Real-Time Tsunami Data Assimilation of S-Net Pressure Gauge Records during the 2016 Fukushima Earthquake

The 2016 Fukushima earthquake (M 7.4) generated a moderate tsunami, which was recorded by the offshore pressure gauges of the Seafloor Observation Network for Earthquakes and Tsunamis (S-net). We used 28 S-net pressure gauge records for tsunami data assimilation and forecasted the tsunami waveforms at four tide gauges on the Sanriku coast. The S-net raw records were processed using two different methods. In the first method, we removed the tidal components by polynomial fitting and applied a low-pass filter. In the second method, we used a real-time tsunami detection algorithm based on ensemble empirical mode decomposition to extract the tsunami signals, imitating real-time operations for tsunami early warning. The forecast accuracy scores of the two detection methods are 60% and 74%, respectively, for a time window of 35 min, but they improve to 89% and 94% if we neglect the stations with imperfect modeling or insufficient offshore observations. Hence, the tsunami data assimilation approach can be put into practice with the help of the real-time tsunami detection algorithm.

Design of a Cabled Seafloor Observatory for Marine Ecological Environment Monitoring

Cabled seafloor in-situ observation systems have drawn much attention in recent years for their capability of facilitating long-term all-weather deep-sea data-intense marine observations. The Penglai in-situ seafloor observation system for ecological environment monitoring is proposed in this paper. The current system consists of an on-shore station, a primary node, and two secondary nodes, but more nodes can be hosted due to its scalability. A looped backbone network connects the on-shore station and primary nodes. Each primary node can host up to four secondary nodes, and each secondary node can host up to eight different sensors. Marine observation data and system work state data are collected and backed up by the on-shore station in a real-time manner. Users can access the ocean observation data via a web page interface. The proposed system has been deployed for more than half a year and will continue to work after that. The field experiment showed that the proposed system worked smoothly in system state monitoring and marine data acquisition. A large amount of oceanographic data with videos has been achieved for future studies.

Synthetic analysis of the efficacy of the S-net system in tsunami forecasting

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.

Hydrothermal fluid ejector for enhanced heat transfer of a thermoelectric power generator on the seafloor

Interest in deep-sea hydrothermal research has been rapidly increasing. Advances in methods for harvesting energy from hydrothermal vents will facilitate long-term seafloor observation systems do not rely on batteries. A...

Ambient noise correlation analysis of S-net records: extracting surface wave signals below instrument noise levels

SUMMARY We applied ambient noise cross-correlation analysis to the cabled ocean bottom seismic network offshore northeast Japan (Seafloor observation network for earthquakes and tsunamis along the Japan Trench: S-net) to extract surface waves propagating in the ocean area of the forearc region. We found two types of peculiar pulses in the cross-correlation functions (CCFs) of ambient seismic noise records: periodic pulses mainly every minute and sharp pulses around the lag time zero. These pulses strongly contaminate the surface wave signals in the CCFs at frequencies below ∼0.1 Hz. The periodic pulses originate from periodic instrument noises, while the zero-lag pulses originate from random instrument noises which are coherent within station pairs. By developing solutions to remove the periodic and zero-lag pulses based on the characteristics of the pulses, we succeeded in extracting Rayleigh and Love wave signals from the S-net records at 0.03–0.3 Hz, while the surface wave signals at 0.03–0.1 Hz were not visible without the application of these solutions. These solutions widen the frequency range of analysis, and may be applicable to other seismic networks, particularly to recent dense but non-broad-band networks. We identified the fundamental and first higher modes of Rayleigh waves and the fundamental mode of the Love wave. The extracted surface wave signals can constrain the shear wave velocity structure from the sediment to seismogenic zone around the megathrust plate boundary in the forearc region.

MOWLAS: NIED observation network for earthquake, tsunami and volcano

National Research Institute for Earth Science and Disaster Resilience (NIED) integrated the land observation networks established since the 1995 Kobe earthquake with the seafloor observation networks established since the 2011 Tohoku earthquake and tsunami as MOWLAS (Monitoring of Waves on Land and Seafloor) in November 2017. The purpose of MOWLAS is to provide comprehensive, accurate, and rapid observation and monitoring of earthquake, tsunami, and volcano events throughout Japan and its offshore areas. MOWLAS data are widely utilized for long-term earthquake forecasting, the monitoring of current seismic activity, seismic and tsunami hazard assessments, earthquake early warning, tsunami warning, and earthquake engineering, as well as earthquake science. Ocean bottom observations provide an extension of observations to areas where no people are living and have the advantage of increasing lead time of earthquake early warning and tsunami warning. The application of recent technology advancements to real-time observations as well as the processing of MOWLAS data has contributed to the direct disaster mitigation of ongoing earthquakes. These observations are fundamental for both science and disaster resilience, and thus it is necessary to continue ceaseless operation and maintenance.

Compact Low-Velocity Ocean Current Energy Harvester Using Magnetic Couplings for Long-Term Scientific Seafloor Observation

A compact low-velocity ocean current energy harvester (LOCH) is developed to power undersea instrument platforms for long-term scientific seafloor observation. Noncontact magnetic couplings are used in the LOCH to eliminate friction and achieve reliable underwater sealing so that the LOCH can adapt the low-velocity ocean current and its energy transmission efficiency can be improved. The parameters of the magnetic couplings are optimized by the three-dimensional finite-element method (3D FEM). A laboratory experiment platform is designed; and the static and dynamic performances of the magnetic couplings with different parameters are tested. The experiment results are compared with computer simulations to verify the optimal parameter design. Finally; a prototype of the LOCH is designed and its underwater experiment proves that it can start smoothly and work stably at a current velocity of as low as 0.4 m/s

Precise Distributed Acoustic Sensing measurements by using seafloor optical fiber cable system for seismic monitoring

<p>Distributed Acoustic Sensing (DAS) measurements which utilize an optical fiber itself as a sensor can be applied for various purposes. An observation of earthquakes using an optical fiber deployed on the seafloor with DAS technology is attractive because DAS measurements enable a dense seismic observation as a long linear array. Spatial resolution of the observation reaches a few meters. The length of the array is determined by the measurement range of the DAS interrogator deployed on the optical fiber, and a fine spatial sensor interval can be configured. DAS measurements have become increasingly accurate and the current state of technology exhibit high signal quality. Because DAS measurement is useful for earthquake observation, there were some trials for an observation of earthquakes using an optical fiber deployed on the land or the seafloor. However, There are few observations using DAS technology on seafloor until the present.</p><p>In 1996, a seafloor seismic tsunami observation system using an optical fiber cable was deployed off the coast of Sanriku by Earthquake Research Institute, the University of Tokyo. The system has three seismic stations and two tsunami-meters, and a length of the cable is approximately 115 km. The system has six spare (dark) optical fibers which are dispersion shifted single mode type, and have been incorporated for future extension of the observation system. We have started development of a seafloor seismic observation system utilizing DAS technology on the Sanriku cable observation system as a next generation of marine seismic observation system. In 2019, we performed DAS measurements using a dark fiber from Sanriku seafloor observation system three times. An interrogator was installed in the cable landing station temporarily. Data were recorded with various values of parameters, such as length of data collection (array aperture), gauge length, ping rate, acquisition offset, for evaluation of data quality and signal to noise ratios. The total recording period for three measurements was approximately three weeks. As a result, many earthquakes including micro-earthquakes were recorded. The obtained data will be used to develop data processing techniques for seismic observations utilizing DAS measurements.</p><p> </p>