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The SWIFT system developed by Nakano et al. (2008) estimates both the moment function and CMT based on waveform inversion of long-period seismic signals in the frequency domain, which enables efficient and rapid computations.
Broadband seismometers produce artifacts resembling long-period pulses (non-seismic pulses) that degrade centroid moment tensor (CMT) estimations based on waveform inversion of broadband seismic records in long-period bands (50 200 s).
Such long-period pulses degrade CMT estimations based on waveform inversion of broadband seismic records in a long-period band, which may cause serious problems in tsunami prediction and early hazard assessment.
Using real-time data from the network, a source inversion analysis system called SWIFT (Nakano et al. 2008, 2010a, source parameter determination based on waveform inversion of Fourier transformed seismograms) automatically determines a CMT solution for an earthquake of moment magnitude greater than 4.5 within 15 min of the start of the earthquake.
Within the framework of an automatic/manual CMT estimation called the source-parameter determinations based on waveform inversion of Fourier Transformed seismograms (SWIFT) system (Nakano et al. 2008, 2010), the NIED has routinely analyzed the observed seismic data and maintained a database of the estimated CMTs of earthquakes that have occurred throughout the regional seismic networks.
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In this study, we introduced a new metric named local similarity based on waveform cross-correlations on spatially close stations for large-N arrays.
BFC discriminates patterns based on waveform, phase and amplitude.
Such evaluations are important for the correct calculations of Green's functions, which are used in broadband seismic monitoring at Taal based on the waveform inversion approach.
This paper focuses on the source rupture processes of the two significant events during the 2016 Kumamoto earthquake sequence based on kinematic waveform inversion analyses using strong motion data.
Herein, we used a proximal GPR method based on full-waveform inversion of ultra-wideband radar data for mapping soil moisture and we evaluated uncertainties in the soil moisture maps by three methods.
Then, in Section 4, using synthetic observed seismograms and Green's functions at real seismic station locations, we examine the effects of the water domains on waveform inversion.
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