Tsunami Detection Research Articles

Intensive seismic activity around the Nankai trough revealed by DONET ocean-floor seismic observations

Megathrust earthquakes anticipated in the Nankai trough will likely cause severe damage in central and western Japan. The Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET), a network of permanent ocean-bottom seismic stations for the early detection of earthquakes and tsunamis developed by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC), is in place above the expected source region of such earthquakes. Data from DONET sensors are transmitted in real time to our laboratory at JAMSTEC. Intensive ongoing seismic activity is being detected off the Kii Peninsula by DONET, mainly distributed in three clusters that overlap with the aftershock distribution of the 2004 off the Kii Peninsula earthquakes (MJMA = 7.1 and 7.4), and most of them are also aftershocks of the 2004 earthquakes. Some are linearly distributed on a different trend from the strike of the 2004 foreshock and mainshock fault planes. This result implies that the 2004 events triggered seismic activity on different faults on the subducting Philippine Sea plate. We also observed changes in seismic activity caused by the 2011 Tohoku-oki earthquake. These results could not have been obtained with on-land observations alone, which indicates the importance of DONET for monitoring seismic activity along the Nankai trough.

TerraSAR-X画像の機械学習による津波被災地の自動検出

A method for rapid detection of tsunami devastated areas using multi-temporal TerraSAR-X data is proposed. To develop the method, machine learning algorithm, a branch of artificial intelligence (AI), is applied. We focus on the multiple bounce reflection which is a specific feature on Synthetic Aperture Radar (SAR) data to estimate building devastated areas. Finally, classifiers which enable automated classifications of damage patterns into predicted damage classes were built. The evaluation of the model was conducted through cross-validation and the best accuracy was obtained as 89.2 %.

Lipa, B. et al. Tsunami Arrival Detection with High Frequency (HF) Radar. Remote Sens. 2012, 4, 1448-1461

We neglected to state that the radar data from Tokushima and Anan is owned by the Ministry of Land, Infrastructure, Transport and Tourism, Shikoku Regional Development Bureau, Komatsushima port and airport office, Japan. Lipa et al. [1] describe results on tsunami detection using data measured by two radars located at Tokushima and Anan on the Kii channel. This data is owned by the Ministry of Land, Infrastructure, Transport and Tourism, Shikoku Regional Development Bureau, Komatsushima port and airport office, Japan. Locations of the radars are shown in Figure 4(a,c) [1]. Results of the data analysis are given in Section 3.1.2, plotted in Figure 6 and listed in Table 1 [1]. [...]

High Frequency (HF) Radar Detection of the Weak 2012 Indonesian Tsunamis

We report here on the observation and offline detection of the weak tsunamis generated by earthquakes near Indonesia on 11 April 2012 using radar systems and tide gauges on the coasts of Sumatra and the Andaman Islands. This work extends the previous observations of the much stronger 2011 Japan tsunami. The distance offshore at which the tsunami can be detected, and hence the warning time provided, depends primarily on the bathymetry: the wider the shallow continental shelf, the greater this time. The weak Indonesia tsunamis were detected successfully in spite of the narrow shallow-water shelf offshore from the radar systems. Larger tsunamis could obviously be detected further from the coast. This paper provides further confirmation that radar is an important tool to aid in tsunami observation and warning.

Development of tsunami early warning systems and future challenges

Abstract. Fostered by and embedded in the general development of information and communications technology (ICT), the evolution of tsunami warning systems (TWS) shows a significant development from seismic-centred to multi-sensor system architectures using additional sensors (e.g. tide gauges and buoys) for the detection of tsunami waves in the ocean. Currently, the beginning implementation of regional tsunami warning infrastructures indicates a new phase in the development of TWS. A new generation of TWS should not only be able to realise multi-sensor monitoring for tsunami detection. Moreover, these systems have to be capable to form a collaborative communication infrastructure of distributed tsunami warning systems in order to implement regional, ocean-wide monitoring and warning strategies. In the context of the development of the German Indonesian Tsunami Early Warning System (GITEWS) and in the EU-funded FP6 project Distant Early Warning System (DEWS), a service platform for both sensor integration and warning dissemination has been newly developed and demonstrated. In particular, standards of the Open Geospatial Consortium (OGC) and the Organization for the Advancement of Structured Information Standards (OASIS) have been successfully incorporated. In the FP7 project Collaborative, Complex and Critical Decision-Support in Evolving Crises (TRIDEC), new developments in ICT (e.g. complex event processing (CEP) and event-driven architecture (EDA)) are used to extend the existing platform to realise a component-based technology framework for building distributed tsunami warning systems.

Improving tsunami warning using commercial ships

Accurate and rapid detection and assessment of tsunamis is critical for effective mitigation. We show here that a modest ∼10 cm tsunami from the M8.8 27 Feb 2010 Maule, Chile earthquake was detected by kinematic Global Positions System (GPS) solutions from a ship underway in the open ocean ‐ the first time shipboard tsunami detection has been achieved. Our results illustrate how the commercial shipping fleet represents a vast infrastructure of potential open ocean GPS platforms on shipping lanes that provide extremely good spatial coverage around most tsunamigenic source regions. Given the affordability of geodetic GPS systems, and ever‐improving satellite communications, it would be possible to equip a significant portion of the shipping fleet with real‐time‐streamed GPS systems and create a cost‐effective tsunami monitoring network with denser and more distributed coverage. We project that such a system would have detected the 2004 Indian Ocean tsunami in less than an hour.

Compare and Draw Lessons — Designing Resilience for Communities at Risk: Socio-technical Decision Support for Near-field Tsunamis

Since the catastrophic 2004 Sumatran earthquake and tsunami, tsunami early warning systems have been established in every major ocean. These systems rely on Deep-ocean sensors for Assessment and Reporting of Tsunamis (DART buoys) as well as seismic stations and tidal gauges for detection. Yet these systems have largely missed the early detection of near-field tsunamis. To evaluate the potential impact of near-field tsunamis generated by earthquakes offshore of Padang, Indonesia, we present a design that couples an underwater sensor network with a land-based communications network to support risk assessment and response operations among emergency response organizations, including warning dissemination to the public.

Acoustic‐gravity waves interacting with the shelf break

A mathematical solution of the two‐dimensional linear problem of an acoustic‐gravity wave propagating over a bottom with a step, in a slightly compressible ocean, is presented. Expressions for the flow field on both sides of the step are derived. Furthermore, an extended problem is given that provides a solution for a group of acoustic‐gravity waves, generated by a submarine earthquake, propagating toward a continental shelf. The dynamic bottom pressure produced by the acoustic‐gravity waves is probably measurable, especially at the vicinity of the seaward face of the shelf break where incident and reflected modes appear simultaneously. A successful recording of such bottom pressures could assist in the early detection of tsunami.

Q‐Advanced Models for Tsunami and Rogue Waves

A wavelet Kq(t), that satisfies the q‐advanced differential equation for q > 1, is used to model N‐wave oscillations observed in tsunamis. Although q‐advanced ODEs may seem nonphysical, we present an application that model tsunamis, in particular the Japanese tsunami of March 11, 2011, by utilizing a one‐dimensional wave equation that is forced by Fq(t, x) = Kq(t)qSin(x). The profile Fq is similar to tsunami models in present use. The function is a wavelet that satisfies a q‐advanced harmonic oscillator equation. It is also shown that another wavelet, , matches a rogue‐wave profile. This is explained in terms of a resonance wherein two small amplitude forcing waves eventually lead to a large amplitude rogue. Since wavelets are used in the detection of tsunamis and rogues, the signal‐analysis performance of Kq and is examined on actual data.

Tsunamis: detection, monitoring, and early-warning technologies

The devastating impacts of tsunamis have received increased focus since the Indian Ocean tsunami of 2004, the most destructive tsunami in over 400 years of recorded history. The tsunamis that occurred as a result of the earthquake in Japan in March 2011 further emphasized the need for detection, monitoring, and early-warning technologies. This professional reference is the first of its kind: it provides a globally inclusive review of the current state of tsunami detection technology and will be a much-needed resource for oceanographers and marine engineers working to upgrade and integrate their tsunami warning systems. It focuses on the two main tsunami warning systems (TWS): International and Regional. Featured are comparative assessments of detection, monitoring, and real-time reporting technologies. The challenges of detection through remote measuring stations are also addressed, as well as the historical and scientific aspects of tsunamis. * Offers readers the only source of practical content on the technological details of the subject* Written by a tsunami detection and monitoring expert who has 32 years of experience in the field* Companion web site featuring multi-media components, timely updates on fast-paced technological developments, and an online forum where scientists can exchange ideas, discuss technological updates and provide the author with valuable feedback

Decision analysis for a tsunami detection system – case study: Sri Lanka

The massive devastation of the Indian Ocean mega tsunami in 2004, clearly calls for an efficient early warning system for the Indian Ocean countries. The ‘Regional Watch Provider’ system currently planned makes some countries entirely dependent on the watch providers. We discuss a feasible and reliable tsunami detection mechanism for Sri Lanka that would give it some independent information for decision making purposes. It contemplates Sri Lanka deploying its own additional detection tools. A stand-alone tide gauge system, a buoy system and a combined gauge and buoy system are tested with the status quo or ‘do nothing’ alternative. A decision analysis exercise investigates the probability of tsunamis, probability of failures of each detection system, the probability of successful completion of an evacuation and the probability of false warnings which have their own costs. This paper concludes with the derived recommendations for a preferred tsunami detection system for Sri Lanka.

Filtering skill for turbulent signals for a suite of nonlinear and linear extended Kalman filters

The filtering skill for turbulent signals from nature is often limited by errors due to utilizing an imperfect forecast model. In particular, real-time filtering and prediction when very limited or no a posteriori analysis is possible (e.g. spread of pollutants, storm surges, tsunami detection, etc.) introduces a number of additional challenges to the problem. Here, a suite of filters implementing stochastic parameter estimation for mitigating model error through additive and multiplicative bias correction is examined on a nonlinear, exactly solvable, stochastic test model mimicking turbulent signals in regimes ranging from configurations with strongly intermittent, transient instabilities associated with positive finite-time Lyapunov exponents to laminar behavior. Stochastic Parameterization Extended Kalman Filter (SPEKF), used as a benchmark here, involves exact formulas for propagating the mean and covariance of the augmented forecast model including the unresolved parameters. The remaining filters use the same nonlinear forecast model but they introduce model error through different moment closure approximations and/or linear tangent approximation used for computing the second-order statistics of the augmented stochastic forecast model. A comprehensive study of filter performance is carried out in the presence of various moment closure errors which are enhanced by additional model errors due to incorrect parameters inducing additive and multiplicative stochastic biases. The estimation skill of the unresolved stochastic parameters is also discussed and it is shown that the linear tangent filter, despite its popularity, is completely unreliable in many turbulent regimes for both parameter estimation and filtering; moreover, regimes of filter divergence for the linear tangent filter are identified. The results presented here provide useful guidelines for filtering turbulent, high-dimensional, spatially extended systems with more general model errors, as well as for designing more skillful methods for superparameterization of unresolved intermittent processes in complex multi-scale models. They also provide unambiguous benchmarks for the capabilities of linear and nonlinear extended Kalman filters using incorrect statistics on an exactly solvable test bed with rich and realistic dynamics.

Tsunami signature in the ionosphere: A simulation of OTH radar observations

In the last ten years ionospheric anomalies following major earthquakes and tsunamis have been detected. Global Positioning System (GPS) and altimeters have been proven effective for this purpose, through Total Electron Content (TEC) measurement. Most of these ionospheric anomalies are deterministic and reproducible by numerical modeling via the coupling mechanism through ocean, neutral atmosphere and ionosphere. Numerical modeling supplies also useful support in the estimation of expected ionospheric effects and in the exploration and identification of new techniques to detect ionospheric tsunami signatures. We explore here a new ground‐based technique, nominally the use of over‐the‐horizon (OTH) radars, for tsunami detection through ionospheric monitoring. OTH radars operate in High Frequency (HF) band and sounding the bottomside ionosphere they could anticipate the detection of tsunami‐driven Internal Gravity Waves (IGW). To validate this hypothesis, we use HF numerical ray‐tracing to simulate synthetic OTH radar measurements through a 3D tsunami‐driven IGW ionospheric model. Our simulations clearly identify the tsunami signature in the OTH radar measurements one hour and a half before the tsunami arrival on the coast. The large coverage of OTH radar and its sensitivity to plasma anomalies open new perspectives in the oceanic monitoring and future tsunami warning systems.

Detection of the 2010 Chilean tsunami using satellite altimetry

Abstract. Tsunamis are difficult to detect and measure in the open ocean because the wave amplitude is much smaller than it is closer to shore. An effective early warning system, however, must be able to observe an impending tsunami threat far away from the shore in order to provide the necessary lead-time for coastal inhabitants to find safety. Given the expansiveness of the ocean, sensors capable of detecting the tsunami must also have very broad areal coverage. The 2004 Sumatra-Andaman tsunami was definitively detected in the open ocean from both sea surface height and sea surface roughness measurements provided by satellite altimeters. This tsunami, however, was exceptionally strong and questions remain about the ability to use such measurements for the detection of weaker tsunamis. Here we study the 2010 Chilean tsunami and demonstrate the ability to detect the tsunami in the open ocean. Specifically, we analyze the utility of filtering in extracting the tsunami signal from sea surface height measurements, and, through the use of statistical analyses of satellite altimeter observations, we demonstrate that the 2010 Chilean tsunami induced distinct and detectable changes in sea surface roughness. While satellite altimeters do not provide the temporal and spatial coverage necessary to form the basis of an effective early warning system, tsunami-induced changes in sea surface roughness can be detected using orbiting microwave radars and radiometers, which have a broad surface coverage across the satellite ground track.

Automatic, real-time detection and characterization of tsunamis in deep-sea level measurements

The already existing algorithms for automatic, real-time tsunami detection in deep-sea level measurements, although capable of detecting a tsunami, fail in characterizing it in terms of both amplitude and period. Such a characterization is carried out by postprocessing the observations once available. A delay between tsunami detection and characterization should be therefore accepted. The present note suggests a simple modification of the existing algorithms capable of guaranteeing the contemporaneous detection and characterization of a tsunami, automatically and in real-time. Tests carried out using actually measured time series show the effectiveness of the presented modification.

Propagating tsunami wave and subsequent resonant response signals detected by HF radar in the Kii Channel, Japan

Signals from the tsunami waves induced by the March 11, 2011 moment magnitude ( M w ) 9.0 Tohoku-Oki earthquake and from subsequent resonances were detected as radial velocity variability by a high-frequency ocean surface radar (HF radar) installed on the eastern coast of the Kii Channel, at a range of about 1000 km from the epicenter along the eastern to southern coasts of Honshu Island. A time–distance diagram of band-passed (9–200 min) radial velocity along the beam reveals that the tsunami waves propagated from the continental shelf slope to the inner channel as progressive waves for the first three waves, and then natural oscillations were excited by the waves; and that the direction of the tsunami wave propagation and the axis of the natural oscillations differed from that of the radar beam. In addition, spectral analyses of the radial velocities and sea surface heights obtained in the channel and on the continental shelf slope suggest complex natural oscillation modes excited by the tsunami waves. The major advantage of the HF radars as tsunami detection is early warning as the tsunami is still far offshore. There is no doubt on this importance beside still technical and operational studies are needed. Our results adds a new role of the HF radars to measure the detailed surface current fields with high spatiotemporal resolution toward understanding detailed processes of resonant response to tsunami waves in coastal regions.

Algorithms for automatic, real-time tsunami detection in wind–wave measurements Part I: Implementation strategies and basic tests

Several, although not all, wind–wave gages are equipped with sensors capable of detecting sea-level oscillations within the tsunami frequency band. The present paper looks at the algorithms to be implemented in the software of these gages in order to automatically perform the real-time detection of a possible tsunami within recorded signals. In particular, a new algorithm is proposed and tested. The first part of the paper concentrates on the algorithms' characteristics, implementation strategies and basic testing. First of all, the situations in which wind–wave measurements are either essential, or useful for real-time tsunami detection are discussed. In the second place, already existing algorithms are recalled, specifying their characteristics and fields of application. Then, the characteristics of the new proposed algorithm – mainly based on an infinite impulse response, time domain filter – are illustrated and analyzed. Performance and efficiency of the considered algorithms are compared using synthetic time series. The second part of the paper discusses the algorithms' use in the framework of Tsunami Early Warning Systems (TEWS), testing them in actual cases.

Imaging and modeling the ionospheric airglow response over Hawaii to the tsunami generated by the Tohoku earthquake of 11 March 2011

[1] Although only centimeters in amplitude over the open ocean, tsunamis can generate appreciable wave amplitudes in the upper atmosphere, including the naturally occurring chemiluminescent airglow layers, due to the exponential decrease in density with altitude. Here, we present the first observation of the airglow tsunami signature, resulting from the 11 March 2011 Tohoku earthquake off the eastern coast of Japan. These images are taken using a wide-angle camera system located at the top of the Haleakala Volcano on Maui, Hawaii. They are correlated with GPS measurements of the total electron content from Hawaii GPS stations and the Jason-1 satellite. We find waves propagating in the airglow layer from the direction of the earthquake epicenter with a velocity that matches that of the ocean tsunami. The first ionospheric signature precedes the modeled ocean tsunami generated by the main shock by approximately one hour. These results demonstrate the utility of monitoring the Earth's airglow layers for tsunami detection and early warning.

Three-dimensional numerical modeling of tsunami-related internal gravity waves in the Hawaiian atmosphere

The tremendous tsunami following the 2011 Tohoku Earthquake produced internal gravity waves (IGWs) in the neutral atmosphere and large disturbances in the overlying ionospheric plasma while propagating through the Pacific ocean. To corroborate the tsunamigenic hypothesis of these perturbations, we use a 3D numerical modeling of the ocean-atmosphere coupling, to reproduce the tsunami signature observed in the airglow by the imager located in Hawaii and clearly showing the shape of the modeled IGW. The agreement between data and synthetics not only supports the interpretation of the tsunami-related-IGW behavior, but strongly shows that atmospheric and ionospheric remote sensing can provide new tools for oceanic monitoring and tsunami detection.

Structure and performance of a real-time algorithm to detect tsunami or tsunami-like alert conditions based on sea-level records analysis

Abstract. The goal of this paper is to present an original real-time algorithm devised for detection of tsunami or tsunami-like waves we call TEDA (Tsunami Early Detection Algorithm), and to introduce a methodology to evaluate its performance. TEDA works on the sea level records of a single station and implements two distinct modules running concurrently: one to assess the presence of tsunami waves ("tsunami detection") and the other to identify high-amplitude long waves ("secure detection"). Both detection methods are based on continuously updated time functions depending on a number of parameters that can be varied according to the application. In order to select the most adequate parameter setting for a given station, a methodology to evaluate TEDA performance has been devised, that is based on a number of indicators and that is simple to use. In this paper an example of TEDA application is given by using data from a tide gauge located at the Adak Island in Alaska, USA, that resulted in being quite suitable since it recorded several tsunamis in the last years using the sampling rate of 1 min.