Figure 1 - uploaded by Paul M Whitmore
Content may be subject to copyright.
Map of the Northeast Pacific Ocean showing DART stations, the SAO seismic station (square) and the epicenters of earthquakes (stars) that have set DART systems into tsunami event mode. These DART systems (dots) are indicated in orange while other DART systems, presenting in place, are shown in blue.
Source publication
Over the period October 1999–January 2001, there were four separate occasions in which real-time reporting tsunami DART systems, deployed by NOAA in the North Pacific, were set into tsunami event reporting mode by regional earthquakes. Fortunately, none of these generated a dangerous tsunami. To go into event mode, the high-frequency fluctuations i...
Contexts in source publication
Context 1
... the period October 1999 to January 2001, there were four occa- sions (Table 1) in which regional earthquakes set DART systems (Fig. 1) into event mode. Rather than being activated by tsunami waves, this was done by seismic waves from the earthquakes. Seismic-wave activation of the DART systems has proven to be a very useful mechanism for alerting the Warning Centers that a tsunami may have been generated and to set in motion an analysis of the real-time reported DART ...
Context 2
... example we will use to illustrate seismic wave triggering of DART sys- tems is the event associated with the 16 October 1999 Hector Mine earth- quake. The epicenter of the M w 7.1 earthquake ( Fig. 1; Table 2) was located in southeastern California, well away from the ocean. A DART station (D123) was deployed during this time off Monterey Bay in 3138 m of water, some 608 km WNW from the epicenter. Providing the broadband seismic data for the analysis was the San Andreas Observatory (SAO in Fig. 1), located 108 km ENE of the D123 ...
Context 3
... The epicenter of the M w 7.1 earthquake ( Fig. 1; Table 2) was located in southeastern California, well away from the ocean. A DART station (D123) was deployed during this time off Monterey Bay in 3138 m of water, some 608 km WNW from the epicenter. Providing the broadband seismic data for the analysis was the San Andreas Observatory (SAO in Fig. 1), located 108 km ENE of the D123 station and 525 km from the epicenter. Since both the D123 and SAO stations were located along similar bear- ings (290 • T and 297 • T, respectively) relative to the epicenter, we can assume that the seismic waves observed at SAO (Fig. 3) are similar to those prop- agating past D123. However, because ...
Context 4
... an operational point of view it appears that the 3 cm H 2 O threshold is fully adequate for the present DART array, in terms of activating the event mode based on seismic surface waves for earthquake magnitudes ≥7.0 and epicenter distances ≤610 km. DART systems farther away (Fig. 1) from the epicenters were not set into event mode by these same earthquakes. Earthquakes of these magnitudes are the kind that are of concern with regard to generating dangerous trans-Pacific tsunamis, the measurement of which is the primary function of the DART array. The threshold is evidently high enough that the numerous, smaller ...
Context 5
... This is important because it is necessary to avoid unduly prolonging the period of time during which the systems are in event mode, which will drain the batteries, or setting DART systems into this mode when there is essentially no chance that a dangerous trans- Pacific tsunami has been generated. The M w 6.2 Blanco Fracture Zone earthquake ( Fig. 1; Table 1) did activate the D130 system, but this is the largest magnitude event ever observed in this offshore region. The recent broadband ocean bottom seismometer projects have provided a much better understanding of the background BP noise as it affects the operation of the DART systems. As these projects expand geographically in ...
Similar publications
An uplift of the ocean bottom caused by a submarine earthquake can generate Acoustic-Gravity Waves (AGW), progressive compression-type waves that travel at near the speed of sound in water. Recent studies indicate that as AGW travel they leave measurable bottom pressure signatures, which can act as tsunami precursors. In this regard, it is anticipa...
A three-dimensional seismic wave speed model in the Kanto region of Japan was developed using adjoint tomography for application in the effective reproduction of observed waveforms. Starting with a model based on previous travel time tomographic results, we inverted the waveforms obtained at seismic broadband stations from 140 local earthquakes in...
Citations
... where negative values of K would correspond to an overall good contribution of SMART cables and vice versa. We note while each instrument has a different frequency and pressure response, SMART cables are significantly more sensitive at short frequencies and to smaller amplitudes (e.g., Mofjeld et al. 2001;Howe et al. 2019). However, for consistency as well as for practical purposes, here we assume a common detection threshold of 2 cm following the example of Meinig et al. (2005). ...
We present results from a series of exploratory numerical experiments based on ocean bottom pressure and seismic data from a simulated linear array of SMART cable stations off the trench in the Sumatra-Java region. We use six rupture scenarios to calculate tsunami propagation using hydrodynamic simulations. Through these experiments we show that such an addition would result in up to several hours of improvement in the detection of earthquakes and tsunamis compared to the existing (minimal) DART systems in the northern and southern Indian Ocean. By simulating tsunamis from 58 submarine landslide scenarios in the region, we show that the SMART system can provide invaluable information in early warning against landslide tsunamis. We also calculate seismic phase arrival times from six source scenarios at existing seismic stations and our proposed SMART cables. Statistical analysis of our results shows that inclusion of such a SMART array can improve the important network parameters for the detection, evaluation and locating of seismic events.
... An important feature of the DART records is the strong high-frequency oscillations caused by the Rayleigh waves (Rw), which are partly measured by open ocean bottom sensors, but not by coastal tide gauges (cf. Mofjeld et al., 2001). The Rw oscillations began almost immediately after the main earthquake shock and continued oscillating for more than an hour (Fig. 5b). ...
The major (Mw 8.2) intraplate normal-fault earthquake of 8 September 2017 in the Gulf of Tehuantepec (Chiapas, Mexico) generated a strong tsunami that severely impacted the nearby coasts of Mexico and Central America. Tsunami waves in the near-field area were measured by seventeen high-resolution coastal tide gauges and by three open-ocean DART stations anchored offshore from the affected region. Data from these sites, together with those from four distant DARTs, were used for comprehensive analyses of the 2017 event. De-tided sea level time series were examined to determine the statistical and spectral characteristics of the 2017 tsunami waves along the Mexican and Central American coastline. The characteristics of the recorded waves from this near-field event were compared with those from two great far-field events: the 2010 Chile and the 2011 Tohoku tsunamis. Maximum trough-to-crest wave heights for the 2017 tsunami were recorded at Puerto Chiapas (351 cm), Salina Cruz (209 cm), Acapulco (160 cm), Huatulco (137 cm) and Acajutla, El Salvador (118 cm). While maximum 2010 and 2011 tsunami waves were observed at specific “hot spots” (sites with a high Q-factor and pronounced resonant properties, such as Manzanillo and Acapulco), the “strengths” of the recorded 2017 tsunami waves were mostly determined by distance from the source. Contrary to the maximum wave heights, the general spectral properties of the tsunami signals for all three events were highly similar at a given coastal site and mainly resemble the spectral structure of background oscillations at the same site. This similarity indicates that the frequency properties of the tsunami waveforms for a steady-state tsunami signal are mainly determined by local topographic features rather than by the source parameters. Estimates of the “colour” of an event (i.e., the open-ocean tsunami frequency content) show that the 2017 Chiapas tsunami was mostly “reddish” (long-period), with 68% (DART 43413) to 87% (DART 43412) of the total tsunami energy related to waves with periods > 35 min. In contrast, the 2010 and 2011 tsunamis were “reddish-blue”, with 48–57% associated with long-period waves (> 35 min) and 52–43% with short-period waves (2–35 min). The dominant periods of the tsunami waves were mostly linked to the shape, length, and width of the source region: the larger the source and the shallower its depth, the longer the periods of the generated tsunami waves. The complicated structure of the source explains the saturated and wide frequency-band character of the tsunami spectra. Our analysis also reveals an anisotropic nature to the 2017 tsunami waves; waves that propagated northeastward along the mainland coast of North America and southeastward along the Central American coast were significantly different from those that propagated southwestward, normal to the source orientation. This aspect of the wave field appears to be related to two distinct types of waves; “trapped (edge) waves” retained on the shelf (which plays the role of a “wave guide”), and “leaky waves” that radiate into the open ocean.
... The authors used the GPS time series and bottom pressure sensor records (BPR) from the NOAA website for simulations. Mofjeld et al. (2001) evaluated slip depth and rupture process using Cornell Multi-Grid Coupled Tsunami Model code already given by Smith and Sandwell (1997). Later, Ide et al. (2011) analyzed fifty seismogram data to conclude that an earthquake rupture is a precursor to a tsunami. ...
In the last fifteen years, tsunami science has progressed at a rapid pace. Three major tsunamis: The Indian Ocean in 2004, the 2011 Tohoku tsunami, and the 2018 Palu tsunami were significant landmarks in the history of tsunami science. All the three tsunamis, as mentioned, suffered from either no warning or poor reception of the alerts issued. Various lessons learned, consequent numerical models proposed, post-2004 tsunami damage findings manifested into solutions. However, the misperceived solutions led to a disastrous impact of the 2011 Tohoku event. In the following years, numerous improvements in warning systems and community preparedness frameworks were proposed and implemented. The contributions and new findings have added multi-fold advancements to tsunami science progress. Later, the 2018 Palu tsunami happened and again led to a massive loss of life and property. The warning systems and community seemed un-prepared for this non-seismic tsunami. A significant change is to take place in tsunami science practices and solutions. The 2018 tsunami is one of the most discussed and researched events concerning the palaeotsunami records, damage assessment, and source findings. In the new era, using machine learning and deep learning prevails in all the fields related to tsunami science. This article presents a complete 15-year bibliometric analysis of tsunami research from Scopus and Web of Science (WoS). The review of majorly cited documents in the form of a progressing storyline has highlighted the need for multidisciplinary research to design and propose practical solutions.
... A model for what is recorded by a DART R buoy during a tsunami event has three components: a tsunami signal, tidal fluctuations and background noise. The latter is due to seismic, meteorological , measurement and other nontidal effects (Cartwright et al., 1987; Niiler et al., 1993; Webb, 1998; Cummins et al., 2001; Mofjeld et al., 2001; Zhao and Alford, 2009). The purpose of detiding is to compensate for tidal fluctuations in the recorded data (Consoli et al., 2014). ...
U.S. Tsunami Warning Centers use real-time bottom pressure (BP) data
transmitted from a network of buoys deployed in the Pacific and Atlantic Oceans
to tune source coefficients of tsunami forecast models. For accurate
coefficients and therefore forecasts, tides at the buoys must be accounted for.
In this study, five methods for coefficient estimation are compared, each of
which accounts for tides differently. The first three subtract off a tidal
prediction based on (1) a localized harmonic analysis involving 29 days of data
immediately preceding the tsunami event, (2) 68 pre-existing harmonic
constituents specific to each buoy, and (3) an empirical orthogonal function
fit to the previous 25 hrs of data. Method (4) is a Kalman smoother that uses
method (1) as its input. These four methods estimate source coefficients after
detiding. Method (5) estimates the coefficients simultaneously with a
two-component harmonic model that accounts for the tides. The five methods are
evaluated using archived data from eleven DART buoys, to which selected
artificial tsunami signals are superimposed. These buoys represent a full range
of observed tidal conditions and background BP noise in the Pacific and
Atlantic, and the artificial signals have a variety of patterns and induce
varying signal-to-noise ratios. The root-mean-square errors (RMSEs) of least
squares estimates of sources coefficients using varying amounts of data are
used to compare the five detiding methods. The RMSE varies over two orders of
magnitude between detiding methods, generally decreasing in the order listed,
with method (5) yielding the most accurate estimate of source coefficient. The
RMSE is substantially reduced by waiting for the first full wave of the tsunami
signal to arrive. As a case study, the five method are compared using data
recorded from the devastating 2011 Japan tsunami.
... It should be noted that the 15 s period of integration is based on extensive studies of seismic-wave contributions to bottom pressure fluctuations in DART tsunami array records as summarized by MOFJELD et al. (2001). Investigating the mechanism by which Rayleigh waves generate fluctuations in the bottom pressure unit, the authors indicate that direct acceleration in the bottom pressure unit is observed for frequencies up to 60 MHz (17 s). ...
... Surface seismic Rayleigh waves generated by regional and distant earthquakes, microseisms and micro-tsunamis, and meteorologically generated fluctuations, provide additional noise signals in the bottom pressure records (MOFJELD, 2009;MOFJELD et al., 2001;EBLÉ and GONZÁ LEZ, 1991). Rayleigh waves propagate over long distances with very small dissipation that is why in the bottom pressure records their signal can be much stronger than the tsunami signal itself even at locations far away from the earthquake epicenter. ...
In the early 1980s, the United States National Oceanic and Atmospheric Administration Pacific Marine Environmental Laboratory established the fundamentals of the contemporary tsunameter network deployed throughout the world oceans. The decades of technological and scientific advancements that followed led to a robust network that now provides real-time deep-ocean tsunami observations routinely incorporated into operational procedures of tsunami warning centers around the globe. All aspects of the network, from research to operations, to data archive and dissemination, are conducted collaboratively between the National Data Buoy Center, the Pacific Marine Environmental Laboratory, and the National Geophysical Data Center, with oversight by the National Weather Service. The National Data Buoy Center manages and conducts all operational network activities and distributes real-time data to the public. The Pacific Marine Environmental Laboratory provides the research component in support of modeling and network enhancements for improved forecasting capability. The National Geophysical Data Center is responsible for the processing, archiving, and distribution of all retrospective data and integrates DART® tsunameter data with the National Geophysical Data Center global historical tsunami database. The role each agency plays in collecting, processing, and disseminating observations of deep-ocean bottom pressure is presented along with brief descriptions of data processing procedures. Specific examples of challenges and the approaches taken to address these are discussed. National Geophysical Data Center newly developed and available tsunami event web pages are briefly described and demonstrated with processed data for both the Tohoku 11 March 2011 and the Haiti 12 January 2010 tsunami events.
... In addition, infragravity motions dominate the run-up of water onto the beach face [Raubenheimer and Guza, 1996], and are associated with morphological features such as beach cusps [Ciriano et al., 2005] and flooding during storms. Farther offshore, infragravity motions contaminate ocean bottom seismology measurements used to detect tsunamis [Mofjeld et al. 2001] and to predict microseisms [Rhie and Romanowicz, ...
Ocean surface infragravity waves (periods from 20 to 200 s) observed along the southern California coast are shown to be sensitive to the bottom topography of the shelf region, where propagation is linear, and of the nearshore region, where nonlinearity is important. Infragravity waves exchange energy with swell and wind waves (periods from 5 to 200 s) via conservative nonlinear interactions that approach resonance with decreasing water depth. Consistent with previous results, it is shown here that as waves shoal into water less than a few meters deep, energy is transfered from swell to infragravity waves. In addition, it is shown here that the apparent dissipation of infragravity energy observed in the surfzone is the result of nonlinear energy transfers from infragravity waves back to swell and wind waves. The energy transfers are sensitive to the shallow water bottom topography. On nonplanar beach profiles the transfers, and thus the amount of infragravity energy available for reflection from the shoreline, change with the tide, resulting in the tidal modulation of infragravity energy observed in bottom-pressure records on the continental shelf. The observed wave propagation over the shelf topography is dominated by refraction, and the observed partial reflection from, and transmission across, a steep-walled submarine canyon is consistent with long-wave theory. A generalized regional model incorporating these results predicts the observed infragravity wave amplitudes over variable bottom topography. Includes bibliographical references. Thesis (Ph. D.)--Joint Program in Physical Oceanography (Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences; and the Woods Hole Oceanographic Institution), 2006.
Ocean-bottom pressure and acceleration data simultaneously recorded by the DONET seafloor network during the 2011 Tohoku earthquake approximately 800 km from the earthquake epicenter are processed and analyzed. The close location of pressure and acceleration sensors together with the high data-sampling rate enable us to quantitatively examine and interpret pressure variations together with ocean-bottom acceleration for the first time to our knowledge. To interpret observed data, we introduce a set of characteristic frequencies that enable us to identify physical processes responsible for water layer behaviour dependent on the frequency of ocean-bottom oscillations. Explicit formulas are given for calculating all of the characteristic frequencies, which are the basis for introducing nonoverlapping frequency bands, i.e., hydroacoustic waves, forced oscillations, and gravity waves. The physical correctness of such a subdivision is confirmed by the high coherence and nearly zero phase difference between in-situ measured pressure and acceleration variations observed in the forced oscillation frequency band – a band neither hydroacoustic nor gravity waves are generated by ocean-bottom oscillation because the water layer simply follows the ocean bottom, generating forced oscillations. The dominant, long-lasting pressure fluctuations recorded by DONET during the 2011 earthquake are associated with the forced oscillation, or, more precisely, with water and sedimentary layer coupling oscillation. DONET clearly observed the 2011 Tohoku tsunami signal during more than 24 hours following the earthquake. In contrast to DART records, phase dispersion was not manifested in the tsunami signals registered by DONET.
The Web-enabled Awareness Research Network (WARN) implements the data acquisition, event detection and correlation aspects of an integrated geo-hazard alert system. The intent of the project is to lead to the delivery of early warning to urban areas, coastal communities and key infrastructure operators.
Offshore observations make it possible to detect tsunamis in advance prior to their arrivals at the shoreline. For this purpose, ocean bottom pressure gauges are widely used. However, in near-and intermediate fields, ocean bottom pressure records usually exhibit a complicated interference of signals related not only to gravitational wave (i.e., tsunami), but also to hydroacoustic and seismic waves. Network of offshore observatories recently deployed in Japan is capable of providing high sampling rate of records of ocean bottom pressure and seismic (acceleration and velocity) signals. In the present study, by taking advantage of simultaneous measurements of pressure and seismic signals that were recorded during the recent tsunamigenic earthquakes, i.e., the 2011 Tohoku earthquake and the related 2013 October earthquake, we reveal particular features of these signals. The bottom pressure follows the bottom acceleration in the inter-mediate frequency band.
Deep-ocean tsunami measurements play a major role in understanding the physics of tsunami wave generation and propagation, and in improving the effectiveness of tsunami warning systems. This paper provides an overview of the history of tsunami recording in the open ocean from the earliest days, approximately 50 years ago, to the present day. Modern tsunami monitoring systems such as the self-contained Deep-ocean Assessment and Reporting of Tsunamis and innovative cabled sensing networks, including, but not limited to, the Japanese bottom cable projects and the NEPTUNE-Canada geophysical bottom observatory, are highlighted. The specific peculiarities of seafloor longwave observations in the deep ocean are discussed and compared with observations recorded in coastal regions. Tsunami detection in bottom pressure observations is exemplified through analysis of distant (22,000 km from the source) records of the 2004 Sumatra tsunami in the northeastern Pacific.
