EGU2020-18422
https://doi.org/10.5194/egusphere-egu2020-18422
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Dynamic source inversion of the 2014 Mw6 South Napa, California, earthquake

Jan Premus and Frantisek Gallovic
Jan Premus and Frantisek Gallovic
  • Charles University, Faculty of Mathematics and Physics, Department of Geophysics, Czechia (janpremus@seznam.cz)

Dynamic rupture modeling coupled with strong motion data fitting (dynamic source inversion) offers an insight into the rupture physics, constraining and enriching information gained from standard kinematic slip inversions. We utilize the Bayesian Monte Carlo dynamic source inversion method introduced recently by Gallovič et al. (2019), which, in addition to finding a best-fitting model, allows assessing uncertainties of the inferred parameters by sampling the posterior probability density function. The Monte Carlo approach requires running a large number (millions) of dynamic simulations due to the nonlinearity of the inverse problem. It is achieved by using GPU accelerated dynamic rupture simulation code FD3D_TSN (Premus et al., submitted) as a forward solver. We apply the inversion to the 2014 Mw6 South Napa, California, earthquake, employing strong motion data (up to 0.5 Hz) from the 10 closest stations. As an output, we obtain samples of the spatial distributions of dynamic parameters (prestress and parameters of the slip-weakening friction law). Regarding the rupture geometry, we consider two, presently ambiguous, fault planes (Pollitz et al., 2019), showing considerable differences in fitting seismograms in very close vicinity of the fault. We investigate properties of the rupture, especially in the region close to the free surface, and the viability of the model samples to explain the observed data in a broader frequency range (up to 5Hz).

How to cite: Premus, J. and Gallovic, F.: Dynamic source inversion of the 2014 Mw6 South Napa, California, earthquake, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18422, https://doi.org/10.5194/egusphere-egu2020-18422, 2020

Displays

Display file