Zhe Jia

Research Experience

Green Postdoc Scholar at IGPP, SIO, UCSD (2022-Present)

With Prof. Peter Shearer and Wenyuan Fan, we are developing near-realtime characterization of source complexities for deep earthquakes with sparsity constraints. We are also extending rupture imaging to smaller magnitudes using high-frequency energy envelopes.

Ph.D student at Caltech (2016-2022)

With Prof. Zhongwen Zhan, we developed a Bayesian subevent inversion algorithm to resolve rupture complexities of large earthquakes, in order to understand the controlling factors of earthquake source properties and probe the interactions between complex earthquakes and structures. Exampled by the 2018 Fiji-Tonga M8 deep earthquake doublet 1, the 2019 Ridgecrest M7 sequence 2, and the 2021 Mw 8.2 South Sandwich Island earthquake 3.

We developed a subevent-guided finite-fault inversion approach to simultaneously constrain multi-fault ruptures and fault geometry of complex earthquakes, with seismic and geodetic data being combined, and realistic 3D structure incorporated. Exampled by Ridgecrest sequence 4.

For moderate-to-small seismic events, we developed a Bayesian differential moment tensor inversion algorithm to remove the common earth structural effects, and improve the resolvability of focal mechanisms. Related work 5.

With Prof. Robert Clayton, we developed dense array seismic tomography and derived high-resolution shallow structural model for the Los Angeles Basin. To deal with the big dataset, we develop a machine learning based algorithm to automatically pick the dispersion curves.Related works 6,7.

M.S. student at USTC (2013-2016)

With Prof. Sidao Ni, we developed a joint inversion algorithm for improved earthquake centroid depths using both waveforms and Rayleigh wave amplitude spectra. Ref 1.

We developed a joint inversion algorithm for improved earthquake full moment tensors using both regional and teleseismic waves. Ref 2.

Research Projects

The Fiji-Tonga subduction zone accounts more than 75% of global deep earthquakes, but lacked large ones (M~8). This puzzling deficit was changed by a pair of Fiji-Tonga M8 earthquakes in two weeks, 2018. We analyzed the focal mechanisms, rupture processes, aftershock seismicity and thermal properties, and found that the doublet events may have ruptured in two distinct slabs, even though they are only ~250 km from each other! The August M8.2 event occurred in the Tonga slab while the September M7.9 event ruptured in a warm detached Australian slab leaning on the Tonga slab. The 2018 Fiji M8 doublet reflects the complex interaction of slabs near the bottom of the mantle transition zone, and also emphasizes local slab temperature's primary control on deep earthquake ruptures and aftershocks. See our Fiji EPSL Paper for more details, and our Tonga GRL Paper for a follow-up fully dynamic simulation study.

In July 2019, a strong earthquake sequence struck the Ridgecrest city and broke the seismic quiescence of Southern California. For quick regional hazard response, it is necessary to integrate the understanding of the earthquake source processes and regional fault structures. Through analyzing seismograms from near and far fields, we found that the Mw 6.4 foreshock on July 4 is composed of three subevents on interlocked orthogonal faults. The Mw 7.1 mainshock on July 6 ruptured towards northwest and southeast, and stopped at bifurcation and horsetail faultings. The Mw 6.4 foreshock ruptured towards the hypocenter of the Mw 7.1 mainshock but stopped at a distance of ~4km. The gap was gradually filled by a series of small earthquakes before the Mw 7.1 mainshock, suggesting that the Mw 6.4 foreshock triggers seismic activities that continuously eroded this 4 km barrier, and eventually induced the occurrence of a 7.1 magnitude earthquake. The multi-fault ruptures are rarely considered in seismic hazards, but the Ridgecrest sequence calls for a re-assessment. See our Ridgecrest Science Paper for more details.

Large earthquakes are often complicated, especially if they occur in relatively immature fault systems. As a good example, the 2019 Ridgecrest sequence ruptured multiple subparallel or orthogonal surface fault traces. How the surface complexities extend to depth and impact earthquake rupture processes is critical for understanding earthquake physics and hazard but hard to assess. By combining a rich dataset of ground shaking (strong motion data, broadband seismograms) and deformation (high rate GPS, InSAR) with realistic 3D structure considered, we found that the ruptures are substantially simpler at depth than near the surface, with four faults explaining all the data reasonably well. Interestingly, both the foreshock and the mainshock started at fault junctions and then ruptured multiple faults. Where the two events overlapped, their slip patterns are largely complementary to each other. See our Ridgecrest GRL Paper for more details.

The 2021 August South Sandwich Island Mw 8.2 earthquake was a surprise, because it was initially reported as a magnitude 7.5 event at a deep depth (47 km) but generated a global-spreading tsunami that would only be expected for a larger and shallower event. By using seismic data with period as long as 500s, we revealed a hidden Mw 8.16 shallow slow event that happened between clusters of regular ruptures in the beginning and end. Although the slow event contributed 70% of the seismic moment, lasted three minutes, and ruptured a 200-km section of the plate interface, it is essentially invisible at short or intermediate periods, which explains its anomalously low body-wave and surface-wave magnitudes. The 2021 South Sandwich Island earthquake represents an extreme example of the broad spectral behaviors of subduction zone earthquakes and calls for attention in the research and warning of similar events. See our South Sandwich Paper for more details.

Moment tensors are key to seismic discrimination but often require accurate assumption on the Earth structure for estimation. This limits the data availability and the precision of moment tensor inversions. To overcome this difficulty, we develop a differential moment tensor inversion (diffMT) method that uses relative measurements to remove the Earth's structural effects shared by clustered events, thereby improves the accuracy of source parameters. In a Bayesian framework, we invert the body- and surface-wave amplitude ratios of an event pair for refined moment tensors. Applications to three North Korea nuclear tests from 2013 to 2016 demonstrate that diffMT reduces the uncertainties substantially compared with the traditional waveform-based moment tensor inversion. Our results suggest high percentages of explosive component with similar double-couple components for the North Korea nuclear tests. See our diffMT paper for more details.

The shallow velocity structure of the Los Angeles (LA) Basin plays an important role in the seismic hazard of this populated area. But most existing velocity models of the LA Basin have limited resolution due to the sparsity of seismic stations, or the restricted coverage of sonic logging and industry reflection profiles. We took a small step forward by combining the aperture of broadband seismic stations and density of industrial nodal arrays, and derive a 3D shear wave velocity model, covering a large portion of the central LA Basin for the depths shallower than 3 km. We found that the small scale heterogeneities are better resolved compared with the conventional models. We also captured the presence of the Newport-Inglewood fault by a NW-SE trending high velocity belt. Our model could better predict the variations in the shallow crustal amplifications, which can improve strong ground motion simulations. See our LABasin JGR paper for more details.

Dispersive surface waves have been important and extensively used for understanding the Earth's structure, since surface waves can be easily extracted from ambient noise correlations and does not depend on a suitable earthquake distribution. However, picking the dispersion curves can be very labor-intensive, particularly when dealing with dense arrays. Here, we develop a machine learning based algorithm to automatically extract surface wave dispersion curves. We first convert the standard frequency-time analysis of seismograms into images, then use a convolutional neural network to drive a supervised learning. Our results show that the machine classification is nearly identical to the human picked phases. See our MLDispersion IEEETGRS paper for more details.

Publications

1. The 2021 South Sandwich Island Mw 8.2 earthquake: a slow event sandwiched between regular ruptures.
   Jia Z., Zhan Z., Kanamori H., 2022, Geophysical Research Letters.. doi.org/10.1029/2021GL097104 PDF

2. Bayesian differential moment tensor inversion: theory and application to the North Korea nuclear tests.
   Jia Z., Zhan Z., Helmberger D., 2022, Geophysical Journal International.. doi.org/10.1093/gji/ggac053 PDF

3. Determination of Near Surface Shear-Wave Velocities in the Central Los Angeles Basin with Dense Arrays.
   Jia Z., Clayton R., 2021, Journal of Geophysical Research: Solid Earth. doi.org/10.1029/2020JB021369 PDF

4. Multi-fault models of the 2019 Ridgecrest sequence highlight complementary slip and fault junction instability.
   Jia Z., Wang X., Zhan Z., 2020, Geophysical Research Letters. doi.org/10.1029/2020GL089802 PDF

5. The 2018 Fiji Mw 8.2 and 7.9 deep earthquakes: One doublet in two slabs.
   Jia Z., Shen Z., Zhan Z., Li C., Peng Z., Gurnis M., 2020, Earth and Planetary Science Letters. doi.org/10.1016/j.epsl.2019.115997 PDF

6. Joint inversion for earthquake depths using local waveforms and amplitude spectra of Rayleigh waves.
   Jia Z., Ni S., Chu R., Zhan Z., 2017, Pure and Applied Geophysics. doi.org/10.1007/s00024-016-1373-1 PDF

7. Preliminary study on aftershock decay rate of the 2013 Ms7.0 Lushan earthquake.
   Jia Z., Chen W., Chu R., 2013, Earthquake Science. doi.org/10.1007/s11589-013-0050-z PDF

8. Tonga Slab Morphology and Stress Variations Controlled by a Relic Slab: Implications for Deep Earthquakes in the Tonga-Fiji Region.
   Liu H., Gurnis M., Leng W., Jia Z., Zhan Z., 2021, Geophysical Research Letters. doi.org/10.1029/2020GL091331 PDF

9. gCAPjoint, A Software Package for Full Moment Tensor Inversion of Moderately Strong Earthquakes with Local and Teleseismic Waveforms.
   Bai Q., Ni S., Chu R., Jia Z., 2020, Seismological Research Letters. doi.org/10.1785/0220200031 PDF

10. Extracting dispersion curves from ambient noise correlations using deep learning.
    Zhang X., Jia Z., Ross Z., Clayton R., 2020, IEEE Transactions on Geoscience and Remote Sensing. doi.org/10.1109/TGRS.2020.2992043 PDF

11. Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence.
    Ross Z., Idini B., Jia Z., et al., 2019, Science. doi.org/10.1126/science.aaz0109 PDF

12. The cause of the 2011 Hawthorne (Nevada) earthquake swarm constrained by seismic and InSAR methods.
    Zha X., Jia Z., et al., 2019, Journal of Geodesy. doi.org/10.1007/s00190-018-1212-5 PDF

13. CAPjoint, a computer software package for joint inversion of moderate earthquake source parameters with local and teleseismic waveforms.
    Chen W., Ni S., Kanamori H., Wei S., Jia Z., Zhu L., 2015, Seismological Research Letters. doi.org/10.1785/0220140167 PDF