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Supplementary Materials
Seismic anisotropy is related to the curvature (η) of the velocity ellipsoid between Vp-fast
3
and Vp-slow axes. In this work we assume hexagonal symmetry with a pure ellipsoid, and
4
therefore the shape of the ellipsoid is the same for both P and S waves where η becomes a
5
function of percent anisotropy alone [see e.g. Porter et al., 2011]. This assumption allows us to
6
approximate η while reducing the number of parameters in the inversion, which increases its
7
stability.
8
We test the effects of background velocities in the inversion by generating synthetic data
9
for various cases and re-inverting for the AML parameters using the fixed background velocities.
10
In all cases we generate receiver functions reproducing the event distribution (back-azimuth and
11
slowness) for station PGC and add 10% Gaussian noise. We perform five different tests (Table
12
S2): in Test 1 we use a slow background velocity model for both the AML and underlying
13
mantle half space and invert assuming higher mantle velocities; in Test 2 we use input velocities
14
intermediate between those of Test 1 and the ones fixed in the inversion; Test 3 is performed
15
using the same input parameters as in the inversion; Test 4 uses faster background velocities; and
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finally, Test 5 uses slow velocities for the underlying mantle half space and AML velocities
17
equal to those used in the inversion. The recovered parameters are shown in Table S2 and Figure
18
S5. These tests indicate that the relative difference between input and recovered thickness and
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percent anisotropy of the AML vary between 0 – 20 percent, with most cases showing
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differences below 10 percent, well within the estimation error. In particular, we find that Tests 1
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and 5 show the largest departure from input values, but for a different combination of
22
parameters. Finally, we find that the orientation of the fast axis of symmetry is very well
23
recovered in all cases (within 1 – 2 degrees).
24
The comparison of our results for Mexico with those of Song and Kim [2011] are most
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relevant since a similar technique was used on the same data set. In their study the authors first
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use conversions from local intra-slab earthquakes and find evidence of a 2-6 km thick high-
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velocity lid (HVL) overlying normal oceanic mantle and underlying a low-velocity, anisotropic
28
layer (LVL). They further use radial receiver functions to show that the HVL is consistent with
29
7% anisotropy, which they rename the anisotropic mantle lid (AML). We suggest three possible
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explanations for the difference in estimates that we obtained and those of Song and Kim [2011].
31
First the difference in thickness may be explained by a combination of two effects: 1) we use a
32
lower cutoff frequency (0.5 Hz) in the receiver function filtering that resolves longer
33
wavelengths, and 2) the thickness of the AML in Song and Kim [2011] is estimated using the
34
direct conversions from local intra-slab earthquakes, which may resolve finer layering (like those
35
obtained from Pn wave velocities) but may not resolve the entire thickness of the AML. Second,
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our two-step inversion procedure for estimating AML parameters is more sensitive to the
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anisotropy contrast between the thicker AML and underlying mantle, as opposed to the
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anisotropy contrast between the overlying oceanic crust and the AML, resulting in different
39
anisotropy estimates between the top and bottom of the AML [e.g., Shinohara et al., 2008].
40
Third, in this study we use both the radial and transverse components in the estimation of the
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LVL and AML parameters, which was not the case in the study by Song and Kim [2011].
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Transverse component receiver functions are more sensitive to anisotropy than radial
43
components alone [Levin and Park, 1998] and the combination of both radial and transverse
44
components allows a more accurate estimation of the heterogeneous, anisotropic structure.
45
46
Figure S6 shows the magnetic anomalies [Korhonen et al., 2007] offshore of each
subduction zone.
2
47
Additional References
48
Audet, P., M. G. Bostock, D. C. Boyarko, M. R. Brudzinski, and R. M. Allen (2010), Slab
49
morphology in the Cascadia fore arc and its relation to episodic tremor and slip, J.
50
Geophys. Res., 115, doi:10.1029/2008JB006053.
51
52
53
Hayes, G. P., D. J. Wald, and R. L. Johnson (2012), Slab1.0: A three-dimensional model of
global subduction zone geometries, J. Geophys. Res., 117, doi:10.1029/2011JB008524.
Korhonen, J. V. et al. (2007), Magnetic Anomaly Map of the World; Map published by
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Commission for Geological Map of the World, supported by UNESCO, 1st Edition,
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GTK, Helsinki, 2007. ISBN 978-952-217-000-2.
56
57
58
Levin, V., and J. Park (1998), P-SH conversions in layered media with hexagonally symmetric
anisotropy: A cookbook, Pure App. Geophys., 151, 669-697.
McCrory, P. A., J. L. Blair, and D. H. Oppenheimer (2006), Depth to the Juan de Fuca slab
59
beneath the Cascadia subduction margin – A 3‐ D model for sorting earthquakes, U.S.
60
Geol. Surv. Data Ser., 91, U.S. Geol. Surv., Reston, Va. (Available at
61
http://pubs.usgs.gov/ds/91/)
62
Porter, R., G. Zandt, and N. McQuarrie (2011), Pervasive lower-crustal seismic anisotropy in
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Southern California : Evidence for underplated schists and active tectonics, Lithosphere,
64
3, 201-220.
65
3
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Table S1. List of networks and broadband stations used in this study. Results of receiver
67
function inversion are shown on the right. H: thickness of the AML; A: percent anisotropy; T
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and P: trend and plunge of the fast axis of hexagonal symmetry.
4
Network
Station
Latitude
Longitude
H (km)
A (%)
T (deg)
P (deg)
CN
BTB
49.4683
-125.5214
5.4 ± 0.8
23 ± 2
78 ± 4
2±2
CN
LZB
48.6117
-123.8236
5.2 ± 0.8
28 ± 3
125 ± 5
34 ± 3
CN
MGB
49.0
-124.6975
15 ± 2
15 ± 2
125 ± 4
3±1
CN
OZB
48.9603
-125.4928
9.0 ± 1.6
17 ± 3
81 ± 9
43 ± 7
CN
PFB
48.5717
-124.44
5.2 ± 0.6
29 ± 2
134 ± 3
1.0 ± 0.7
CN
PGC
48.65
-123.45
5.6 ± 1.3
27 ± 3
127 ± 4
10 ± 1
CN
SNB
48.775
-123.1708
7.6 ± 1.6
24 ± 3
117 ± 4
5±2
CN
VGZ
48.4139
-123.3244
7±1
29 ± 3
107 ± 5
27 ± 3
FNET
TSA
33.1781
132.82
16 ± 2
17 ± 2
261 ± 3
20 ± 2
FNET
OKW
33.8272
133.469
17 ± 2
26 ± 4
222 ± 4
65 ± 2
FNET
UMJ
33.5795
134.037
21 ± 2
8±2
51 ± 18
12 ± 7
FNET
ISI
34.0606
134.455
35 ± 7
3±2
220 ± 15
63 ± 8
TO
EL30
17.00
99.78
15 ± 2
13 ± 2
47 ± 6
29 ± 5
TO
EL40
17.05
99.76
17 ± 2
11 ± 2
21 ± 7
29 ± 6
TO
PLAY
17.12
99.67
25 ± 2
14 ± 2
13 ± 4
13 ± 2
TO
TICO
17.17
99.54
24 ± 4
8±1
350 ± 9
31 ± 7
TO
XALT
17.10
99.71
30 ± 10
12.5 ± 1
354 ± 3
8±2
TO
XOLA
17.16
99.62
18 ± 2
14 ± 2
9±4
12 ± 3
XF
ACHA
9.828
-85.2476
22 ± 8
21 ± 4
348 ± 5
23 ± 3
XF
ARDO
10.213
-85.5964
24 ± 8
28 ± 4
42 ± 5
30 ± 4
5
XF
BANE
9.929
-84.9564
26 ± 10
28 ± 3
350 ± 5
29 ± 2
XF
GRZA
9.9155
-85.635
27 ± 6
21 ± 3
19 ± 4
4±1
XF
INDI
9.865
-85.5011
32 ± 10
13 ± 2
346 ± 5
14 ± 5
XF
JUDI
9.865
-85.5387
22 ± 6
19 ± 3
38 ± 5
30 ± 3
XF
MANS
10.099
-85.3811
19 ± 6
14 ± 2
40 ± 6
23 ± 3
XF
PNCB
9.589
-85.0917
15 ± 6
17 ± 2
9±5
16 ± 3
XF
POPE
10.063
-85.2634
24 ± 8
30 ± 4
5±4
36 ± 4
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Table S2. Results of tests for the robustness of the inversion. For each case below we produce
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synthetic receiver functions (with 10% added Gaussian noise) for incoming waves that match the
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distribution of data for station PGC. We use various input P and S velocities with fixed
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parameters for the AML and re-invert the synthetic data with fixed P and S velocities of 8 and
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4.5 km s-1, respectively, to estimate the bias in the recovered parameters for the AML. P and S
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velocities separated by dashes and with subscripts A and M are input values for the AML and sub-
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slab mantle, respectively. H: thickness of the AML; A: percent anisotropy; T and P: trend and
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plunge of the fast axis of hexagonal symmetry. In all cases the input (subscript i) AML
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parameters are Hi = 20 km, Ai = 15%, Ti = 125° and Pi = 15°. Recovered values have subscript f.
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These results show that T and P are well constrained in the inversion, regardless of the input
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velocity structure. H and A slightly trade-off with the input velocities.
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Test #
VpA – VpM (km s-1)
VsA – VsM (km s-1)
Hf (km)
Af (%)
Tf (deg)
Pf (deg)
1
7.6 – 7.6
4.1 – 4.1
23.0
15.8
126
17
2
7.8 – 7.8
4.3 – 4.3
21.4
15.5
126
16
3
8.0 – 8.0
4.5 – 4.5
19.9
15.1
125
15
4
8.2 – 8.2
4.6 – 4.6
19.9
15
125
14
5
8.0 – 7.6
4.5 – 4.1
21.2
18.4
124
13
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7
83
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Figure S1. Stacked radial (A) and transverse (B) component receiver functions for station PGC
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showing double polarity pulses in converted (Ps at 4-5 sec) and back scattered (Pps at 13-15 sec
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and Pss at 18-20 sec) waves indicating the signature of a low-velocity zone. Solid and dashed
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lines in C show the distribution of events in slowness and back-azimuth bins, respectively.
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Receiver functions are filtered between 0.01 and 0.5 Hz.
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90
8
91
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Figure S2. Inversion results for the isotropic background velocity model at station PGC showing
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stacked radial (A) and transverse (B) component receiver functions as well as best fit radial (C)
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and transverse (D) component synthetic data. Scatter plots in E-J show the results of Monte
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Carlo inversion for various combinations of parameters where warm colors represent lower
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misfit. HCC and RCC: thickness and Vp/Vs of forearc continental crust; HLVL and RLVL: thickness
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and Vp/Vs of low-velocity zone corresponding to upper oceanic crust; HLOC and RLOC: thickness
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and Vp/Vs of lower oceanic crust.
99
9
100
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Figure S3. Inversion results for the anisotropic mantle lid (AML) model at station PGC showing
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stacked radial (A) and transverse (B) component receiver functions as well as best fit radial (C)
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and transverse (D) component synthetic data. The phase corresponding to conversions from the
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base of the AML is more evident in A and C as a negative arrival at ~7 sec between bin numbers
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15-60. Scatter plots in E-F show the results of Monte Carlo inversion for the anisotropic
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parameters where warm colors represent lower misfit.
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10
108
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Figure S4. Same format as Figure S3 but for station PNCB in Costa Rica. AML signals are
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evident at 4-5 sec in all panels A-D. Later arrivals (>6 sec) are reverberations from shallow LVL.
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112
Figure S5. Same format as Figure S3 but for station PLAY in Mexico.
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113
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Figure S6. Same format as Figure S3 but for station ISI in southwest Japan.
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Figure S7. Relative difference between input and recovered parameters for the AML for
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different synthetic tests. H: thickness of the AML; A: percent anisotropy; T and P: trend and
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plunge of the fast axis of hexagonal symmetry. The thickness and magnitude of anisotropy are
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more sensitive to background velocities than the orientation of the fast axis.
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120
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Figure S8. Seafloor magnetic anomalies. (A) Southwest Japan; (B) southern Mexico; (C)
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southern Vancouver Island (Canada); and (D) Nicoya Peninsula (Costa Rica). Inverted red
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triangles show the locations of seismic stations used in this study. Brown triangles are arc
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volcanoes. Yellow lines are slab contours shown at 10 km intervals from the SLAB1.0 model
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[Hayes et al., 2012] (A, B, D) and from McCrory et al. (2005) and Audet et al. (2010) (C, solid
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and dashed lines, respectively). The fossil spreading direction is calculated from the average of
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the directional gradient of long-wavelength magnetic anomalies for areas close to the trench.
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