2016
DOI: 10.1002/2015jc010877
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Abstract: We propose a method for accurately estimating the initial tsunami source. Our technique is independent of the earthquake parameters, because we only use recorded tsunami waveforms and an auxiliary basis function, instead of a fault model. We first use the measured waveforms to roughly identify the source area using backward propagated travel times, and then infer the initial sea surface deformation through inversion analysis. A computational intelligence approach based on a genetic algorithm combined with a pa… Show more

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Cited by 15 publications
(11 citation statements)
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“…The ATSUI method assumes an instantaneous fault slip and sea surface displacement, which may not be suitable for large earthquakes. Although tsunami data are usually not sensitive to the rupture propagation (Fujii & Satake, 2007), the ATSUI method can be extended by incorporating an excitation time delay for each unit source (Mulia & Asano, 2016) to model high-frequency sampling of near-field tsunami data (Satake et al, 2013). On the other hand, applications of the method to smaller earthquakes may require a further treatment due to the assumption of equating the seafloor to the sea surface displacement (Saito & Furumura, 2009).…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…The ATSUI method assumes an instantaneous fault slip and sea surface displacement, which may not be suitable for large earthquakes. Although tsunami data are usually not sensitive to the rupture propagation (Fujii & Satake, 2007), the ATSUI method can be extended by incorporating an excitation time delay for each unit source (Mulia & Asano, 2016) to model high-frequency sampling of near-field tsunami data (Satake et al, 2013). On the other hand, applications of the method to smaller earthquakes may require a further treatment due to the assumption of equating the seafloor to the sea surface displacement (Saito & Furumura, 2009).…”
Section: Methodsmentioning
confidence: 99%
“…Such locations can be determined using an optimization method. The same technique has been applied to several tsunami events such as the 2011 Tohoku‐oki tsunami (Mulia & Asano, ), the 2012 Haida Gwaii tsunami (Gusman et al, ), and the 2017 Tehuantepec tsunami (Gusman et al, ). The method provides advantages over the conventional tsunami source inversion with equidistant unit sources, but it requires the computation of synthetic waveforms for each iteration.…”
Section: Introductionmentioning
confidence: 99%
“…In the WI analysis, tsunami waveforms at observation stations are approximated using a linear superposition of the Green's function, that is, ζ|x,t=false∑iGi|x,tmi, where ζ|x,t is the observed tsunami waveforms at location x and at time t; Gi|x,t is the Green's function (synthetic tsunami waveforms originating from the ith unit source, recorded at x); mi is the model parameter to be determined by the inversion that indicates the water height at the ith unit source centroid. We use a Gaussian basis function to represent the initial water surface |z at each unit source with amplitude |A of 1 m height and 40 km spread |L (Mulia & Asano, ), zi|φ,ϑ=Ai[]||φφi2|ϑϑi2|L/22, where φ and ϑ are longitude and latitude, respectively. We consider 246 unit sources at 20 km interval as shown in Figure b.…”
Section: Tsunami Waveform Inversion With Coseismic Seafloor Deformatimentioning
confidence: 99%
“…Initially, we distribute 189 unit sources at 15 km equidistant interval covering the source area (green dots in Figure 2). This leads to a reduction of the unit sources because the GA removes any unit source that has similar information in terms of surface height from the adjacent source points (black dots in Figure 2b) [Mulia and Asano, 2016]. In the first stage, the GA selects the optimal unit sources among the initial ones.…”
Section: Genetic Algorithm To Estimate the Initial Sea Surface Elevationmentioning
confidence: 99%
“…In the first stage, the GA selects the optimal unit sources among the initial ones. This leads Geophysical Research Letters 10.1002/2016GL070140 to a reduction of the unit sources because the GA removes any unit source that has similar information in terms of surface height from the adjacent source points (black dots in Figure 2b) [Mulia and Asano, 2016]. In the second stage, the GA adjusts the locations of the selected unit sources from the first stage in order to further improve the waveform fit [Mulia and Asano, 2015].…”
Section: Genetic Algorithm To Estimate the Initial Sea Surface Elevationmentioning
confidence: 99%