Forecast of Tsunamis from the Japan–Kuril–Kamchatka Source Region

Yamazaki, Yoshiki; Wei, Yong; Cheung, Kwok Fai; Curtis, George D.

doi:10.1007/s11069-005-2075-7

Cited by 18 publications

(14 citation statements)

References 42 publications

(36 reference statements)

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“…Satake, 1987Chubarov and Shokin, 1995;Korolev and Poplavsky, 1995;Poplavsky et al, 1997;Voronina and Tcheverda, 1998;Wei et al, 2003;Titov et al, 2005;Yamazaki et al, 2006). However, only recent advances in tsunami measurement and numerical modeling technology made it possible to create effective tsunami forecasting systems.…”

Section: Introductionmentioning

confidence: 99%

An approximate method of short-term tsunami forecast and the hindcasting of some recent events

Korolev

2011

Nat. Hazards Earth Syst. Sci.

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Abstract. The paper presents a method for a short-term tsunami forecast based on sea level data from remote sites. This method is based on Green's function for the wave equation possessing the fundamental property of symmetry. This property is well known in acoustics and seismology as the reciprocity principle. Some applications of this principle on tsunami research are considered in the current study. Simple relationships and estimated transfer functions enabled us to simulate tsunami waveforms for any selected oceanic point based only on the source location and sea level data from a remote reference site. The important advantage of this method is that it is irrespective of the actual source mechanism (seismic, submarine landslide or other phenomena). The method was successfully applied to hindcast several recent tsunamis observed in the Northwest Pacific. The locations of the earthquake epicenters and the tsunami records from one of the NOAA DART sites were used as inputs for the modelling, while tsunami observations at other DART sites were used to verify the model. Tsunami waveforms for the 2006, 2007 and 2009 earthquake events near Simushir Island were simulated and found to be in good agreement with the observations. The correlation coefficients between the predicted and observed tsunami waveforms were from 0.50 to 0.85. Thus, the proposed method can be effectively used to simulate tsunami waveforms for the entire ocean and also for both regional and local tsunami warning services, assuming that they have access to the real-time sea level data from DART stations.

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Section: Introductionmentioning

confidence: 99%

An approximate method of short-term tsunami forecast and the hindcasting of some recent events

Korolev

2011

Nat. Hazards Earth Syst. Sci.

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“…This portends well for the implementation of the present non-hydrostatic model with realistic topography as already demonstrated by Kowalik et al [22] for the hydrostatic part of the model. Future applications include tsunami inundation mapping and forecasting along with the inverse algorithm [37][38][39].…”

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confidence: 99%

Depth‐integrated, non‐hydrostatic model for wave breaking and run‐up

Yamazaki

Kowalik

Cheung

2008

Numerical Methods in Fluids

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259

260

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SUMMARYThis paper describes the formulation, verification, and validation of a depth-integrated, non-hydrostatic model with a semi-implicit, finite difference scheme. The formulation builds on the nonlinear shallow-water equations and utilizes a non-hydrostatic pressure term to describe weakly dispersive waves. A momentumconserved advection scheme enables modeling of breaking waves without the aid of analytical solutions for bore approximation or empirical equations for energy dissipation. An upwind scheme extrapolates the free-surface elevation instead of the flow depth to provide the flux in the momentum and continuity equations. This greatly improves the model stability, which is essential for computation of energetic breaking waves and run-up. The computed results show very good agreement with laboratory data for wave propagation, transformation, breaking, and run-up. Since the numerical scheme to the momentum and continuity equations remains explicit, the implicit non-hydrostatic solution is directly applicable to existing nonlinear shallow-water models.

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“…t is time, ρ is the density of water, ν is the kinetic viscosity coefficient; P is the pressure, and g is the gravitational acceleration. The pressure at any point is divided into two components: the hydrostatic pressure and the non-hydrostatic pressure, as follows [20]:…”

Section: The Governing Equationsmentioning

confidence: 99%

Numerical simulation of tidal flow in Danang Bay Based on non-hydrostatic shallow water equations

Phung²,

Tran

2016

Pac. J. Math. Ind.

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This paper presents a numerical simulation of the tidal flow in Danang Bay (Vietnam) based on the non-hydrostatic shallow water equations. First, to test the simulation capability of the non-hydrostatic model, we have made a test simulation comparing it with the experiment by Beji and Battjes 1993, Coastal Engineering 23, 1-16. Simulation results for this case are compared with both the experimental data and calculations obtained from the traditional hydrostatic model. It is shown that the non-hydrostatic model is better than the hydrostatic model when the seabed topography variation is complex. The usefulness of the non-hydrostatic model is father shown by successfully simulating the tidal flow of Danang Bay.

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Forecast of Tsunamis from the Japan–Kuril–Kamchatka Source Region

Cited by 18 publications

References 42 publications

An approximate method of short-term tsunami forecast and the hindcasting of some recent events

An approximate method of short-term tsunami forecast and the hindcasting of some recent events

Depth‐integrated, non‐hydrostatic model for wave breaking and run‐up

Numerical simulation of tidal flow in Danang Bay Based on non-hydrostatic shallow water equations

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