@article{KtenidouRoumeliotiAbrahamsonetal.2018,
  author    = {Ktenidou, Olga-Joan and Roumelioti, Zafeiria and Abrahamson, Norman and Cotton, Fabrice Pierre and Pitilakis, Kyriazis and Hollender, Fabrice},
  title     = {Understanding single-station ground motion variability and uncertainty (sigma)},
  series = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering},
  volume    = {16},
  journal   = {Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering},
  number    = {6},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1570-761X},
  doi       = {10.1007/s10518-017-0098-6},
  pages     = {2311 -- 2336},
  year      = {2018},
  abstract  = {Accelerometric data from the well-studied valley EUROSEISTEST are used to investigate ground motion uncertainty and variability. We define a simple local ground motion prediction equation (GMPE) and investigate changes in standard deviation (σ) and its components, the between-event variability (τ) and within-event variability (φ). Improving seismological metadata significantly reduces τ (30-50\%), which in turn reduces the total σ. Improving site information reduces the systematic site-to-site variability, φ S2S (20-30\%), in turn reducing φ, and ultimately, σ. Our values of standard deviations are lower than global values from literature, and closer to path-specific than site-specific values. However, our data have insufficient azimuthal coverage for single-path analysis. Certain stations have higher ground-motion variability, possibly due to topography, basin edge or downgoing wave effects. Sensitivity checks show that 3 recordings per event is a sufficient data selection criterion, however, one of the dataset's advantages is the large number of recordings per station (9-90) that yields good site term estimates. We examine uncertainty components binning our data with magnitude from 0.01 to 2 s; at smaller magnitudes, τ decreases and φ SS increases, possibly due to κ and source-site trade-offs Finally, we investigate the alternative approach of computing φ SS using existing GMPEs instead of creating an ad hoc local GMPE. This is important where data are insufficient to create one, or when site-specific PSHA is performed. We show that global GMPEs may still capture φ SS , provided that: (1) the magnitude scaling errors are accommodated by the event terms; (2) there are no distance scaling errors (use of a regionally applicable model). Site terms (φ S2S ) computed by different global GMPEs (using different site-proxies) vary significantly, especially for hard-rock sites. This indicates that GMPEs may be poorly constrained where they are sometimes most needed, i.e., for hard rock.},
  language  = {en}
}