High-resolution Vs tomography of South China by joint inversion of body wave and surface wave data

Continental Reworking in the Eastern South China Block and Its Adjacent Areas Revealed by F‐J Multimodal Ambient Noise Tomography

“…Second, our results (Figure 9c) are significantly different from the results of these two studies (Figures 9a and 9e) in the crust, as we demonstrate the existence of MCLVZs. Gao2022 (Figure 9a) and Shen2016 (Figure 9e) have almost the same characteristics in the crust, although Gao et al (2022) introduced earthquake body wave data during the shear-wave velocity inversion. The reason for this is that long-period body wave data cannot strongly constrain the shallow velocity We chose a northern subarea (Figure 10a) to further explain how higher-mode dispersion curves impact the shear-wave velocity inversion.…”

“…Gao2022 (Figure 9a) and Shen2016 (Figure 9e) have almost the same characteristics in the crust, although Gao et al. (2022) introduced earthquake body wave data during the shear‐wave velocity inversion. The reason for this is that long‐period body wave data cannot strongly constrain the shallow velocity structure.…”

Joint Inversion of Body Wave Arrival Times, Surface Wave Dispersion Data and Receiver Functions: Method and Application to South China

“…Chen (2017) determined the Vs model of continental China by inverting the surface wave dispersion curves from Shen et al (2016) by the conventional surface wave tomography. From the Vs model of Chen (2017), Gao et al (2022) first calculated the Vp model via the Vp-Vs relationship of Brocher (2005) and then used them as initial models to invert coarse Vp and Vs models with a horizontal grid interval of 1.0 𝐴𝐴 • and a coarse grid in depth by double-difference seismic travel time tomography. We interpolated the velocity models to a finer grid with a horizontal interval of 0.5° and varying intervals in the vertical direction, which were subsequently used as initial models for the joint inversion.…”

“…Then we conducted trade‐off analysis near the reference weights (Figure 6) and chose the optimal data weights as 40 and 45, respectively. During this process, the smoothing parameters $${\eta }_{\mathit{1}}$$ and $${\eta }_{\mathit{2}}$$ are the same as those selected for joint inversion of surface wave and body wave data using the same datasets (Gao et al., 2022). Appropriate damping parameter is selected so that the joint inversion system has a proper condition number of 100–200 (Zhang et al., 2014).…”

Magnetotelluric Evidence for Lithospheric Alteration Beneath the Wuyi‐Yunkai Orogen: Implications for Thermal Structure of South China

“…Thus, to improve the stability and accuracy of the (Sun et al, 2013). (d) Vertical shear-wave velocity section along the MT profile (Gao et al, 2022), the white dotted line shows the fluctuation in the Moho depth (He et al, 2014).…”