RESEARCH
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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 compressive sensing (CS) techniques in the frequency domain (Yao et al., 2011, GRL; Yin & Yao, 2016, GJI) and wavelet domain (Fang, Yao, Zhang, 2018, GJI) 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 (Yao et al., 2011, GRL; Yao et al., 2013, PNAS; Yin et al., 2016, GRL, ...). Together with coseismic slip models and early aftershock locations, our results suggest depth-varying frictional properties at the subducting plate interfaces.

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 location results for the 2011 Mw 9.0 Tohoku-Oki Earthquake (Yao et al., 2012, GJI, 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 (Qiao, Yao et al., 2018, Tectonics), North China Craton, Southeastern mainland China and Taiwan (Zhang, Yao et al., 2018, JGR), 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 and the wave speed model is 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 (Fang, Yao, et al., 2015, GJI), Hefei urban area (Li, Yao et al., 2016, SRL), fault zone regions (Gu et al., 2019, PAGEOPH), a shale gas production field in SW China (Liu et al., 2018, JAG), Taiwan Strait (Zhang, Yao et al., 2018 JGR), and many other regions. 

(Download: https://github.com/HongjianFang/DSurfTomo)

New seismic tomographic methods and joint inversion

1. We have developed a new joint inversion methods for better imaging 3-D Vp and Vs 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). With a new parameterization approach, we have proposed a new method of directly invert for more reliable 3-D Vp/Vs models using both body and surface wave travel times (Fang, Yao , Zhang et al., 2019, GJI).

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.). In addition, we have developed an iterative linearized inversion approach for 1-D crustal Vs structure as well as interfaces using surface wave dispersion, Rayleigh wave ZH ratio and P wave receiver functions. (Zhang P. & Yao, 2017, Earthquake Science)

3. We have developed a linear array ambient noise adjoint tomography strategy for imaging high-resolution crustal Vs structure. (Zhang C., Yao, et al., 2018, JGR)

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Copyright © 2015 Huajian Yao All Rights Reserved
Email: hjyao @ ustc.edu.cn Tel: +86 - 551 - 63607201 Add: 96 Jinzhai Road, Hefei, Anhui Province, 230026, China