Direct Inversion for Three‐Dimensional Shear Wave Speed Azimuthal Anisotropy Based on Surface Wave Ray Tracing: Methodology and Application to Yunnan, Southwest China

Abstract

Azimuthal anisotropy retrieved from surface waves is important for constraining depthvarying deformation patterns in the crust and upper mantle. We present a direct inversion technique for the three-dimensional shear wave speed azimuthal anisotropy based on mixed-path surface wave traveltime data. This new method includes two steps: (1) inversion for the 3-D isotropic Vsv model directly from Rayleigh wave traveltimes and (2) joint inversion for both 3-D Vsv azimuthal anisotropy and additional 3-D isotropic Vsv perturbation. The joint inversion can significantly mitigate the trade-off between strong heterogeneity and anisotropy. With frequency-dependent ray tracing based on 2-D isotropic phase speed maps, the new method takes into account the ray-bending effect on surface wave propagation. We apply the new method to a regional array in Yunnan, southwestern China. Using Rayleigh wave phase velocity dispersion data in the period band of 5-40 s extracted from ambient noise interferometry, we obtain a 3-D model of shear wave speed and azimuthal anisotropy in the crust and uppermost mantle in Yunnan. This model reveals that two midcrust low-velocity zones are possible weak channels, and the azimuthal anisotropy at a depth of 5 to 30 km is mainly controlled by nearby strike-slip faults, some of which also approximately coincide with the lateral boundaries of the crustal low-velocity zones. Approximately south of 26°N, the upper crustal azimuthal anisotropy from our model is significantly different from the upper mantle anisotropy inferred by shear wave splitting, indicating different deformation styles between the crust and upper mantle in southern Yunnan.

Azimuthally Anisotropic Structure in the Crust and Uppermost Mantle in Central East China and Its Significance to Regional Deformation Around the Tan‐Lu Fault Zone

“…And the isotropic model may have already fit the data quite well. Thus the improvement of data fitting is usually not significant when we perform joint inversion of both isotropic and azimuthally anisotropic parameters (C. Liu et al., 2019; Z. Zhang et al., 2022). This may limit the variation of the misfit to just a reasonable range enough to give a robust model as also shown by several model resolution tests (Section 3.1).…”

“…Overall, with the checkerboard test, one can get a rough estimate of the noise level tolerance in a given dataset. This means that increasing noise level in a dataset will amplify the uncertainty in the model, and for azimuthal anisotropy, a larger noise level reduces the anisotropic strength (amplitudes) and increases the deviations of anisotropic patterns (C. Liu et al., 2019). Nevertheless, the azimuthally anisotropic Vsv could be well recovered for synthetic datasets with 0.5% and 1% Gaussian noise levels within regions with dense raypath coverage.…”

Diffuse deformation in the SE Tibetan Plateau: New insights from geodetic observations

“…Deep structures of the Ailaoshan, Wuliangshan, Puwen, Pu'er, and Lancangjiang faults to the southwest of the Ailaoshan shear zone are less constrained and largely based on seismic relocation results, seismic S wave Liu et al (2019). Leveling velocities are from Hao et al (2014).…”

“…This indicates higher crustal temperature, higher geothermal gradient, and thinner brittle upper crust in the SE and eastern Tibetan Plateau, which would lead to smaller fault spacing (Yang et al, 2020). Additionally, low electrical resistivity (Bai et al, 2010), high Vp/Vs ratios (Sun et al, 2014), low-velocity zones (Liu et al, 2019) indicate the existence of rheologically weak zone in the midlower crust due to partial melt. The NW-/NNW-striking active faults may be restricted above or within this layer instead of into the Moho, which is assumed to be~40-50 km in our study area (Huang et al, 2018).…”

“…Relocated earthquakes, seismic S wave velocity, topography, and leveling data across the Qujiang, Jianshui, Red River, Ailaoshan, Wuliangshan, Pu'er, Puwen, and Lancangjiang faults. Seismic S wave velocity data are collected fromLiu et al (2019). Leveling velocities are fromHao et al (2014).…”