Physics of the Earth and Planetary Interiors 140 (2003) 319–329
Anelastic structure of the upper mantle beneath
the northern Philippine Sea
Azusa Shito∗ , Takuo Shibutan
Research Center for Earthquake Prediction, Disaster Prevention Research Institute,
Kyoto University, Gokasyo, Uji City, Kyoto 611-0011, Japan
Abstract
We investigated the upper mantle anelastic structure beneath the northern Philippine Sea region, including the Izu-Bonin
subduction zone and the Shikoku Basin. We used regional waveform data from 69 events in the Pacific and the Philippine
Sea slabs, recorded on F-net and J-array network broadband stations in western Japan. Using the S–P phase pair method,
we obtained differential attenuation factors, δt ∗ , which represent the relative whole path Q. We conducted a tomographic
inversion using 978 δt ∗ values to invert for a fine-scale (50–100 km) three-dimensional anelastic structure.
The results shows two high-Q regions (QP > 1000) which are consistent with the locations of the Pacific and the Philippine
Sea slabs. Also there is a low-Q (QP ∼ 110) area extending to the deeper parts (350–400 km) of the model just beneath the
old spreading center and the Kinan Seamount Chain in the Shikoku Basin. A small depth dependence of the laterally averaged
QP was found, with values of 266 (0–250 km), 301 (250–400 km), and 413 (400–500 km).
© 2003 Elsevier B.V. All rights reserved.
Keywords: Anelasticity; Upper mantle; Northern Philippine Sea; Phase pair method; Q
1. Introduction
Observations and explanations of the heterogeneous structures in the Earth’s mantle have long been
an important area of research in the Earth sciences.
Conventionally, in discussions of velocity tomography results, low velocity zones are often interpreted
as hot regions and high velocity zones are interpreted
as cold regions. However, such interpretations may be
not always be appropriate because of various effects,
such as different mineralizations or water content.
∗ Corresponding author. Present address: Department of Geology and Geophysics, Yale University, 210 Whitney Avenue, New
Haven, CT 06520, USA.
Tel.: +81-774-38-4190 (Japan)/1-203-432-5990 (USA);
fax: +81-774-38-4206 (Japan)/1-203-432-3134 (USA).
E-mail addresses: [email protected],
[email protected] (A. Shito).
In this and the following paper (Shito and
Shibutani, 2003), we study the anelastic (Q) structure of the upper mantle, to help explain the physical
characteristics of the heterogeneities quantitatively.
The anelastic structure can provide some important
constraints on the structure for two reasons. First, the
attenuation is sensitive to temperature, water content,
chemical composition and partial melting in a way
that differs from that of velocity (Romanowicz, 2000).
Comparing the attenuation and velocity distributions
should help us to distinguish the cause of the seismic
attenuation and velocity anomalies. Another reason
relates to the physical dispersion effect of anelastic structure on elasticity (Kanamori and Anderson,
1977; Minster and Anderson, 1981; Karato, 1993).
To correctly estimate the physical properties from the
velocity distribution, the physical dispersion effect of
anelasticity has to be clarified.
0031-9201/$ – see front matter © 2003 Elsevier B.V. All rights reserved.
doi:10.1016/j.pepi.2003.09.011
320
A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
Despite its importance, regional scale studies of
the lateral and radial variations in attenuation are few,
especially for seismic waves of short periods. In this
paper, we investigate the three-dimensional upper
mantle anelastic structure in the northern Philippine
Sea region, which includes the Izu-Bonin trench and
the Shikoku Basin. The Philippine Sea region, one of
the marginal seas of the Pacific Ocean, is surrounded
only by convergent plate boundaries, and was formed
by frequent episodes of back arc spreading (Seno
et al., 1993; Okino et al., 1999).
Using bathymetric data and geomagnetic data,
Okino et al. (1999) proposed a detailed evolutionary process model which is consists of five
stages of back arc spreading in the Shikoku and the
Parece Vela Basins. In the Shikoku Basin, spreading
started (30 Ma) from the northern side and propagated southward and the spreading direction changed
gradually from ENE-WSW to NE-SW (20–15 Ma).
After spreading cessation, post-spreading volcanism
(15–7 Ma) formed the Kinan Seamount Chain at the
spreading center of the Shikoku Basin (Ishii et al.,
2000; Sato et al, 2002).
Seismic velocity tomography studies (Fukao et al.,
1992; Widiyantoro et al., 1999) reveal that there is
a large amount of the subducted Pacific slab in the
transition zone. It is suggested that the rapid retreat
of the Izu-Bonin trench, accompanied by the back-arc
spreading of the Shikoku Basin, shallowed the dip
angle of the Pacific slab and resulted in its stagnation
in the upper mantle (van der Hilst and Seno, 1993).
In this study, we use the S–P phase pair method
to determine path averaged differential Q estimates
for 978 paths across our target region. These values are then used in a tomographic inversion to obtain a three-dimensional attenuation model. There are
previous studies of the attenuation structure for this
region (Revenaugh and Jordan, 1991; Flanagan and
Wiens, 1994), but this paper is the first attempt at trying to resolve the three-dimensional distribution over
a fine-scale of 50–100 km.
2. Earthquake data
High quality waveform data recorded with dense
and equally spaced coverage for both P and S waves
are necessary for this investigation of the fine-scale
anelastic structure. Such data were provided from
two broadband seismograph networks in Japan,
J-array (Shibutani et al., 1999) and F-net (formerly
FREESIA).
We used regional waveform data from 69 events in
the vicinity of the Pacific and the Philippine Sea plates
35º
Izu-B
Shikoku Basin
Pacific
Plate
in
Cha
h
Trenc
30º
onin
t
oun
eam
an S
Kin
Eurasian Plate
Philippine Sea Plate
25º
125º
130º
135º
140º
145º
Fig. 1. Map showing target area and the major tectonic settings of the northern Philippine Sea region. The stars and the triangles indicate
the locations of events and stations, respectively, used in this study. The grid shows the modeled region.
A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
which were recorded at 63 stations in western Japan
from 1997 to 2002. The origin times and the locations
were taken from catalogues of IRIS and JMA. The
events ranged in depth from 77 to 520 km and the event
magnitudes ranged from 4.1 to 6.8 mb. We used deeper
events to avoid the more complicated waveforms of
the shallower earthquakes. We used events as small as
possible which had sufficient ratio of signal to noise.
All the data were recorded at epicentral distances of
1 to 10◦ . We obtained a total of 978 pairs of P and
S waveforms from the same event to a given station,
which will be used in the S–P pair method described
in the next section. The locations of the events and
stations are shown in Fig. 1.
3. S–P phase pair method
In order to study anelastic structure of the target
area, we first obtained the differential attenuation factor δt ∗ using the S–P phase pair method (e.g. Teng,
1968; Roth et al., 1999). The method compares the
relative high frequency decay of S to P waves from
the same earthquake at a given station.
The amplitude spectra of recorded P and S waves
can be expressed by
A(f) = cS(f)R(f)I(f)exp(−πft∗ )
(1)
where f is frequency, c a constant expressing the radiation pattern and the geometrical spreading, S(f) the
source spectra, R(f) the crustal response, I(f) the instrumental response and the last term is the attenuation
function. Assuming that the seismic quality factor Q
is independent of frequency
dT
t∗ =
(2)
Q
where T is the travel time.
The instrumental response I(f) is known and the
appropriate corrections are made to the data. If we assume that the source spectra S(f) and the crustal response R(f) are the same for both phases, the spectral
ratio of S to P phases from Eq. (1) yields the differential attenuation factor δt ∗ (Roth et al., 1999).
AS (f)
cS
= exp(−πδt ∗ )
AP (f)
cP
(3)
where
∗
δt =
tS∗
− tP∗
=
S
dTS
−
QS
P
dTP
QP
321
(4)
where subscripts P and S indicate P and S waves,
respectively.
Taking the natural logarithm of both sides of Eq. (3)
ln AS–P (f) = −πfδt ∗ + c
(5)
where c is a constant containing the radiation pattern, geometrical spreading, focusing and defocusing
effects of the two waves. The values of δt ∗ can be
measured from the slope of the spectral ratio curve
of observed S to P phases, and is independent of the
constant c in Eq. (5).
We show an example of the process described above
using Fig. 2. Fig. 2a shows an example of time domain
waveforms of the P and S waves. The P and S phases
were taken from vertical and transverse components,
respectively. The arrival times were manually picked
by eye. The length of the time window is 5 s before
and 15 s after the onset of each phase.
A fast Fourier Transform was applied to obtain the amplitude spectra after the data were 10%
cosine-tapered and normalized to the maximum amplitude. Then the spectra were smoothed using a
Hanning window with the bandwidth of 0.1 Hz.
Fig. 2b shows the natural log amplitude spectra of the
waveforms in Fig. 2a. The frequency band used was
0.5–1.5 Hz, which was determined taking into account
the signal to noise ratio. Samples of the noise spectra
taken from 25 to 5 s before the P phase arrival are also
shown in Fig. 2b to evaluate the data quality. It can
be seen that the signals are higher than the noise over
the frequency band. The frequency range with high
signal to noise ratios varies among the data. However, we fixed the frequency band for all the data in
order to deal with them equally and not to be swayed
by random fluctuations of the spectra. The frequency
band of 0.5–1.5 Hz was chosen to make the best use
of our data set. Spectral division of the S over P data
was carried out for each frequency point (frequency
sampling is 0.04 Hz). The spectral ratios are shown in
Fig. 2c. We fitted a trend to the spectral ratio curve
using a least-squares linear regression. The slope of
the regression line yielded the differential attenuation
factor δt ∗ .
322
A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
1
0.050
SE(δt*), s
Amplitude
P
S
0
-1
0
(a)
5
10
Time, s
0.025
0.000
0.0
15
0.5
ln Amplitude
1
Q̄P = (γTS − TP ) ∗
δt
1 1
Q̄S = TS −
γ δt ∗
5
Amplitude Ratio
2.5
then
5
(b) 0
0
1.0
Frequency, Hz
1.5
Fig. 2. (a) Typical P and S velocity waveforms used for estimation
of δt ∗ . The hypocenter is located at the depth of 362 km in the
Pacific slab with an epicentral distance of 2◦ . P wave is shown
as solid line and S wave is shown as dashed line. (b) Natural
logarithm of amplitude spectra of P and S waves shown in (a).
Signals and noise are indicated by thick and thin lines, respectively.
P wave is shown as solid line and S wave is shown as dashed line.
(c) Solid line indicates the spectra ratio of S to P waves shown in
(b). The regression line obtained by least-square fitting is plotted
as a dashed line, whose slope yields a value of δt ∗ .
The δt ∗ values range roughly from 0.0001 to 2.0 s.
The standard errors of the δt ∗ data, S.E.(δt ∗ ) were
derived from the estimation of the least-squares fitted
line. We eliminated the δt ∗ data with S.E.(δt ∗ ) larger
than 0.05 s. For almost all the data used, the standard
errors are 10% or less than the δt ∗ value, as shown in
Fig. 3.
Here we define the ratio of QP to QS
QP
γ=
QS
2.0
Fig. 3. Estimate of δt ∗ and the standard error derived from leastsquares fitting. For almost all the data, the standard errors are 10%
or less than the δt ∗ value.
10
(c)
1.5
δt*, s
15
-5
0.5
1.0
(6)
(7)
(8)
where Q̄P and Q̄S are path averaged QP and QS . We
will determine the best fitting value of γ later by minimizing residuals of δt ∗ in the inversion process. In
this section, using the value of γ = 2.25, which is
obtained if it is assumed
that there is no bulk attenua√
tion and VP /VS = 3, we calculate Q̄P values. Fig. 4
shows all the P wave paths, which are classified by
the level of Q̄P value. One can see some systematic
differences in the estimated Q̄P values for the various paths. High-Q paths (Q̄P > 450) concentrate in
the eastern region of the study area. Many of these
paths are largely traveling northward through the Pacific slab from events along the Izu-Bonin subduction
zone, and qualitatively show the high-Q properties of
the slab. In the vertical cross-section, the longer paths
that sample deeper portions (400–500 km) of the mantle show high-Q, and are an indication of the higher Q
in the deeper region. This contrasts with the lower Q
values (0 < Q̄P < 150) for places such as the mantle
wedge. These features which can be seen qualitatively
are the basis of the three-dimensional attenuation inversion which will be described in the next section.
4. Attenuation tomography
In this study, we use the differential attenuation factor δt ∗ obtained in the previous section to invert for a
three-dimensional anelastic structure.
A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
323
Latitude
35
30
0 < Qp < 150
Depth, km
25
0
150 < Qp < 450
450 < Qp
200
400
600
125
0 < Qp < 150
130
135
140
Longitude
145
150 < Qp < 450
125
130
135
140
Longitude
145
450 < Qp
125
130
135
140
Longitude
145
Fig. 4. Path averaged QP determined from S–P spectral ratios. Horizontal (top) and vertical (bottom) projection of raypaths are classified
by the path averaged QP value into three groups: 0 < Q̄P < 150 (left); 150 < Q̄P < 450 (middle); and 450 < Q̄P (right). High-Q paths
(450 < Q̄P ) concentrate on the east side, suggesting that these raypaths sample mainly the Pacific slab. Long raypaths that sample the
deeper part of mantle also have high-Q values. The raypaths that travel through the mantle wedge have low-Q values (0 < Q̄P < 150).
Each δt ∗ value can be expressed as a sum of travel
times and QP values for a discretized ray path
δtj∗ =
n grid
i=1
(γ TS,ij − TP,ij )
1
QP,i
(9)
Eq. (9) is the discretized version of Eq. (4), where
TP,ij and TS,ij are fractions of the P and S wave
travel times, respectively, for the ith grid point and jth
raypath, and Q−1
P,i is the model parameter of the ith
grid point.
In order to compute the travel time kernels, TP,ij
and TS,ij , we traced rays though the regional
three-dimensional velocity model of Widiyantoro
et al. (1999), using a pseudo-bending method (Koketu
and Sekine, 1998). We used rays for which the residuals between observed and calculated travel times
were less than ±5% of the total travel time.
The target region for the inversion is shown by the
grid in Fig. 1. We arranged the grid with intervals of
1.0◦ × 0.5◦ in the latitudinal and longitudinal directions, respectively, and 50 km intervals in depth. There
were 4×31 grid points in the horizontal directions and
15 grid points in the vertical direction. The grid interval in the latitude direction is larger than those of the
other two directions because we assume that the structure does not vary as much parallel to the Izu-Bonin
trench.
To stabilize the inversion, we introduced smoothing
constraint on the model parameters m = Q−1
P by the
following equation. This smoothing constraint minimizes the difference between Q−1
P values of adjacent
grid points.
1
2 (mp+1,q,r
− mp,q,r ) + (mp,q+1,r − mp,q,r )
+(mp,q,r+1 − mp,q,r )
= 21 (mp,q,r − mp−1,q,r ) + (mp,q,r − mp,q−1,r )
+(mp,q,r − mp,q,r−1 )
(10)
Because the grid interval in the latitude direction is
about two times larger than that in the longitude and
depth directions, the strength of the smoothing constraint in the latitude direction is set to be two times
smaller than the other two directions. We arranged
imaginary grid points far (about 1000 km) outside the
modeled area which include all the raypaths inside.
The attenuation of the grid points assumed to be the
same value as the outermost grid points of the modeled area.
Adding the smoothing constraint, the final inversion
problem in matrix form is represented by


γ TS − TP
δt ∗

 [m] =
(11)
1
s
0
β
324
where

A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
Q−1
1

 −1 
 Q2 
 −1 


m =  Q3 
 . 
 . 
 . 
(12)
Q−1
M
where s is the roughness matrix computed by Eq. (10),
β a roughness parameter and m the vector of model parameter. We chose a value of β = 0.001 in this study.
Eq. (11) is the standard damped least-square equation that is solved for many geophysical problems. We
solved Eq. (11) with a least-square algorithm that used
the LU decomposition method for model parameters
at grid points that had hit counts which were larger
than five. For the inversion, the total number of the
unknown parameters was 674, and the number of the
data was 978.
5. Results
5.1. Preferred model
The final results of the inversion for the three-dimensional attenuation model are shown in four crosssections (Fig. 5). The positions of the cross-sections
are illustrated in Fig. 1. Although we obtained the
values of Q−1
P as model parameters in the inversion
the process, the actual QP values are displayed.
We can recognize large structures in the model, two
high-Q areas and a low-Q area between them are consistent in all the cross-sections north to south. The two
very strong high-Q areas are likely subducting slabs.
The eastern one corresponds to the Pacific slab and the
western one may relate to the Philippine Sea slab. It
seems that the dip angle of the Pacific slab feature becomes steeper toward south. The high temperature due
to the young age of the Philippine Sea slab may produce relatively high attenuation at the shallow depths.
This may be the reason why the shallow portions of the
Philippine Sea plate from 135 to 138◦ E do not show
high-Q values. The QP value in the slab-like high-Q
regions exceeds 1000, and some areas have even larger
values. However in such extremely low-attenuation re-
Fig. 5. Vertical cross-sections of the resultant QP model obtained
from the tomographic inversion, with hypocenters used in this
study (stars). The cross-section are oriented in east–west directions
at latitudes of 35, 34, 33 and 32◦ N from top to bottom.
A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
325
Fig. 6. Close up of the cross-section of the resultant QP model at latitude 33◦ N with hypocenters used in this study (stars) and recent
seismicity (circles).
gions, the absolute value of Q is not well determined,
as mentioned in the following section.
Beneath the Shikoku Basin, a low-Q area extends
to the deeper part of the model (350–400 km). In this
area, the average QP value of 175 is clearly lower than
that of the surrounding mantle. The lowest value of
QP is 111 and located near 33◦ N, 135.5◦ E and 250 km
depth. Fig. 6 shows an expanded view of the third
cross-section with the hypocenters of recent earthquakes. The distribution of earthquake hypocenters,
which likely represent the subducting slab, is consistent with the high-Q region. Also, the low-Q portion described above, is located just beneath the recent
(30–15 Ma) spreading center and the Kinan Seamount
Chain (15–7 Ma) in the Shikoku Basin.
5.2. γ(QP /QS ratio)
In this anelastic inversion one has to assume a value
for γ, which is constant over the target area, for the
calculation of the travel time kernels through Eq. (11).
We carried out the inversion repeatedly changing the
value of γ to determine the best value. The parameter
γ is searched from 1.75 to 2.50 with intervals of 0.05.
In order to evaluate the fit of the model to the data,
the standard error of δt ∗ , S.E.(δt ∗ ), is used.
∗ − δt ∗ )2
(δtobs
cal
∗
S.E.(δt ) =
N −M
(13)
where N and M are the number of data and model
∗ are the data values and
parameters, respectively. δtobs
∗
δtcal are the calculated values using the QP and QS
models obtained in the inversion process. Fig. 7 indicates that the best fitting value of γ is 2.15. For the
final model, using the value of γ = 2.15 the obtained
S.E.(δt ∗ ) is 0.0290, which represents a variance reduction of 44% relative to the starting PREM model
(Dziewonski and Anderson, 1981). However, the differences of misfit between γ of 1.75 or 2.5 and 2.15 is
only 0.3%. It suggests that the γ is poorly constrained
in this study. Theoretically a Poisson solid has a value
of γ = 2.25. The value of γ = 2.15 from this study
is reasonable.
5.3. Resolution and error estimation
In order to examined the resolution and accuracy of
the resultant model, we computed the model resolution
matrix. In almost all areas, the diagonal elements of
the resolution matrix the values of them range from 0.5
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A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
0.0292
SE(δt*), s
0.0291
0.0290
0.0289
0.0288
1.8
1.9
2.0
2.1 2.2
γ<Qp/Qs>
2.3
2.4
2.5
Fig. 7. γ = QP /QS for values from 1.75 to 2.50 vs. data standard
error. The minimum error is obtained at γ = 2.15.
to 0.8, indicating that the model parameters are well
determined except near the edges of the solved area.
We also computed the standard error of the model
parameters, which is obtained by the square roots of
the diagonal elements of the covariance matrix. The
standard errors are mostly less than 5% of each value
of the model parameter, however on the edges of the
calculated area where the resolution are not good (less
than 0.5), we cannot obtain reliable accuracies. The
grid points with extremely small model parameters
(Q−1
P < 0.001 namely QP > 1000) have relatively
high standard errors (>10%). This can be explained by
the insensitivity of δt ∗ to the low-attenuation areas, because there is little change in the spectral amplitudes
across the limited frequency range of the study. Above
error estimation of the model parameters only takes
into account the data error which is derived from linear
regression of spectral ratio curve. However, additional
error might arise from such effects as multi-pathing,
non-ray theoretical wave propagation, and scattering.
Although it is hard to take such effects into consideration, we try to estimate them roughly. If the residuals in travel time are considered to be within ±5% of
themselves, the standard error of the model parameters would become up to 10%.
In addition, we performed a checkerboard resolution
test. A checkered pattern of alternative Q−1
P values of
e−4.5 and e−7 was created. Corresponding Q−1
S values
Fig. 8. Results from a checker board resolution test. Input model
−4.5 and e−7 . Corresponding Q−1
has alternative Q−1
P values of e
S
values were calculated using γ = 2.25. Not only the pattern but
also the absolute values of the input model are recovered for most
of the the calculation area.
A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
were calculated using γ = 2.25, and we calculated
synthetic δt ∗ data. Then the inversion process was performed, and the recovered model is shown in Fig. 8.
Not only the pattern but also the absolute values of the
input model are recovered in almost all of the calculation area except near the edges of the solved area.
We found that acceptable resolution (>0.5) was obtained and that the standard error of the resultant model
was smaller than 10%, except the edges of the calculation area and slab like high-Q portions. We define the
reliable area as region where the resolution is larger
than 0.5, and only the reliable regions are displayed
and will be used in the following discussions.
6. Discussion
6.1. Comparison with previous studies and
frequency dependence of Q
There are two previous body wave studies that have
investigated the anelastic property in this target region.
Revenaugh and Jordan (1991), using spectral ratios of
ScS reverberations at a reference frequency of 30 mHz,
find a QS of 41 ± 18 in the upper mantle around the
Izu-Bonin trench. Multiplying by γ = 2.15, this QS
value corresponds to QP = 88.
To compare the results of our study with the above
paper, we calculated the averaged QP value in the
mantle. In this calculation, the grid points whose QP
values were greater than 700 were regarded as parts of
the slabs and excluded from the calculation. The averaged value of QP for our model in the mantle is 281.
Flanagan and Wiens (1994) measured QS value beneath the Shikoku Basin using differential attenuation
of sS–S and sScS–ScS phase pairs in the frequency
band of 10–83 mHz. They found depth variations
of QS values that varied from 55 in the uppermost
mantle (0–263 km) to 177 in the transition zone
(386–493 km). Their best resolved values in the upper mantle can be compared to our results. The value
QS = 55 multiplied by γ = 2.15 gives QP = 118.
We calculated the averaged QP values to compare
our model with the study of Flanagan and Wiens
(1994) in equivalent depth ranges. A small depth
dependence in the laterally averaged QP values was
found, 266 (0–250 km), 301 (250–400 km), and 413
(400–500 km).
327
The values QP of our study are systematically larger
than those of the previous two studies. The difference
between the two previous studies and this study may
come from a frequency dependence of Q. Although
our results are consistent with no frequency dependence over the limited frequency band used in this
study (0.5–1.5 Hz), there may be some dependence
when looking at a much wider frequency range. Assuming the frequency dependence of Q as Q−1 ∝
f −α , we roughly estimated the frequency dependence
factor α. We used the QP value of 88 at 30 mHz from
Revenaugh and Jordan (1991), and QP value of 281 at
1 Hz from this study. The estimation gives α = 0.33.
We also calculated for the QP value of 118 at 50 mHz
from Flanagan and Wiens (1994), and QP value of
266 at 1 Hz from this study, and obtained α = 0.27.
These values of α are comparable to the results of previous studies (Flanagan and Wiens, 1998; Tan et al.,
1997). This indicates that the absolute values of QP
in our results are consistent with the previous studies.
If we assume QP = 150 at the center frequency of
f = 1 Hz, the change of QP due to the frequency dependence of Q (α = 0.3) is ±20 within the frequency
band of this study (0.5–1.5 Hz). This is small enough
to be neglected in the tomographic inversion.
One of the most prominent feature of the resultant
model in our study is the high attenuation area beneath
the Shikoku Basin. It is distributed at depths greater
than 200–400 km. The lowest value of QP is 111 at
250 km and the average QP value is 150 at 350 km
depth in this area. The QP values are clearly lower
than that of the surrounding mantle.
6.2. Comparison with previous regional anelastic
tomography
Tsumura et al. (2000) conducted a joint inversion
for source parameters, crustal response and attenuation structure beneath the northeastern Japan arc. The
estimated QP value of the Pacific slab is larger than
1000. The lowest QP values in the mantle is about
150. The contrast of the high-Q and low-Q values is
comparable to that of our study. They pointed out that
the low-Q zones are distributed along the volcanic
front discretely and concentrated beneath each of the
volcano groups.
Sekiguchi (1991) investigated the attenuation
structure beneath the Kanto-Tokai district where the
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A. Shito, T. Shibutan / Physics of the Earth and Planetary Interiors 140 (2003) 319–329
Eurasian, Pacific, and Philippine Sea plates are converging. In his results, the subducted Pacific and
Philippine Sea slabs are characterized by high-Q
(QP > 500) zones. There is a low-Q (QP < 125)
zone under the Philippine Sea plate. His target area
is just north of this study. The northern edge of my
model and the southern edge of his model (around
34◦ N) are consistent.
Roth et al. (1999) mapped the attenuation structure of the Tonga-Fiji region. Using a method similar to ours, they determined a best fit value of γ =
1.75, which is much smaller than that of this study
(γ = 2.15). They found the highest attenuation (QP =
90) within the upper 100 km beneath the spreading
center of Lau Basin. In contrast, the highest attenuation (QP = 111) in our study is at 250 km beneath
the old (30–15 Ma) spreading center of the Shikoku
Basin. The difference of the depth of highest attenuation may come from the differences in the activity of
the back arc basin. The Lau Basin has been opening
since only 6 Ma and the spreading rate is 90–160 mm
per year. They also pointed out that the high attenuation region correlates well with the low P wave velocity zone. They found that the entire back arc is
characterized by a gradual decrease in attenuation to
a depth of 300–400 km. Their low-attenuation values
for a slab-like high-Q (QP > 900) area consistent
with this study.
6.3. Comparison with velocity structure
We compare the attenuation model to the velocity
model of Widiyantoro et al. (1999). The velocity and
attenuation images are similar for large structures,
such as the Pacific slab. One difference is that the
lowest attenuation (QP = 111) of is in the mid mantle (250 km) in this study, however the center of the
low velocity anomaly (>3% for VP ) is in the shallower region (<100 km) of the mantle wedge. These
three-dimensional distributions of attenuation and velocity will be useful in the following paper to infer
the thermal and material properties of the study area.
7. Conclusions
Using the δt ∗ data, we obtained a fine-scale (50–
100 km) three-dimensional attenuation model for the
northern Philippine Sea region. The results shows
two high-Q regions (QP > 1000) indicating the
Pacific and the Philippine Sea slabs, and a low-Q
(QP ∼ 110) area extending to the deeper part of the
model (350–400 km) just beneath the old spreading
center in the Shikoku Basin. A small depth dependence of the laterally averaged QP was found, with
values of 266 (0–250 km), 301 (250–400 km), and
413 (400–500 km).
The attenuation model correlated with the velocity
model of Widiyantoro et al. (1999) for large structures, such as slab images. One difference is that the
lowest attenuation of our model is in the mid mantle, however the center of the low velocity anomaly
is in the shallower region of the mantle wedge. These
three-dimensional distributions of attenuation and velocity will be useful for inferring the physical properties of the mantle in the study area.
Acknowledgements
The authors would like to thank Prof. Jim Mori for
his critical comments, suggestions, and continuous
encouragement. The broadband seismogram records
were provided by seismograph networks in Japan,
J-array operated by a consortium of universities and
F-net operated by National Research Institute for
Earth Science and Disaster Prevention. This research
was supported by a Research Fellowship for Young
Scientists from the Japan Society for the Promotion
of Science.
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