Anomalous Radial Anisotropy and Its Implications for Upper Mantle Dynamics Beneath South China From Multimode Surface Wave Tomography

Tang, Qingya; Sun, Weijia; Yoshizawa, Kazunori; Fu, Li‐Yun

doi:10.1029/2021jb023485

Cited by 3 publications

(4 citation statements)

References 124 publications

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“…The radial anisotropy distribution of the mantle component of SREM-SC is illustrated in Figure 8, which is compatible with the work of Tang et al (2022), who had discussed the similarities and differences between the upper mantle of South China and previous regional and global radial anisotropy models (e.g., Tao et al, 2018;Witek et al, 2021). The study region largely displays positive radial anisotropy at a shallower depth of 60 km (Figure 8A).…”

Section: Radial Anisotropysupporting

confidence: 88%

“…This is a consistent feature revealed by earlier regional models, for example, the shear wave velocity models described in Section 2, as well as global models. The distribution of radial anisotropy correlates well with the results of Tang et al (2022), since we adopt their SH wave velocity as the SH wave representation. The research on SH wave determined from Love wave in South China need to be enhanced.…”

Section: Density Modelsupporting

confidence: 75%

“…At a depth of 300 km, the anisotropy in the Sichuan Basin decreases while the negative anisotropy of the Cathaysia Block increases, especially beneath the Leizhou Peninsula and its environs and the southeastern coastal region. The negative radial anisotropy beneath the Sichuan Basin and its western portion may reflect the influence of the compression of the Tibetan Plateau and the thermal erosion of mantle flow (Tang et al, 2022). The obvious negative radial anisotropy in the asthenosphere of the coastal region of Cathaysia Block reveals that the vertical movement of mantle material is dominant, which may be related to the smallscale mantle convection above the back arc subduction plate due to the subduction of the Philippine Sea plate (Peng et al, 2007).…”

Section: Radial Anisotropymentioning

confidence: 99%

“…wave velocity model that covers the mainland China down to a depth of 150 km Tang et al (2022). refilled the inversion depth of the radially anisotropic 3-D shear-wave model of the whole South…”

mentioning

confidence: 99%

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Seismological reference earth model in South China (SREM-SC): Upper mantle

Tang

Sun²,

Hu³

et al. 2023

Front. Earth Sci.

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This work is the mantle component of constructing the Seismological Reference Earth Model in South China (SREM-SC). Although there has been a wide range of research for imaging the upper mantle structures beneath South China, most of them focus on the large-scale features of the upper mantle, and the depth resolution is insufficient for existing surface wave tomography models to distinguish anomalies below 200 km. This study aims to develop a 3-D upper mantle Seismological Reference Earth Model in South China based on the prior tomography models. The shear wave velocity model comes from the analysis of several seismic surface wave tomography, supplemented by body wave tomography and the P-wave velocity model is constructed by the conversion from S-wave velocity. The radial anisotropy model is calculated from the SV-wave and SH-wave velocity. The Density model of the upper mantle is derived using the empirical relationship linking the density to the shear-wave velocity. The model is grid with 0.5° × 0.5° in latitude and longitude and 5 km interval in depth from 60 to 300 km. The mantle component of Seismological Reference Earth Model in South China is expected to provide a good representation of the upper mantle structures for further detailed studies. The mantle component of Seismological Reference Earth Model in South China provides new insights into upper mantle structures that should be meaningful to reveal the dynamic mechanism and tectonic evolution of South China.

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Section: Radial Anisotropysupporting

confidence: 88%

Section: Density Modelsupporting

confidence: 75%

Section: Radial Anisotropymentioning

confidence: 99%

mentioning

confidence: 99%

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Seismological reference earth model in South China (SREM-SC): Upper mantle

Tang

Sun²,

Hu³

et al. 2023

Front. Earth Sci.

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High mantle helium flux unveils active mantle melting beneath the cathaysia block, south China

Wang,

Huang,

Wang

et al. 2024

Applied Geochemistry

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Multimodal surface wave inversion with automatic differentiation

Liu,

Li,

et al. 2024

Geophysical Journal International

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Summary Investigating subsurface shear-wave velocity (vs) structures using surface wave dispersion data involves minimizing a misfit function that is commonly solved through gradient-based optimization. Sensitivity kernels for model updates are commonly estimated using numerical differentiation, variational methods or implicit functions which however, may involve numerical instability and computational challenges when dealing with complex velocity models and large datasets. In this study, we propose a novel surface wave inversion framework in which error-free gradients are calculated by automatic differentiation (AD) and forward modeling is implemented by convenient computational graphs in the state-of-the-art deep learning framework. The AD-based inversion approach is first validated using two synthetic datasets. Then the subsurface structures at three distinct locations, namely the Great Plains and the Long Beach in the US and Tong Zhou in China, are also derived using this method with seismic ambient noise data, which show nice consistency with those obtained using traditional methods. With the significantly improved computational efficiency, a great number of initial models can be inverted simultaneously to mitigate the impact of local minima and to estimate the uncertainty in the invert models. We have developed a new surface wave inversion package named ADsurf based on automatic differentiation and computational graphs in the deep learning framework, and its computational efficiency is also compared with the traditional finite-difference based gradient estimation approach. While a great number of intriguing studies on the geophysical inverse problems have been conducted recently using deep learning for end-to-end mapping, the use of AD provided in the in the deep learning frameworks to assist and expedite the gradient computations are still underexploited in geophysics. Thus, it is expected that various geophysical inverse problems in many different areas beyond the surface wave inversion can also be tackled with this new paradigm in the future.

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Anomalous Radial Anisotropy and Its Implications for Upper Mantle Dynamics Beneath South China From Multimode Surface Wave Tomography

Cited by 3 publications

References 124 publications

Seismological reference earth model in South China (SREM-SC): Upper mantle

Seismological reference earth model in South China (SREM-SC): Upper mantle

High mantle helium flux unveils active mantle melting beneath the cathaysia block, south China

Multimodal surface wave inversion with automatic differentiation

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