Seismic structure of the underthrusting Indian ... | Wiley Online Library

TECTONICS, VOL. 29, TC6021, doi:10.1029/2010TC002722, 2010

Seismic structure of the underthrusting Indian crust in Sikkim Himalaya Arun Singh,1 M. Ravi Kumar,1 and P. Solomon Raju1 Received 12 April 2010; revised 8 October 2010; accepted 20 October 2010; published 30 December 2010.

[1] This study presents the first results of the seismic

character of the underthrusting Indian crust in the Sikkim Himalaya deduced through an analysis of ∼3600 receiver functions (RFs) abstracted from waveforms registered at 11 broadband stations spanning a 110 km long N‐S profile from the foothills to the higher Himalaya. Common conversion point stacks of receiver functions prominently trace the northward dipping geometry of the Indian Moho beneath the Himalaya. Monte Carlo inversion of the azimuthal variations of the RFs at individual stations adopting the nearest neighborhood algorithm approach reveals that the crustal thickness varies from ∼40 km to 61 km from south to north, with a dip varying between 4° and 10° among stations. A Moho doublet prominently seen at a depth of ∼40 km in the higher Himalaya to the north of Main Boundary Thrust has been interpreted in terms of possible (partial) eclogitization of a granulitic Indian lower crust, akin to the finding just north of the study region beneath southern Tibet. A strong layer of anisotropy (∼17%) localized within a low‐velocity layer between 20 and 30 km has a NW‐ SE oriented fast polarization direction counterintuitive to the convergence‐parallel and range‐perpendicular alignment expected in a convergent setting due to shear processes. Midcrustal transcurrent deformation in Sikkim and Bhutan, evidenced by a conjugate system of strike‐slip faulting with NW to NE trending P axis orientations is the most feasible mechanism for causing a near strike parallel oriented fast axis of anisotropy in this segment of Himalaya. Citation: Singh, A., M. R. Kumar, and P. S. Raju (2010), Seismic structure of the underthrusting Indian crust in Sikkim Himalaya, Tectonics, 29, TC6021, doi:10.1029/2010TC002722.

1. Introduction [2] High‐resolution imaging of the subsurface structure of continental collision zones like the Himalaya provides valuable clues toward understanding the geodynamics and genesis of Great earthquakes. The basic models proposed for thickening of Tibetan crust up to 70 km favor under1 National Geophysical Research Institute, Council of Scientific and Industrial Research, Hyderabad, India.

Copyright 2010 by the American Geophysical Union. 0278‐7407/10/2010TC002722

thrusting of the Indian crust and mantle lithosphere beneath Tibet [Argand, 1924; Barazangi and Ni, 1982] or indentation of an intact Indian crust into a comparatively weak Tibetan lower crust [Zhao and Morgan, 1987; DeCelles et al., 2001]. The Indian plate continues to subduct beneath the Tibetan plateau up to the southern Lhasa block facilitated by the Main Himalayan Thrust (MHT) that is regarded as the decollement plane [Nelson et al., 1996]. The MHT acts as a gliding plane between the Himalayan mountains and the Indian shield and accommodates a 20 mm/yr convergence between India and Eurasia [Zhao et al., 1993]. Aseismic slip across this thrust sheet is thought to be responsible for present‐day deformation and associated seismicity in the Himalayan region [Cattin and Avouac, 2000]. [3] Newer insights on the structure and geometry of the Indian plate as it under thrusts Eurasia have been gleaned through data accrued from prolific deployments of broadband stations in the eastern Himalaya and southern Tibet under various passive seismological experiments like the INDEPTH, HIMNT, NAMCHEBARWA, HIMPROBE and Hi‐CLIMB. Receiver function analysis of data from the HIMNT and Hi‐CLIMB stations that sample the Nepal Himalaya bring out a Moho configuration that gently dips northward from ∼40 km beneath the Ganga basin to ∼50 km beneath the high Himalaya [Schulte‐Pelkum et al., 2005]. Interestingly, the MHT and the bottom of the Indian crust (Moho) have been imaged as continuous entities from the Nepal Himalaya right up to 31°N [Nábělek et al., 2009]. A significant finding in the Nepal Himalaya has been the detection of a strong (∼20%) layer of anisotropy coinciding with the decollement surface. It is inferred that such a strong anisotropy is developed in response to the shear processes responsible for occurrence of great earthquakes in this portion of Himalaya [Schulte‐Pelkum et al., 2005]. Further north, beneath the Tibetan plateau, the results of Nábělek et al. [2009] favor an anisotropic crust mantle boundary. [4] Compared to the Nepal Himalaya, seismic signatures that characterize the continent‐continent collision remain obscure in the adjacent Sikkim Himalaya (Figure 1), owing mainly due to paucity of seismic networks. The first constraints on the crustal structure in this segment of Himalaya are obtained from gravity and magnetic data collected along a NS profile. Joint modeling of these measurements suggests that the long wavelength gravity anomalies arise due to variations in crustal thickness from about 36 km in the South to 60 km in the North beneath the higher Himalaya [Tiwari et al., 2006]. At the shallow level, recent magnetotelluric studies reveal that the Main Frontal Thrust (MFT) and Main Boundary Thrust (MBT) are expressed as high conductive features with values in the range of 10–40 Wm. An anomalously high conductive body (2–5 Wm) at a depth

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SINGH ET AL.: CRUST SIKKIM HIMALAYA

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Figure 1. Tectonic map of the Himalaya and Tibetan plateau with the Sikkim region indicated as a rectangular box. Seismic stations operated under the SIKKIM (red) and INDEPTH‐II (blue) experiments are shown as inverted triangles. MBT, Main Boundary Thrust; MCT, Main Central Thrust. The inset shows an enlarged view of the study region along with the prominent lineaments, faults, and stations.

of 3–15 km is attributed to presence of Himalayan sediments trapped with fluids [Patro and Harinarayana, 2009]. [5] With the primary objective of investigating the seismic structure of the underthrusting Indian plate in the Sikkim Himalaya, an experiment was launched by the National Geophysical Research Institute, under which 11 broadband seismic stations have been installed and operated in the region, in a phased manner during 2004– 2009. These stations spaced at an interval of 10 km along a N‐S profile traverse the prominent tectonic features like the Main Central Thrust (MCT) (which takes a sinusoidal turn in the region) and MBT, and form a southward extension of the INDEPTH‐II profile (Figure 1). The units are a combination of KS2000M and STS‐2 sensors connected to REFTEK‐130 data acquisition systems continuously recording the ground motion at 20 samples per second. All the stations yielded high‐quality teleseismic data that were used for receiver function analysis and modeling for subsurface structure. This study presents the first results of the seismic manifestation of the geological processes operative in this geodynamically active part of Himalaya through high‐ resolution imaging of the geometry of the underthrusting Indian crust and its nature of anisotropy.

2. Receiver Functions [6] Waveforms of teleseismic earthquakes in the epicentral distance range of 30° to 100° have been extracted and

quality checked automatically using the vertical components, to retain those having an SNR≥2.5. Subsequently, the data are further sifted based on a visual inspection of all the three components. Although the back azimuthal distribution of the earthquakes sources is skewed toward eastern azimuths, the sufficiently long period of operation of the stations enabled good registration of events from the western azimuths also (Figure 2). Prior to the computation of receiver functions (RFs) the Z, N and E components are rotated into a ray coordinate system [Vinnik, 1977] using the near surface velocities of P and S waves [Kennett, 1983]. Under the assumption of lateral homogeneity, Ammon et al. [1990] have demonstrated that the amplitudes of the source equalized direct teleseismic P waves registered on the radial components are related to the near surface shear velocity directly beneath the station. Therefore, by measuring these amplitudes for a suite of waveforms representing various slowness values, it is possible to obtain a representative near surface velocity. The rotation operation decomposes the wavefield into its P (L), SV(Q) and SH(T) components. The converted phases are then isolated from the P coda by deconvolving the P from the SV and SH components by simple spectral division using a water level stabilization, resulting in a total of 3605 SV and SH P wave receiver functions. In order to qualitatively assess the layering beneath each station, the receiver functions in the slowness range of 4.4 to 8.8 s/° are sorted in 50 bins and stacked. Prior to stacking, IASP91 velocity model has been used to correct

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within a 5 × 5 km grid. The migration is performed for direct conversions (Ps) as well as multiples (PpPs and PpSs), which are later combined to enhance the coherent features from all the three images [Wilson et al., 2003; Nábělek et al., 2009]. The migrated image (Figure 4) clearly brings out the geometry of the Indian crust beneath Himalaya. A pronounced Moho at a depth of ∼40 km south of MBT deepens to ∼61 km north of MCT in the higher Himalaya. Although there seems to be an abrupt deepening of the Moho across the MBT, it generally follows a gently dipping trend north of it. The other identifiable feature in the crustal section is a positive conversion at ∼20 km depth, although not very prominent and coherent across the profile. A few patches of low velocity in the shallow crust mainly observed at stations PHG and NAM may be attributed to localized features or reverberations.

4. Seismic Character of the Crust

Figure 2. Earthquakes in distance range of 30°–100° during the period 2004–2009 used in this study. The study region is indicated as a square. the traces for the moveout arising due to geometry of the raypaths corresponding to different epicentral distances. The RFs are reduced to a fixed slowness of 6.4 s/°, corresponding to an epicentral distance of 67°. In case of isotropic crustal layers with a gentle dip, such a move out correction would make the Ps conversion times at different slowness values comparable. The slowness sections (Figure 3) reveal that the P‐to‐s conversion from the Moho (Pms) although weak at a few stations, is identifiable with its arrival time varying from ∼4 s to 7.5 s from south to north. A strong conversion corresponding to an intracrustal layer (Pcs) can be traced at most of the stations. The RFs at a few stations, particularly PHG and NAM indicate presence of a strong negative phase at shallow depths. The positive arrivals between 2 and 3 s are not so prominent in this region, as observed in the nearby Nepal Himalaya [Schulte‐Pelkum et al., 2005].

3. Image of the Crust [7] The spatial variations in the crustal configuration beneath the Sikkim Himalaya are imaged by transforming the P wave SV receiver functions into depth by back projecting the energy along their raypaths. Using the IASP91 model for this purpose results in an apparent deepening of the observed Moho due to stretching of the signal below this interface in view of the crustal conversions being migrated with mantle velocities (the IASP Moho being shallower). To avoid this problem, a modified IASP model having a 55 km thick crust has been used. A depth migrated image is then obtained by projecting the amplitudes corresponding to different depth offsets onto a 2‐D reference plane perpendicular to the local strike of Himalaya (Figure 1) and stacking those which have common conversion points

[8] Presence of energy on the transverse component of receiver functions may be indicative of dipping isotropic layers or anisotropy. In either case, the Ps conversions from these layers and their free surface multiples exhibit variations in polarity and amplitude as a function of back azimuth, with a periodicity of 360° for dip and 180° for anisotropy [Cassidy, 1992; Levin and Park, 1997, 1998; Savage, 1998]. Ray theoretical forward modeling approaches capable of simulating dipping and anisotropic layers [Frederiksen and Bostock, 2000] have a great utility in investigating the seismic structure of regions like the Himalaya where deformations due to large‐scale shear processes along the plane of detachment are expected to produce a combination of anisotropy and dipping effects in the data. In order to decipher these effects at individual stations, the traces are first grouped in 50 back azimuthal bins and then sorted by slowness within each bin. To discriminate the variations within each station due to 2‐D structure/anisotropy, the dependence of the travel times on the different dominant slowness ranges in each back azimuth is accounted for by applying a slowness correction to each of the traces. These azimuthal receiver function sweeps at the individual stations that are sorted by latitude enable us to trace the disposition of the Moho and the intracrustal layers from south to north along the profile. In the Sikkim Himalaya region, combined effects of both dip and anisotropy beneath the stations are evidenced in terms of strong energy on the transverse components (Figure 5). [9] In order to parameterize the layered structure beneath a seismic station in terms of the P and S velocity variations, layer dip and anisotropy, we adopt the neighborhood algorithm [Sambridge, 1999] in conjunction with the forward modeling scheme of Frederiksen and Bostock [2000]. As described in detail by Frederiksen et al. [2003], the neighborhood algorithm approach involves search for the optimal model within a predefined range of parameters that best satisfy a suite of SV and SH P wave receiver functions. Starting with a random number of points in a model space, forward modeling is performed for each model, retaining the best models with lowest misfits and preferentially searching in their neighborhoods during the next iteration along with a

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Figure 3. SV components of P wave receiver functions at stations, stacked in narrow slowness bins. Stations are arranged from south to north. Summation traces moveout corrected for converted (bottom) and multiple (top) phases are shown in the top row. Pms, Moho conversion (black arrow); Pcs, conversion from intracrustal layer (gray arrow). 4 of 12

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Figure 4. (top, middle, and bottom) Migrated image of SV component of P wave receiver functions along a S–N profile at 88.55° longitude. Elevations and station locations (inverted triangles) are shown in Figure 4 (top). Figure 4 (bottom) shows the major features of the image, together with seismicity and focal mechanisms in map view (source is Hazarika et al. [2010]). Crustal thickness estimates obtained through inversion are plotted by small white bars in the migrated image (Figure 4, middle). The gray shaded area represents anisotropic layer obtained through inversion. ILC, top of Indian lower crust.

fresh set of random models. The misfit function is based on the correlation coefficient between synthetic and real traces, with a weighting factor assigned to the SV and SH traces. [10] As a first step, a 1‐D crustal velocity structure beneath each station is obtained by modeling only the slowness dependence of the prominent converted phases. In the absence of good a priori knowledge about the Vp and Vs for Sikkim Himalaya, the available information from Nepal Himalaya is used as a starting model [Schulte‐Pelkum et al., 2005]. With this as the base model, a search is made for the optimal dip and anisotropy of the layers, without including multiples, which are not so clear in the data. Tests on synthetics and also using real data suggest that the models can be recovered well even without multiples [Frederiksen et al., 2003]. The effect of exclusion of multiples on the model parameterization using the NNA approach is dis-

cussed in detail by Sherrington et al. [2004]. Due to constraints imposed by the back azimuthal coverage and complicated nature of the receiver functions (particularly the transverse components), it was possible to model the data only at six stations. The velocity models obtained for these stations (Figure 6) reveal that the crustal thickness values are 42 km for SIN, 49 km for GAN, 59 km for MGN, 58 km for TNG, 59 km for LCN and 61 km for TGU. The dip of the Moho is recovered well for these stations and ranges from ∼4° to 10° with a variation in strike between ∼270° and 300° or equivalently a down dip direction of 0°N to 30°N. A small positive jump indicated by the models for stations, SIN, GAN, TNG, LCN and TGU at depths of ∼18 to 22 km are supported by the data as seen from the migrated image (Figure 4). However, at station MGN, strong low‐velocity layers are prominent at these depths. Another feature seen

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Figure 6. Crustal models at stations indicated. Circles with black bars show strike directions of the anisotropic layer in map view (gray shade) obtained through inversion. Moho (black arrow) and the intracrustal layer interpreted as top of the Indian lower crust (gray arrow) are indicated at each station. Moho depth can be obtained by substracting topography from the crustal thickness.

from the velocity models is a positive discontinuity between ∼40 and 44 km observed for stations north of MBT. The velocity contrast across this layer is large for station MGN, which is close to the MCT and very small for TNG. Also, the models suggest an increase in lower crustal P velocities from ∼6.5 km/s (∼3.7 km/s for S) in the south to ∼6.7 km/s (∼3.9 km/s for S) in the north beneath Greater Himalaya. Such an increase in lower crustal velocity from south to north was also observed by Schulte‐Pelkum et al. [2005], in the nearby Nepal Himalaya.

5. Evidence for Strong Lower Crustal Anisotropy [11] The energy on the transverse component at most of the stations beneath Sikkim Himalaya appears too large implying a complicated structure. A wide range of back azimuth and slowness coverage at stations GAN and TGU (Figure 7) permitted us to model for both dip and anisotropy at these stations. The complexity of the data warranted extensive trials using various possible combination of starting models using 6 to 7 layers to explain the SV and SH receiver functions. The dependency of the data has been checked for dip, anisotropy and their combined effects. Although the large energy on the transverse component can be satisfactorily modeled (with low misfit) by introducing only isotropic layers with a steep dip, the final models obtained were often geometrically more complex and unrealistic. Inversions performed with a combination of layer dip and anisotropy produce geologically acceptable models, with a decrease in misfits favoring a combination of these effects. In view of the highly nonlinear nature of parameterization using the neighborhood algo-

rithm approach, the search is done with a different random seed, thus enabling a wider search of the model space. Tests with 10 random seed value gave almost similar results. For each seed value a total of 1000 iterations was performed for GAN and 500 iterations for TGU, using a sample size of 25 models and retaining 8 models per cycle. These numbers define the convergence rate and efficiency of search. A high ratio of initial models generated, (here 25) and models retained for the next iteration (here 8), ensures a slowly converging search widely sampling the model space. [12] Albeit the forward modeling scheme being very efficient in generating ray‐theoretical synthetics for planar interfaces, considering more layers results in an exponential increase in the number of possible converted phases. In view of the absence of clear multiples at most stations, inversion was carried out only for direct conversions. Equal weight was given to all the SV and SH binned P wave receiver functions. The misfits for about 25,000 models for GAN and 15,000 models for TGU are shown in Figure 8. A large misfit for station GAN is due to a strong negative phase below the Moho, which is not included in the model. Synthetic data indicates that this strong negative phase may be a multiple from an intracrustal layer. The inversions were performed to recover the dip and anisotropic parameters for different crustal layers obtained from 1‐D inversions. The best resolved parameters seem to be a combination of dip and anisotropy at depths of 20 to 30 km. [13] Attempts to parameterize anisotropy in upper crust as observed in nearby Nepal Himalaya [Schulte‐Pelkum et al., 2005] using data from GAN and TGU did not yield well constrained results. The anisotropic layer found at depths of

Figure 5. Back azimuthal variation of (top) SV and (bottom) SH components of P wave receiver functions corrected for slowness dependence of arrival times. Positive amplitudes are represented by red, and negative ones are represented by blue. A total of 3605 receiver functions are used to make this image. The gray shades separating the panels represent the back azimuthal range of the traces (shown at the bottom left corner) for each station. 7 of 12

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Figure 7. Back azimuth (black line) and slowness (gray line) values corresponding to the trace numbers assigned to data at stations GAN and TGU. 20 km is checked for consistency to verify whether this feature can be produced by dip alone, without a combination of anisotropy. Misfits are calculated for all combinations of dip (0° to 30°) and strike (0° to 180°) and all combinations of anisotropy. Since the hexagonal symmetry axis for crustal minerals often represents the slow axis which is characterized by negative percentage of anisotropy, the strength of anisotropy is allowed to vary from −20% to 20% for P and −20% to 20% for S. These tests suggest that invoking large dips results in higher misfits at both the stations while introducing anisotropy reduces the misfits. A combination of small dip and large positive anisotropy however results in a good fit between observed data and synthetics. [14] The inversion results beneath both these stations in Sikkim Himalaya show a 10 km thick strong (16.4 ± 0.8% at GAN and 18.5 ± 1.2% at TGU) anisotropic layer below the plane of detachment, at a depth of 20 km. This layer does not show much dip (∼3° to 4°) as also evident from the migrated image of receiver functions (Figure 4) and has a well constrained strike and plunge of 120° ± 1.2° and 19° ± 1.6° for GAN and 141° ±3.0° and 17° ±2.9° for TGU, respectively (Figure 9). The error estimates have been obtained by computing the standard deviation of the best 1000 models obtained by combining the inversion results of 10 random seed values. The observed data matches rea-

Figure 8.

sonably well with the synthetics generated using the models incorporating dip and anisotropy (Figure 10).

6. Discussion [15] Migration of ∼3600 P receiver functions in the Sikkim Himalaya and modeling the data at individual stations traces the north dipping character of the Indian plate, with the crustal thickness varying from ∼40 km to ∼61 km from south to north along the profile. Modeling of gravity data almost along the same profile constrains the Moho to vary from 36 to 60 km [Tiwari et al., 2006]. This variation in crustal structure particularly across the MBT in Sikkim Himalaya appears rather large compared to that in the adjacent Nepal Himalaya [Schulte‐Pelkum et al., 2005; Nábělek et al., 2009]. The results from HIMNT experiment showed a gently dipping Moho from ∼45 km, along with a midcrustal interface that coincides with the decollement surface. Also, these results suggest that the upper crust is detached from its lower part and incorporates in Himalaya, while the lower crust continues its descent beneath Tibet. However, the decollement surface in Sikkim Himalaya is rather weak or absent (modeled only at stations SIN and GAN) compared to that in nearby Nepal Himalaya, where it is observed as a strong layer that gently dips northward in azimuthal stacks. Incidentally, the weak decollement in the

Misfit values for (left) GAN and (right) TGU stations for various models tested. 8 of 12

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Figure 9. Anisotropic parameters for stations (left) GAN and (right) TGU obtained through inversion. Values with lowest misfit are shown as white crosses. Values with lowest misfit are shown as white crosses. The values obtained using 10 different random are shown as white rectangles.

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Sikkim region comprises the lesser active part of the 2500 km stretch of the very active Himalayan belt, which has not experienced any great earthquakes in the past. The recent results of Hi‐CLIMB also suggest a gently dipping Moho, with crustal depths varying from ∼40 km beneath the Gangetic plains to 50 km beneath Himalaya [Nábělek et al., 2009; Wittlinger et al., 2009]. Beneath the higher Himalaya in Sikkim, receiver functions at the northernmost station TGU clearly show arrivals at around 7.5 s corresponding to a crustal depth of 61 km. A similar value is observed for station SP27 of INDEPTHII, where a Moho thickness of 62 ± 2 km is reported [Mitra et al., 2005]. For the same station, the Moho arrivals at ∼11.5 s interpreted by Yuan et al. [1997] may not be reliable. The Moho thickness estimates from NE India and Bhutan also suggest a deeper Moho at ∼60 km [Priestley et al., 2007] beneath Greater Himalaya. The steepening of Moho (∼15°) beneath higher Himalaya is also observed from gravity results [Tiwari et al., 2006]. We favor the idea of Tiwari et al. [2006] that such a deepening in this segment of Himalaya may be due to flexural compensation of the high topography and partially due to weakening of the lithosphere. [16] Our analysis also indicates a possible Moho doublet arising from a positive velocity jump prominently seen at a depth of ∼40 km beneath most stations in the higher Himalaya, to the north of MBT (Figure 3). Continuous presence of such a feature just north of the study region

Figure 10. (left) Real and (right) synthetic data generated by the final models shown in Figure 9, using the appropriate back azimuth/slowness values (shown in Figure 7) of traces at GAN and TGU stations. Black and white shades represent negative and positive polarities, respectively. The layer between ∼2.5 and 4 s represents the anisotropic layer modeled at these stations. 9 of 12

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beneath southern Tibet has been interpreted as the top of Indian lower crust [Yuan et al., 1997]. In other regions like in the Cheyenne belt in southwest Wyoming, such as feature was interpreted in terms of a shallower Archean Moho where the P velocity jumps from 6.4 to 7.4 km/s and a deeper imbricated Proterozoic Moho with a velocity jump from 7.4 to 7.9 km/s across it [Hansen and Dueker, 2009]. Although it is tempting to invoke presence of an Asian Moho to explain the shallower feature in the doublet in Sikkim Himalaya, the smaller velocity associated with it (S velocity of ∼3.6 km/s) makes it an unlikely candidate for a Moho. Similar presence of a Moho doublet north of YTS in Tibet characterized by high shear wave velocities (∼ 4.73 km/s), low Vp/Vs (∼1.69) and a weakening of the Moho has been related to the presence of eclogites [Kind et al., 2002; Schulte‐Pelkum et al., 2005; Nábělek et al., 2009; Wittlinger et al., 2009]. Laboratory measurements of P and S wave velocities of eclogite measured at room temperature under 600 MPa pressure reveal that the shear velocities are very sensitive to the amount of water contained in them and composition. While dry mafic eclogite has the characteristic high velocity and density, hydrated eclogites can show large variations with S velocities ranging from ∼3.5 to 4.9 km/s [Gao et al., 2001]. In view of this and the fact that partial eclogitization of granulite may also result in intermediate velocities [e.g., Austrheim et al., 1997] similar to those for the top layer underneath Sikkim Himalaya, eclogitization of Indian lower crust at these depths cannot be ruled out. [17] Although our observation of anisotropy at midcrustal levels seems less robust compared to the dip and depth to the Moho, we attempt to discuss the results in view of a similar observation in the adjacent Nepal Himalaya inferred from forward modeling of receiver functions [Schulte‐ Pelkum et al., 2005]. As seen from the inversion results, the crust beneath Sikkim Himalaya is highly anisotropic in nature (∼17%) with the fast axis trending nearly 120° at GAN and 141° at TGU. Interpreting these results in terms of orientation of anisotropic minerals in the crust or material flow at midcrustal levels is ridden with uncertainties, since resolving the axis of symmetry as being fast or slow is highly nonunique considering hexagonal symmetry. Most receiver function modeling approaches similar to the one used in this study adopt this simplest and widely used form of symmetry to parameterize an anisotropic medium. However, the ambiguity posed by assuming hexagonal symmetry is that it can either represent the fast axis of anisotropy for mantle minerals like olivine or the slow axis typically for crustal minerals like mica, amphibole and plagioclase. In the formalism used by us [Frederiksen and Bostock, 2000], the former and latter scenarios are described by a positive and negative percentage of anisotropy, respectively. Since the waves propagate faster in a plane orthogonal to the slow axis of hexagonal symmetry, modeling the slow axis of symmetry as the fast one is likely to recover a projection of the fast axis with a strike orthogonal to the actual slow axis. In order to explore the part of model space with negative percentage anisotropy (i.e., slow axis symmetry) we searched the model space for positive and negative anisotropy (−20% to +20%). However, the data at

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stations TGU and GAN have a preference for positive percentage of anisotropy, with a range parallel alignment of fast axis (Figure 9). This result appears counterintuitive since shear‐generated alignment due to convergence, would produce convergence‐parallel and range‐perpendicular alignment. [18] The main sources of anisotropy in the upper crust are microcracks/pore alignment [Babuska and Pros, 1984] or laminated solid materials with contrasting elastic properties [Backus, 1962]. The “extensive dilatancy anisotropy” (EDA) [Crampin, 1984, 1989] that is produced at low pressures in the upper brittle crust due to aligned cracks, tends to disappear at greater depths where pressures are greater than 200–300 Mpa, due to their closure [Kern, 1982]. Hence, the EDA is unlikely to be the cause of crustal anisotropy observed in Sikkim Himalaya. The observed anisotropic layer at depths of 20 to 30 km, could be due to strain‐induced orientation of mineral grains [Babuska, 1981]. Most of the crustal minerals like mica, amphibole and plagioclase which produce anisotropy exhibit a slow axis of symmetry prompting earlier workers to model anisotropy in regions like Nepal Himalaya [Schulte‐ Pelkum et al., 2005], Western Tibet [Levin et al., 2008], Tibet [Ozacar and Zandt, 2004] in terms of slow axis. On the other hand, studies from western Tibet [Sherrington et al., 2004], considered fast axis of anisotropy within mid to lower crustal depths, where mineral alignment due to lateral flow provides a possible explanation for a weak Tibetan crust. The minerals amphibole and sillimanite given as possible cause of anisotropy beneath Tibet at mid crustal depths tend to align with the fast axis in the lineation direction, but they also often have a fast girdle in the foliation plane [e.g., Tatham et al., 2008] and a slow axis perpendicular to the foliation plane (as opposed to olivine LPO, which is often well approximated by a slow girdle perpendicular to a fast symmetry axis). [19] Our range parallel fast axis of anisotropy coupled with the fact that the anisotropic layer coincides with a low‐ velocity layer can be reconciled by drawing an analogy with the results from Tibet where such a layer is modeled in terms of positive percentage of anisotropy, considering the fact that the change in orientation of the anisotropy axis (from slow to fast) may happen at these depths. As stated earlier, the fast and slow axis of symmetry can produce similar effects in the data given the two axis (fast and slow) have opposite trends and supplementary plunges [Erickson et al., 2002]. The studies of rock samples suggest that foliation and lineation fabrics in rocks are often statistically coincident with flow planes [Mainprice and Nicolas, 1989]. Regardless of the data being modeled in terms of fast or slow symmetry axis, the fabric orientation in the slow axis scenario and the lineation directions in the fast axis scenario are equivalent [Ozacar and Zandt, 2004]. In regions like the Himalayan collision belt, the observed trends of anisotropic axis need to be viewed in conjunction with the prevailing geodynamic interpretations. For instance, in the adjacent Nepal Himalaya, the strong anisotropy detected above the decollement was interpreted to be in the hanging wall, due to the shear processes that are taken up as slip in great earthquakes at shallower depths [Schulte‐Pelkum et al.,

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2005]. Also, the southward increase in anisotropy along the thrust in Nepal Himalaya has been interpreted to be due to the expected transition from relatively mica‐poor granulite to a mica‐rich, foliated tectonite as the rocks in the mid crustal channel are hydrated and cooled through granite‐ amphibolite transition [Mahan, 2006]. If the dominant mechanism for creating anisotropy in Himalaya is due to shear processes, then the NW fast axes trends in the Sikkim Himalaya cannot be explained in terms of crustal deformation due to simple shear. Even considering the NW trend of anisotropy as being dubious, issues like (1) a weak decollement (near absence) in Sikkim Himalaya (Figure 4) and (2) depth of anisotropy (∼20–30 km) being more likely to be in the footwall, deter adopting an interpretation akin to that proposed in the adjacent Nepal Himalaya. [20] Most of the crustal rocks that are formed at deeper depths are exported to upper portions under different geologic and tectonic processes. Under the temperature and pressure conditions prevailing at those depths, foliations and mineral orientations that are formed may result in anisotropy [Brocher and Christensen, 1990] which is frozen in these rocks during their transportation to upper parts. This frozen anisotropy is likely to be oriented in the NW to WNW direction in Sikkim Himalaya, in response to the N‐S compression, as also indicated by the mantle deformation inferred from SKS/SKKS studies [Singh et al., 2007]. Also, the Sikkim, Bhutan and eastern Nepal regions are known to be characterized by strike‐slip motion on certain deep rooted faults like the Golpara lineament, whose geomorphology is suggestive of a NW‐NNW striking transverse tectonic features [De and Kayal, 2003; Drukpa et al., 2006; Hazarika et al., 2010]. Occurrence of strike‐slip‐type earthquakes at midcrustal depths (∼40 km [de la Torre et al., 2007]) in Sikkim and Bhutan with NW to NE trending P axis orientations were interpreted as a conjugate system of strike‐slip faulting that accompanies the formation of grabens in the Himalaya and southern Tibetan Plateau [Dasgupta et al., 1987] and with midcrustal transcurrent deformation [Drukpa et al., 2006]. Strike‐slip faulting rather than a strong anisotropic deformation fabric in the downgoing crust as a candidate mechanism for anisotropy gains support from the argument that distributed deformation across major faults may pro-

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duce subhorizontal foliations beneath the faulted upper crust and lineation directions roughly parallel to slip direction [Wilson et al., 2004].

7. Conclusions [21] Analysis of ∼3600 receiver functions from 11 broadband stations along a N‐S profile traversing the MBT and MCT in Sikkim Himalaya enabled high‐resolution imaging of the underthrusting Indian crust and characterize its shear wave structure incorporating layer dip and anisotropy. Depth migration and Monte Carlo inversion of azimuthal variations of the receiver functions at individual stations reveal an abrupt increase in crustal thickness across the MBT, beyond which the Moho exhibits a gentle northward dip. The crustal thickness generally varies from ∼40 km in the foot hills to 61 km in the Higher Himalaya, with dips in the range of 4° to 10° at individual stations. The results reveal an incoherent midcrustal layer at ∼20 km, corresponding to the Main Himalayan Thrust that was imaged at similar depths in Nepal Himalaya. A Moho doublet ensuing from an additional interface at 40 km prominently seen beneath the Higher Himalaya probably reveals presence of the partially eclogitized Indian lower crust, whose northward continuation is revealed from results of INDEPTH‐II experiment in southern Tibet. Interestingly, a strongly anisotropic layer coinciding with an LVL confined to a depth of 20–30 km has its fast axis oriented near parallel to the strike of the Himalaya. This is in contrast to the Nepal Himalaya where strong anisotropy coinciding with the decollement has been interpreted in terms of strain associated with shear along the detachment plane. A candidate mechanism for generating crustal anisotropy with a NW‐SE oriented fast axis azimuth in Sikkim Himalaya could be transcurrent deformation at midcrustal levels resulting in foliation planes that localize anisotropy. [22] Acknowledgments. The SIKKIM experiment is supported by the Seismology division of Department of Science and Technology (now under Ministry of Earth Sciences), India, under a project DST/23(337)/ SU/2002. We sincerely thank Vijaya Raghavan, Satish Saha, and M. Kousalya for providing excellent support for conducting the experiment. The three anonymous reviewers and the Associate Editor are profusely thanked for their extremely insightful comments.

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