Heterogeneity of the Japanese islands as inferred from transverse component analyses of teleseismic P-waves observed at a seismic station network, Hi-net
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Teleseismic P-waves are observed even in a transverse component, and the ratio of the peak energy of the transverse component to that of the sum of the three components (peak energy ratio) is a good indicator to represent the strength of the heterogeneity in the structure. We analyze the short-period teleseismic P-waves recorded at a dense seismic network in Japan (Hi-Net) and determine the spatial changes of the heterogeneity in the Japanese islands. The results show that east Japan is characterized mainly by large peak energy ratios that represent strong heterogeneity. On the other hand, west Japan shows small peak energy ratios. Comparison of the results with detailed geological maps further shows that large peak energy ratios are observed at regions located close to both quaternary volcanoes and active faults, and the active fault region is characterized by slightly smaller peak energy ratios. Non-active regions, located far from volcanoes or faults, indicate the smallest ratios, although the ratios are larger than those estimated on stable continents. Plains that consist mainly of sediments show the largest peak energy ratios. However, peak delay times observed at the plains are much longer than the others, which suggests a different mechanism for generating the amplitudes in the transverse component.
Key wordsTeleseismic P-wave transverse component heterogeneity volcano active fault plain
Recent analyses of short-period waves recorded by a dense seismic network (Hi-net) have succeeded in determining small-scale heterogeneities of the crust and lithosphere. Multi-lapse time window analyses for S-waves and their coda from local earthquakes clarified detailed spatial distributions of intrinsic and scattering Q of the crust in Japan (Carcore and Sato, 2009). Peak delay times of S-waves propagating in the medium characterized by von Kerman type spectrum of fluctuations are also used to evaluate the small-scale heterogeneity beneath the Tohoku region, Japan (Takahashi et al., 2009). Their spatial resolutions are high enough to compare the elastic parameters related with the small-scale heterogeneity to the tectonic settings at the target regions, such as volcanoes, active seismic faults, and so on.
Energy partitioning of a teleseismic P-wave into a transverse component, which is perpendicular to the propagation direction on the ground surface, is also used to evaluate the heterogeneity in the lithosphere. This method has the merit in that we can evaluate the heterogeneity even at regions where local earthquakes are not observed. Large amplitudes are observed in the transverse component at stations located on active tectonic regions, while small amplitudes are observed on stable continents (Nishimura, 1996; Nishimura et al., 2002; Kubanza et al., 2006, 2007). Sato (2006) has formulated the vector waves of P-waves incident to the heterogeneity characterized by a Gaussian power spectrum of the fluctuation, and has shown that the peak energy ratio, which is the ratio of the maximum amplitude of the mean square envelope of the transverse component to that of the sum of the three components, is approximately equal to 1.81∊2z/a, where ∊ is the fractional change of seismic velocity, a is the correlation length and z is the thickness of the heterogeneous medium.
In the present study, we analyze teleseismic P-waves observed at a highly-dense seismic network, Hi-net, Japan, which deploys short-period seismometers with an average spacing of a few tens of kilometers. Comparing the geological settings in Japan, we quantify the small-scale heterogeneity and discuss the origins that produce amplitudes in the transverse component of the P-wave.
2. Data and Analyses
To investigate systematically the origins of heterogeneity that produce transverse energy in a P-wave, we classify the Japanese islands into the following five regions by using the digital map shown in Fig. 3: (i) the active fault regions that are within a distance of 20 km from an active fault, or an estimated active fault which is not directly observed on the ground surface but is inferred from topography, (ii) volcano regions that are within a distance of 20 km from a quaternary volcano, (iii) the plains, as defined above, which are characterized by sediments, (iv) the volcano and fault regions that are within a distance of 20 km both from a quaternary volcano and an active fault, and (v) regions that are more than 20 km removed from volcanoes and faults, and which are not located on a plain (we refer to these as ‘non-active regions’). The five regions do not overlap: each of the regions of (i)–(iii) contains only one of volcano, fault or plain, (iv) includes both volcano and fault, and (v) includes none of them.
Averages and the 95% confidence level of peak energy ratios and peak delay times.
Peak Delay Time (s)
Quaternary Volcano & Active Fault
From the average peak energy ratios shown in Table 1 (about 0.1–0.2) and Sato (2006), we estimate the quantity ∊2/a to be about 5.5 × 10−4−1.1 × 10−3 km−1 for tentatively assuming the thickness of heterogeneity z = 100 km. The fluctuation ∊ ranges 5 to 7% for a = 5 km.
Spatial distributions of the peak energy ratios (Fig. 2) are not well correlated with three-dimensional P- or S-wave velocity distributions (e.g., Matsubara et al., 2008). For example, a drastic change from east to west Japan is not recognized in the P- and S-wave velocity distributions. Carcole and Sato (2009) have determined intrinsic absorption Open image in new window and scattering loss Open image in new window values in the Japanese islands from multi-lapse time window analyses. Spatial distributions of the scattering loss obtained at 1–2 and 2–4 Hz are similar to those of the peak energy ratios. For example, large values of scattering loss are found in east Japan and in the middle of Kyushu, while small values are found in west Japan and along the Sanriku coast. This consistency strongly suggests that the peak energy ratios represent the strength of scattering in the structure, although the results at 4–8 Hz show some differences in the spatial distributions: for example, a large scattering loss in west Japan from Chugoku to central Japan.
We further examine the peak delay time that is the time lag from P-wave onset to the maximum amplitude, and summarize these in Table 1. The peak delay times are measured for the mean square envelopes both of the transverse component and for the sum of the three components. It is clearly recognized that the peak delay times for the plains are longer than those for the other regions: the peak delay times for the sum of three components are about 4–7 s for the plain and 3–4 s for the others, and those for the transverse component are 9–14 s for the plain, while about 6–11 s for the others. Observed long peak delay times are probably due to the differences in the mechanisms generating the seismic amplitudes in the transverse component. Conversion phases or surface waves generated by the sedimentary layers are considered to be the origins of the transverse component in teleseismic P-waves observed at the plains.
Sato (2006) relates peak delay times with the heterogeneous media by Open image in new window for the sum of the three components and Open image in new window for the transverse component, where Open image in new window and VP is the P-wave velocity. The peak delay times predicted from the observed peak energy ratio (0.09–0.24) for the regions except the plain are estimated to be less than about 2 s for z = 100 km and Vp = 6 km/s. This estimated value (<2 s) is much shorter than the observations. Also, the peak delay times do not seem to increase with the peak energy ratios, although Sato’s (2006) model predicts a positive correlation between the two parameters. This is probably because source duration times of earthquakes with magnitudes of 5.5–6.5 are a few seconds or more, and we stack envelopes of different earthquakes.
This study is greatly indebted to the data of high sensitivity seismograph network (Hi-net) by the National Research Institute for Earth Science and Disaster Prevention (NIED), Japan. Careful comments by two anonymous reviewers improved this manuscript. This study is partly supported by the Ministry of Education, Culture, Sports, Science and Technology in Japan MEXT (No. 20540405).
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