scholarly journals Evaluation for hypocenter estimation error in the southwestern Kuril trench using Japan and Russia joint seismic data

2020 ◽  
Author(s):  
Masayoshi Ichiyanagi ◽  
Mikhaylov Valentin ◽  
Dmitry Kostylev ◽  
Yuri Levin ◽  
Hiroaki Takahashi
Keyword(s):  
Real Time ◽  
Seismic Data ◽  
Estimation Error ◽  
Tsunami Warning ◽  
Disaster Mitigation ◽  
Border Zone ◽  
Japan Meteorological Agency ◽  
Estimation Accuracy ◽  
Waveform Data ◽  
Kuril Trench

Abstract The southwestern Kuril trench is seismically active due to the subduction of the Pacific plate. Great earthquakes in this zone have frequently induced fatal disasters. Seismic monitoring and hypocenter catalogues provide fundamental information on earthquake occurrence and disaster mitigation. Real-time hypocenter and magnitude estimates are extremely crucial data for tsunami warning systems. However, this region is located in the international border zone between Japan and Russia. The Japan Meteorological Agency and Russian Academy of Sciences have routinely determined hypocenters and issued earthquake information independently. Waveform data have not yet been exchanged internationally in real time. Here, we evaluated how a hypothetical Japan-Russia joint seismic network could potentially improve the hypocenter estimation accuracy. Experiments using numerical and observed data indicated that the joint network extended the distance over which hypocenters can be accurately determined over 100 km eastward compared to the Japan network only. This fact suggests that joint seismic data have the potential to improve the hypocenter accuracy in this region, which would provide improved performance in gathering disaster information at the moment of a tsunami warning.

Capturing, Preserving, and Digitizing Legacy Seismic Data from the Montserrat Volcano Observatory Analog Seismic Network, July 1995–December 2004

2020 ◽  
Vol 91 (4) ◽  
pp. 2127-2140 ◽  
Author(s):  
Glenn Thompson ◽  
John A. Power ◽  
Jochen Braunmiller ◽  
Andrew B. Lockhart ◽  
Lloyd Lynch ◽  
...  
Keyword(s):  
Real Time ◽  
Seismic Data ◽  
Original Data ◽  
South Florida ◽  
Seismic Network ◽  
Quality Data ◽  
Spectral Amplitude ◽  
Assistance Program ◽  
Waveform Data ◽  
Amplitude Measurement

Abstract An eruption of the Soufrière Hills Volcano (SHV) on the eastern Caribbean island of Montserrat began on 18 July 1995 and continued until February 2010. Within nine days of the eruption onset, an existing four-station analog seismic network (ASN) was expanded to 10 sites. Telemetered data from this network were recorded, processed, and archived locally using a system developed by scientists from the U.S. Geological Survey (USGS) Volcano Disaster Assistance Program (VDAP). In October 1996, a digital seismic network (DSN) was deployed with the ability to capture larger amplitude signals across a broader frequency range. These two networks operated in parallel until December 2004, with separate telemetry and acquisition systems (analysis systems were merged in March 2001). Although the DSN provided better quality data for research, the ASN featured superior real-time monitoring tools and captured valuable data including the only seismic data from the first 15 months of the eruption. These successes of the ASN have been rather overlooked. This article documents the evolution of the ASN, the VDAP system, the original data captured, and the recovery and conversion of more than 230,000 seismic events from legacy SUDS, Hypo71, and Seislog formats into Seisan database with waveform data in miniSEED format. No digital catalog existed for these events, but students at the University of South Florida have classified two-thirds of the 40,000 events that were captured between July 1995 and October 1996. Locations and magnitudes were recovered for ∼10,000 of these events. Real-time seismic amplitude measurement, seismic spectral amplitude measurement, and tiltmeter data were also captured. The result is that the ASN seismic dataset is now more discoverable, accessible, and reusable, in accordance with FAIR data principles. These efforts could catalyze new research on the 1995–2010 SHV eruption. Furthermore, many observatories have data in these same legacy data formats and might benefit from procedures and codes documented here.

Practical Site-Specific Earthquake Early Warning Application

2009 ◽  
Vol 4 (4) ◽  
pp. 579-587 ◽  
Author(s):  
Katsuhisa Kanda ◽  
◽  
Tadashi Nasu ◽  
Masamitsu Miyamura
Keyword(s):  
Early Warning ◽  
Estimation Error ◽  
Seismic Intensity ◽  
Earthquake Early Warning ◽  
P Wave ◽  
Japan Meteorological Agency ◽  
Estimation Accuracy ◽  
Intensity Estimation ◽  
Site Specific ◽  
Wide Range

Real-time hazard mitigation we have developed using earthquake early warning (EEW) (1) enhances seismic intensity estimation accuracy and (2) extends the interval between when an EEW is issued and when strong tremors arrive. We accomplished the first point (enhancing seismic intensity estimation) by reducing estimation error to less than that commonly used based on an attenuation relationship and soil amplification factor by considering source-location and wave propagation path differences based on site-specific empiricism. We accomplished the second point (shortening the time between warnings and when tremors arrive) using a high-speed, reliable communication network for receiving EEW information from the Japan Meteorological Agency (JMA) and quickly transmitting warning signals to users. In areas close to quake epicenters, however, warnings may not arrive before the arrival of strong ground motions. The on-site warning system we developed uses P-wave pickup sensors that detect P-wave arrival at a site and predict seismic intensity of subsequent S-waves. We confirmed the on-site warning prototype’s feasibility based on numerical simulation and observation. We also developed an integration server for combining on-site warnings with JMA information to be applied to earthquakes over a wide range of distances. We installed a practical prototype at a construction site near the 2008 Iwate-Miyagi Inland Earthquake epicenter to measure its aftershocks because JMA EEW information was too late to use against the main shock. We obtained good aftershock results, confirming the prototype’s applicability and accuracy. Integration server combination logic was developed for manufacturing sites requiring highly robust, reliable control.

Differences in Subjective Estimation of Risks and Assessment for the Modified Tsunami Warning System by the Japan Meteorological Agency Among University Students Located in Damaged and Non-Damaged Prefectures Around the Period of the 2011 off Pacific Coast of Tohoku Earthquake

2014 ◽  
Vol 9 (4) ◽  
pp. 571-578 ◽  
Author(s):  
Erina Gyoba ◽  
Keyword(s):  
University Students ◽  
Pacific Coast ◽  
Damage Zone ◽  
Warning System ◽  
Tohoku Earthquake ◽  
Tsunami Warning ◽  
Disaster Mitigation ◽  
Japan Meteorological Agency ◽  
Tsunami Height ◽  
Tsunami Warning System

The Japan Meteorological Agency (JMA) released a new version of tsunami warning system using three qualitative expressions for tsunami height. Understanding disaster mitigation information requires adequate knowledge on disaster occurrence mechanisms and precise action in emergencies. We surveyed differences in understanding and assessing tsunami warning information among university students in two prefectures – one damaged by the 2011 off Pacific Coast of Tohoku Earthquake and the other outside of the damage zone. Results revealed that those outside of the damage zone tended to estimate tsunami heights as higher than those inside the damage zone when reading qualitative tsunami heights in the JMA’s new tsunami warning version. They also tended to need more concrete, precise information to understand appropriate evacuation procedures provided by public institutions, including the JMA.

Gisola: Real-Time Moment Tensor computation optimized for multicore and manycore architectures

2021 ◽  
Author(s):  
Nikolaos Triantafyllis ◽  
Ioannis Venetis ◽  
Ioannis Fountoulakis ◽  
Erion-Vasilis Pikoulis ◽  
Efthimios Sokos ◽  
...  
Keyword(s):  
Web Services ◽  
Point Source ◽  
Real Time ◽  
Seismic Data ◽  
Moment Tensor ◽  
Multiple Point ◽  
Grid Search ◽  
Waveform Data ◽  
Fortran Code ◽  
Event Information

<p>Automatic Moment Tensor (MT) determination for regional areas is essential for real-time seismological applications such as stress inversion, shakemap generation, and tsunami warning. In recent years, the combination of two powerful tools, SeisComP and ISOLA (Sokos and Zahradník, 2008), paved the way for the release of Scisola (Triantafyllis et al., 2016), an open-source Python-based software for automatic MT calculation of seismic events provided by SeisComP -a well-known software package-, in real-time. ISOLA is an extensively used manual MT retrieval utility, based on multiple-point source representation and iterative deconvolution, full wavefield is taken into consideration and Green's functions are calculated with the discrete wavenumber method as implemented in the Axitra Fortran code (Cotton and Coutant, 1997). MT of subevents is found by least-square minimization of misfit between observed and synthetic waveforms, while position and time of subevents is optimized through grid search. Scisola monitors SeisComP and passes the event information, the respective waveform data and the station information to the ISOLA software for the Green’s Functions and MT computation. Gisola is a highly evolved version of Scisola software, oriented for High-Performance Computing. Unlike Scisola, the new program applies enhanced algorithms for waveform data filtering via quality metrics such as signal-to-noise ratio, waveform clipping, data and meta-data inconsistency, long-period (“mouse”) disturbances, and current station evaluation based on comparison between its daily Power Spectral Density (PSD) and various reference metrics for the frequency bands of interest, featuring a CPU multiprocessing implementation for faster calculations. Concerning the Green’s Functions computation, Gisola operates a newer version of the Axitra, highlighting the power of simultaneous processing in the CPU domain. Likewise, the inversion procedure code has been intensively improved by exploiting the performance efficiency of GPU-based multiprocessing implementation (with an automatic fallback to CPU-based multiprocessing in case of GPU hardware absence) and by unifying sub-programs to minimize I/O operations. In addition, a fine-grained 4D (space-time) adjustable source grid search is available for more accurate MT solutions. Moreover, Gisola expands its seismic data input resources by interconnecting to the FDSN Web Services. Furthermore, the new software has the ability to export the results in the well-known QuakeML standard, and in this way, provide clients -such as SeisComP- with MT results attached to the seismic event information. Finally, the operator has full control of all calculation aspects, with an extensive and adapted to regional data, configuration. The program can be installed on any computer that operates a Linux OS and has access to the FDSN Web Services, while the source code will be open and free to the scientific community.</p><p> </p><p>Cotton F. and Coutant O., 1997, Dynamic stress variations due to shear faults in a plane-layered medium, GEOPHYSICAL JOURNAL INTERNATIONAL,Vol 128, 676-688, doi: 10.1111/j.1365-246X.1997.tb05328.x.<br>Sokos, E. N., and J. Zahradník (2008). ISOLA a FORTRAN code and a MATLAB GUI to perform multiple-point source inversion of seismic data, Comp. Geosci. 34, no. 8, 967–977, doi: 10.1016/j.cageo.2007.07.005.<br>Triantafyllis, N., Sokos, E., Ilias, A., & Zahradník, J. (2016). Scisola: automatic moment tensor solution for SeisComP3. Seismological Research Letters, 87(1), 157-163, doi: 10.1785/0220150065.</p>

Building a Natural-Hazard-Resilient High-Quality Seismic Network: How WI Network Sustained Hurricanes Maria and Irma

2020 ◽  
Vol 92 (1) ◽  
pp. 77-84 ◽  
Author(s):  
Jean-Marie Saurel ◽  
Jordane Corbeau ◽  
Sébastien Deroussi ◽  
Tristan Didier ◽  
Arnaud Lemarchand ◽  
...  
Keyword(s):  
Real Time ◽  
Seismic Data ◽  
Warning System ◽  
Volcanic Eruptions ◽  
Seismic Network ◽  
Tsunami Warning ◽  
Coastal Hazards ◽  
Lesser Antilles ◽  
Research Centre ◽  
Small Aperture

Abstract Between 2008 and 2014, the Institut de Physique du Globe de Paris (IPGP) and the University of the West Indies, Seismic Research Centre (UWI-SRC) designed and built a regional seismic network across the Lesser Antilles. One of the goals of the network is to provide real-time seismic data to the tsunami warning centers in the framework of the Intergovernmental Coordination Group working toward the establishment of a tsunami and other coastal hazards early warning system (ICG-CARIBE-EWS) for the Caribbean and adjacent regions (McNamara et al., 2016). In an area prone to hurricanes, earthquakes, tsunamis, and volcanic eruptions, we chose different techniques and technologies to ensure that our cooperated network could survive and keep providing data in case of major natural hazards. The Nanometrics very small aperture terminal (VSAT) technology is at the heart of the system. It allows for duplicated data collection at the three observatories (Trinidad, Martinique, and Guadeloupe; Anglade et al., 2015). In 2017, the network design and implementation were put to the test with Saffir–Simpson category 5 hurricanes Irma and Maria that went, respectively, through the north and central portion of the Lesser Antilles, mainly impacting the sites operated by volcanological and seismological observatories of IPGP in Martinique (Observatoire Volcanologique et Sismologique de Martinique [OVSM]) and in Guadeloupe (Observatoire Volcanologique et Sismologique de Guadeloupe [OVSG]). Our concepts proved to be valid with a major data shortage of less than 12 hr and only two stations having sustained heavy damage. In this article, we review the strengths and weaknesses of the initial design and discuss various steps that can be taken to enhance the ability of our cooperated network to provide timely real-time seismic data to tsunami warning centers under any circumstances.

Real-Time Ground Motion Forecasting Using Front-Site Waveform Data Based on Artificial Neural Network

2009 ◽  
Vol 4 (4) ◽  
pp. 588-594 ◽  
Author(s):  
H. Serdar Kuyuk ◽  
◽  
Masato Motosaka ◽  
Keyword(s):  
Real Time ◽  
Ground Motion ◽  
Structural Control ◽  
Japan Meteorological Agency ◽  
Earthquake Ground Motion ◽  
S Wave ◽  
Property Damage ◽  
Ground Acceleration ◽  
Waveform Data ◽  
Artificial Neural

Real-time earthquake information made available by the Japan Meteorological Agency (JMA) publicly since October 2007 is intended to dramatically reduce human casualties and property damage following earthquakes. Its current limitations, however, such as a lack of applicability to near-source earthquakes and the insufficient accuracy of seismic ground motion intensity leave much to be desired. The authors have suggested that the forward use of front-site waveform data leads to improve accuracy of real-time ground motion prediction. This paper presents an advanced methodology based on artificial neural networks (ANN) for the forward forecasting of ground motion parameters, not only peak ground acceleration and velocity but also spectral information before S wave arrival using the initial P waveform at a front site. Estimated earthquake ground motion information can be used as a warning to lessen human casualties and property damage. Fourier amplitude spectra estimated highly accurately before strong shaking can be used for advanced engineering applications, e.g., feed-forward structural control. The validity and applicability of the proposed method have been verified using Kyoshin Network (K-NET) observation datasets for 39 earthquakes occurring in the Miyagi Oki area.

scholarly journals Evaluation for hypocenter estimation error in the southwestern Kuril trench using Japan and Russia joint seismic data

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Masayoshi Ichiyanagi ◽  
Valentin Mikhaylov ◽  
Dmitry Kostylev ◽  
Yuri Levin ◽  
Hiroaki Takahashi
Keyword(s):  
Seismic Data ◽  
Estimation Error ◽  
Kuril Trench

scholarly journals A Bimodal Model to Estimate Dynamic Metropolitan Population by Mobile Phone Data

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3431 ◽  
Author(s):  
Jie Feng ◽  
Yong Li ◽  
Fengli Xu ◽  
Depeng Jin
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Mobile Networks ◽  
Mobility Management ◽  
Population Distribution ◽  
Estimation Error ◽  
Population Estimation ◽  
Mobile Phone Data ◽  
Estimation Accuracy ◽  
Estimation Interval

Accurate, real-time and fine-spatial population distribution is crucial for urban planning, government management, and advertisement promotion. Limited by technics and tools, we rely on the census to obtain this information in the past, which is coarse and costly. The popularity of mobile phones gives us a new opportunity to investigate population estimation. However, real-time and accurate population estimation is still a challenging problem because of the coarse localization and complicated user behaviors. With the help of the passively collected human mobility and locations from the mobile networks including call detail records and mobility management signals, we develop a bimodal model beyond the prior work to better estimate real-time population distribution at metropolitan scales. We discuss how the estimation interval, space granularity, and data type will influence the estimation accuracy, and find the data collected from the mobility management signals with the 30 min estimation interval performs better which reduces the population estimation error by 30% in terms of Root Mean Square Error (RMSE). These results show us the great potential of using bimodal model and mobile phone data to estimate real-time population distribution.

scholarly journals Development of Application Systems for Earthquake Early Warning

2009 ◽  
Vol 4 (4) ◽  
pp. 546-556 ◽  
Author(s):  
Yukio Fujinawa ◽  
◽  
Yoshinori Rokugo ◽  
Yoichi Noda ◽  
Yoshinobu Mizui ◽  
...  
Keyword(s):  
Real Time ◽  
Early Warning ◽  
Seismic Waves ◽  
Earth Science ◽  
Earthquake Early Warning ◽  
Disaster Mitigation ◽  
Japan Meteorological Agency ◽  
Governmental Organizations ◽  
Application Systems ◽  
Non Governmental Organizations

In Japan, governmental organizations, non-governmental organizations, and private companies cooperated to develop the Earthquake Early Warning (EEW) system from 2003 to 2007. It is for overall use in the country to mitigate earthquake disasters. Real-time Earthquake Information Consortium (REIC) is in charge of developing the application system for EEW. All data are from the networks of the Japan Meteorological Agency (JMA) and the National Research Institute for Earth Science and Disaster Prevention (NIED). Those data are collected and analyzed in real time using the system developed by the NIED and JMA. The JMA officially issues two kinds of EEW: one for general public and one for advanced users. Once earthquakes occur, the focal parameters are calculated as quickly as possible after sufficient number of observation sites detect seismic waves, and are transmitted to the advanced users, generally within seconds. The parameters disseminated can be used by any private party or organization for their own purposes. We have developed 14 particular application systems to help with various countermeasures, including automated and/or semi-automated responses in each field. The systems are being adopted gradually for earthquake disaster mitigation.

Network Selection in Wireless Heterogeneous Environment Based on Available Bandwidth Estimation

2019 ◽  
Vol 12 ◽  
Author(s):  
Kiran Ahuja ◽  
Brahmjit Singh ◽  
Rajesh Khanna
Keyword(s):  
Real Time ◽  
Estimation Error ◽  
Network Selection ◽  
Bandwidth Estimation ◽  
Heterogeneous Environment ◽  
Bootstrap Approximation ◽  
Available Bandwidth ◽  
Internet Connection ◽  
Available Bandwidth Estimation ◽  
Selection Of

Background: With the availability of multiple options in wireless network simultaneously, Always Best Connected (ABC) requires dynamic selection of the best network and access technologies. Objective: In this paper, a novel dynamic access network selection algorithm based on the real time is proposed. The available bandwidth (ABW) of each network is required to be estimated to solve the network selection problem. Method: Proposed algorithm estimates available bandwidth by taking averages, peaks, low points and bootstrap approximation for network selection. It monitors real-time internet connection and resolves the selection issue in internet connection. The proposed algorithm is capable of adapting to prevailing network conditions in heterogeneous environment of 2G, 3G and WLAN networks without user intervention. It is implemented in temporal and spatial domains to check its robustness. Estimation error, overhead, estimation time with the varying size of traffic and reliability are used as the performance metrics. Results: Through numerical results, it is shown that the proposed algorithm’s ABW estimation based on bootstrap approximation gives improved performance in terms of estimation error (less than 20%), overhead (varies from 0.03% to 83%) and reliability (approx. 99%) with respect to existing techniques. Conclusion: Our proposed methodology of network selection criterion estimates the available bandwidth by taking averages, peaks, and low points and bootstrap approximation method (standard deviation) for the selection of network in the wireless heterogeneous environment. It monitors real-time internet connection and resolves internet connections selection issue. All the real-time usage and test results demonstrate the productivity and adequacy of available bandwidth estimation with bootstrap approximation as a practical solution for consistent correspondence among heterogeneous wireless networks by precise network selection for multimedia services.

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