate interface in the northern Japan Trench subduction zone. The observed tremor, localized in the regions off Tokachi and Sanriku, were synchronized in space and time with very low frequency earthquakes and moved across the region during active periods. Tremor off the Tokachi and Sanriku regions had different characteristics, including duration and recurrence time. This difference is likely caused by different frictional properties at the plate interface near the trench. Key Points: We identified offshore shallow low‐frequency tremor parallel to the trench strike in the northern Japan Trench subduction zone using S‐netTremor occurred in the two clusters separated by a gap and coincided with very low frequency earthquakesSpatial differences in tremor behavior imply lateral heterogeneities in frictional properties at the shallow plate interface [ABSTRACT FROM AUTHOR]

It is important to advance preparation for a tsunami disaster, one of the great concerns in Japan. Forecasting tsunami inundation is one such solution, which contributes to perceiving the danger of the tsunami, as the inundation is directly linked with the damage. Therefore, we developed a new real-time tsunami forecast system, aimed at rapidly and accurately forecasting tsunami inundation on land, based on offshore tsunami data observed by the seafloor observation network along the Japan Trench, S-net. The developed system takes a database approach. A database called a tsunami scenario bank was constructed by assuming all the possible tsunami sources affecting the target region and simulating offshore pressure data, coastal tsunami heights, and tsunami inundation. The forecast system searches for suitable tsunami scenarios whose offshore pressure data explain the observed data, based on the multi-index method. The multiindex method can evaluate the resemblance of offshore pressure data by using three indices, which are sensitive to different aspects of the pressure change distribution. When tsunami scenarios meet the criteria of the multi-index method, the system provides forecast information generated from coastal tsunami heights and tsunami inundation of the selected scenarios. A prototype system was constructed for the Pacific coastal region of Chiba prefecture as a target region and has been updated through a test operation. We also investigated the comprehensible visualization and effective disaster response using tsunami forecast information. Through workshops and tabletop exercises with local government officers using the forecast system, timelines and local disaster management plans for tsunamis were tested and revised. This led to the establishment of a standard operating procedure for tsunami disaster response through the use of tsunami observation and forecast information. [ABSTRACT FROM AUTHOR]

Petri net language is a powerful tool for describing dynamic behaviors of physical systems. However, it is not easy to obtain the language expression for a given Petri net especially a structure-complex net. In this paper, we first analyze the behaviors of S-nets, which are structure-simple. With the decomposition method based on a given index function on the place set, a given structure-complex Petri net can be decomposed into a set of structure-simple S-nets. With the language relationships between the original system and the decomposed subnets, an algorithm to obtain the language expression of a given structure-complex net system is presented, which benefits the analysis of physical systems based on the Petri net language. [ABSTRACT FROM AUTHOR]