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Lithospheric and Upper Mantle Structure of the Northeastern
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Tibetan Plateau
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Han Yue1, Y. John Chen1*, Eric Sandvol2, James Ni3, Thomas Hearn3, Shiyong Zhou1, Yongge Feng1,
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Zengxi Ge1, Andrea Trujillo3, Yanbin Wang1, Ge Jin1, Mingming Jiang1, Youcai Tang1, Xiaofeng Liang1,
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Songqiao Wei1, Haiyang Wang1, Wenyuan Fan1, and Zheng Liu1
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1.
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Department of Geological Sciences, University of Missouri-Columbia, MO, USA.
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Department of Physics, New Mexico State University, Las Cruces, NM, USA.
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Department of Geophysics, Peking University, Beijing, China.
Email: johnyc@pku.edu.cn
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Supplement materials
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1.
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We summarized the station information, the optimal values in the slant-stack result, the standard deviation
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and also the available data numbers in table S1. 81 stations with acceptable results were selected
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manually and corrected for optimal value. The results are shown in Table S2, and plotted in Figure 4 in
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the text. Slant-stack images of all stations are plotted in Figure S1-S5.
Slant-stack results
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Data processing and parameters used in S wave receiver function processing
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Here we present more details about the S wave receiver function processing.
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S wave receiver function calculation
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The raw seismograms are cut using a time window of about 20s to 40s with reference to the
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theoretical S wave arrival time. The vertical and radial components are then rotated to the Sv and S
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components using the theoretical ray parameters. Subsequently we remove the mean value and linear
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trend from the data and then apply a two pass fourth order tapered bandpass filter with a corner frequency
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between 0.001 and 1 Hz. In order to make the S-wave receiver functions directly comparable with the P-
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wave receiver functions, we reverse the sense of time since the Sp phases arrive prior to the primary
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teleseismic phase. After this step we perform , a time domain deconvolution procedure with a 1.5 Hz
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Gaussian filter to obtain.
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2.
SRF CCP stacking
In order to stack SRFs by their common conversion points, we first interpolate 1D velocity models
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from the CUB 2.0 model for each station, we then calculate the piercing point location and arrival time
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difference between S and Sp waves at each depth (0~250 km) for each record. Since the plane wave
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assumption is not applicable in calculating the SRFs for deeper conversions, we need to calculate the ray
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parameters for each source-converter-receiver set. This information is used to trace the Sp ray paths to
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obtain the piercing points from different conversion depths. The theoretical ray parameters are calculated
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using a global 1D velocity model, AK135 model [Kenneth et al. 1995]. We assign all SRF amplitudes to
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their appropriate bin in depth and along the profile according to their ray path; all SRF amplitudes in a
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common bin are then stacked. When stacking the SRFs in our designated profiles, we make profiles
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following the station distribution on the surface, and the profiles are dipped toward the east so that they
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are parallel to the predominant raypath direction. Bin size is adjusted at various depths to keep a relatively
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constant number of stacking bins. The equation used for stacking all SRF amplitudes in all bins is given
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by the following expression:
G

G
(| x j  xi |, z )
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Aj ( z )
 Ai ( z )
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(S1)
(| x j  xi |, z )
i
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In equation S1, Aj(z) stands for the stacked SRF amplitude of the jth stacking bin at depth z. G(|Xj-Xi|,z)
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is the stacking weight at each depth which is calculated by the distance between the jth stacking point and
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the ith piercing point. Ai(z) is the SRF amplitude of the ith SRF at the depth z. The stacking weight is
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calculated in the following equation.
G(|x j xi |, z )  exp[(
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| x j  xi |
cdist( z )
)2 ] (S2)
|xj-xi| stands for the distance between the jth stacking point and the ith piercing point. The
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parameter cdist is the the bin size that increases linearly with the depth z. Only the SRFs whose piercing
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points are included by the critical bin size are used in stacking. It is calculated by cdist=a*z+b, where a
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and b are two constants controlling the bin size and the increasing rate. The shapes of the bins are shown
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in both Figure 7 and Figure S6.
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Figure Captions:
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Figure S1 – S5. Slant-stack and bootstrap results of all I4 and DKL stations; the description of the
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method can be found in Al-Damegh, et al., (2005). The maximum values of all slant-stack images
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are plotted as the white star. We manually chose the optimal Moho depth and Vp/Vs ratio by
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considering the continuity of adjacent stations. Stations in the Qiangtang Terrane (region A in
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Figure 4) are identified by 65-70 km Moho depth and 1.8 Vp/Vs ratio, including (C08-C14, F16,
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F17). Stations in the Songpan-Ganzi region (Region B in Figure 4), are identified by 70-75 km
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Moho depth and 1.7 Vp/Vs ratio (station B02 and the rest of the stations in the high plateau south
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of the Kunlun Mountains).
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Figure S6. SRF CCP stacking result in three EW profiles. Red circles represent the location of each
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station, blue circles are piercing points of SRF at 150 km depth, and piercing points of SRF at 200
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km depth are shown by green circles. Brown line marks the boundary of the image with less than
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20 traces. The red polygon marks where underthrusted Lhasa block lithosphere slab (ULS) is
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found in the stacked SRFs. ULS and LAB are marked as dash lines in Figure b, c, and d. Gaussian
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stacking weight functions are shown as a trapezoid with the same scale as the stacking section.
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References:
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Al-Damegh, K., E. Sandvol, and M. Barazangi (2005), Crustal structure of the Arabian plate: new
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constraints from the analysis of teleseismic receiver functions, Earth and Planetary Science
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Letters, 231(3–4), 177-196.
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Kennett, B. L. N., E. R. Engdahl, and R. Buland (1995), Constraints on seismic velocities in the Earth
from traveltimes, Geophysical Journal International, 122(1), 108-124.
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