Estimation of Empirical Green^|^rsquo;s Tensor Spatial Derivatives Using Aftershocks of the 2001 Hyogo-ken Hokubu Earthquake and Simulation of Mainshock (MJ5.4) Strong Motion

道広, 大堀; 嘉章, 久田

doi:10.4294/zisin.59.133

Cited by 4 publications

(15 citation statements)

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“…To enhance the accuracy of simulation by the EGTD method, it is desirable to know the focal mechanisms and source time functions accurately as much as possible. In this study, we used the source model which was reevaluated in our previous work [6]. Among 15 events, 4 aftershock events, 3, 7, 19, 26, are excluded in the following EGTD inversion because of the relatively large discrepancy in waveform matching between the observation data and synthesis.…”

Section: Targeted Events and Stationsmentioning

confidence: 99%

“…The estimation method of the EGTD has been fully explained by Ohori and Hisada [6,8]. It is applicable to simulation of the strong motion in a frequency range below the corner frequency.…”

Section: Estimation Of the Egtdmentioning

confidence: 99%

“…The EGTD elements are estimated through a kind of single-station inversion using waveform data for several small events whose focal mechanisms and source time functions are well determined. This technique is expected to provide considerably accurate and stable prediction results, but discussion of its application has been limited in the literature [4][5][6][7][8]. In the previous studies [6,8], considering the lowest corner frequency of about 1.0 Hz for the mainshock, we targeted 0.2-1.0 Hz band-pass-filtered velocity waveforms.…”

Section: Introductionmentioning

confidence: 99%

“…This technique is expected to provide considerably accurate and stable prediction results, but discussion of its application has been limited in the literature [4][5][6][7][8]. In the previous studies [6,8], considering the lowest corner frequency of about 1.0 Hz for the mainshock, we targeted 0.2-1.0 Hz band-pass-filtered velocity waveforms. In the present study, we simulate the broadband strong motions between 0.2 and 10 Hz for the same events as in the previous studies [6,8].…”

Section: Introductionmentioning

confidence: 99%

“…In the previous studies [6,8], considering the lowest corner frequency of about 1.0 Hz for the mainshock, we targeted 0.2-1.0 Hz band-pass-filtered velocity waveforms. In the present study, we simulate the broadband strong motions between 0.2 and 10 Hz for the same events as in the previous studies [6,8].…”

Section: Introductionmentioning

confidence: 99%

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Simulation of Broadband Strong Motion Based on the Empirical Green’s Spatial Derivative Method

Ohori

2016

Earthquakes, Tsunamis and Nuclear Risks

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In our previous studies (Ohori and Hisada, Zisin 2(59): 133-146, 2006, Bull Seismol Soc Am 101:2872-2886, 2011, we simulated the strong-motion records of the mainshock (M J 5.4) of the 2001 Hyogo-ken Hokubu earthquake, Japan, on the basis of the empirical Green's tensor spatial derivative (EGTD) estimated from data of 11 aftershocks (M J 3.5-4.7). The agreement between the observed and calculated waveforms at the closest station in source distance was satisfactory over a long duration, and the amplitude was well reproduced. But considering the lowest corner frequency of about 1.0 Hz for the mainshock, we targeted 0.2-1.0 Hz band-pass-filtered velocity waveforms. In the present study, we tried to simulate the broadband strong motions beyond the corner frequencies for the same events as in our previous studies mentioned above. To correct the discrepancies among the corner frequencies of events, we assumed the scaling law based on the ω À2 model (Aki, J Geophys Res 72:1217-1231, 1967) and compensated the spectral amplitude decay beyond the corner frequency. After estimating the EGTD from 11 aftershock events using 0.2-10 Hz band-pass-filtered waveforms, we simulated the strong-motion records for the mainshock and aftershocks. In simulation of each event, the EGTD elements were multiplied by the moment tensor elements followed by summation and corrected in the spectral amplitude, taking the corner frequency of each event into account. As example results, the simulated waveforms at the closest epicentral distance was compared with the observed ones. The agreement between the calculated and observed waveforms was acceptable for most of events.

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Section: Targeted Events and Stationsmentioning

confidence: 99%

“…The estimation method of the EGTD has been fully explained by Ohori and Hisada [6,8]. It is applicable to simulation of the strong motion in a frequency range below the corner frequency.…”

Section: Estimation Of the Egtdmentioning

confidence: 99%