Exciting news! We're transitioning to the Statewide California Earthquake Center. Our new website is under construction, but we'll continue using this website for SCEC business in the meantime. We're also archiving the Southern Center site to preserve its rich history. A new and improved platform is coming soon!

Sensitivity and Comparison of Two Broad-band Synthetic Generation Methods

Leonardo Ramirez-Guzman, Miguel A. Jaimes, & Carlos Mendoza

Published August 15, 2017, SCEC Contribution #7820, 2017 SCEC Annual Meeting Poster #248

The use of synthetic seismograms with engineering applications in mind is starting to gain acceptance worldwide, and validation efforts are a current topic of several research groups. Here we analyze the performance and sensitivity of two methodologies to include high frequencies (>1 Hz) to low-frequency ground motion simulations (<1 Hz). The methodologies studied (Kohrs-Sansorny, 2005; Irikura, 1986) are based on Empirical Green's Functions (Hartzell, 1978). The low-frequency ground motions are computed using the Carnegie Mellon finite element toolchain Hercules (Tu et al., 2006), together with a complex subduction zone velocity model. Low and high-frequency signal are linked by a matching filter with a cross-over frequency at 1Hz to generate synthetics valid up to 30 Hz. We use as performance metrics the goodness of fit proposals of Olsen and Mayhew (2010) and Anderson (2004). We conclude, through the analysis of a substantial number of observations and synthetic realizations for the 2014 Mw 7.4 Papanoa, Mexico earthquake, that the methods behave similarly in the near and far field within the frequency range of typical engineering applications (<20Hz).

References
Anderson, J. G. (2004). Quantitative measure of the goodness-of-fit of synthetic seismograms. In 13th World Conference on Earthquake Engineering Conference Proceedings, Vancouver, Canada, Paper (Vol. 243).
Hartzell, S. H. (1978). Earthquake aftershocks as Green's functions. Geophysical Research Letters, 5(1), 1-4.
Irikura, K. (1986). Prediction of strong acceleration motion using empirical Green’s function. In Proc. 7th Japan Earthq. Eng. Symp (Vol. 1986, pp. 151-156).
Kohrs-Sansorny, C., Courboulex, F., Bour, M., & Deschamps, A. (2005). A two-stage method for ground-motion simulation using stochastic summation of small earthquakes. Bulletin of the Seismological Society of America, 95(4), 1387-1400.
Olsen, K. B., & Mayhew, J. E. (2010). Goodness-of-fit criteria for broadband synthetic seismograms, with application to the 2008 M w 5.4 Chino Hills, California, earthquake. Seismological Research Letters, 81(5), 715-723.
Tu, T., Yu, H., Ramirez-Guzman, L., Bielak, J., Ghattas, O., Ma, K. L., & O'hallaron, D. R. (2006). From mesh generation to scientific visualization: An end-to-end approach to parallel supercomputing. In Proceedings of the 2006 ACM/IEEE conference on Supercomputing (p. 91). ACM.

Key Words
ground motions, empicial green's functions

Citation
Ramirez-Guzman, L., Jaimes, M. A., & Mendoza, C. (2017, 08). Sensitivity and Comparison of Two Broad-band Synthetic Generation Methods. Poster Presentation at 2017 SCEC Annual Meeting.


Related Projects & Working Groups
Ground Motions