Single-Station Sigma for the Iranian Strong Motion Stations

Zafarani, Hamid; Soghrat, M. R.

doi:10.1007/s00024-017-1613-z

Cited by 6 publications

(1 citation statement)

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“…The single‐station sigma was introduced to detect and avoid double counting those components of ground motion variability at a specific station that are repeatable from different sources (Atkinson, ; Kuehn & Scherbaum, , ; Morikawa et al, ; Rodriguez‐Marek et al, ; Rodriguez‐Marek, Montalva, Cotton, & Bonilla, ). To obtain the single‐station standard deviation, either we need a station‐specific data set (Atkinson, ; Chen & Faccioli, ; Lin et al, ; Morikawa et al, ; Rodriguez‐Marek et al, ; Zafarani & Soghrat, ) or we propose a nonergodic model (Kuehn & Scherbaum, , ). With respect to the ergodic assumption, there is no difference in ground motion variability observed in a global data set and the one at a specific station source.…”

Section: Resultsmentioning

confidence: 99%

Bayesian hierarchical model for variations in earthquake peak ground acceleration within small‐aperture arrays

et al. 2018

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Knowledge of the characteristics of earthquake ground motion is fundamental for earthquake hazard assessments. Over small distances, relative to the source–site distance, where uniform site conditions are expected, the ground motion variability is also expected to be insignificant. However, despite being located on what has been characterized as a uniform lava‐rock site condition, considerable peak ground acceleration (PGA) variations were observed on stations of a small‐aperture array (covering approximately 1 km2) of accelerographs in Southwest Iceland during the Ölfus earthquake of magnitude 6.3 on May 29, 2008 and its sequence of aftershocks. We propose a novel Bayesian hierarchical model for the PGA variations accounting separately for earthquake event effects, station effects, and event‐station effects. An efficient posterior inference scheme based on Markov chain Monte Carlo (MCMC) simulations is proposed for the new model. The variance of the station effect is certainly different from zero according to the posterior density, indicating that individual station effects are different from one another. The Bayesian hierarchical model thus captures the observed PGA variations and quantifies to what extent the source and recording sites contribute to the overall variation in ground motions over relatively small distances on the lava‐rock site condition.

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