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  5. The pan-European engineering strong motion (ESM) flatfile: consistency check via residual analysis
 
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The pan-European engineering strong motion (ESM) flatfile: consistency check via residual analysis

Author(s)
Bindi, D.  
Kotha, S.-R.  
Weatherill, G.  
Lanzano, Giovanni  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Milano, Milano, Italia  
Luzi, Lucia  
Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sezione Milano, Milano, Italia  
Cotton, F.  
Language
English
Obiettivo Specifico
5T. Sismologia, geofisica e geologia per l'ingegneria sismica
Status
Published
JCR Journal
JCR Journal
Peer review journal
Yes
Journal
Bulletin of Earthquake Engineering  
Issue/vol(year)
/17 (2019)
Pages (printed)
583–602
Date Issued
2019
DOI
10.1007/s10518-018-0466-x
URI
https://www.earth-prints.org/handle/2122/12061
Abstract
We present the results of a consistency check performed over the flatfile extracted from the engineering strong motion (ESM) database. The flatfile includes 23,014 recordings from 2179 earthquakes in the magnitude range from 3.5 to 7.8 that occurred since the 1970s in Europe and Middle East, as presented in the companion article by Lanzano et al. (Bull Earthq Eng, 2018a). The consistency check is developed by analyzing different residual distributions obtained from ad-hoc ground motion prediction equations for the abso- lute spectral acceleration (SA), displacement and Fourier amplitude spectra (FAS). Only recordings from earthquakes shallower than 40 km are considered in the analysis. The between-event, between-station and event-and-station corrected residuals are computed by applying a mixed-effect regression. We identified those earthquakes, stations, and record- ings showing the largest deviations from the GMPE median predictions, and also evaluated the statistical uncertainty on the median model to get insights on the applicable magni- tude–distance ranges and the usable period (or frequency) range. We observed that robust median predictions are obtained up to 8 s for SA and up to 20 Hz for FAS, although median predictions for Mw≥7 show significantly larger uncertainties with ‘bumps’ starting above 5 s for SA and below 0.3 Hz for FAS. The between-station variance dominates over the other residual variances, and the dependence of the between-station residuals on logarithm of Vs30 is well-described by a piece-wise linear function with period-dependent slopes and hinge velocity around 580 m/s. Finally, we compared the between-event residuals obtained by considering two different sources of moment magnitude. The results show that, at long periods, the between-event terms from the two regressions have a weak correlation and the overall between-event variability is dissimilar, highlighting the importance of magnitude source in the regression results.
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