JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 109, B04308, doi: /2003jb002774, 2004

Transcription

1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 109,, doi: /2003jb002774, 2004 Configuration of subducting Philippine Sea plate beneath southwest Japan revealed from receiver function analysis based on the multivariate autoregressive model Katsuhiko Shiomi, 1 Haruo Sato, 2 Kazushige Obara, 1 and Masakazu Ohtake 2 Received 2 September 2003; revised 19 January 2004; accepted 13 February 2004; published 21 April [1] We construct a detailed image of velocity discontinuity beneath southwest Japan by using receiver functions. We first propose an improved receiver function estimation method based on the statistical multivariate autoregressive model. Then we apply the new method to the teleseismic waveform data recorded by the high-density seismograph network in southwest Japan. The results show a clear velocity discontinuity at 30 km depth beneath the southern Shikoku region. This discontinuity, corresponding to the boundary between the oceanic crust and the high-velocity layer (the oceanic Moho) of the Philippine Sea plate (PHS), continues down to the north indicating that the aseismic PHS extends to the central Chugoku region. The continental Moho is also clearly imaged beneath the Chugoku region. The depth contour of the PHS shows a rather complicated feature with ridges and valleys. The most significant ridge is located around longitude 133 E, west of which the contours are basically directed north-south, changing to westeast to the east. Beneath the western part of this ridge, hypocenters of microearthquakes are located above this velocity discontinuity, while earthquakes mainly occur below the discontinuity, within the oceanic mantle, beneath the eastern part of the ridge. INDEX TERMS: 7218 Seismology: Lithosphere and upper mantle; 7230 Seismology: Seismicity and seismotectonics; 8150 Tectonophysics: Plate boundary general (3040); 9320 Information Related to Geographic Region: Asia; KEYWORDS: Philippine Sea plate, receiver function, seismicity Citation: Shiomi, K., H. Sato, K. Obara, and M. Ohtake (2004), Configuration of subducting Philippine Sea plate beneath southwest Japan revealed from receiver function analysis based on the multivariate autoregressive model, J. Geophys. Res., 109,, doi: /2003jb Introduction [2] The Philippine Sea plate (PHS) is subducting toward the northwest from the Nankai Trough beneath the Chugoku-Shikoku region, southwest Japan. Subduction of the PHS has caused the Nankai earthquakes of magnitude (M) about 8 and a few inland earthquakes with M 7. Knowledge of the detailed configuration of the PHS is very important for understanding the subduction process and evaluating the source process of impending large earthquakes. Recently, various seismological, petrological and/or thermal models of the subducting PHS have been proposed and the relations between the slab geometry and the local seismicity have been discussed [e.g., Ohkura, 2000; Kurashimo et al., 2002; Gutscher and Peacock, 2003; Hacker et al., 2003]. So far, most of the configuration models of the PHS are based on investigations of hypocentral distribution of microearthquakes [e.g., Yamazaki and Oida, 1985; Nakamura et al., 1997] and wide-angle reflection and/or refraction surveys 1 National Research Institute for Earth Science and Disaster Prevention, Japan. 2 Graduate School of Science, Tohoku University, Japan. Copyright 2004 by the American Geophysical Union /04/2003JB002774$09.00 [e.g., Kodaira et al., 2000; Baba et al., 2002; Kurashimo et al., 2002]. However, in the Chugoku region of Honshu Island, seismicity along the subducting PHS is very low, and no reflection and/or refraction phases from the PHS have been observed by artificial explosion surveys. Figure 1 is a location map of Japan and southwest Japan with the depth contours of the PHS according to the depth distribution of microearthquakes [Nakamura et al., 1997]. It is not clear from this map whether the PHS continues toward the north beneath the Chugoku region or not. Nakanishi [1980] and Nakanishi et al. [1981] clearly identified the subducting PHS as a high-velocity layer (HVL) underlying a relatively low velocity layer, identified as the oceanic crust, by analyzing the ScSp phase of teleseismic waves observed in the western Chugoku and Shikoku region. They also indicated that the PHS descending from the Nankai Trough may have reached the upper mantle beneath the Chugoku region without seismic activity there. Tomography studies on velocity structure have been done in this area by Hirahara [1981], Zhao et al. [2002], and Honda and Nakanishi [2003]. They stated that the HVL in the uppermost mantle beneath the Chugoku region is evidence of the existence of the PHS there. However, tomography is sensitive to the gradual velocity change within the Earth and is not effective at detecting an abrupt velocity discontinuity. There are significant inconsistencies in the depths of the 1of13

2 Figure 1. Map of (top) Japan and (bottom) southwest Japan, where N.T. means the Nankai Trough. Triangles in the southwest Japan map represent Quaternary volcanoes in the Chugoku region, and the contour lines indicate the predominant focal depth of microearthquakes along the subducting Philippine Sea slab [Nakamura et al., 1997]. upper boundary of the HVL among those tomographic results, and none of them gave a clear configuration of the PHS in this region. [3] The spatial relationship between the configuration of the plate and the local seismicity is essential to understanding the seismotectonics of southwest Japan. For earthquakes that occur in the Shikoku region with depth range of km, one can frequently find a distinct pair of later P and S phases after the initial P and S waves at stations in the eastern part of the Chugoku and/or the Shikoku region. Ohkura [2000] demonstrated that these later phases are guided waves traveled through both the oceanic crust (the low-velocity layer) and the continental lower crust. These guided waves can be observed if the earthquakes occur in the oceanic crust and if the oceanic crust is in contact with the lower crust between the hypocenters and the receivers. Analyzing the wide-angle reflection and refraction survey data, Kurashimo et al. [2002] found that the HVL corresponds to the oceanic mantle of the PHS. They concluded that the subcrustal earthquakes beneath the eastern part of the Shikoku region are located within the HVL of the PHS, underlying the oceanic crust. However, this is inconsistent with the findings of Ohkura [2000]. A similar discrepancy in the locations of the intermediate depth earthquakes is reported for the region along the Nazca slab at 21 S, where the seismicity in Wadati-Benioff zone is located in the slab mantle area [ANCORP Working Group, 1999], but most of the earthquakes at km depth occur within the subducting crust at 22 S to 23 S [Yuan et al., 2000]. More recently, Preston et al. [2003] reported that along the Cascadia slab, shallow earthquakes occur in the slab mantle and deep earthquakes are mainly located within the subducting crust, similar to that in the Shikoku region and the Nazca slab. [4] A receiver function is obtained by deconvoling the source wavelet from teleseismic waveform, in either the time or frequency domain. This method does not require measurements of the arrival time of direct P or converted phases, so the reading error of the phase arrival would not affect the accuracy of depth estimates for discontinuities beneath a station. This technique has been intensively used to investigate the geometry of the continental Moho worldwide [e.g., Sheehan et al., 1995; Zhu, 2000; Zhu and Kanamori, 2000; Levin et al., 2002; Stankiewicz et al. 2002] and subducting slabs [e.g., Li et al., 2000; Yuan et al., 2000; Ferris et al., 2003]. Beneath the Japanese Islands, Li et al. [2000] described the receiver function images of velocity discontinuity using broadband seismographs records. They indicated the locations of the subducting Pacific slab and the upper mantle discontinuities at 410 and 660 km. [5] Recently, the National Research Institute for Earth Sciences and Disaster Prevention has established a highsensitivity seismograph network (Hi-net) with an average station interval of 20 km nationwide over Japan [Obara et al., 2000]. The waveform data accumulated by this highdensity seismograph network offer an unprecedented opportunity to study both the spatial configuration of the PHS and the seismicity beneath southwest Japan. [6] Yamauchi et al. [2003] applied the conventional receiver function analysis method to the teleseismic waveform data observed by the Hi-net and other seismograph networks. They found a seismic velocity discontinuity in the uppermost mantle beneath southwest Japan and stated that the PHS subducts, asesimically, under the western Chugoku region. They proposed depth contours for the upper boundary of the PHS. However, the contours of their PHS model are significantly different from those derived from the spatial distribution of the microearthquakes beneath the Shikoku region. [7] In this paper, we first improve the conventional receiver function analysis method based on a statistical model, where a special focus is put on the method of spectral estimation. Then, by applying this method to teleseismic waveform data recorded by the Hi-net seismograph stations in southwest Japan, we derive a spatially varying of depth profile of receiver function amplitude. Finally, we discuss the relationship between 2of13

3 Figure 2. Comparison of the synthetic receiver functions estimated by the conventional method and the MAR model method. (a) Synthetic waveforms calculated for the incidence of a Ricker wavelet into the bottom of the model structure with incidence angle of 25. (b) One-dimensional structure model which has a weak low-velocity layer at about 30 km in depth. (c) Synthetic receiver functions estimated by the conventional method with different water level (W.L.) values c and the ideal receiver function calculated from the response of the structure. (d) Synthetic receiver function estimated by the MAR model method and the ideal receiver function. the depth contours of the PHS and the distribution of microearthquakes. 2. Estimation of Receiver Function 2.1. Receiver Function and Conventional Estimation Method [8] The receiver function analysis is a method to extract the P-to-S converted phases from teleseismic waves to provide information about the subsurface structure beneath the seismic station. The receiver function h(t) is given by the deconvolution of radial component X r (t) by vertical component X z (t). In frequency domain, the receiver function is given by Hðf Þ¼Rðf Þ=Zðf Þ¼Rðf ÞZðf Þ*=Zðf ÞZðf Þ*; where Z( f ) and R( f ) are vertical and radial component data in the frequency domain, respectively, and the asterisk means complex conjugation. Taking the inverse Fourier transform of H( f ), we obtain a time domain receiver function h(t) [e.g., Langston, 1979; Ammon, 1991]. ð1þ [9] The fast Fourier transform (FFT) technique is widely used to calculate the spectrum of the vertical Z( f ) and radial R( f ) components for a given lapse time window. When we estimate the receiver function by using FFT, we sometimes encounter serious instability in the frequency domain deconvolution process. The calculated spectrum by Fourier transform can be considered as a convolution of a spectrum of the infinite data and that of a finite time window. If the sidelobe of the time window spectrum is not negligible, the estimated spectrum will be contaminated. The contaminations by such time window effect and noise can, usually, cause serious instability for the spectrum estimation and the division in equation (1). To stabilize the receiver function estimation, the water level method [e.g., Helmberger and Wiggins, 1971] has frequently been used. The water level method replaces the notch spectrum in the denominator of equation (1) with a constant value. The constant value is determined by the product of the maximum amplitude of a power spectrum of the vertical components and a water level value c (c 1). Obviously, such a process smoothes out not only the noise but also information about subsurface structure and sometimes significantly distorts estimated receiver functions. As an example, we compare the ideal 3of13

4 receiver function with the one estimated by using the water level method (see Figure 2). The synthetic seismograms are theoretically calculated by using the reflection matrix method [Kennett and Kerry, 1979] for the incidence of a Ricker wavelet of dominant frequency 1 Hz into the bottom of the model structure with an incidence angle of 25. Figure 2c shows a comparison of ideal receiver function and estimated receiver functions by using the water level method with water level values c of 0.01 and 0.001, respectively. The ideal receiver function is given by the deconvolution of the radial response of the one-dimensional (1-D) structure by vertical one. The radial and vertical structural responses are also calculated by the reflection matrix, theoretically. The receiver functions derived by the conventional method by using FFT and the water level method show strong distortion with a large negative amplitude around the initial motion (t = 0). In this example, the distortion decreases with decreasing water level value. However, the spectral roughness may include information about the characteristics of the structure. Hence there is a trade-off between stability and spectral information in this process. Moreover, since a negative amplitude of receiver function is usually interpreted as a low-velocity layer, the distortion may lead to a serious misinterpretation on the structure. Therefore distortion control is critical for the receiver function interpretation. [10] As both seismic observation and computer techniques develop, methods for receiver function estimation have evolved. Soda et al. [2001] proposed a method to smooth FFT spectrum with the Hanning window to stabilize receiver function estimation. This is superior to the water level method because its meaning, in frequency domain, is clear and it causes less distortion of the receiver function. However, this method requires choices of the window width for the spectrum smoothing. To avoid the instability in conventional frequency domain deconvolution, time domain deconvolution methods have been proposed [e.g., Gurrola et al., 1995; Sheehan et al., 1995; Ligorría and Ammon, 1999]. Receiver functions estimated this way keep spectral characteristics of low-frequency components and satisfy causality (no leakage appears before direct P wave arrival). Time domain deconvolution tends to be dominated by the Fourier components with largest amplitude [Park and Levin, 2000], and the difficulty is that this method sometimes requires to set the damping parameter, subjectively. Park and Levin [2000] developed a frequency domain receiver function estimation method using multiple-taper correlation estimates. This method is able to calculate a variance of receiver functions in the frequency domain, with which one can evaluate a weighted-average stack to improve a signal-to-noise ratio. However, it also requires choosing time-bandwidth product. In this paper, we propose new technique using another spectral estimation method with objective parameter selection. This improved technique is suitable for imaging shallow structure (crust and uppermost mantle) Improved Receiver Function Estimation Method Based on the Multivariate Autoregressive Model [11] The maximum entropy method (MEM) and the autoregressive (AR) model method [Akaike, 1969] estimate spectra based on statistical models. These methods have advantages over the FFT for high stability and high resolution. With the multivariate autoregressive (MAR) model, power and cross spectra can be estimated by the same statistical model, simultaneously. Thus this method is also very effective for receiver function estimation. [12] Sampling the vertical and radial components of seismic waves with time interval Dt, we construct time series x z (n) and x r (n). The M-dimensional MAR model is a model that explains the multivariate time series, X(n) = (x z (n), x r (n)) t with the past value X(n 1),, X(n M) and white noise matrix U(n): XðnÞ ¼ XM m¼1 AðmÞXðn mþþuðnþ ðn ¼ 1; ; NÞ; ð2þ UðnÞ ¼½u z ðnþ; u r ðnþš t ; ð3þ where N is the number of discrete waveform data and superscript t means transposition. Two-dimensional square matrix A(m) is an AR coefficients matrix. To apply this model to time series, we estimate the AR coefficients and the covariance matrix of the white noise. In Appendix A, we explain how to calculate these parameters using observed time series. [13] We define a nondimensional parameter f s as the ratio of seismic wave frequency f to sampling frequency F s (= 1/Dt): f s ¼ f =F s ¼ f Dt: The time series X(n) is interpreted as an output of linear system for input U(n), where the response function in frequency domain is A(f s ) 1. Therefore the cross-spectral matrix, P(f s ) is represented as ð4þ h i *; Pðf s Þ¼Aðf s Þ 1 P u ðf s Þ Aðf s Þ 1 ð5þ where P u (f s ) is a cross-spectral matrix of input U(n). Diagonal components P zz (f s ) and P rr (f s ) of cross-spectral matrix P(f s ) give the power spectra of x z (n) and x r (n), respectively, and the off-diagonal component P rz (f s ) gives the cross spectrum. Hence the Fourier transform of receiver function estimated by using the MAR model is given by H MAR ðf Þ¼ P rzðf Þ ð P zz ðf Þ f ¼ f s=dtþ: ð6þ To search the statistically suitable order of autoregression M, we use Akaike s information criteria (AIC): AICðmÞ ¼2N log 2p þ N log^v m þ 2N þ 8m þ 6; where ^V m is the estimated covariance matrix of white noise (see Appendix A). The m value that minimizes the AIC value gives the optimum order of the MAR model. A bold curve in Figure 2d shows the synthetic receiver function estimated by using the MAR model for the synthetic waveforms shown in Figure 2a. The receiver function shown in Figure 2d is significantly improved around the ð7þ 4of13

5 Figure 3. Distribution of the Hi-net seismograph stations used in this study (open circles and squares). Receiver functions at three stations indicated by squares with their names are shown in Figure 5 as examples. Lines indicate locations of vertical cross sections of receiver functions (see Figure 7). direct P wave arrival (t 0 [s]). It is worth noting that the obtained receiver function decays with lapse time and the amplitude become small over 15 s. These are expected characteristics. A receiver function may be considered as one of filtered cross-correlation functions without phase change and lag time of cross-correlation function corresponds to the lapse time in receiver functions. Generally, the accuracy of the correlation function estimated from finite data decreases with increasing lag time. A spectrum estimated by using the MAR model does not extract the information that is not statistically significant. As a result, amplitude of receiver function estimated by using the MAR model gradually attenuates with increasing lapse time. The characteristic of that the accuracy of receiver function decreases with lapse time has been discussed in the multitaper spectral correlation method [Park and Levin, 2000] and in time domain deconvolution method [Gurrola et al., 1995; Ligorría and Ammon, 1999]. [14] Our improved MAR model method has two advantages, at least, over the conventional frequency domain deconvolution method: one can objectively select the most suitable parameters with statistical conditions by using AIC instead of ambiguous choices of the parameters and the deconvolution process is much more stable without specific filtering process like the water level method. 3. Data [15] We use the teleseismic waveform data recorded at 181 Hi-net stations in the Chugoku-Shikoku region, southwest Japan (Figure 3). We select 241 earthquakes (October 2000 to March 2003) with magnitudes 5.5 or larger and epicentral distances between 27 and 90. Figure 4 represents the epicenter distribution of teleseismic events used in this study. The incidence angles at each station are in the range of We analyze waveforms with duration of 120 s starting from 30 s in advance to the onset of P wave to estimate the receiver functions. Figure 4. Epicenter distribution of teleseismic events used in this study. 5of13

6 for frequencies lower than 1 Hz. To exclude low-frequency components, a high-pass filter with corner frequency of 0.1 Hz is applied to seismogram with the instrument response correction, giving 0.1 to 0.6 Hz band-pass-filtered seismograms. In total, 9911 receiver functions are estimated. Figure 5. JMA2001, one-dimensional reference velocity model [Ueno et al., 2002] used to transform the receiver function from lapse time to depth in this study. This onedimensional model is also used for JMA hypocentral locating routines. [16] Each Hi-net station is equipped with a three-component short-period velocity seismograph of natural frequency 1 Hz at the bottom of a borehole with depth more than 100 m. To avoid the contamination by the surface reflection and other high-frequency noise, we select the stations with sensor depth shallower than 350 m and apply a Gaussian low-pass filter with cutoff frequency 0.6 Hz to raw seismograms. The response of the Hi-net system to the ground motion decreases proportionately to the square of frequency 4. Results and Discussion 4.1. Examples of Receiver Functions [17] To investigate the depth distribution of the velocity discontinuities, we transform the independent variable of the estimated receiver functions from lapse time to depth by using the JMA2001 [Ueno et al., 2002] as the reference velocity model (Figure 5). Figure 6 shows examples of receiver functions in depth domain estimated at the three stations shown by squares in Figure 3. In Figure 6, we line up the receiver functions according to the backazimuth. Large amplitudes at 0 km depth indicate the arrival of direct P wave. The later phase with positive amplitude indicates the existence of seismic velocity discontinuity, where the deeper layer has higher velocity than that of the shallower one. After the direct P wave, the later coherent phases are clearly shown in Figure 6. For station OOTH, the remarkable phases, indicated with arrows, appear at about 30 km in depth. For earthquakes located south-southeast of the station (in backazimuthal range ), the phases are slightly shallower than the other traces. For earthquakes located west of the station (in backazimuthal range ), the amplitudes of the same phases are larger and slightly deeper than the other traces. Such characteristics indicate that there is a HVL at 30 km in depth beneath the station OOTH and the HVL declines toward the west or northwest Cross Sections of Receiver Functions Subducting Philippine Sea Plate [18] If only data from a sparse seismic network are available, it would be difficult to identify what these discontinuities represent and to discuss its spatial distribution. Many investigations on the depth distribution of velocity discontinuities from receiver function s images using dense seismic arrays [e.g., Neal and Pavlis, 1999; Yuan et al., 2000; Zhu, 2000; Ferris et al., 2003]. The high Figure 6. Examples of estimated receiver functions at three stations shown in Figure 3. For plotting the receiver functions, time is converted to depth by using JMA2001 model (Figure 5). The ordinate is depth, and the abscissa is backazimuth. Arrows indicate the coherent phases which correspond to the oceanic or the continental Moho discontinuities. 6of13

7 Figure 7. Vertical cross sections of the receiver functions amplitude along 10 lines shown in Figure 3. Black dots indicate hypocenters of microearthquakes for the focal depth range from 25 to 60 km according to the hypocentral catalogue of the Japan Meteorological Agency. Solid and open triangles on the top of each panel indicate the locations of stations within 5 km and 25 km of the lines, respectively. Color scale for amplitude is shown at the bottom. PHS with thick lines indicates the location of the upper boundary of the high-velocity layer (the oceanic Moho) of the subducting Philippine Sea plate (PHS), and M with thin lines indicates the continental Moho. Ambiguous parts are shown with dashed line. 7of13

8 Figure 7. (continued) density of the Hi-net stations enables us to trace these discontinuities spatially beneath southwestern Japan. For each event-station pair, the ray parameter is evaluated using the IASP91 Earth model [Kennett and Engdahl, 1991] with the epicentral distance and the focal depth, and the ray is traced beneath the station using JMA2001 model (Figure 5). We divide the study area into blocks with sizes of 2.5 km in horizontal and 2 km in depth. The amplitude of the receiver function shown at a certain depth is attributed to the block where the ray passed through the same depth. If many rays pass the same block, we take the average of amplitude over all rays. Through this procedure for all seismic rays, the configuration of a velocity discontinuity is constructed. Figure 7 shows cross sections of the receiver function amplitude along 10 lines shown in Figure 3. Red blocks indicate the positive amplitude of the receiver functions. 8of13

9 Figure 8. Two-dimensional model structure to evaluate the depth estimation error. A high-velocity slab with dip angle j is embedded into the JMA2001 (Figure 5). P-to-S conversion point Z is set at 30, 40, and 50 km in depth. Black dots in Figure 7 represent microearthquake hypocenters (October 1997 to about June 2003, M 0.0) beneath the crust. These hypocenters are determined by using JMA2001 velocity model by Japan Meteorological Agency (JMA) routines. As illustrated in profiles A-A 0 to E-E 0 in Figure 7, the continuous distribution of red blocks indicated by thick lines beneath the Shikoku region shows that there is a velocity discontinuity subducting toward the north from the south with a low dip angle. This discontinuity also descends toward the Kyushu region, in west of the Shikoku region as shown in profiles G-G 0 to I-I 0 in Figure 7. The depth of this discontinuity is 30 km beneath the southern Shikoku region (J-J 0 ) and 40 km beneath the Seto Inland Sea (G-G 0 ) and continues down to the north reaching to about 60 km beneath the Chugoku region (F-F 0 ). The southern segment of this discontinuity corresponds well with the hypocenter distribution of microearthquakes. Therefore the clear HVL in Figure 7 indicates the upper boundary of the HVL (the oceanic Moho discontinuity) of the PHS. As shown in sections C-C 0 and D-D 0 in Figure 7, the northern portion of the HVL of the PHS clearly extends to the central part of the Chugoku region, where red blocks continue from the south toward north with very few earthquake hypocenters. It demonstrates that the aseismic PHS extends, at least, to the central part of the Chugoku region Continental Moho Discontinuity [19] In Figure 7, aligned red blocks around km depth beneath the Chugoku region can be seen as indicated by the thin line. As illustrated in A-A 0 to E-E 0 in Figure 7, these discontinuities tend to incline toward the Pacific side. This feature and the depth of these discontinuities are consistent with the configuration of the continental Moho discontinuity revealed by Zhao et al. [1992] from a travel time inversion analysis. According to their results, the continental and oceanic Moho beneath KYDH and IAMH stations are located 35 and 31 km in depth, respectively. We can find the converted phases corresponding to them in Figure 6, as shown with arrows. Looking at profiles A-A 0 and E-E 0 in Figure 7 in detail, we find a valley beneath the central Chugoku region. The same feature seems to exist in B-B 0 to D-D 0 in Figure 7 but not as clearly. The location of this valley corresponds to the mountainous area with elevation in a range of 1000 m. This area shows a negative Bouguer gravity anomaly [Gravity Research Group in Southwest Japan, 2001], indicating that the thickness of the continental crust (the depth of the continental Moho) is larger beneath the central Chugoku region. This is consistent with the receiver function images shown in Figure 7. The continental Moho shown from A-A 0 to E-E 0 in Figure 7 becomes obscure beneath the southern Chugoku region and the Seto Inland Sea, where the subducting oceanic Moho exist quite near. Ohkura [2000] insisted that the mantle wedge does not exist beneath the Shikoku region, where the oceanic crust is in contact with the continental crust. It is hard to image this area from our results because the ray path is not enough around the Seto Inland Sea. However, profile E-E 0 in Figure 7 confirms that the mantle wedge is absent in the western Shikoku region around 33.4 N, at least, in the northern end of the Shikoku region. In the eastern Shikoku region, the edge is located around 33.5 N, as shown in profile A-A 0 of Figure 7. These features are consistent with the results of Ohkura [2000] Evaluation of the Error of Depth Conversion [20] A simple horizontally layered velocity model is used to transform the receiver function lapse time to depth. To evaluate the error of depth estimation caused by dipping structure, we perform the following experiment. Figure 8 illustrates a profile of a two-dimensional (2-D) structure where a dipping high-velocity (V P = 8.0 km/s) slab embedded into the JMA D model. The P-to-S conversion depths are set at 30, 40, and 50 km corresponding to different station locations. We let dip angle j vary from 0 to 30 with a step of every 5. For direct P wave with an incidence angle q = 35 from the updip direction, the lapse time of the conversion phase at the dipping slab after the arrival of direct P is calculated and then transformed to the depth for each j at different stations. This assumed incidence angle is equivalent to a source about 45 distance. As listed in Table 1, the maximum change in the depth is within 15% (several kilometers) between dipping angle Since the dipping angle of the subducting slab shown in Figure 7 is mostly within 10, it would be reasonable to say that the error on the estimated conversion depth caused by the simple 1-D model is around 2 3 km. Of course, we should keep in mind that the error increases with the increase of the dipping angle, and this error estimation is empirical. Table 1. Estimation of Depth Conversion Errors for Dipping Slab Model a Z 30 km 40 km 50 km Dip t, s D, km t, s D, km t, s D, km a Dip indicates dip angles of subducting slab. The parameters Z, t, and D mean the assumed P-to-S conversion point depth, the lapse time of the conversion phase at the dipping slab after the arrival of direct P wave and the resultant conversion depth using 1-D model, respectively. 9of13

10 Figure 9. E-W profile of the spatial distribution of the focal depth differences determined using 3-D and 1-D velocity models beneath the Shikoku region. The hypocenter relocation using the 3-D velocity model was done by Matsubara et al. [2003], which is constructed by using the travel time tomographic approach. The vertical bars indicate the standard deviation. [21] The hypocenters used in this study are located using the 1-D regional velocity structure (JMA2001). Matsubara et al. [2003] constructed a 3-D velocity structure beneath the Japanese Islands based on travel time tomography, then relocated the hypocenters using their 3-D model. Figure 9 gives the E-W profile of the spatial variation of the average differences between the focal depths beneath the Shikoku region determined using their 3-D (Dep 3D ) and 1-D (Dep 1D ) models. Within our study region, the average error of the focal depth caused by the 1-D velocity model is within ±2 km, while the standard deviation of the average is ±1.5 km. Beneath the eastern Shikoku region (east of 134 E), Dep 3D is 2 km shallower than Dep 1D, systematically. Considering the uncertainty of both the depth conversion of receiver function and the focal depth, the hypocenters that are close to (within 5 km) the slab boundary are eliminated in the discussion about spatial relationship between the configuration of the PHS and the local seismicity Depth Contour of the Philippine Sea Plate and Local Seismicity [22] We made more than 100 cross sections of receiver functions amplitude, half of them have strike with NW-SE direction and the others in NE-SW direction to construct the PHS model with high resolution. Figure 10 shows the depth contours of the upper boundary of the HVL (the oceanic Moho discontinuity) of the PHS. Clearly, the PHS dips to north with a dip angle about 10 beneath Shikoku. The dipping angle becomes low at the Seto Inland Sea and then changes to 25, approximately, at the central part of the Chugoku region. The depth contours show a rather complicated feature with ridges and valleys. The most significant ridge is located around longitude 133 E (R1 in Figure 10). East of the ridge, the contours trend NE-SW and bend to south-north on the west of it. The depth contours of local seismicity (Figure 1) also bend around longitude E. There is a small valley (V1 in Figure 10) in the depth contours of the PHS in the area west of the ridge R1. This valley is coincident with seismicity in depth range of km, represented by orange and yellow in Figure 7. In the eastern part of the Shikoku region, the depth contours of the PHS show a small ridge around E (R2 in Figure 10), where the depth contours of the local seismicity are smooth. In our PHS model, there is a valley at E (V2in Figure 10). Seismicity is higher in the east of this valley, although seismic activity is low at the central part of the Shikoku region. Figure 10. Depth contour of the boundary between the oceanic crust and the high-velocity layer (HVL) of the Philippine Sea plate (PHS) revealed from the improved receiver function analysis. Local seismicity is also plotted, where the depth is given by color scale. Thick dashed lines with labels R1 and R2 are locations of significant ridges. Thin dashed lines with label V1 and V2 mean a location of valley. 10 of 13

11 Figure 11. Hypocenters of microearthquakes and the depth contour of the upper boundary of the highvelocity layer (HVL) of the Philippine Sea plate (PHS). (a) Distribution of hypocenters with depths more than 5 km above the upper boundary. (b) Distribution of hypocenters with depths more than 5 km under the upper boundary. [23] Yamauchi et al. [2003] carried out the conventional receiver function analysis to generate a PHS model. They showed a large valley around our valley V1 in Figure 10, and the contours of their model are directed east-west in the west of the valley. However, in profiles G-G 0 and I-I 0 of Figure 7, the velocity discontinuity represented by red blocks appears to decline to the west, monotonously. Also, the south-north directed depth contours of the distribution of the microearthquakes in the western part of the Shikoku region do not support their model but is consistent with our model. Because their PHS model is constructed of few profiles with only parallel strike, it is hard to trace the configuration of the velocity discontinuities if the contours of the discontinuities are parallel to the cross sections. In constructing our PHS model, we add the information obtained from the cross sections with NE-SW strikes, shown in F-F 0 to J-J 0 of Figure 7 as examples. Therefore our PHS model has much higher spatial resolution than the previous one, especially in the western part of the Shikoku region. [24] As shown in Figure 11a, almost all local earthquakes are located above the HVL west of the ridge at around 133 E. This result confirms the observation of later phases interpreted by Oda et al. [1990] and Ohkura [2000], as mentioned earlier. Ohkura [2000] suggested that this high-seismicity zone in the subducting oceanic crust might be caused by the gabbro to eclogite phase transformation. East of the ridge, where the subducting PHS runs east-west with a lower dip angle, earthquakes mainly occur within the slab mantle (Figure 11b). The dip angle of the HVL becomes larger east of 134 E, while the seismicity is significantly lower. Those features are also consistent with the analyses of refraction and wide-angle reflection survey by Kurashimo et al. [2002]. The Kinan seamount chain exists to the southeast off the Shikoku region (upper map in Figure 1), and these seamounts may be subducting beneath the eastern part of the Shikoku region [Kodaira et al., 2000; Seno and Yamasaki, 2003]. Seno and Yamasaki [2003] suggested the possibility that dehydration may not take place in the subducting seamounts because of the lack of hydrous minerals. This might be a reason why no earthquake occurs above the HVL. Seno and Maruyama [1984] proposed that the subduction direction of the PHS is west-northwest in southwest Japan at the present time but it was northwest 17 Ma. The dipping direction of the PHS is also northwest (R1 and R2 in Figure 10). The complicated stress field generated by discrepancy between the plate motion and the slab geometry may be one of the major causes of the different pattern of the seismicity under the crust between the eastern area and the western area of the Shikoku region. 5. Conclusion [25] We developed the new receiver function estimation method based on the MAR model and applied it to teleseismic waveform data recorded by the Hi-net. Taking advantage of the high density of the Hi-net stations, we constructed a detailed image of velocity discontinuities beneath southwest Japan. The largest discontinuity, which corresponds to the boundary between the oceanic crust and the HVL (the oceanic Moho) of the PHS, subducts from south toward the north continuously. We have confirmed the extension of the aseismic PHS beneath the central part of Chugoku region. We found a deepening of this discontinuity toward the Kyushu region in the west of the Shikoku region. The continental Moho discontinuity was also imaged clearly. We found that the Moho has a valley beneath the central Chugoku region. The location of the valley is corresponds to high surface topography, and the shape of the continental Moho is consistent with the gravity anomaly. The depth contours of the HVL of the PHS trend NE-SW from the east to the west then bend to south-north direction around 133 E. All local earthquakes occur above the HVL to the west of the significant ridge around longitude 133 E, although almost all earthquakes are located in the upper mantle east of the ridge. The configuration of the PHS resolved by this study enables us to investigate the relation- 11 of 13

12 ships between seismicity in the slab and the slab geometry for the first time. Appendix A: Estimation of AR Coefficients and Covariance Matrix of White Noise [26] In this paper, we adopt the Yule-Walker method [e.g., Kitagawa, 1998] to calculate AR coefficients and covariance matrix of white noise. A cross-covariance matrix R(m) for multivariate time series X(n) is generally defined as RðmÞ ¼E XðnÞXðn mþ t ; ða1þ where E means an expected value. Using equation (1), we can rewrite equation (A1) as "( ) # X M RðmÞ ¼E AðjÞXðn jþþuðnþ Xðn mþ t ¼ XM j¼1 j¼1 AðjÞE Xðn jþxðn mþ t þ E UðnÞXðn mþ t : ða2þ If a lag m is not equal to zero, the second term of equation (A2) becomes zero. If m is equal to zero, the second term is modified to ( " #) E UðnÞXðnÞ t X M ¼ E UðnÞ Xðn mþ t AðmÞ t þ UðnÞ t m¼1 ¼ E UðnÞUðnÞ t W; ða3þ where W is a covariance matrix of white noise. Correlation coefficients of white noise are zero when lag time is not equal to zero. Because both power spectrum and cross spectrum of white noise take constant values without frequency dependences, a covariance matrix W coincides with a cross-spectral matrix P u ( f s ) in equation (5). From equations (A2) and (A3), we can get the multivariate Yule-Walker equations : Rð0Þ ¼ XM j¼1 RðmÞ ¼ XM j¼1 AðjÞRð jþþw AðjÞRðm jþ ðm ¼ 1; 2; Þ : ða4þ [27] On the other hand, a cross-covariance matrix ^R(m) for observed multivariate time series, ^X (1),, ^X(N), is written as ^RðmÞ ¼ 1 N X N n¼mþ1 ^XðnÞ^Xðn mþ t : ða5þ When we substitute ^R(m) of equation (A5) for R(m) of equation (A4), we get simultaneous equations for matrices, A(1),, A(M): ^RðmÞ ¼ XM j¼1 Að jþ ^Rðm jþðm ¼ 1; 2; ; MÞ: ða6þ Solutions of simultaneous equation (A6) are estimated AR coefficients, ^A(1),, ^A(M). By using these estimated coefficients and the first equation of equation (A4), we can calculate the estimated covariance matrix of white noise, ^V m : ^VðmÞ ¼^Rð0Þ XM j¼1 ^Að jþ ^Rð jþ: ða7þ [28] This covariance matrix of white noise, ^V m is used to search the statistically suitable order of autoregression, M by AIC derived by equation (7). Power and cross spectra of observed time series are calculated with estimated AR coefficients, ^A(1),, ^A(M) using equation (5). [29] Acknowledgments. We thank Anshu Jin, Shigeo Kinoshita, Toru Matsuzawa, and two anonymous reviewers who kindly gave us many useful comments. We are grateful to Charles J. Ammon for providing receiver function estimation software and to Makoto Matsubara, who provided hypocentral data determined using his 3-D velocity model. We also thank Japan Meteorological Agency and Ministry of Education, Culture, Sports, Science and Technology, Japan for providing hypocentral data. We used GMT software [Wessel and Smith, 1991] to draw figures. This work is partially supported by the Japan-Germany Research Cooperative Program of JSPS. References Akaike, H. (1969), Power spectrum estimation through autoregressive model fitting, Ann. Inst. Stat. Math., 21, Ammon, C. J. (1991), The isolation of receiver effects from teleseismic P waveforms, Bull. Seismol. Soc. Am., 81, ANCORP Working Group (1999), Seismic reflection image revealing offset of Andean subduction-zone earthquake locations into oceanic mantle, Nature, 397, Baba, T., Y. Tanioka, P. R. Cummins, and K. Uhira (2002), The slip distribution of the 1946 Nankai earthquake estimated from tsunami inversion using a new plate model, Phys. Earth Planet Inter., 132, Ferris, A., G. A. Abers, D. H. Christensen, and E. Veenstra (2003), High resolution image of the subducted Pacific (?) plate beneath central Alaska, km depth, Earth Planet. Sci. Lett., 214, Gravity Research Group in Southwest Japan (2001), Gravity database of southwest Japan [CD-ROM], Spec. Rep. 9, Nagoya Univ. Mus., Nagoya, Japan. Gurrola, H., G. E. Baker, and J. B. Minster (1995), Simultaneous timedomain deconvolution with application to the computation of receiver functions, Geophys. J. Int., 120, Gutscher, M. A., and S. M. Peacock (2003), Thermal models of flat subduction and the rupture zone of great subduction earthquakes, J. Geophys. Res., 108(B1), 2009, doi: /2001jb Hacker, B. R., S. M. Peacock, G. A. Abers, and S. D. Holloway (2003), Subduction factory: 2. Are intermediate-depth earthquakes in subducting slabs linked to metamorphic dehydration reactions?, J. Geophys. Res., 108(B1), 2030, doi: /2001jb Helmberger, D. V., and R. Wiggins (1971), Upper mantle structure of midwestern Unites States, J. Geophys. Res., 76(14), Hirahara, K. (1981), Three-dimensional seismic structure beneath southwest Japan: The subducting Philippine Sea plate, Tectonophysics, 79, Honda, S., and I. Nakanishi (2003), Seismic tomography of the uppermost mantle beneath southwestern Japan: Seismological constraints on modeling subduction and magmatism for the Philippine Sea slab, Earth Planets Space, 55, Kennett, B. L. N., and E. R. Engdahl (1991), Traveltimes for global earthquake location and phase identification, Geophys. J. Int., 105, Kennett, B. L. N., and N. J. Kerry (1979), Seismic waves in a stratified half space, Geophys. J. R. Astron. Soc., 57, Kitagawa, G. (1998), Model of multivariate time series (in Japanese), in The Method of Time Series Analysis, edited by T. Ozaki and G. Kitagawa, pp , Asakura-shoten, Tokyo. Kodaira, S., N. Takahashi, A. Nakanishi, S. Miura, and Y. Kaneda (2000), Subducted seamount imaged in the rupture zone of the 1946 Nankaido earthquake, Science, 289, Kurashimo, E., M. Tokunaga, N. Hirata, T. Iwasaki, S. Kodaira, Y. Kaneda, K. Ito, R. Nishida, and S. Kimura (2002), Geometry of the subducting 12 of 13

13 Philippine Sea plate and the crustal and upper mantle structure beneath eastern Shikoku Island revealed by seismic refraction/wide-angle reflection profiling (in Japanese with English abstract), J. Seismol. Soc. Jpn., Ser. 2, 54, Langston, C. A. (1979), Structure under Mount Rainier, Washington, inferred from teleseismic body waves, J. Geophys. Res., 84(B9), Levin, V., J. Park, M. Brandon, J. Lees, V. Peyton, E. Gordeev, and A. Ozerov (2002), Crust and upper mantle of Kamchatka from teleseismic receiver functions, Tectonophysics, 358, Li, X., S. V. Sobolev, R. Kind, X. Yuan, and C. Estabrook (2000), A detailed receiver function image of the upper mantle discontinuities in the Japan subduction zone, Earth Planet. Sci. Lett., 183, Ligorría, J. P., and C. J. Ammon (1999), Iterative deconvolution and receiver-function estimation, Bull. Seismol. Soc. Am., 89, Matsubara, M., S. Sekine, K. Obara, and K. Kasahara (2003), Low-velocity oceanic crusts at the top of subducting plates beneath Japan Islands imaged by tomographic method using the NIED Hi-net data, Eos Trans. AGU, 84(46), Fall Meet. Suppl., Abstract T52B Nakamura, M., H. Watanabe, T. Konami, S. Kimura, and K. Miura (1997), Characteristic activities of subcrustal earthquakes along the outer zone of southwestern Japan (in Japanese with English abstract), Annu. Disaster Prev, Res. Inst. Kyoto Univ., Ser. B1, 40, Nakanishi, I. (1980), Precursors to ScS phases and dipping interface in the upper mantle beneath southwestern Japan, Tectonophysics, 69, Nakanishi, I., K. Suyehiro, and T. Yokota (1981), Regional variations of amplitudes of ScSp phases observed in the Japanese Islands, Geophys. J. R. Astron. Soc., 67, Neal, S. L., and G. L. Pavlis (1999), Imaging P-to-S conversions with multichannel receiver functions, Geophys. Res. Lett., 26(16), Obara, K., S. Hori, K. Kasahara, Y. Okada, and S. Aoi (2000), Hi-net: High sensitivity seismograph network in Japan, Eos Trans. AGU, 81(48), Fall Meet. Suppl., Abstract S71A-04. Oda, H., T. Tanaka, and K. Seya (1990), Subducting oceanic crust on the Philippine Sea plate in Southwest Japan, Tectonophysics, 172, Ohkura, T. (2000), Structure of the upper part of the Philippine Sea plate estimated by later phases of upper mantle earthquakes in and around Shikoku, Japan, Tectonophysics, 321, Park, J., and V. Levin (2000), Receiver functions from multiple-taper spectral correlation estimates, Bull. Seismol. Soc. Am., 90, Preston, L. A., K. C. Creager, R. S. Crosson, T. M. Brocher, and A. M. Trehu (2003), Intraslab earthquakes: Dehydration of the Cascadia slab, Science, 302, Seno, T., and S. Maruyama (1984), Paleogeographic reconstruction and origin of the Philippine Sea, Tectonophysics, 102, Seno, T., and T. Yamasaki (2003), Low-frequency tremors, intraslab and interpolate earthquakes in southwest Japan From a viewpoint of slab dehydration, Geophys. Res. Lett., 30(22), 2171, doi: / 2003GL Sheehan, A. F., G. A. Abers, C. H. Jones, and A. L. Lerner-Lam (1995), Crustal thickness variations across the Colorado Rocky Mountains from teleseismic receiver functions, J. Geophys. Res., 100(B10), 20,391 20,404. Soda, Y., T. Matsuzawa, and A. Hasegawa (2001), Seismic velocity structure of the crust and uppermost mantle beneath the northeastern Japan arc estimated from receiver functions (in Japanese with English abstract), J. Seismol. Soc. Jpn., Ser. 2, 54, Stankiewicz, J., S. Chevrot, R. D. van der Hilst, and M. J. de Wit (2002), Crustal thickness, discontinuity depth, and upper mantle structure beneath southern Africa: Constraints from body wave conversions, Phys. Earth Planet. Inter., 130, Ueno, H., S. Hatakeyama, T. Aketagawa, J. Funasaki, and N. Hamada (2002), Improvement of hypocenter determination procedures in the Japan Meteorological Agency (in Japanese with English abstract), Q. J. Seismol., 65, Wessel, P., and W. H. F. Smith (1991), Free software helps map and display data, Eos Trans. AGU, 72, 441, Yamauchi, M., K. Hirahara, and T. Shibutani (2003), High resolution receiver function imaging of the seismic velocity discontinuities in the crust and the uppermost mantle beneath southwest Japan, Earth Planets Space, 55, Yamazaki, F., and T. Oida (1985), Configuration of subducted Philippine Sea plate beneath the Chubu district, central Japan (in Japanese with English abstract), J. Seismol. Soc. Jpn., Ser. 2, 38, Yuan, X., et al. (2000), Subduction and collision processes in the central Andes constrained by converted seismic phases, Nature, 408, Zhao, D., S. Horiuchi, and A. Hasegawa (1992), Seismic velocity structure of the crust beneath the Japan Islands, Tectonophysics, 212, Zhao, D., O. P. Mishra, and R. Sanda (2002), Influence of fluids and magma on earthquakes: Seismological evidence, Phys. Earth Planet. Inter., 132, Zhu, L. (2000), Crustal structure across the San Andreas Fault, southern California from teleseismic converted waves, Earth Planet. Sci. Lett., 179, Zhu, L., and H. Kanamori (2000), Moho depth variation in southern California from teleseismic reciever functions, J. Geophys. Res., 105(B2), K. Obara and K. Shiomi, National Research Institute for Earth Science and Disaster Prevention, 3-1, Tennodai, Tsukuba-shi, Ibaraki-ken , Japan. (obara@bosai.go.jp; shiomi@bosai.go.jp) M. Ohtake and H. Sato, Graduate School of Science, Tohoku University, Aoba-ku, Sendai, Miyagi , Japan. (ohtake@zisin.geophys.tohoku. ac.jp; sato@zisin.geophys.tohoku.ac.jp) 13 of 13