Tsunami Detection Research Articles

A STUDY ON OPTIMAL DEPLOYMENT OF TSUNAMI OBSERVATION INSTRUMENTS IN KOREA

Tsunamis are one of the most destructive natural phenomena (Pugh and Woodworth, 2014). For past decades, the risk of potential earthquake zones has been issued by Japanese researchers, which could occur tsunami, in Niigata and Tottori area located in the west coast of Japan and the Ryukyu trench located in Okinawa as well (Disaster Prevention Research Institute, Japan). Also, there is a Yamamoto Rise on the East Sea, where it strongly affects tsunami propagation. This topography causes high tsunami energy to concentrate on the east coast of Korea (Cho and Lee, 2013). For example, the 1983 Akita and 1993 Hokkaido earthquake induced tsunamis, Japan, respectively cause the property and life damages to the certain cities on the east coast of Korea. Therefore, it is important to propose the optimal deployment location of offshore tsunami observation instruments to contribute to the tsunami early warning system by increasing probability of tsunami detection with the minimal number of instruments considering a large number of potential tsunami scenarios. In this study, by considering various factors, the optimal location of instruments is suggested based on the numerical model results of possible tsunami scenarios.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/q3PLE6EgtrY

Application of particle swarm optimization in optimal placement of tsunami sensors.

Rapid detection and early warning systems demonstrate crucial significance in tsunami risk reduction measures. So far, several tsunami observation networks have been deployed in tsunamigenic regions to issue effective local response. However, guidance on where to station these sensors are limited. In this article, we address the problem of determining the placement of tsunami sensors with the least possible tsunami detection time. We use the solutions of the 2D nonlinear shallow water equations to compute the wave travel time. The optimization problem is solved by implementing the particle swarm optimization algorithm. We apply our model to a simple test problem with varying depths. We also use our proposed method to determine the placement of sensors for early tsunami detection in Cotabato Trench, Philippines.

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

AbstractMarine renewable energy (MRE) encompasses the harvest of energy from the movement of ocean waters in the form of either currents or waves, as well as temperature and salinity differentials. To date, most MRE development has focused on utility-scale electrical grid generation, but a growing body of work focuses on non-grid applications in the blue economy where MRE could provide power on-site and at the scale needed for specific maritime sectors. One of the blue economy sectors with promising applications for MRE is ocean observations using both mobile and stationary platforms. This paper documents the steps and results of engaging with experts across the myriad ocean observation platforms and capabilities to inform five use cases. These use cases include descriptions of specific ocean observation applications performing measurements of high societal value (e.g., data for weather forecasting and tsunami detection) that closely resemble specific sensing systems and, in most cases, are placed in a particular area of the ocean. Rapid resource assessments (i.e., first-order estimates) were performed at these locations to determine the suitability of marine and other renewable energy sources. From the information gathered so far, MRE has significant potential to enable improved ocean observation missions, expand ocean observing capacity, and develop as an industry in parallel with the needs of our changing oceans.

Numerical and Probabilistic Study on the Optimal Region for Tsunami Detection Instrument Deployment in the Eastern Sea of Korea

A tsunami is a significant coastal hazard that causes destructive damage to coastal cities in the world. Besides, tsunamis, generated on the west coast of Japan, damaged coastal cities on the east coast of Korea in 1983 and 1993. In recent years, there has been increasing interest in the potential tsunami zone near the west coast of Japan. Therefore, it is important to have tsunami observation instruments in proper locations for tsunami detection and warning aspect. This study proposes the optimal region for offshore tsunami observation instrument deployment under the limited condition that the tsunami source in out of the territorial sea by investigating areas with the highest tsunami detection probability along with maximum evacuation time and bottom slope. Using the Cornell Multi-grid Coupled Tsunami (COMCOT) numerical model and a probabilistic approach, this study suggests the optimal region for offshore tsunami detection instrument deployment to be the northeast area of Ulleung-do Island in the eastern sea of Korea.

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.

FLCEER

Underwater acoustic sensor networks (UASN) play a crucial role in various applications such as tsunami detection, surveillance of the ocean by the defense department, monitoring offshore oil, and identifying gas basins underwater. UASNs can be one of the supporting infrastructures for the Internet of Things (IoT). UASNs have the problems of long latency, high bit error rate, and low bandwidth. These pose various challenges such as high consumption of energy, low reliability, low packet retransmission, and high delay for UASNs. To overcome the shortcomings mentioned above, various approaches are suggested. This article proposes a multi-layer fuzzy logic cluster-based energy-efficient routing protocol for UASNs. It splits the network area into equal sized rings. The priority number (PRN) is utilized for all underwater cluster heads (UCHs). Based on the highest PRN, the UCH starts communicating among UCHs. Here, the PRN makes the task very selective avoiding collisions and also reducing propagation delays. The cluster formation is done by sending a message to all underwater cluster members (UCMs) and the selection of UCH and UCM are done. Each has a threshold value. The intra-ring clustering process splits a ring into equal-sized clusters. Additionally, inter-cluster routing applies the fuzzy logic metrics to choose the optimum data route in transferring the data from the underwater cluster head (UCH) to the sink node (SN). It is tested using Aqua-Sim simulation which is based on NS2. It is compared with an existing protocol such as multi-layer cluster energy efficient (MLCEE), depth-based routing (DBR), energy efficient DBR (EEDBR). The results prove that it has improved energy efficiency, packet delivery ratio, throughput, and the network's lifetime.

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.

The Sendai Framework for Disaster Risk Reduction at Five: Lessons from the 2011 Great East Japan Earthquake and Tsunami

The Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) represents an inclusive approach to disaster risk reduction, linked to development and recovery. Building on previous international guidelines, the SFDRR promotes practical and measurable outcomes for reducing disaster losses, including indicators to measure progress towards seven specific global targets. Evaluated in the context of the priorities and global targets of the SFDRR, the article considers the case of the Great East Japan Earthquake and Tsunami of 2011 to illustrate advances and limitations in pre-disaster tsunami hazard engineering and post-disaster recovery. With respect to the targets set out in the Sendai Framework related to risk reduction and tsunami engineering, especially Priority 1, understanding disaster risk, there have been significant advances in hazard assessment and systems for tsunami detection and warning. Although the SFDRR emphasizes actions in the recovery phase through Priority 4, enhancing disaster preparedness with an emphasis on the concept of build back better, on its own this does not function as a clear directive for guiding recovery. However, the overall people-centered and inclusive approach of the SFDRR, as well as the global targets and several sub-priorities, can be a useful way to shape good practices in recovery and evaluate recovery progress.

Advanced tsunami detection and forecasting by radar on unconventional airborne observing platforms

Sustaining an accurate, timely, and global tsunami forecast system remains a challenge for scientific communities. To this end, various viable geophysical monitoring devices have been deployed. However, it is difficult to implement new observation networks in other regions and maintaining the existing systems is costly. This study proposes a new and complementary approach to monitoring the tsunami using existing moving platforms. The proposed system consists of a radar altimeter, Global Navigation Satellite Systems receiver, and an adequate communication link on airborne platforms such as commercial airplanes, drones, or dedicated high-speed aircraft, and a data assimilation module with a deterministic model. We demonstrated, through twin-data experiment, the feasibility of the proposed system in forecasting tsunami at the Nankai Trough of Japan. Our results demonstrated the potential of an airborne tsunami observation as a viable future technology through proxy observations and rigorous numerical experiments. The wide coverage of the tsunamigenic regions without a new observation network is an advantage while various regulatory constraints need to be overcome. This study offered a novel perspective on the developments in tsunami detection and forecasting technology. Such multi-purpose observation using existing platforms provides a promising and practical solution in establishing sustainable observational networks.

An update of proposed Sri Lanka warning system for east and west coast tsunamis

PurposeBased on the existing provisions/operations of tsunami warning in the Indian Ocean, authors observed that detection as well as arrival time estimations of regional tsunami service providers (RTSPs) could be improved. In particular, the detection mechanisms have been eccentrically focussed on Sunda and Makran tsunamis, although tsunamis from Carlsberg ridge and Chagos archipelago could generate devastating tsunamis for which inadequate provisions exist for detection and arrival time/wave height estimation. RTSPs resort to assess estimated arrival time/wave heights from a scenario-based, pre-simulated database. These estimations in terms of Sri Lanka have been found inconsistent. In addition, current warning mechanism poorly manages non-seismic tsunamis. Thus, the purpose of this study is to investigate these drawbacks and attempt to carve out a series of suggestions to improve them.Design/methodology/approachThe work initiated with data retrieved from global earthquake and tsunami databases, followed by an estimation of probabilities of tsunamis in the Indian Ocean with particular emphasis on Carlsberg and Chagos tsunamis. Second, probabilities of tsunami detection in each sub-region have been estimated with the use of available tide gauge and tsunami buoy data. Third, the difficulties in tsunami detection in the Indian Ocean are critically assessed with case studies, followed by recommendations to improve the detection and warning.FindingsProbabilistic estimates show that given the occurrence of a significant earthquake, both Makran and Carlsberg/Chagos regions possess higher probabilities to harbour a tsunami than the Sunda subduction zone. Meanwhile, reliability figures of tsunami buoys have been declined from 79-92 to 68-91 per cent over the past eight years. In addition, a Chagos tsunami is left to be detected by only one tide gauge prior to it reaching Sri Lankan coasts.Research limitations/implicationsThe study uses an averaged tsunami speed of 882 km/h based on 2004 Asian tsunami. However, using exact bathymetric data, Tsunamis could be simulated to derive speeds and arrival times more accurately. Yet, such refinements do not change the main derivations and conclusions of this study.Practical implicationsTsunami detection and warning in the Indian Ocean region have shown room for improvement, based on the inadequate detection levels for Carlesberg and Chagos tsunamis, and inconsistent warnings of regional tsunami service providers. The authors attempted to remedy these drawbacks by proposing a series of suggestions, including a deployment of a new tsunami buoy south of Maldives, revival of offline buoys, real-time tsunami simulations and a strategy to deal with landslide tsunamis, etc.Social implicationsIndian Ocean is prone to mega tsunamis as witnessed in 2004. However, more than 50 per cent of people in the Indian Ocean rim countries dwell near the coast. This is verified with deaths of 227,898 people in 14 countries during the 2004 tsunami event. Thus, it is of paramount importance that sufficient detection levels are maintained throughout the Indian Ocean without being overly biased towards Sunda tsunamis. With respect to Sri Lanka, Makran, Carlesberg or Chagos tsunamis could directly hit the most populated west coast and bring about far worse repercussions than a Sunda tsunami.Originality/valueThis is the first instance where the threats from Carlesberg and Chagos tsunamis to Sri Lanka are discussed, probabilities of tsunamis are quantified and their detection levels assessed. In addition, reliability levels of tsunami buoys and tide gauges in the Indian Ocean are recomputed after eight years to discover that there is a drop in reliability of the buoy data. The work also proposes a unique approach to handle inconsistencies in the bulletins of regional tsunami service providers, and to uphold and improve dwindling interest on tsunami buoys.

Ionospheric Detection of Natural Hazards

AbstractNatural hazards (NH), such as earthquakes, tsunamis, volcanic eruptions, and severe tropospheric weather events, generate acoustic and gravity waves that propagate upward and cause perturbations in the atmosphere and ionosphere. The first NH‐related ionospheric disturbances were detected after the great 1964 Alaskan earthquake by ionosondes and Doppler sounders. Since then, many other observations confirmed the responsiveness of the ionosphere to NH. Within the last two decades, outstanding progress has been made in this area owing to the development of networks of ground‐based dual‐frequency Global Navigation Satellite Systems (GNSS) receivers. The use of GNSS‐sounding has substantially enlarged our knowledge about the solid earth/ocean/atmosphere/ionosphere coupling and NH‐related ionospheric disturbances and their main features. Moreover, recent results have demonstrated that it is possible to localize NH from their ionospheric signatures and also, if/when applicable, to obtain the information about the NH source (i.e., the source location and extension and the source onset time). Although all these results were obtained in retrospective studies, they have opened an exciting possibility for future ionosphere‐based detection and monitoring of NH in near‐real time. This article reviews the recent developments in the area of ionospheric detection of earthquakes, tsunamis, and volcanic eruptions, and it discusses the future perspectives for this novel discipline.

Evaluating HF Coastal Radar Site Performance for Tsunami Warning

We describe theoretical and experimental work for evaluating the suitability of coastal High Frequency (HF) radar sites for tsunami detection. A method is outlined which involves superimposing simulated tsunami velocities on typical radial current velocities measured at the radar site. This leads to an estimate of the minimum detectable tsunami height at the site. Results are presented from application of these methods to data measured over a day by a radar located at Brant Beach, New Jersey.

An Optimized Array Configuration of Tsunami Observation Network Off Southern Java, Indonesia

AbstractHistorical records have proven that the southern coasts of Java, Indonesia, are prone to tsunamis. The existing tsunami observing system using bottom pressure gauges, also known as tsunameters, composes a global network but is too sparse for regional tsunami forecasts. The nearest tsunameter to Indonesia is located approximately 500‐km offshore, which is not very useful for the area, particularly for a tsunami source in eastern part of the Sunda megathrust. Here we propose a methodology to optimally place offshore tsunameters with the main consideration of operational costs, which is proportional to the number of observation points. We use a stochastic slip model of earthquakes with Mw 8.8–9.2 to generate multiple tsunami source realizations representing possible future events in the region. Based on the sources, we then identify a potential zone where an early tsunami detection is feasible. Furthermore, empirical orthogonal functions derived from tsunami simulations are used to determine the initial locations for tsunameter placement inside the specified zone. Finally, we apply an optimization scheme to improve the initial locations that facilitates both tsunami forecasts and source characterizations through a tsunami waveform inversion analysis. Our result indicates that six tsunameters are sufficient to efficiently cover the major seismogenic region in the study area.

Observation of sea surface height using airborne radar altimetry: a new approach for large offshore tsunami detection

This study proposes the detection of large offshore tsunamis by airborne radar. Altimeter measurements were carried out south of Japan by an observational aircraft along the Jason satellite tracks crossing over the Kuroshio Current. A nadir-pointing frequency-modulated continuous wave (FM-CW) radar and a global navigation satellite system (GNSS) based positioning system were concurrently used to measure the sea surface height (SSH). The SSH was validated against the Jason-2 and Jason-3 satellite altimeter SSH. After the removal of the geoid and tidal signals, the observation error was less than 10 cm. This is sufficiently small to capture offshore tsunamis within 10 min after the genesis. This was demonstrated by virtual airborne radar-detected SSH from a numerically simulated hypothetical large offshore tsunami south of Japan. The feasibilities and limitations of utilizing commercial airplanes with altimeters to create a dense tsunami observation network are discussed. The suggested methodology can be adapted to various emerging airborne platforms such as unmanned aerial vehicles. Moreover, a dense coverage of SSH observations is invaluable from an oceanographic point of view.

Measurement and validation of tsunami Eigen values for the various water wave conditions

This paper proposes the mathematical model to investigate how to compute and analyze the tsunami wave parameters and the retrieval of its early warning using remote sensing technique to improve the detection rate. The different methods available for the evaluation of the tsunami detection systems are also introduced. This research work is to compute and analyze the tsunami wave parameters such as Eigen functions in deep, intermediate and shallow water regions.The computational and algorithmic analysis of tsunami wave parameters are achieved in three steps: the first step is to calculate the earthquake fault parameters such as length, width, area and displacement from the epicenter, which corresponds to the effect of its variation with respect to the earthquake magnitude. The variation of each fault parameters have been measured and recorded out over the certain moment of magnitudes (M). This shows smaller values as compared to the earthquake magnitude M9.5 at which all the parameters shows very large response. The second step involves the measurements of water wave angular frequency in deep, intermediate and shallower region of ocean. The values of angular frequencies in deep water shows the lesser response as compared to other two water conditions because, in deep water the angular velocity of water particles travels with the lesser speed as compared to the shallower region as per Airy's wave theory. The simulation results show the angular velocity in Deep Ocean is very less, moderate in the intermediate water and very high on the coastal region. It indicates the higher impact on coastal region. The third step involves the simulation study of measurement of tsunami Eigen functions such as orbital velocity, acceleration, wave potential in deep, intermediate and shallower water regions. The simulation result shows the resultant orbital velocity and accelerations in deep, intermediate and shallow water regions provides the similar response as angular velocity due to same proportion of the water displacement from deep to coastal regions. Hence the dynamic forces are very high approximately 1 km from the beaches. Once the Tsunami waves approaches to the beach, wave height increases whereas particle acceleration decreases because near the coast, due to geological structure of the earth's surface, inertia and gravity forces increase to the extreme limits, while particle acceleration and velocity values reach close to zero. The wave potential Eigen function has also been plotted and measured with respect to the water depth condition and the similar response is obtained in the simulation result. The validation of each result has also been presented with the standard simulated data, which shows the results as less than 10% of the accuracy.

ADDTID: An Alternative Tool for Studying Earthquake/Tsunami Signatures in the Ionosphere. Case of the 2011 Tohoku Earthquake

In this work, we characterized the ionospheric disturbances generated during the Japan Tohoku earthquake of 11 March 2011, by means of the Atomic Decomposition Detector of Traveling Ionospheric Disturbances (ADDTID) algorithm. This algorithm automatically detects and characterizes Traveling Ionospheric Disturbances (TIDs) from Global Navigation Satellite System (GNSS) measurements. Applying the high-precision estimates of ADDTID, the propagation parameters would make it easier to distinguish TIDs from different origins, in particular the characteristics conforming the acoustic gravity waves driven by the earthquake/tsunami. This method does not assume that disturbances follow a circular pattern of propagation, and can estimate the location by the propagation pattern of tsunami wavefronts and related TIDs. In this work, we present in a single framework a description of phenomena observed by different researchers. By means of the ADDTID algorithm, we detect: (a) simultaneous TIDs of different characteristics, where the detection was robust against the curvature of the wave fronts of the perturbations and the accuracy of the estimated parameters. The results were double-checked by visual inspection from detrended Vertical Total Electron Content (VTEC) maps and keogram plots, and the parameters of the slow-speed TIDs were consistent with the tsunami waveform measurements; (b) different wavefronts between the west and east TIDs around the epicenter, consistent in time and space with the post-earthquake tsunami; (c) complete evolution of the circular TIDs driven by the tsunami during the GNSS observable area; (d) fast and short circular TIDs related to the acoustic waves of earthquake; (e) the pre-seismic activity consisting of a set of fast westward TIDs, and the comparison with neighboring days; (f) the location estimation of the tsunami wavefront along the coast and the possible use as early warning. Finally, we report disturbances that had not been previously published with a possible application to local and real-time detection of tsunamis.

Ocean Observations Required to Minimize Uncertainty in Global Tsunami Forecasts, Warnings, and Emergency Response

It is possible that no catastrophe has mobilized the global ocean science and coastal emergency management communities more than the 2004 Indian Ocean tsunami. Though the Pacific tsunami threat was recognized, and a warning system had been in place since 1965, there was no warning system in the Indian Ocean, and almost 230,000 people perished. More broadly, the event highlighted critical gaps in global tsunami science and observation systems. In 2004, real-time coastal and deep-ocean observation systems were almost nonexistent. Tsunami sources were inferred based on rough seismic parameters. Since then, tremendous strides have been made under the auspices of IOC/UNESCO toward better understanding tsunami mechanisms, deploying advanced real-time tsunami observation systems, and establishing tsunami warning and mitigation systems for the four main ocean basins at risk from tsunamis. Nevertheless, significant detection, measurement, and forecast uncertainties remain to meet emergency response and community needs. A new generation of ocean sensing capabilities presents an opportunity to address several of these uncertainties. Ocean bottom pressures can be measured over dense, multisensor grids linking stand-alone buoy systems with emerging capabilities like fiber-optic cables. The increasing number of coastal sea-level stations can better verify forecasts and account for local variability. In addition, GNSS sensors may be able to provide solid-earth data needed to define seismic tsunami sources more precisely in the short timescales required. When combined with advances in seismology, other emerging techniques, and state-of-the-art modeling and computational resources, these capabilities will enable more timely and accurate tsunami detection and measurement to meet identified user needs and save lives. Because of these advances in detection and measurement, the opportunity exists to greatly reduce and/or quantify uncertainties associated with forecasting tsunamis. Providing more timely and accurate information related to tsunami location, arrival time, height, inundation, and duration would improve public trust and confidence and fundamentally alter tsunami emergency response. Additionally, this capability could be integrated with related fields (e.g., storm surge, sea-level rise, tide predictions, and ocean forecasting) to develop and deploy one continuous, real-time, accurate depiction of the always moving boundary that separates ocean from coast, wet from dry, and, sometimes, life from death.

Development and Sea Test Results of a Deep-Sea Tsunami Warning Buoy System

AbstractTsunamis are catastrophic ocean waves that could cause devastating damage to human lives, properties, and coastal infrastructures. This article presents the design and sea test results of a deep-sea tsunami warning buoy system. The system consists of a seafloor tsunami detection subsystem and a surface buoy. The tsunami detection subsystem monitors the tsunami waves through seafloor water pressure measurement. Detection of tsunami waves is achieved by separating the influence of astronomical tidal waves from the seafloor measurements via a cubic polynomial extrapolation method. The deep seafloor measurements and the tsunami detection results are transmitted in real time from the seafloor subsystem to the surface buoy via underwater acoustic communications; the buoy then relays the data to an onshore tsunami warning center via satellite links. The tsunami warning buoy system was evaluated in four deep-sea tests at different locations. In the last sea test, the system achieved an effective working duration of 108 consecutive days. This article analyzes the causes of false alarms and data transmission failures in the sea tests and puts forward effective solutions for system improvement. The system design and the sea test results could serve as references for future development of deep-sea infrastructures.

Magnetic Signals at Easter Island During the 2010 and 2015 Chilean Tsunamis Compared with Numerical Models

Tsunami flow across the geomagnetic field induces electric currents in both the ocean and the ionosphere. These currents generate secondary magnetic fields, observable at the seafloor and on land. Magnetic field disturbances during two Chilean tsunamis (2010 and 2015) were recorded at Easter Island Observatory. These tsunamis were produced after the earthquakes in Chile on February 27, 2010, at 06:34 UTC, and September 16, 2015, at 22:55 UTC, respectively. Differences between existing studies regarding the origin of the tsunamigenic disturbances, and the lack of studies using a numerical model for both the water velocity and the induced magnetic field, motivated us to compare magnetic records with computed magnetic fields for the two events. Modeled disturbances were calculated by applying the Biot–Savart law to tsunami simulations. Our model can calculate tsunami-induced perturbations in the vertical component of the geomagnetic field, obtaining a good agreement with the observations. We hypothesize that the magnetic measurements may be produced by a combination of oceanic and ionospheric electric currents. Our analysis further reveals that even a relatively small tsunami, such as the one produced by the 2015 $$M_\text {w}$$ 8.2 earthquake, induces an observable magnetic perturbation due to the water movement. Future improvements to our model may allow us to identify situations in which magnetic variations precede the tsunami arrival, thereby allowing early tsunami detection.