Data Collection and Processing

The data analyzed in my study are collected from 168 permanent and temporary broadband stations from 5 seismic networks: Indepth IV, Namche Barwa network, MIT- China network, NETS network and ASCENT network (Figure 3.1). 350 regional events are used in my study with magnitudes greater than 4.5 and hypocentral depths less than the Moho. The epicentral distances are limited between 3° to 15°. 5737 seismograms (Figure 3.2) are picked with good signal noise ratio and clear Pn arrivals.

I have applied a band pass filter (0.1Hz - 0.5HZ) to maximize signal to noise in order to characterize the efficiencies of Sn phases (Figure 3.2). Then I used the method of Sandvol et al. (2001) and Al-Damegh et al. (2004) to tomographically map regions of Sn blockage (Figure 3.3a). I also perform synthetic tests (Figure 3.3b) to assess the

resolution in the Sn efficiency tomography.

In addition to looking at Sn blockage, I used TSM and RTM to measure Sn Q at 0.5Hz (0.1Hz-1.0Hz), 1Hz (0.5Hz-1.5Hz) and 2Hz (1.5Hz-3.0Hz). Then I applied the LSQR algorithm to tomographically map the lateral variations of Q in the eastern Tibetan Plateau (Figure 3.4 and Figure 3.8). I also performed checkerboard tests (Figure 3.6) and bootstrap error estimations (Figure 3.7) to examine the resolution and stability of the Sn attenuation tomography.

3.3 Results

3.3.1 Sn Efficiency Tomography

The Sn efficiency tomography is shown in figure 3.3a. The most prominent feature is that Sn propagates efficiently in the southern Tibet and inefficient or blocked in the northern Tibet. This feature is consistent with previous attenuation studies (Molnar and Oliver, 1969; Barazangi and Ni, 1982; McNamara and Owens, 1995; Rapine and Ni, 1997; Barron and Priestley, 2009). Efficient Sn propagation in the southern Tibet also correlates well with fast Pn waves (Liang and Song, 2006) and a fast body wave velocity anomaly (Liang et al., 2012) and it can be interpreted as the underthrusting Indian

continental lithosphere (UICL). Further north, a blocked Sn zone is observed (BSZ1) within the UICL. Some seismic velocity studies (Figure 3.11) also confirm the UICL is not uniform and low velocity zones are observed within the UICL (Ceylan et al., 2012; Liang et al., 2012; Liang et al., 2016). It is notable that an efficient Sn zone (ESZ) is observed at ~91°E~31°N and bounded north by BNS. This feature is consistent with high P wave velocity anomalies (Li et al., 2008) and fast Rayleigh waves in this region

(Ceylan et al., 2012). In the QTB and SGFB, Sn is blocked or inefficient and shows east- west lateral variations. The BSZ2 extends southward to BNS and the ISZ extends further south to the IYS. This observation correlates with Pn wave studies (Figure 3.10) very well because they also observe a low velocity zone (LVZ) beneath QTB and SGFT in northern Tibet. This positive correlation extends further south into Indo-China. The Sn blockage in the BSZ2 also coincides with Cenozoic volcanism. In the stable QB, efficient Sn is observed.

I performed a checkerboard test (Figure 3.3b) to assess the resolution of my model by using the same ray geometries that are used for the inversion of actual data. A 300km blockage path length and 10% noise was assigned to my Sn synthetic test. The checkerboard test shows my model can be well resolved by 4°×4° cells covering the eastern Tibetan Plateau and it is good enough to show first order features. The Sn smearing is observed at the edges of my model where ray paths are confined in the same direction. The Sn leakage is also observed (for example at Sichuan Basin) because of poor ray coverage.

path length of 300km. Black lines are major tectonic boundaries. Red triangle represents volcano.

3.3.2 Sn Q Tomography

The TSM Sn Q0 map is shown in figure 3.4a. From north to south, I observe high Q (~500) values in the QB. In the SGFB and QTB, I observe relative low Q (~300) values. Another high Q value zone (HQZ) is observed between 91°E-95°E and bounded north by BNS. Further southward in the LB, a low Q value zone (LQZ) is observed.

The RTM Sn Q0 map is shown in figure 3.4b. As discussed in chapter 2, the RTM Q measurements are more accurate because it is not affected by inaccurate instrument responses or relative differences in site terms that may bias the TSM Q measurements; however it dramatically reduces the ray coverage due to more strict recording geometry. As a result, I use RTM measurements to verify the accuracy of the TSM measurements. The RTM Sn Q0 map (Figure 3.4b) shows very similar features with those observed on TSM Sn Q0 map (Figure 3.4a). In the QB, I observe high Q (~500) values. In the SGFB, I observe low Q (~150) values. A different pattern between these two models is that in RTM Sn Q0 map, I observe a relative high Q value zone in the QTB while relative low Q values in this region are observed in the TSM Sn Q0 map; however, this is very likely caused by artificial effect due to the poor ray coverage in this area (Figure 3.6b). In order to obtain more reliable RTM Sn Q0 model in the Tibet, I have added results from Pan J. J. (2016) to my model (Figure 3.5). I observe high Q (~500) values in the QB, QL and SB. I also observe low Q (~150) values in the SGFB. Further south, a high Q value zone is

observed along the BNS. A relative low Q (300) value zone is also observed in LB which corresponds with the BSZ1 in figure 3.3a.

I also performed checkerboard tests to examine the resolution of my models. The checkerboard test illustrates that Sn Q0 anomalies with a size of 2°×2° can be well

resolved by the TSM ray coverage. Figure 3.6a shows TSM Sn Q0 model is well resolved in most of my study area. The synthetic anomalies are smeared and distorted in regions lacking dense ray coverage such as the eastern part of the model. Figure 3.6b shows the RTM Sn Q0 map is not well resolved because of poor ray coverage.

I performed a bootstrap resampling technique to test the stability of my

tomographic models (Figure 3.7). In this test, I randomly resample my data until I reach the same number of observations as in my original data and then I invert the resampled data for a bootstrap model. I repeated this procedure for 100 times and the resulting set of bootstrap solutions is used to estimate the variance of the solutions. The result of the bootstrap test for the TSM Sn Q0 model is shown in figure 3.7a. It shows an uncertainty less than 50 within the Tibetan plateau and high uncertainty at the edge of the model. The result of the bootstrap test for the RTM Sn Q0 model (Figure 3.7b) shows low uncertainty within most of the Tibetan plateau.

I also construct Sn Q maps at different frequencies (0.5HZ, 1HZ, 2HZ) both using TSM and RTM (Figure 3.8). The main features are consistent with the Sn Q0 maps. At low frequency (0.5HZ), the HQZ extends further northward beneath QTB. At high

frequency (2HZ), the HQZ vanishes. This feature is consistent with Barron and Priestley (2009) and can be explained by low frequency Sn can dive deeper in the uppermost mantle while high frequency Sn travels more like head wave beneath the Moho. There are discrepancies at the edges of these models that may be caused by poor ray coverages.

The frequency dependent factor η map of TSM is shown in figure 3.9a. Across most of my model, the frequency dependent factor is low to normal (0-0.5) indicating the intrinsic attenuation is the dominant mechanism. In figure 3.9b, I observe relative high η along the Kunlun fault indicating that scattering attenuation is the dominant mechanism.

3.3.3 A Comparison of Efficiency and Q Tomographys

Comparing the results of Sn efficient tomography and Sn Q tomography, the Sn efficient tomography can resolve more features than the Sn Q tomography because the Sn Q tomography requires more strict geometry of recording geometry and incorporates far more information that the efficiency tomography. Recall that the efficiency tomography essentially reduces Sn amplitudes to a binary data set; either blocked or efficient. Still the main features between these models are very similar. I observe both efficient Sn and high Q values in the QB indicating a cold and strong lithosphere. I also observe blocked Sn and low Q values in the SGFB and QTB that suggests a hot and weak lithosphere.

Another important feature is that at ~91°E~31°N I observe efficient Sn and high Q values. At LB, I both observe blocked Sn and a low Q value zone. There are, however, clear discrepancies between these models. The Sn efficient tomography shows strong lateral variations in the SGFB and QTB while I do not see this feature in the Sn Q tomography.

This may be caused by the poor ray coverage in the Sn Q tomography and thus I should be skeptical about this part of the Sn Q model.

Figure 3.4 (a) Two Station (TSM) Sn Q0 tomographic map. Circles represent seismic attenuation anomalies. (b) Reverse Two Station (RTM) Sn Q0 tomographic map. Black lines are major tectonic boundaries.

Figure 3.5 Reverse Two Station (RTM) Sn Q0 tomographic map based on Pan J. J. 2016. Black lines are major tectonic boundaries.

Figure 3.6 Checkerboard tests for the Two Station (TSM) Sn Q0 tomographic map (a) and Reverse Two Station (RTM) Sn Q0 tomographic map (b). Black lines are major tectonic boundaries.

Figure 3.7 Map showing the standard deviations computed by bootstrap analysis for the

TSM (a) and RTM (b) Sn Q0 tomographic models. Black lines are major tectonic boundaries.

Figure 3.8 Two Station (TSM) Sn tomographic map at 0.5Hz (a), 1Hz (c), 2Hz (e).

Reverse Two Station (RTM) Sn tomographic map at 0.5Hz (b), 1Hz (d), 2Hz (f). Black lines are major tectonic boundaries.

Figure 3.9 Tomographic map of frequency-dependent (η) of (a) Two Station Method Sn

Q measurements and (b) Two Station Method Sn Q measurements. Black lines are major tectonic boundaries.

Figure 3.10 Pn wave velocities. The gray lines show major tectonic features of Tibet.

(Liang and Song, 2006)

Figure 3.11 Shear wave velocities for depth of 100km. The gray lines show major

tectonic features of Tibet. (Ceylan et al., 2012)

3.4 Discussion

Previous studies have confirmed the existence of the UICL. However, the geometry of UICL is still under debate. Ni and Barazangi (1984) proposed a wholesale underthrusting Indian lithosphere beneath the south Tibet while Tilmann et al. (2003) shows in the central Tibet, the UICL is subducting vertically at BNS. Yue et al. (2008) fails to see the subvertical downwelling feature, instead, they found north dipping discontinuity beneath BNS and interpreted it as underthrusting Lhasa terrace or remnant oceanic slab. Recently, a number of seismic studies (Li et al., 2008; Ceylan et al., 2012; Liang et al., 2012; Liang et al., 2016) have proposed a fragmented underthrusting Indian lithosphere beneath the south Tibet. It suggests the UICL has a sub-horizontal geometry, and tears laterally into two fragments. The west branch appears to be detached and vertically sinking into the asthenosphere.

I observe efficient Sn in the most southeastern Tibet indicating the UICL. A prominent feature is at ~91°E~31°N I observe efficient Sn and high Q values. This feature coincides with high Pn velocity anomalies (Liang and Song, 2012) and fast Rayleigh wave (Ceylan et al., 2012). Typically, efficient Sn and high seismic velocities indicate cold and strong lithosphere (Barron et al. 2009). As a result, I interpret this feature as a sinking slab detached from the UICL.

In addition, I also observe high Q zone extends as far as QTB at low frequency; at high frequency, I do not see this feature. According to previous studies (Molnar and Oliver, 1969; Barron et al. 2009), low frequency Sn can dive deeper than high frequency

Sn. It can be interpreted that the UICL is dipping northward rather than vertically subduction.

The Sn efficient map also shows east-west lateral variation of the UICL, A BSZ extends southward to BNS and the ISZ extends further south to the IYS. This observation correlates with Pn wave studies (Liang and Song, 2006) very well. My results show the UICL extends further north in the central Tibet than it extends in east Tibet.

3.4.2 SGFB and QTB

The blocked Sn and low Q values in the SGFB and QTB is consistent with low Pn velocity anomalies (Liang and Song, 2012) and slow Rayleigh wave (Ceylan et al., 2012). It thus suggests a hot and weak lithosphere. The blocked Sn and low Q values also

coincide with Cenozoic volcanism. A number of studies (Li et al., 2008; Ceylan et al., 2012; Liang et al., 2012; Liang et al., 2016) propose that the low velocity zone in the SGFB and QTB is caused by upwellings induced by the sinking slab detached from the UICL. My observations can also support this hypothesis.

3.4.3 KL and QB

I observe efficient Sn and high Q values in the QB indicating a cold and strong lithosphere. The KL outlines a boundary between efficient Sn and blocked/inefficient Sn, I also observe high frequency dependent factor η and negative site term north of KL suggesting a strong scattering attenuation. These observations can be caused by the Moho offset along the KL.

3.5 Conclusions

I have collected a large data set in the eastern Tibetan Plateau. Two tomographic techniques have been used to determine the attenuation structure of the uppermost mantle beneath the eastern Tibetan Plateau. My primary conclusions are as follows:

(1) I observe efficient Sn in the southern Tibet and I interpret this feature as the UICL. (2) I also observe efficient Sn with high Q values (~450) at ~91°E~31°N and it suggests a sinking slab detached from the UICL.

(3) Sn is blocked with relative low Q values (~300) across the QTB and SGFB indicating a hot and weak lithosphere. This observation can be caused by upwellings induced by the sinking slab detached from the UICL.

(4) The lateral heterogeneity of Sn attenuation indicates a complex geometry of the UICL. In the central Tibet, The UICL is dipping northward and can extend further north beneath the QTB.

(5) I observe efficient Sn and high Q values (~500) in the QB indicating a cold and strong lithosphere.

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Chapter 4: Sn Attenuation in the Northern Middle East