GNGTS 2014 - Atti del 33° Convegno Nazionale

GNGTS 2014 S essione 2.1 13 scale and distance conversions were applied. Moreover, GMPEs were corrected to predict the geometric mean of the horizontal components (Beyer and Bommer, 2006). Following good practice, the aleatory variability associated to conversion equations was carried across into the aleatory variability of each GMPE (Bommer et al. , 2005). Analyzing the hazard curves in Fig. 3, one may observe the largest uncertainty in the results (the spread between the hazard curves is an index of the epistemic uncertainty affecting the results) produced by older GMPEs (black curves in Fig. 3). Independently of the site, recent GMPEs (red curves in Fig. 3) appear to lead to a lower dispersion in the results, with hazard curves showing similar trend; after all, this was partly expectable given our previous observations concerning Fig. 2. Fig. 3 – PSH curves for PGA and Sa(1s) for the sites of Barisciano (BRS) and Malcesine (MLC). Scoring GMPEs. In order to evaluate the actual improvement in the GMPE performance (i.e., their effectiveness in predicting the ground motion), at least for application to the Italian area, we tested and scored different hazard models, each of which uses one of the GMPEs in Tab. 1. Given a set E of seismic occurrences (Evidence) and assuming that model outcomes are independent, the likelihood that in the i -th model the evidence E occurs (score) is given by (Albarello and D’Amico, 2008): (1) where: (2)