Scoring and ranking probabilistic seismic hazard models: an application based on macroseismic intensity data

Abstract

Abstract. A probabilistic seismic hazard model consists of a set of weighted models/branches that describes the center, the body and the range of seismic hazard. Owing to the intrinsic nature of this kind of analysis, the weight of each model/branch represents its scientific credibility. However, practical uses of this model may sometimes require the selection of one or a few hazard curves that are sampled from the whole model, which often consists of thousands of branches. Here we put forward an innovative procedure that facilitates the scoring, ranking and selection of the hazard curves to account for the requirements of a specific application. The approach consists of a careful quality check of the data used for scoring and the adoption of a proper scoring rule. To show the applicability of this approach, we present an example that consists of scoring and ranking a set of multiple models/branches constituting a recent seismic hazard model of Italy. To score these branches, hazard estimates produced by each of them are compared with time series of macroseismic observations available in the Italian macroseismic database for a carefully selected set of localities deemed sufficiently representative, homogeneously distributed in space and complete with respect to time and intensity levels. The proper scoring parameter used for such a comparison is the logarithmic score, which can always be applied independently of the distribution of the data.