Intermediate-term middle-range earthquake predictions in Italy: a review

Analysis of precursory seismicity patterns in Zagros (Iran) by CN algorithm

“…If the condition m 3 > m 2 > m 1 ≥ M c is satisfied, assuring that all functions are computed for earthquakes above the completeness threshold M c , the monitoring of seismicity can start. Owing to the normalization of its functions, CN can be applied to regions with a different seismicity level without any adjustment (data fitting) of the functions and parameters (Peresan et al, 2005). With the CN algorithm, the monitoring of seismicity is performed every 2 months; thus, the availability of a catalog updated with a time delay not exceeding a couple of weeks is required.…”

“…unpredictability often associated with the self-organized criticality paradigm (e.g., Bak et al, 2002). Rule 3 ensures that the detection level controls, to some extent, the timespace uncertainty of prediction (Keilis-Borok, 1996), and thus the possibility of reducing the spatial uncertainty is controlled by the difficulty of keeping a high level of detection due to unavoidable logistic problems (Peresan et al, 2005).…”

“…The threshold for the selection of strong events, M 0 , was chosen to correspond to the minimum number of events in the histogram versus magnitude (Peresan et al, 2005), and 3 values of M 0 (6.0, 6.1, and 6.2) satisfied this condition within the CN region shown in Figure 3. According to the catalog analysis, M c is about 4.0; however, in order to test the sensitivity of the results on the choice of value for this parameter, we considered 4.5, as well.…”

“…The seismicity patterns are quantified by means of a specific set of functions, namely the "functions of seismic flow", defined by a detailed retrospective analysis of seismicity in the CaliforniaNevada region. This method has been undergoing realtime prospective testing for more than 20 years in several regions worldwide (Rotwain and Novikova, 1999;Peresan et al, 2005 and the results show that CN could be used as a statistically significant earthquake forecasting method.…”

A seismological and engineering perspective on the 2016 Central Italy earthquakes

“…Based on the neo-deterministic approach, an operational integrated procedure for seismic hazard assessment has been developed that allows for the definition of time dependent scenarios of ground shaking, through the routine updating of intermediate-term middle-range earthquake predictions, performed by means of the algorithms CN and M8S (Peresan et al, 2005). The results from real-time testing of the time-dependent NDSHA scenarios have been recently illustrated with specific reference to the August 24th, 2016 Central Italy earthquake by Peresan et al (2016).…”