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My main research interests include seismic imaging using earthquake waveforms and ambient noise, lithospheric structure and deformation, earthquake rupture processes, array analysis, and geophysical inversion methods.

Earthquake Rupture Imaging from Compressive Sensing and Back Projection

1. We developed a compressive sensing (CS) technique to image frequency-dependent seismic radiation and rupture processes of great earthquakes. For the four largest megathrust earthquakes in the past 10 years. Our results reveal generally low-frequency radiation closer to the trench at shallower depths and high-frequency radiation farther from the trench at greater depths. Together with coseismic slip models and early aftershock locations, our results suggest depth-varying frictional properties at the subducting plate interfaces.

Results for the 2011 Mw 9.0 Tohoku-Oki Earthquake in Japan (PDF download)

* Results for the 4 largest subduction zone megathrust earthquakes since 2000 (PDF download) 

2. We developed an iterative backprojection method with subevent signal stripping to determine the distribution of subevents (large energy bursts) during the earthquake rupture.We also relocate the subevents initially determined by iterative backprojection using the traveltime shifts from subevent waveform cross-correlation, which provides more accurate subevent locations and source times.

* Subevents for the 2011 Mw 9.0 Tohoku-Oki Earthquake (PDF download)

Ambient Noise and Earthquake Surface Wave Tomography for Lithospheric Structure and Deformation

We have developed the joint ambient noise and earthquake surface wave tomographic method (Yao et al., 2006; 2008; GJI) for better constraining the crust and upper mantle structure using seismic array data. In this method, we combine shorter period phase velocity dispersion curves from ambient noise cross-correlation functions and longer period dispersion data from earthquake surface wave two-station analysis. Then 2D phase velocity maps are constructed and 3-D Vs model can be obtained by point-wise inversion using the Neighborhood Algorithm (Yao et al., 2008, GJI). We have also investigated radial and azimuthal anisotropy of the lithospheric structure from surface waves (e.g., Yao et al., 2010, JGR; Huang, Yao, van der Hilst, 2010, GRL), which provides essential information for understanding the deformation patterns in the crust and upper mantle. 

The current study regions include the Tibetan Plateau, Southwest China and Vietnam, North China Craton, Southeastern mainland China and Taiwan, the equatorial eastern Pacific Rise, etc.

Near Surface or Shallow Crustal Imaging using Ambient Noise and Surface Waves

We proposed a method to invert surface wave dispersion data directly for 3-D variations of shear wave speed, that is, without the intermediate step of phase or group velocity maps, using frequency-dependent ray tracing and a wavelet-based sparsity-constrained tomographic inversion (Fang, Yao*, et al., 2015, GJI). A fast marching method is used to compute, at each period, surface wave travel times and ray paths between sources and receivers. This avoids the assumption of great-circle propagation that is used in most surface wave tomographic studies, but which is not appropriate in complex media. We represent the 3-D shear wave speed model by means of 1-D profiles beneath grid points, which are determined from all dispersion data simultaneously using a wavelet-based sparsity-constrained tomographic method. The wavelet coefficients of the wave speed model are estimated with an iteratively reweighted least squares algorithm, and upon iteration the surface wave ray paths and the data sensitivity matrix are updated using the newly obtained wave speed model. This method has been applied to Taipei Basin in Taiwan, Hefei urban area, and a shale gas production field in SW China. (Download:

Joint Inversion of Surface Wave Dispersion, ZH Ratio, Body Wave Traveltimes, Receiver Functions

1. We have developed a new joint inversion methods for better imaging 3-D crust structure using direct inversion of surface wave travel times (based on frequency-dependent ray tracing) and body wave travel times. (Fang, Zhang, Yao, et al., 2016)

2. We have developed a joint inversion method (using the Neighborhood Algorithm) that combines dispersion data and Rayleigh wave ZH ratios for the inversion of crustal Vs and Vp/Vs.  (Yuan, Yao, Qin, 2016, Chin. J. Geophys.)

3. We are developing an iterative inversion approach for 1-D crustal Vs and Vp structure as well as interfaces using surface wave dispersion data, Rayleigh wave ZH ratio (ellipticity) and P wave receiver functions. (Zhang & Yao, submitted to GJI)

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