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Waveform Cross-Correlation-Based Methods in Observational Seismology

Recent developments in observational seismology rely heavily on the mining of increasingly large datasets through waveform cross-correlation-based techniques to improve signal to noise ratios and extract useful information from continuous seismograms. These include obtaining accurate differential arrival times with waveform correlation analysis for accurate earthquake relocation and 3D seismic tomography, detecting low-magnitude events using array-based waveform matching, extracting empirical Green’s functions (e.g., surface and body waves) from cross-correlation of continuous ambient noise waveform and creating virtual sources or receivers from cross-correlating earthquake coda waveforms. In this session, we welcome both methodologically and observationally focused contributions that utilize correlation-based methods to detect repeating earthquakes near creeping faults and volcanoes, relocate microearthquakes and low-frequency earthquakes around seismically active regions and image subsurface structures and monitor their temporal changes with ambient noise and earthquake coda correlation techniques. We hope to provide a platform for discussing how to efficiently apply correlation-based methods to ultra-dense arrays and long-duration continuous waveforms to better extract useful seismic events and image subsurface structures.

Conveners
Zhigang Peng, Georgia Institute of Technology (zpeng@gatech.edu); Esteban J. Chaves, Volcanological and Seismological Observatory of Costa Rica, Universidad Nacional (esteban.j.chaves@una.cr); Marine Denolle, Harvard University (mdenolle@g.harvard.edu); William Frank, University of Southern California (wbfrank@usc.edu); Taka'aki Taira, Berkeley Seismology Laboratory, University of California, Berkeley (taira@berkeley.edu); Haijiang Zhang, University of Science and Technology of China (zhang11@ustc.edu.cn)

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