Probabilistic modelling of macroseismic attenuation and forecast of damage scenarios

According to the idea now widespread that macroseismic intensity should be expressed in probabilistic terms, a beta-binomial model has been proposed in the literature to estimate the probability of the intensity at site in the Bayesian framework and a clustering procedure has been adopted to define learning sets of macroseismic fields required to assign prior distributions of the model parameters. This article presents the results concerning the learning sets obtained by exploiting the large Italian macroseismic database DBM1I11 (Locati et al. in DBMI11, the 2011 version of the Italian Macroseismic Database, 2011. http://emidius.mi.ingv.it/DBMI11/) and discusses the problems related to their use in probabilistic modelling of the attenuation in seismic regions of the European countries partners of the UPStrat-MAFA project (2012), namely South Iceland, Portugal, SE Spain and Mt Etna volcano area (Italy). Anisotropy and the presence of offshore earthquakes are some of the problems faced. All the work has been carried out in the framework of the Task B of the project.