@article {fang_sequencing_2023,
	title = {Sequencing Seismic Noise Correlations for Improving Surface Wave Retrieval and Characterizing Noise Sources},
	journal = {Seismological Research Letters},
	volume = {95},
	number = {2A},
	year = {2023},
	month = {03/2024},
	pages = {848{\textendash}858},
	abstract = {Cross-correlating continuous seismic data is a commonly employed technique to extract coherent signals to image and monitor the subsurface. However, due largely to site effects and poorly characterized noise sources in oceanic environments, its application to ocean-bottom seismometer (OBS) recordings often requires additional processing. In this contribution, we propose a method to improve the quality of the retrieved surface waves from OBS data and characterize the noise sources. We first cluster the pre-stack noise cross-correlation functions (NCFs) based on a sequencing algorithm, followed by selectively stacking those consisting of coherent and stable signals that are consistent with predicted surface-wave arrival times. Synthetic tests show that the sequenced NCFs can be used to recover the spatial and temporal distribution of noise sources. Applying the method to an OBS array offshore California increases the signal-to-noise ratios of the obtained Rayleigh waves. In addition, we find that the annual temporal distribution of selected NCFs with frequencies ranging from 0.04 to 0.1~Hz is nearly homogeneous during the recording period. In contrast, many NCFs excluded for stacking are temporally clustered. This method has the potential to be applied to other OBS recordings or possibly onland deployments, thus helping to obtain high-quality surface waves and to analyze temporal noise source characteristics.},
	issn = {0895-0695},
	doi = {10.1785/0220230151},
	url = {https://doi.org/10.1785/0220230151},
	author = {Fang, Hongjian}
}
@article {fang_smatstack_2023,
	title = {SMatStack to Enhance Noisy Teleseismic Seismic Phases: Validation and Application to Resolving Depths of Oceanic Transform Earthquakes},
	journal = {Geochemistry, Geophysics, Geosystems},
	volume = {24},
	number = {11},
	year = {2023},
	note = {_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2023GC011109},
	month = {10/2023},
	pages = {e2023GC011109},
	abstract = {The depths of most moderate-sized oceanic earthquakes are poorly constrained because of the lack of local recording stations and noisy teleseismic recordings. This hampers our understanding of slip behaviors along oceanic faults and the mechanical properties of the oceanic lithosphere. In this study, we develop a new method to enhance the weak body-wave signals, particularly the depth phases, associated with earthquakes on oceanic transform faults using large-aperture arrays in the teleseismic range. We simulate the enhanced teleseismic signals to refine the centroid depths of moderate-sized earthquakes. We validate the new approach using synthetic waveforms and show it outperforms conventional methods when dealing with noisy signals. We obtain the depth estimates for three moderate-sized earthquakes on the Chain transform fault in the equatorial Atlantic Ocean and find two of them are consistent with a local catalog derived using oceanic bottom seismometers. Application of the new method to the past decades of teleseismic recordings of moderate-sized earthquakes on the large and slow-slipping transform faults will provide significantly improved constraints on the width of the seismogenic zone, thus advancing our understanding of the rheology of oceanic lithosphere and earthquake processes in oceanic settings and, by comparison, their more dangerous continental counterparts. The new method is not limited to oceanic transform earthquakes, but can be easily adapted to other seismological studies in which noisy but coherent signals could be revisited for better usage.},
	keywords = {array analysis, earthquake depths, oceanic transform faults, seismogenic zone},
	issn = {1525-2027},
	doi = {10.1029/2023GC011109},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2023GC011109},
	author = {Fang, Hongjian and Abercrombie, Rachel E.}
}
