Understanding the source of earthquakes is important for predicting seismic ground motions and tsunami flooding in many coastal cities near active faults. An improved understanding of earthquake physics relies on better knowledge of how earthquakes rupture and how faults release stress. The goal of this proposal is to obtain more robust observations of earthquake rupture. The intent is to help us better predict the hazards related to these events. As part of this CAREER grant, the researcher will develop several advanced observational methods and integrate different earthquake datasets. The goal of the educational activities is to reduce the vulnerability of the immigrant community to seismic and tsunami hazard. The project will enhance the science literacy and earthquake preparedness of newly-arrived immigrants. This is achieved by partnering with the local immigrant community in Los Angeles. The project will host education workshops for Chinese American and other media. Earthquake awareness seminars for the general public and outreach activities for predominantly immigrant K-12 schools will also be included. Finally, the project will engage Hispanic, African American, and Asian undergraduates through research and summer internships.
This project integrates research of observational seismology and tsunami sciences to enhance the capacity to extract reliable information about earthquake rupture and nucleation processes. This project develops multi-scale signal analysis tools based on back-projection of high-frequency seismic array data and integrate these results with more traditional source inversion approaches at lower frequencies. The researcher will also probe the mechanisms of tsunami-genic earthquakes and sub-marine landslides with an adjoint inversion method of tsunami waves that does not rely on prior assumptions of fault geometry and earth structures. The project will study previous events to correlate earthquake rupture mechanics with tsunamis in order to develop better algorithms to predict the tsunami direction and amplitude. In addition, the project will enhance the detection capabilities of the precursory foreshocks and tremors using Machine Learning techniques. Understanding earthquake nucleation processes will be improved, which is essential for physics-based earthquake forecasting models. This project will support Ph.D. level graduate students and train them with cutting edge computational and data-processing skills. The research results and implications will be presented in scientific conferences, published in top peer-reviewed journals and used as class materials taught in a major public school, at University of California, Los Angeles. This project is supported by the Geophysics and Education and Human Resources programs in the Division of Earth Sciences.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
