The California-Nevada Adjoint Simulations (CANVAS) Model

Claire D. Doody, Arthur J. Rodgers, Michael Afanasiev, Christian Boehm, Lion Krischer, Andrea Chiang, & Nathan Simmons

Published September 8, 2024, SCEC Contribution #14052, 2024 SCEC Annual Meeting Poster #227 (PDF)

We present the California-Nevada Adjoint Simulations (CANVAS) model, an adjoint waveform tomography model of the crust and uppermost mantle of California and Nevada. We used WUS256 (Rodgers et al., 2022) as a starting model and ran 161 iterations in 5 period bands, reaching a minimum period of 12 seconds. At 20 seconds minimum period, we inverted moment tensors using mttime (Chiang, 2020) to constrain source parameters. The CANVAS model resolves known tectonic features throughout California and western Nevada and accurately determined the depths to basement of large basins throughout California. CANVAS also greatly improved waveform fits to dispersed surface waves compared to WUS256, especially for small magnitude events (MW< 4.75). We hope CANVAS can serve as a starting model for smaller-scale regional seismic tomography studies across California and western Nevada or in place of 1D models in other applications such as moment tensor inversion, earthquake relocation, and earthquake ground motion modelling.

Key Words
Waveform Tomography, Moment Tensor Inversion

Citation
Doody, C. D., Rodgers, A. J., Afanasiev, M., Boehm, C., Krischer, L., Chiang, A., & Simmons, N. (2024, 09). The California-Nevada Adjoint Simulations (CANVAS) Model. Poster Presentation at 2024 SCEC Annual Meeting.

Related Projects & Working Groups
Community Earth Models (CEM)