scholarly journals A new multi-sensor approach to simulation assisted tsunami early warning

2010 ◽  
Vol 10 (6) ◽  
pp. 1085-1100 ◽  
Author(s):  
J. Behrens ◽  
A. Androsov ◽  
A. Y. Babeyko ◽  
S. Harig ◽  
F. Klaschka ◽  
...  
Keyword(s):  
Early Warning ◽  
Near Field ◽  
Warning System ◽  
Tsunami Warning ◽  
Accurate Estimation ◽  
Tsunami Early Warning ◽  
Arrival Times ◽  
Rigorous Approach ◽  
Tsunami Forecasting ◽  
Wave Heights

Abstract. A new tsunami forecasting method for near-field tsunami warning is presented. This method is applied in the German-Indonesian Tsunami Early Warning System, as part of the Indonesian Tsunami Warning Center in Jakarta, Indonesia. The method employs a rigorous approach to minimize uncertainty in the assessment of tsunami hazard in the near-field. Multiple independent sensors are evaluated simultaneously in order to achieve an accurate estimation of coastal arrival times and wave heights within very short time after a submarine earthquake event. The method is validated employing a synthetic (simulated) tsunami event, and in hindcasting the minor tsunami following the Padang 30 September 2009 earthquake.

History and Challenge of Tsunami Warning Systems in Japan

2009 ◽  
Vol 4 (4) ◽  
pp. 595-599 ◽  
Author(s):  
Fumihiko Imamura ◽  
◽  
Ikuo Abe
Keyword(s):  
Warning System ◽  
Tsunami Warning ◽  
Japan Meteorological Agency ◽  
Tsunami Forecast ◽  
Tsunami Warning System ◽  
Arrival Times ◽  
History Of Development ◽  
The People ◽  
Tsunami Forecasting ◽  
History Of

History of development of Tsunami Warning System in Japan started in 1952 after the tsunami warning/forecast system formulated at Sanriku is introduced. The system estimated the earthquake epicenter and magnitude, and issued the forecast by referring to the tsunami forecast maps. In 1999, the Japan Meteorological Agency (JMA) has introduced the computer-aided simulation system for quantitative tsunami forecasting, in which tsunami arrival times and heights are simulated and stored in the database for forecasting tsunamis. The JMA has been further updating the system and now can issue the forecast 2 to 3 minutes after occurrence of an earthquake. By reviewing the response of the people for past tsunamis forecasting and information in an example case of the 2006 Kurile Earthquake tsunami, we discuss the issues such as accuracy, detail and canceling in order to improve the system.

A study of people-centered early warning system in the face of near-field tsunami risk for Indonesian coastal cities

2020 ◽  
Vol 11 (2) ◽  
pp. 241-262 ◽  
Author(s):  
Harkunti Pertiwi Rahayu ◽  
Louise K. Comfort ◽  
Richard Haigh ◽  
Dilanthi Amaratunga ◽  
Devina Khoirunnisa
Keyword(s):  
Early Warning ◽  
Near Field ◽  
Warning System ◽  
City Government ◽  
Primary Data ◽  
Current Policy ◽  
Structured Interviews ◽  
Content Type ◽  
Tsunami Early Warning ◽  
Populations At Risk

Purpose This study aims to identify the gaps in current policy and propose a viable framework for policy improvement regarding people-centered tsunami early warning chain in Padang City. The objectives are: to describe the gaps and flaws in the current policy regarding local tsunami early warning chain, to identify potential actors to be involved in the tsunami early warning chain and to assess the roles and capacity of actors, and their potential for involvement in early warning. Design/methodology/approach This study is an exploratory study using social network analysis (SNA) on regulations and other legal documents, and primary data sources from a focus group discussion and semi-structured interviews. Findings The study found that the existed regulation lacks extension nodes to relay warnings to the populations at risk, often referred to as “the last mile.” Moreover, receiving warning information from both formal and informal sources is important to mobilize people evacuation more effectively during an emergency. The study found that mosque communities and disaster preparedness leaders are the potential actors who should be involved in the local early warning chain. Practical implications The research findings were presented as a recommendation to Padang City Government and have been legalized as the new tsunami early warning chain procedure in the Padang City Mayor Regulation 19/2018. Originality/value This research investigated local tsunami early warning dissemination in Padang City using SNA. The study demonstrates a close collaboration between researchers, practitioners and the community.

scholarly journals Development of tsunami early warning systems and future challenges

2012 ◽  
Vol 12 (6) ◽  
pp. 1923-1935 ◽  
Author(s):  
J. Wächter ◽  
A. Babeyko ◽  
J. Fleischer ◽  
R. Häner ◽  
M. Hammitzsch ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Early Warning Systems ◽  
Tsunami Warning ◽  
Information And Communications Technology ◽  
Warning Systems ◽  
System Architectures ◽  
Tsunami Early Warning ◽  
Distant Early Warning

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.

scholarly journals Decision support system for predicting tsunami characteristics along coastline areas based on database modelling development

2010 ◽  
Vol 13 (1) ◽  
pp. 96-109 ◽  
Author(s):  
Iwan K. Hadihardaja ◽  
Hamzah Latief ◽  
Iyan E. Mulia
Keyword(s):  
Neural Network ◽  
Numerical Modelling ◽  
Early Warning ◽  
Early Warning System ◽  
Numerical Models ◽  
Near Field ◽  
Warning System ◽  
Database System ◽  
Tsunami Early Warning ◽  
Neural Network Learning

Tsunamis are extraordinary occurrences that are difficult to identify; most of the incidents have no recorded predictions and tsunamis are generally infrequent events with poor data acquisition. The development of a tsunami database system has become important for improving the management of information with regard to a tsunami early warning system for vulnerable communities along coastline areas. Numerical modelling is usually employed to simulate the wave height and travel time of a wave arriving at a coastline area. However, numerical modelling for tsunami prediction is too time-consuming to be useful as an early warning system for the mitigation of tsunami-related damage and loss. Therefore, this model was used to develop a tsunami database system, based on hypothetical data, in order to develop a recognition pattern for a neural network learning process that will improve the speed and accuracy of tsunami prediction. To improve the accuracy of numerical modelling and observation, an adjustment was established for an advanced training process which used a generalised regression neural network. In other words, the training and testing datasets were obtained by correcting near-field tsunami numerical models from hypothetical earthquakes. The case study was performed on part of the Southern Pangandaran coastline in West Java, Indonesia.

scholarly journals KOERI’s Tsunami Warning System in the Eastern Mediterranean and Its Connected Seas: A Decade of Achievements and Challenges

2021 ◽  
Vol 11 (23) ◽  
pp. 11247
Author(s):  
Öcal Necmioğlu ◽  
Fatih Turhan ◽  
Ceren Özer Sözdinler ◽  
Mehmet Yılmazer ◽  
Yavuz Güneş ◽  
...  
Keyword(s):  
Early Warning ◽  
Eastern Mediterranean ◽  
Warning System ◽  
Lessons Learned ◽  
Tsunami Warning ◽  
Tsunami Warning System ◽  
Tsunami Early Warning ◽  
The North ◽  
Earthquake Research ◽  
Monitoring Center

A tsunami warning system providing services in the Eastern Mediterranean, Aegean, Marmara and Black Seas under the UNESCO Intergovernmental Oceanographic Commission (IOC)—Intergovernmental Coordination Group (ICG) for the Tsunami Early Warning and Mitigation System in the North-Eastern Atlantic, the Mediterranean and Connected Seas (NEAMTWS) framework was established in Turkey by the Kandilli Observatory and Earthquake Research Institute (KOERI) (Özel et al., 2011). KOERI’s Regional Earthquake and Tsunami Monitoring Center (RETMC) was established on the foundations of the legacy KOERI National Earthquake Monitoring Center (NEMC) by adding observation, analysis and operational capability related to tsunami early warnings after an extensive preparatory period during 2009 and 2011. The center initiated its test-mode 7/24 operational status as a national tsunami warning center in 2011, and after a one year period it became operational as a candidate tsunami warning center for NEAMTWS on 1 July 2012, together with CENALT (Centre d’Alerte aux Tsunamis—France) and followed by the NOA (National Observatory of Athens—Greece) on 28 August 2012, INGV (Instituto Nazionale di Geofisica e Vulcanologia—Italy) on 1 October 2014 and IPMA (Instituto Português do Mar e da Atmosfera—Portugal) on 1 February 2018, completing full coverage of the tsunami-prone regions monitored by NEAMTWS. In this paper, an overview of the progress and continuous improvement of KOERI’s tsunami early warning system will be presented, together with lessons learned from important tsunamigenic events, such as the 20 July 2017 Bodrum–Kos Mw 6.6 and 30 October 2020 Samos–Izmir Mw 6.9 earthquakes. Gaps preventing the completion of an effective tsunami warning cycle and areas for future improvement are also addressed.

scholarly journals Concept study of radar sensors for near-field tsunami early warning

2010 ◽  
Vol 10 (9) ◽  
pp. 1957-1964 ◽  
Author(s):  
T. Börner ◽  
M. Galletti ◽  
N. P. Marquart ◽  
G. Krieger
Keyword(s):  
Early Warning ◽  
Near Field ◽  
Warning System ◽  
Microwave Remote Sensing ◽  
Tsunami Early Warning ◽  
Tsunami Waves ◽  
Radar Sensors ◽  
Near Space ◽  
New Concepts ◽  
Remote Sensing Techniques

Abstract. Off-shore detection of tsunami waves is a critical component of an effective tsunami early warning system (TEWS). Even more critical is the off-shore detection of local tsunamis, namely tsunamis that strike coastal areas within minutes after generation. In this paper we propose new concepts for near-field tsunami early detection, based on innovative and up-to-date microwave remote sensing techniques. We particularly introduce the NESTRAD (NEar-Space Tsunami RADar) concept, which consists of a real aperture radar accommodated inside a stationary stratospheric airship providing continuous monitoring of tsunamigenic oceanic trenches.

Review on Near-Field Tsunami Forecasting from Offshore Tsunami Data and Onshore GNSS Data for Tsunami Early Warning

2014 ◽  
Vol 9 (3) ◽  
pp. 339-357 ◽  
Author(s):  
Hiroaki Tsushima ◽  
◽  
Yusaku Ohta ◽  
Keyword(s):  
Early Warning ◽  
Near Field ◽  
Leading Edge ◽  
Early Warning Systems ◽  
Satellite System ◽  
Coastal Communities ◽  
Tsunami Early Warning ◽  
Tsunami Forecasting ◽  
Global Navigation Satellite ◽  
Gnss Data

This paper reviews recent studies on methods of realtime forecasting for near-field tsunamis that use either offshore tsunami data or onshore global navigation satellite system (GNSS) data. Tsunami early warning systems for near-field coastal communities are vital because evacuation time before tsunami arrival is usually very short. We focus on forecasting between the occurrence of a tsunamigenic earthquake and the arrival of the first tsunami at a near-field coast – typically a few tens of minutes or less after the earthquake. Offshore tsunami measurement that provides coastal communities with direct information on impending tsunamis is very effective in providing reliable tsunami predictions. Crustal deformation due to coseismic slips at an earthquake fault detected by real-time GNSS analysis is quite useful in estimating fault expansion and the amount of slip, which in turn contributes to timely tsunami warnings, e.g., within 10 minutes, even for huge interplate earthquakes. Our review encompasses methods on the leading edge of research and those already in the process of being applied practically. We also discuss an effective combination of methods developed for mitigating tsunami disasters.

scholarly journals Probabilistic tsunami forecasting for early warning

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
J. Selva ◽  
S. Lorito ◽  
M. Volpe ◽  
F. Romano ◽  
R. Tonini ◽  
...  
Keyword(s):  
Early Warning ◽  
Tsunami Warning ◽  
False Alarms ◽  
Forecasting Accuracy ◽  
Tsunami Early Warning ◽  
Tsunami Forecasting ◽  
Wide Range ◽  
The Mediterranean ◽  
High Uncertainty

AbstractTsunami warning centres face the challenging task of rapidly forecasting tsunami threat immediately after an earthquake, when there is high uncertainty due to data deficiency. Here we introduce Probabilistic Tsunami Forecasting (PTF) for tsunami early warning. PTF explicitly treats data- and forecast-uncertainties, enabling alert level definitions according to any predefined level of conservatism, which is connected to the average balance of missed-vs-false-alarms. Impact forecasts and resulting recommendations become progressively less uncertain as new data become available. Here we report an implementation for near-source early warning and test it systematically by hindcasting the great 2010 M8.8 Maule (Chile) and the well-studied 2003 M6.8 Zemmouri-Boumerdes (Algeria) tsunamis, as well as all the Mediterranean earthquakes that triggered alert messages at the Italian Tsunami Warning Centre since its inception in 2015, demonstrating forecasting accuracy over a wide range of magnitudes and earthquake types.

scholarly journals Source modeling and inversion with near real-time GPS: a GITEWS perspective for Indonesia

2010 ◽  
Vol 10 (7) ◽  
pp. 1617-1627 ◽  
Author(s):  
A. Y. Babeyko ◽  
A. Hoechner ◽  
S. V. Sobolev
Keyword(s):  
Real Time ◽  
Scaling Laws ◽  
Near Field ◽  
Warning System ◽  
Source Characterization ◽  
Source Modeling ◽  
Plate Interface ◽  
Tsunami Warning System ◽  
Tsunami Early Warning ◽  
Source Models

Abstract. We present the GITEWS approach to source modeling for the tsunami early warning in Indonesia. Near-field tsunami implies special requirements to both warning time and details of source characterization. To meet these requirements, we employ geophysical and geological information to predefine a maximum number of rupture parameters. We discretize the tsunamigenic Sunda plate interface into an ordered grid of patches (150×25) and employ the concept of Green's functions for forward and inverse rupture modeling. Rupture Generator, a forward modeling tool, additionally employs different scaling laws and slip shape functions to construct physically reasonable source models using basic seismic information only (magnitude and epicenter location). GITEWS runs a library of semi- and fully-synthetic scenarios to be extensively employed by system testing as well as by warning center personnel teaching and training. Near real-time GPS observations are a very valuable complement to the local tsunami warning system. Their inversion provides quick (within a few minutes on an event) estimation of the earthquake magnitude, rupture position and, in case of sufficient station coverage, details of slip distribution.

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