Abstract
<p>The quantitative assessment of the performance of earthquake prediction and/or forecast models is essential for evaluating their applicability for risk reduction purposes. Here we assess the earthquake prediction performance of the CN model applied to the Italian territory. This model has been widely publicized in Italian news media, but a careful assessment of its prediction performance is still lacking. In this paper we evaluate the results obtained so far from the CN algorithm applied to the Italian territory, by adopting widely used testing procedures and under development in the Collaboratory for the Study of Earthquake Predictability (CSEP) network. Our results show that the CN prediction performance is comparable to the prediction performance of the stationary Poisson model, that is, CN predictions do not add more to what may be expected from random chance.</p>
Highlights
Earthquake prediction is one of the ways in which seismologists make statements about the future seismic activity, usually on the basis of the observation of one or more candidate diagnostic precursors [Sykes and Jaumé 1990, Pulinets and Davidenko 2014]
In this paper we evaluate the results obtained so far from the CN algorithm applied to the Italian territory, by adopting widely used testing procedures and under development in Collaboratory for the Study of Earthquake Predictability (CSEP)
The Parimutuel Gambling Score results are shown in Table 4; the results indicate that the Poisson model is better in all three macro-zones
Summary
Earthquake prediction is one of the ways in which seismologists make statements about the future seismic activity, usually on the basis of the observation of one or more candidate diagnostic precursors [Sykes and Jaumé 1990, Pulinets and Davidenko 2014]. A prediction consists in casting an alarm, i.e., a deterministic assertion that one target earthquake of a given magnitude will occur in a specified space-time window. Another way in which seismologists make statement about the future seismic activity is through probabilistic forecasting that consists of the estimation of the probability of one or more events in well-defined magnitude-space-time windows (e.g., Marzocchi et al [2014], for the Italian region).
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