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Towards a better understanding of the Los Angeles basin structure using data recorded from the LAB2022 nodal array

Konstantinos Gkogkas, Fan-Chi Lin, Valeria Villa, Robert W. Clayton, Heather A. Ford, & Amir A. Allam

Submitted September 10, 2023, SCEC Contribution #12950, 2023 SCEC Annual Meeting Poster #008

In the summer of 2022, we deployed ~300 nodal geophones (Fairfield Z-Land and SmartSolo sensors) in the Los Angeles basin, structured by two dense linear arrays (station spacing of ~ 0.6 km) and a 2-D distributed shotgun array (inter-station spacing of ~2 km). The continuous data recorded provide unique research opportunities, including imaging the 3-D basin structure with unprecedented resolution. In this study, we compute multi-component ambient-noise cross-correlations between all available stations in the area, including stations from both regional networks and the new nodal arrays. Clear Rayleigh and Love wave signals are observed between 1 and 10 sec periods, where higher mode Rayleigh waves are also apparent below ~4 sec. We use array processing techniques to measure phase velocity and Rayleigh wave ellipticity, or horizontal-to-vertical (H/V) amplitude ratio. Benefiting from the broad period range, for each location, we can determine the Rayleigh wave H/V ratio curve and identify the first time the peak fundamental mode Rayleigh wave H/V frequency, which is highly sensitive to basin structure and important to understand ground motion amplification. The comparison between these new observations across the nodal arrays and predictions based on the CVM will be shown and discussed, where the discrepancies highlight areas of CVM that can be further improved. Our preliminary results stimulate future efforts to constrain the 3-D basin geometry and comparisons with independent datasets, including Receiver Functions and gravity.

Citation
Gkogkas, K., Lin, F., Villa, V., Clayton, R. W., Ford, H. A., & Allam, A. A. (2023, 09). Towards a better understanding of the Los Angeles basin structure using data recorded from the LAB2022 nodal array. Poster Presentation at 2023 SCEC Annual Meeting.


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