Ocean Bottom Pressure Gauges Research Articles

Improving Indonesia's Tsunami Early Warning: Part I: Developing Synthetic Tsunami Scenarios and Initial Deployment

Indonesia's Java subduction zone has triggered devastating tsunamis, emphasizing the need for a robust Tsunami Early Warning System, specifically for Southern Java, Bali, and Nusa Tenggara. With only six Ocean Bottom Pressure Gauges (OBPGs) currently monitoring tsunami propagation in the deep sea, optimized future sensor deployment is crucial. This paper, the first in a two-part series, proposes new observation networks to enhance tsunami early warning system. Our methodology involves developing synthetic stochastic-slip earthquake-induced tsunami simulations, delineating tsunami lead times, and applying empirical orthogonal functions (EOF) to determine spatial modal energy. We also assess the reliability of spacing and bathymetry for potential sensor locations. Our analysis reveals potential locations for additional OBPGs across the area. The proposed network consists of 42 additional sensors, demonstrating the potential for earlier warnings. These findings lay the groundwork for the second part of our series, where we will develop advanced forecasting models incorporating deep learning techniques based on the proposed location and further optimize sensor locations with the novel approach of hybrid optimizer and deep learning model. By establishing an improved observation network, this study contributes to more effective tsunami early warning systems in Indonesia, potentially mitigating the impact of future events on coastal communities.

Harnessing electromagnetic data for tsunami source estimation: a comprehensive review.

Ocean-bottom pressure gauges are widely used for tsunami observations due to their established accuracy and stability. Recent advancements reveal that the magnetic field fluctuates when a large tsunami passes over the ocean, suggesting potential alternatives to pressure gauges in the form of ocean-bottom electromagnetometers (OBEMs). This article offers a comprehensive synthesis of recent findings concerning tsunami magnetic fields and their utility in tsunami source estimation. In addition, we scrutinize the effectiveness of tsunami observations employing OBEMs. Despite the promise of electromagnetometers, it is worth noting that the background noise inherent in electromagnetic observations tends to be approximately 10 times greater than that of pressure observations within the critical tsunami frequency bands. The Earth's magnetic field sporadically disrupts tsunami magnetic fields, presenting a potential limitation to the utility of electromagnetometers in tsunami detection when compared with pressure gauges. Nevertheless, our investigation underscores the potential of electromagnetic observations in detecting tsunamis propagating over the ocean at magnitudes of a few centimetres. An invaluable advantage of electromagnetometers over pressure monitoring lies in their capability to observe tsunami velocity fields, suggesting a promising avenue for further research and development in tsunami observation technology.This article is part of the theme issue 'Magnetometric remote sensing of Earth and planetary oceans'.

Segmented Trapdoor Fault in Kita‐Ioto Caldera, Japan: Insights From Millimeter Tsunami Waves Captured by an Array Network of Ocean Bottom Pressure Gauges

AbstractSubmarine calderas with active magma supply have recently been identified as potential sources of volcanic tsunamis due to sudden meter‐scale uplift by trapdoor faulting, occurring every few years to a decade. These trapdoor uplifts are seismically recorded as non‐double‐couple earthquakes with magnitudes M > 5. Kita‐Ioto Caldera, a submarine caldera in the Izu‐Bonin arc, caused such earthquakes every 2–5 years. Our previous study (Sandanbata & Saito, 2024, https://doi.org/10.1029/2023jb027917) analyzed data from a single ocean bottom pressure (OBP) gauge in the Philippine Sea, confirming trapdoor uplifts during the earthquakes in 2008 and 2015. However, high temporal‐resolution data for the earthquakes in 2017 and 2019 were lost, preventing source mechanism investigation. To address this, we examine OBP data of the two recent earthquakes from the array network of Dense Oceanfloor Network system for Earthquakes and Tsunamis, deployed off the southwestern coast of Japan. Despite the poor signal‐to‐noise ratio in each record, we successfully detect clear tsunami signals associated with the earthquakes using a waveform stacking method, with sea‐surface wave amplitudes of only 1–2 mm. By analyzing the data, we propose source models that represent trapdoor uplifts in the submarine caldera and accurately reproduce the detected tsunami waveforms, confirming the recurrence of trapdoor uplifts. Notably, differences in the tsunami waveforms between the 2017 and 2019 earthquakes suggest that different segments of the intra‐caldera fault system were activated. This segmentation likely influences the recurrence characteristics of the inflation cycle in calderas, which would be a key to understanding the magma accumulation process and assessing the sizes and timings of future trapdoor uplifts.

Estimating Vertical Movement and Slip Distribution During the 2018 Boso, Japan, Slow Slip Event From Ocean Bottom Pressure Gauge Data and an Oceanic Model

AbstractMany slow slip events (SSEs) occur beneath the ocean, and continuous ocean‐bottom pressure gauge (OBP) observations provide useful data. OBPs record both oceanic variations and crustal movements, so we developed a multi‐channel singular spectrum analysis method to remove oceanic variations and applied our method to OBPs and oceanic model data. Then components of the oceanic model with good correlations to the OBP data were subtracted from the observed data. This method compensates for the incompleteness of the oceanic model and removes oceanic variations better than use of the original model. We applied the method to OBP data for the 2018 Boso, Japan, SSE to estimate its slip distribution. Comparing slip distributions obtained with and without the OBP data, we found that the distribution obtained using OBP data extended further offshore, and the offshore estimation error was smaller. Our study shows that offshore observations using OBPs are important for characterizing SSEs.

Modeling the 2022 Tonga Eruption Tsunami Recorded on Ocean Bottom Pressure and Tide Gauges Around the Pacific

AbstractTsunamis generated by the Hunga Tonga–Hunga Ha’apai volcanic eruption on January 15, 2022 were recorded on ocean bottom pressure and tide gauges around the Pacific Ocean, earlier than the expected arrival times calculated by tsunami propagation speed. Atmospheric waves from the eruption were also recorded globally with propagation speeds of ~ 310 m/s (Lamb wave) and 200–250 m/s (Pekeris wave). Previous studies have suggested that these propagating atmospheric waves caused at least the initial part of the observed tsunami. We simulated the tsunamis generated by the propagation of the Lamb and Pekeris waves by adding concentric atmospheric pressure changes. The concentric sources are parameterized by their propagation speeds, initial atmospheric wave amplitudes that decay with the distance, and a rise time. For the Lamb wave, inversions of the observed tsunami waveforms at 14 U.S. and nine New Zealand DART stations indicate the start of the positive rise at 4:16 UTC, the peak amplitude of 383 hPa, and the propagation speed of 310 m/s, assuming a rise time of 10 min. The later phases of the observed tsunami waveforms can be better reproduced by adding another propagating concentric wave (Pekeris wave) with a negative amplitude (− 50 hPa) and propagation speeds of 200–250 m/s. The DART records around the Pacific indicate that the Pekeris wave speed is faster toward the northwest and slightly slower toward the northeast. The synthetic waveforms roughly reproduced the far-field tsunami waveforms recorded at tide gauge stations, including the later phases, suggesting that the large amplitude in the later phase may be due to the coupling of the Pekeris wave and the tsunami, as well as resonance around tide gauge stations.

Island-based GNSS-IR network for tsunami detecting and warning

Deep-sea tsunami detection relies on Deep-ocean Assessment and Reporting of Tsunamis (DART), GNSS buoys, and cabled Ocean-Bottom Pressure (OBP) gauges, which are very expensive and difficult to maintain, and often suffer from vandalism or negligent damage. Here, we exploit the potential of establishing a less expensive and more robust island-based geodetic network for tsunami detecting, source reconstruction and warning. The network locates at the coastline of islands and uses a new technique: GNSS Interferometric Reflectometry (GNSS-IR). GNSS-IR retrieves sea levels from combination of the direct and reflected signals from the sea surface sent by satellites. To test the feasibility and efficiency of such a new geodetic network, we use the South China Sea region as an example, and compare its performance in reconciling the variable slip distribution on the Manila megathrust with the previously designed deep-sea monitoring system, i.e., DARTs and planned cable-based OBP gauges. We find that the newly designed GNSS-IR network could work equally well as the cabled OBP network in detecting tsunamis if the stations are built in strategically chosen locations. Combining GNSS-IR with a Kalman filter approach, we demonstrate that carefully situated coastal GNSS stations at global remote deep-ocean islands could function similarly to conventional tide gauges but with advantages of simultaneously measuring relative sea-level and land-height changes, meanwhile suffering lower risk from damaging sea-level events and potential vandalism.

Enigmatic Tsunami Waves Amplified by Repetitive Source Events Near Sofugan Volcano, Japan

AbstractOn 8 October 2023, mysterious tsunamis with a maximum wave height of 60 cm were observed in Izu Islands and southwestern Japan, although only seismic events with body‐wave magnitudes mb 4–5 have been documented to the west of Sofugan volcano. To investigate the source process, we analyze tsunami waveforms recorded by an array network of ocean bottom pressure gauges. Stacked waveforms of pressure gauge records suggest recurrent arrivals of multiple wave trains. Deconvolution of the stacked waveforms by tsunami waveforms from an earlier event revealed over 10 source events that intermittently generated tsunamis for ∼1.5 hr. The temporal history of this sequence corresponds to the origin times of T‐phases estimated by an ocean bottom seismometer and of the seismic swarm, implying a common origin. Larger events later in the sequence occurred at intervals comparable to the tsunami wave period, causing amplification of later phases of the tsunami waves.

Adjoint Inversion of Near‐Field Pressure Gauge Recordings for Rapid and Accurate Tsunami Source Characterization

AbstractWe explore the potential of the adjoint‐state tsunami inversion method for rapid and accurate near‐field tsunami source characterization using S‐net, an array of ocean bottom pressure gauges. Compared to earthquake‐based methods, this method can obtain more accurate predictions for the initial water elevation of the tsunami source, including potential secondary sources, leading to accurate water height and wave run‐up predictions. Unlike finite‐fault tsunami source inversions, the adjoint method achieves high‐resolution results without requiring densely gridded Green's functions, reducing computation time. However, optimal results require a dense instrument network with sufficient azimuthal coverage. S‐net meets these requirements and reduces data collection time, facilitating the inversion and timely issuance of tsunami warnings. Since the method has not yet been applied to dense, near‐field data, we test it on synthetic waveforms of the 2011 Mw 9.0 Tohoku earthquake and tsunami, including triggered secondary sources. The results indicate that with a static source model without noise, using the first 5 min of the waveforms yields a favorable performance with an average accuracy score of 93%, and the largest error of predicted wave amplitudes ranges between −5.6 and 1.9 m. Using the first 20 min, secondary sources were clearly resolved. We also demonstrate the method's applicability using S‐net recordings of the 2016 Mw 6.9 Fukushima earthquake. The findings suggest that lower‐magnitude events require a longer waveform duration for accurate adjoint inversion. Moreover, the estimated stress drop obtained from inverting our obtained tsunami source, assuming uniform slip, aligns with estimations from recent studies.

Reduction of non-tidal oceanographic fluctuations in ocean-bottom pressure records of DONET using principal component analysis to enhance transient tectonic detectability

Ocean bottom pressure-gauge (OBP) records play an essential role in seafloor geodesy. Oceanographic fluctuations in OBP data, however, pose as a significant noise source in seafloor transient crustal deformation observations, including slow slip events (SSEs), making it crucial to evaluate them quantitatively. To extract the significant fluctuation phenomena common to multiple observation networks, including oceanographic fluctuations and tectonic signals, we applied principal component analysis (PCA) to the 3-year Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) OBP time series for 40 stations during 2016–2019. PCA could separate several oceanographic signals based on the characteristics of their spatial distributions, although evident transient tectonic signals could not be confirmed from the observed pressure records during this observed period. The spatial distribution of the first four principal components (PCs) reflected the common component, inclined component along sea depth, longitude component, and parabola-like pattern, respectively. By subtracting each PC (in particular, PC-2 and PC-4) from the time series, we could significantly reduce the sea depth dependence of OBP records, which has been highlighted in several previous studies and is also evident in this region. We interpreted PCs 2–4 as the reflection of the strength and meandering of ocean geostrophic currents based on a comparison with the PC spatial distribution of the numerical oceanographic models. In addition, to evaluate the ability of PCA to separate transient tectonic signal from OBP time series, including oceanographic fluctuations, we conducted a synthetic ramp assuming an SSE by rectangular fault and then applied PCA. The assumed synthetic tectonic signal could be separated from the oceanographic signals and included in the principal component independently depending on its amplitude, suggesting that the spatial distribution of each PC would change if the amplitude of the synthetic signal were sufficiently large. We propose a transient event-detection method based on the spatial distribution difference of a specific PC with or without a tectonic signal. We used the normalized inner product (NIP) between these PCs as the indicator of their similarities. This method can detect transient tectonic signals more significantly than the moment-magnitude scale of 5.9 from OBP records.Graphical

Joint inversion of ocean-bottom pressure and GNSS data from the 2003 Tokachi-oki earthquake

When the 2003 Tokachi-oki earthquake generated a large tsunami off eastern Hokkaido, Japan, it was detected by cabled ocean-bottom pressure gauges (OBPs) installed within the seismic source region. The OBP records included characteristic features of tsunami waveforms in the source region, indicating significant offset due to the permanent sea-bottom displacement, which can provide critical information about the earthquake source. However, no studies have considered the OBP tsunami data observed in the focal region for the source inversion of the Tokachi-oki earthquake. Here, in order to better understand the 2003 Tokachi-oki earthquake source, we estimate the spatial distribution of fault slip by conducting a joint inversion using two different datasets: tsunami data from four OBPs, located in the focal region and about 300 km away to the south, as well as Global Navigation Satellite System (GNSS) data obtained throughout Hokkaido and northern Honshu. Through our joint inversion, we found that the most dominant slip peak is located 40 km northwest from the hypocenter with an abnormally large slip of sim15 m. This large slip may result from releasing a high amount of slip deficit accumulated by a stick–slip patch surrounded by stable slip regions on the southernmost Kuril subduction zone. By comparing the OBP observations and the synthetic tsunami waveforms derived from our fault model and other fault models, we conclude that the OBP tsunami data recorded within the focal region better constrained the magnitude and the location of the slip compared to other geophysical data.Graphical

Interpretation of Signals Recorded by Ocean-Bottom Pressure Gauges during the Passage of Atmospheric Lamb Wave on 15 January 2022

The eruption of the Hunga Tonga–Hunga Ha’apai volcano on 15 January 2022 was the first powerful explosive eruption in history to be recorded with high quality by a wide range of geophysical equipment. The atmospheric Lamb wave caused by the explosion repeatedly circled the Earth and served as one of the reasons for the formation of tsunami waves. In this paper, the Lamb wave manifestations are analyzed in the recordings of tsunamimeters, i.e., in data from DONET and DART pressure sensors located in the area of the Japanese Islands. The work is aimed at studying the physics of the formation of pressure variations at the ocean floor in order to develop a method for isolating free gravity waves in records obtained by bottom pressure sensors. Within the framework of shallow water theory, an analysis of the response of the water layer to the atmospheric Lamb wave was performed. This response combines a forced perturbation, the amplitude of which depends on the depth of the ocean, and free gravity waves arising as a result of the restructuring of the forced perturbation on the submarine slopes. Analytical formulas are given for the amplitude and energy of the forced perturbation and free waves arising at the depth jump. With the aid of numerical simulation, the finite length of a slope was revealed to significantly affect the parameters of free waves when exceeding 50 km. The analysis of in situ data (DONET, DART) confirms the validity of theoretical concepts presented in the work. In particular, it is shown that variations of bottom pressure in the deep ocean exceed the amplitude of atmospheric pressure fluctuations in the Lamb wave.

Ocean-Wave Gradiometry: Visualizing and Extracting Propagation Features of the 15 January 2022 Tsunami Wavefield with Dense Ocean-Bottom Pressure Gauge Arrays

Abstract Dense geophysical observation networks have recently enabled monitoring the wavefield of sea-bottom pressure changes. Significant sea-bottom pressure disturbances were recorded by ocean-bottom pressure gauge (OBPG) arrays around Japan on 15 January 2022, the day of the massive eruption of Hunga Tonga–Hunga Ha’apai volcano in the Tonga Islands. At the same time, sea-surface height disturbances and atmospheric pressure disturbances were recorded by tide gauges around the Pacific Ocean and barometers around the world. Because the atmospheric disturbances may have affected the propagation of the sea-surface height changes, we investigated the propagation properties of the sea-bottom pressure disturbances recorded by the OBPG arrays around Japan using wave gradiometry. We found that the leading pressure disturbances propagated from southeast to northwest with a velocity expected from linear long-wave theory for ocean waves, that is, tsunamis. We also detected several later coherent sea-bottom pressure disturbances that propagated at the velocity of tsunamis. In addition, we detected anomalous short-period later phases of pressure disturbances with propagation directions more nearly north–south than those of the leading disturbances at the coast of southwestern Japan. These results indicate that the pressure disturbances recorded at the OBPG arrays propagated as tsunamis rather than sea-surface disturbances excited by atmospheric Lamb waves, although atmospheric pressure disturbances might have affected the amplitude of sea-surface height changes. This study demonstrates that wave gradiometry can be successfully applied to data from a dense OBPG array and may be suitable for real-time monitoring of sea-bottom pressure wavefields.

Re-examination of Slip Distribution of the 2004 Sumatra\u2013Andaman Earthquake (Mw 9.2) by the Inversion of Tsunami Data Using Green\u2019s Functions Corrected for Compressible Seawater Over the Elastic Earth

We re-examined the slip distribution on faults of the 2004 Sumatra–Andaman (M 9.1 according to USGS) earthquake by the inversion of tsunami data with phase-corrected Green’s functions applied to linear long waves. The correction accounts for the effects of compressibility of seawater, elasticity of solid earth, and gravitational potential variation associated with the motion of mass to reproduce the delayed arrivals and the reversed phase of the first tsunami waves. We used sea surface height (SSH) data from satellite altimetry (SA) measurements along five tracks, and the tsunami waveforms recorded at tide gauges (TGs) and ocean bottom pressure gauges (OBPGs) in and around the Indian Ocean. The inversion results for both data sets for different rupture velocities (Vr) show that the reproducibility of the spatiotemporal SSHs and tsunami waveforms is improved by the phase corrections, although the effects are not so significant within the Indian Ocean. The best slip distribution model from joint inversion of SA, TG and OBPG data with Vr of 1.3 km/s shows the largest slips of 16–25 m off Sumatra Island, large slips of 2–11 m off the Nicobar Islands, and moderate slips of 2–6 m in the Andaman Islands. The inversion results reproduce the far-field tsunami waveforms well at distant stations even more than 13,000–25,000 km from the epicenter. The total source length is about 1400 km and the seismic moment is Mw 9.2, longer and larger than that of our previous estimates based on TG records.

Detection of “Rapid” Aseismic Slip at the Izu‐Bonin Trench

AbstractNo great earthquakes have been historically documented at the Izu‐Bonin Trench, where subduction is believed to occur largely by aseismic slip, although the details are poorly understood. We deployed an array of ocean bottom pressure gauges here for a year from May 2015. The array recorded the coseismic seafloor uplift/subsidence and tsunamis generated by the nearby Mw6.0 thrust earthquake. In association with this event, we detected two much larger aseismic slip events with rise times around 1 h. The total moment of these two aseismic events was 17 times larger than that of the mainshock. Such aseismic, yet still rapid, slip can be interpreted as one amid the transitional regime. This regime is expected to host slow slip events near its boundary with the stable sliding regime and, possibly, tsunami earthquakes and very low frequency earthquakes near the boundary with the unstable seismic slip regime. Slip in the transitional regime may be a prevalent mode of subduction in the Izu‐Bonin trench, where effective normal force on the frictional plate interface is tectonically reduced.

Phase delay of short-period tsunamis in the density-stratified compressible ocean over the elastic Earth

SUMMARY Tsunamis are often modelled as surface gravity waves of incompressible homogenous water propagating over a rigid seafloor. Previous studies have noted that when computing long-period tsunamis travelling at trans-oceanic distances with dominant periods of thousands of seconds, we need to consider four factors that are not included in the surface gravity wave theory: compressibility of seawater, density stratification of oceans, elasticity of the Earth and gravitational potential change associated with the tsunami motion. However, their effects on short-period tsunamis with dominant periods below 1000 s have not been examined. Here, we investigate how the four factors influence short-period tsunamis. Theoretical analyses and 1-D simulations using phase speeds of different tsunami models indicate that the resultant phase delay of short-period tsunamis becomes apparent after ∼1000 km propagation, mainly because of the first three factors. We then introduce a new phase correction method for dispersive short-period tsunamis with consideration of period-dependent ray paths and apply it to a 2-D simulation of a short-period tsunami from a submarine volcanic earthquake near Japan in 2015. The correction of the traveltime of a synthetic waveform by including the four factors amounts to ∼40 s at a distant station 1430 km away from the source, whereas the effects of the four factors on the waveforms are negligibly small at stations < ∼500km from the source. The observed traveltime at the ocean bottom pressure (OBP) gauge with a sampling interval at 15 s of the distant station can be explained only when these factors are incorporated into synthetic waveforms, indicating the effects due to the four factors are detectable by high-sampling OBP gauges that are deployed over broad oceanic regions.

A Significant Change in Ocean Bottom Pressure Off Eastern Taiwan, Southwestern Ryukyu Subduction Zone

Three real-time permanent observatories (EOS02–EOS04) connected by a submarine cable were constructed and deployed to monitor seismicity, tsunamis, and other geophysical phenomena off eastern Taiwan, southwestern Ryukyu subduction zone. In this study, we process the pressure data (January 26, 2017, to December 31, 2019) recorded by three ocean bottom pressure gauges. After removing of tidal and short-period oceanographic effects and the linear trend caused by long-term sensor drift, overall, the variation patterns of the ocean bottom pressure (OBP) records at stations EOS02 and EOS03 are similar, while that at station EOS04 (located on a slope) exhibits different characteristics. The amplitude fluctuations of the OBP records are very large, even reaching approximately 3 × 102 mbar at station EOS02. In addition, we observe a significant permanent change in the OBP data at station EOS04 where the pressure variation reaches approximately 4.2 × 102 mbar (approximately equals a 4.2 m water column variation). Considering the seismicity and background tectonic characteristics of station EOS04, we speculate that this permanent pressure change may have been caused by submarine landslides and/or slumps (triggered by nearby earthquakes).

Slip distribution of the 2005 Nias earthquake (Mw 8.6) inferred from geodetic and far-field tsunami data

SUMMARYWe estimated the slip distribution on the fault of the 2005 Nias earthquake (Mw 8.6) by inversions of local GPS and coastal uplift/subsidence data and tsunami waveform data. The 2005 Nias earthquake occurred approximately three months after the 2004 Sumatra–Andaman earthquake (Mw 9.1) at the southern extension off Sumatra Island, Indonesia. The tsunami from the 2005 earthquake caused significantly less damage than the 2004 tsunami, yet was recorded at tide gauges and ocean bottom pressure gauges around the Indian Ocean, including the coasts of Africa and Antarctica. The elastic and gravitational coupling between the solid earth and the ocean causes not only a traveltime delay but also the change of waveforms of far-field tsunamis relative to the prediction based on the long-wave theory. We corrected the computed tsunami Green's functions for the elastic and gravitational coupling effect in the tsunami waveform inversion. We found a diffused slip (∼2 m over an area of 400 km × 100 km) at deeper parts (20–54 km) of the fault with a large localized slip (7 m over 100 km × 100 km) slightly south of the epicentre. The large slips at deeper parts of the fault were responsible for the small tsunami generation. Inversion using far-field tsunami data yielded a slip distribution similar to that obtained using local geodetic data alone and that from the joint inversion of local geodetic and far-field tsunami data, which is also similar to slip distributions from previous studies based on local geodetic data. This demonstrates that far-field tsunami waveforms, once corrected for propagation effects, can be used to estimate the slip distribution of large submarine earthquakes leading to results that are similar to those obtained using sparse local geodetic data.

Early Tsunami Detection With Near‐Fault Ocean‐Bottom Pressure Gauge Records Based on the Comparison With Seismic Data

AbstractOffshore real‐time ocean bottom networks of seismometers and ocean bottom pressure (OBP) gauges have been recently established such as DONET and S‐net around the Japanese islands. One of their purposes is to practice rapid and accurate tsunami forecasting. Near‐fault OBP records, however, are always contaminated by nontsunami components such as sea‐bottom acceleration change until an earthquake stops its fault or sea‐floor motions. This study proposes a new method to separate tsunami and ocean bottom displacement components from coseismic OBP records in a real‐time basis. Associated with the Off‐Mie earthquake of 2016 April 1, we first compared OBP data with acceleration, velocity, and displacement seismograms recorded by seismometers at common ocean bottom sites in both time and frequency domains. Based on this comparison, we adopted a band‐pass filter of 0.05–0.15 Hz to remove ocean‐bottom acceleration components from the OBP data. Resulting OBP waveforms agree well with the tsunami components estimated by a 100‐s low‐pass filter with records of several hundred seconds in length. Our method requires only an early portion of a given OBP record after 30 s of an origin time in order to estimate its tsunami component accurately. Our method enhances early tsunami detections with near‐fault OBP data; that is, it will make a tsunami forecasting system faster and more reliable than the previous detection schemes that require data away from source regions or after coseismic motions are over.

A Method of Real-Time Tsunami Detection Using Ensemble Empirical Mode Decomposition

AbstractWe propose a method of real-time tsunami detection using ensemble empirical mode decomposition (EEMD). EEMD decomposes the time series into a set of intrinsic mode functions adaptively. The tsunami signals of ocean-bottom pressure gauges (OBPGs) are automatically separated from the tidal signals, seismic signals, as well as background noise. Unlike the traditional tsunami detection methods, our algorithm does not need to make a prediction of tides. The application to the actual data of cabled OBPGs off the Tokohu coast shows that it successfully detects the tsunami from the 2016 Fukushima earthquake (M 7.4). The method was also applied to the extremely large tsunami from the 2011 Tohoku earthquake (M 9.0) and extremely small tsunami from the 1998 Sanriku earthquake (M 6.4). The algorithm detected the former huge tsunami that caused devastating damage, whereas it did not detect the latter microtsunami, which was not noticed on the coast. The algorithm was also tested for month-long OBPG data and caused no false alarm. Therefore, the algorithm is very useful for a tsunami early warning system, as it does not require any earthquake information to detect the tsunamis. It detects the tsunami with a short-time delay and characterizes the tsunami amplitudes accurately.

Developments of Tsunami Observing Systems in Japan

Being situated on the major subduction zones in conjunction with a considerable number of submarine active faults and coastal volcanoes, Japan has a long history of catastrophic tsunami events. Consequently, enormous efforts in disaster mitigation, particularly in relation with tsunami hazards have been made across the country. It is of our interest to review the developments of tsunami observing systems in Japan, which may lead to a global implication beyond national boundaries. In this paper, we first discuss in general the evolution of past to present tsunami observing systems available around the territory of Japan. More specifically, we identify the existing offshore observational networks that are mainly consisted of cabled ocean bottom pressure gauges and global navigation satellite system buoys, and briefly analyze their performance and viability in the long-term future. In that context, we also appraise the potential of emerging technologies in the offshore tsunami detection leveraging unconventional platforms such as commercial ships and airplanes, which have recently been introduced by several studies in Japan.