3d Cmt Solutions Of Moderate Earthquakes Beneath Kanto Region
Figures 2b–d show an example of the 3D CMT inversion. The optimal solution for an earthquake on June 8, 2017 is a low-angle (22°) thrust faulting at a depth of 48 km, close to the upper surface of the Pacific Plate. The F-net MT solution of this earthquake was also a similar focal mechanism; however, its centroid depth was slightly deeper than that of our solution. The spatial variation of the VRs at each source grid is illustrated in Fig. 2c. Although the optimal depth was very close to the upper surface of the Pacific Plate, high (> 80%) VR solutions appeared at a wider depth range (36–56 km). These features are similar to CMT solutions in the Hyuga-nada region, southwest Japan (Fig. 4 of Takemura et al. 2020). The synthetic seismograms of the optimal solution accurately reproduce the observations.
We obtained 74 CMT solutions for shallow earthquakes (< 50 km) with an Mw of 4.2–6.3; Fig. 3a illustrates the spatial distribution of these CMT solutions. All parameters for these CMT solutions are available from the data repository site (https://doi.org/10.5281/zenodo.3926884). While the centroid times are essentially described in Japan Standard Time (JST), the comma-separated values file for the catalog also provides this in the Coordinated Universal Time (UTC) format.
Cross-sections of profiles A and B are also plotted at the bottom of Fig. 3a. Along with profile B, many earthquakes occurred just below the upper surface of the Pacific Plate. This seismicity was also confirmed in the hypocenter distribution determined by temporal ocean bottom seismometers (Ito et al. 2017b, a). However, these aligned intraslab earthquakes were not confirmed in the F-net catalog (Fig. 3b). As such, although the resolution of centroid depth is not very high, the 3D CMT inversion is also considered to work well in the Kanto region.
Differences between 3D CMT and F-net MT catalogs
The F-net solutions of corresponding earthquakes are also plotted in Fig. 3b. Spatial distributions of both catalogs seem to be similar. To quantitatively evaluate differences between the 3D CMT in this study and the F-net MT catalogs, we calculated cross-correlation coefficients of P-wave radiation patterns (e.g., Kuge and Kawakatsu 1993; Helffrich 1997), depth, and Mw differences between the 3D CMT and F-net MT catalogs (Fig. 4). A large negative value (-0.6) of cross-correlation coefficients only appeared in a solution for an earthquake on February 23, 2019. Only 4 F-net stations (N.JIZF, N.KZKF, N.YMZF, and N.KSKF; see Fig. 2b) were applicable for the CMT inversion of this earthquake because of the signal-to-noise ratio (SNR) for 25–100 s periods. Additionally, the VR of the 3D CMT solution was not high (~ 57%). With the exception of this event, differences in focal mechanisms and centroid depths were not significant compared to offshore earthquakes along the Nankai Trough (Fig. 8 of Takemura et al. 2020).
On the other hand, we found that the Mw values based on the 3D CMT were systematically smaller than those of the F-net MT catalog (Fig. 4c). The Mw values are very important for ground motion simulations because values of seismic moments are directly related to the amplitude of the simulated ground motion. Using the 3D CMT catalog along the Nankai Trough (Takemura et al. 2020; https://doi.org/10.5281/zenodo.3674161), we also evaluated the differences in the Mw between 3D CMT and F-net MT solutions. We found both larger and smaller Mw values compared to the F-net catalog in the Nankai region (Fig. 5). In the Kanto and Nankai regions, the differences in Mw for offshore earthquakes were larger than those of onshore earthquakes; these differences may be caused by 3D heterogeneities.
To investigate the cause of these Mw differences, we conducted ground motion simulations for earthquakes on November 17, 2017 (Event a) and August 4, 2018 (Event b). Using the 3D CMT method, Events a and b were located just below the upper surface of the oceanic crust layer 2 and the boundary between oceanic crust layers 2 and 3 of the Pacific Plate, respectively. The Mw differences for events a and b were − 0.31 and − 0.25, respectively, and the estimated seismic moments of the 3D CMT solutions were approximately 35% and 42% of the F-net 1D solutions, respectively. We conducted simulations using the same source models and three different heterogeneous models; the JIVSM (Koketsu et al. 2012), the JIVSM without sediments, and the F-net 1D model (Kubo et al. 2002). The source models were the optimal solutions of 3D CMT inversion for two earthquakes (Events a and b in Table 3).
Figure 6 compares the simulated and observed vertical velocity seismograms. Two F-net stations were selected, and other simulation results were stored at https://doi.org/10.5281/zenodo.3926888. We found that simulation results using the JIVSM and the JIVSM without sediments reproduced observed F-net seismograms, with the exception of the N.JIZF seismograms for the JIVSM without sediments. This suggests that the effects of low-velocity sediments around the Kanto region on CMT inversion using long-period (25–100 s) seismograms are minor. Because the Kanto Basin and marine sediments exist along the path from event b to N.JIZF, the difference in waveforms of N.JIZF for periods of 10–50 s might appear. Around the Nankai Trough, a thicker (> 5 km) accretionary prism has a significant influence on surface waves even for periods longer than 20 s, and consequently the affects results of CMT inversions and ground motion simulations (e.g., Nakamura et al. 2015; Takemura et al. 2018b, a, 2019a, b, 2020).
On the other hand, the amplitudes of simulation seismograms with a similar source and the F-net 1D model were approximately 35–45% of the observed amplitudes. The effects of the Kanto Basin have a minor influence on ground motion at outcrop rock sites (F-net), and differences in mechanisms and depths compared with F-net solutions that are not significant. This difference could be explained by differences in heterogeneities around the seismic source. The 3D CMT solutions of events a and b were located just beneath the upper surface of the oceanic crust layer 2 and near the boundary between oceanic crust layers 2 and 3 of the Pacific Plate, respectively. In the JIVSM (Table 1), the rigidities of source areas for both events were 20.4–34.3. In contrast, the rigidity at depths between 33–100 km was a uniform value (63.7 GPa; Table 2) in the F-net 1D model. The differences in rigidities around source regions between the JIVSM and the F-net 1D model correspond to differences in seismic moments between the 3D CMT and F-net MT solutions (34–42%). As such, it may be concluded that the major cause of differences in seismic moments between the 3D CMT and F-net 1D MT solutions is the difference in rigidity around the source areas.
Table 2
F-net 1D velocity model. The physical parameters were referred from Kubo et al. (2002).
Thickness (Depth)
[km]
|
VP
[km/s]
|
VS
[km/s]
|
ρ
[kg/m3]
|
µ
[GPa]
|
QP
|
QS
|
3 (0–3)
|
5.5
|
3.14
|
2.3
|
22.7
|
600
|
300
|
15 (3–18)
|
6.0
|
3.55
|
2.4
|
30.2
|
600
|
300
|
15 (18–33)
|
6.7
|
3.83
|
2.8
|
41.1
|
600
|
300
|
67 (33–100)
|
7.8
|
4.46
|
3.2
|
63.7
|
600
|
300
|
125 (100–225)
|
8.0
|
4.57
|
3.3
|
67.7
|
600
|
300
|
100 (225–325)
|
8.4
|
4.80
|
3.4
|
78.3
|
600
|
300
|
100 (325–425)
|
8.6
|
4.91
|
3.5
|
84.4
|
600
|
300
|
–
|
9.3
|
5.31
|
3.7
|
104
|
600
|
300
|
For the Nankai Trough, both overestimations and underestimations of seismic moments compared to the F-net catalog were observed (Fig. 5). Large Mw differences only appeared in the offshore region, where many intraslab and interplate earthquakes occurred. In particular, intraslab earthquakes along the Nankai Trough occurred within the low-velocity oceanic crust and high-velocity oceanic mantle (see Figs. 5 and 6 of Takemura et al. 2020), not modeled in the F-net 1D model. The difference in Mw values along the Nankai Trough could also be explained by the differences in heterogeneous structures between the 3D and 1D models.
In the F-net routine system, the origin times and epicenters were fixed as those in the JMA unified hypocenter catalog, and time shifts between observed and synthetic seismograms at each station were enabled. Miyoshi et al. (2017) notes that prior to estimating structural properties, the re-evaluation of centroid times for F-net MT solutions should be required to obtain suitable waveform inversion results. In this study, we found that the estimation of seismic moments was affected by the rigidity structure around the source region. The difference in the estimation of seismic moments directly impacts the amplitude of ground motion simulations. The amplitude of ground motion simulation is important to evaluate seismic hazards and estimate structural properties along propagation paths. For 3D forward and inverse modeling of seismic ground motion, the adjusted source model observed and synthetic seismograms in the assumed local 3D model should be used, such as the 3D CMT solution.
Long-period ground motion simulations in the Kanto region
By using our the 3D CMT solutions based on the JIVSM, we conducted numerical simulations of long-period ground motions and compared with the observed seismograms. For the SNR of the MeSO-net for periods longer than 5 s, three earthquakes were selected with an Mw equal to or larger than 5.5 for simulations of long-period ground motion in the Kanto Basin. The source parameters of selected events (A–C) are listed in Table 3. Complete files of simulated velocity waveforms and wavefields are available online https://doi.org/10.5281/zenodo.3926888.
Figure 7 shows an example of simulated vertical velocity wavefields for the simulation of Event A at 40, 60, 80, 100, 120, 140, 160, and 180 s from the earthquake origin (movie file is also available from https://doi.org/10.5281/zenodo.3926888). The seismic waves radiated from the source complicatedly propagate through the Kanto region. In the Kanto, Niigata, and offshore regions, the wavelengths and propagation speeds of the Rayleigh waves became shorter and slower due to low-velocity sediments. The energy of these shorter-wavelength components (i.e., long-period ground motion) was trapped within low-velocity sediments. Thus, the duration of long-period ground motion was elongated in the Kanto, Niigata, and offshore regions (lapse time of 180 s). Peak ground velocities (PGVs) were calculated by the vector sum of three-component filtered seismograms at the F-net and MeSO-net stations; the passband period was 5–30 s. Figure 8 shows the spatial distributions of PGVs for each event. With the exception of Event C, the simulations were able to roughly reproduce the observed features of PGVs. Large PGVs appeared in regions with bedrock depths greater than 3 km.
Figures 9, 10, and 11 compare the filtered seismograms (15–30, 10–20, and 5–16 s) between observations and simulations. We selected two F-net stations and three MeSO-net stations. The selected MeSO-net stations are located at the site with deeper (> 3 km) bedrock depths. Simulattions reproduced the observed seismograms at two F-net stations (N.ASIF and N.JIZF), with the exception of the simulation results for Event C for periods of 5—16 s. These results suggest that these 3D CMT solutions have the ability reproduce observed ground motion with sufficient accuracy for periods longer than 5 s at F-net stations, which are deployed at outcrop rock sites. Although the observed seismograms at MeSO-net stations were reproduced by the simulated seismograms for periods longer than 10 s with the exception of the later phases at E.YROM, the simulation results for 5–16 s periods could not explain the observed seismograms in the Kanto Basin. These seismogram discrepancies at the MeSO-net stations could be caused by the JIVSM sedimentary structure. For Event C, because the centroid depth was 8 km, the ground motion for 10–20 and 5–16 s periods were affected by the Kanto sedimentary basin oceanic sediments from the epicenter to coastal regions. Thus, these sedimentary structures in the offshore region may decrease waveform fitness for this event. The overestimation of PGVs (Fig. 8c) may also be attributed to the models of the Kanto Basin and the oceanic sediments along propagation paths.