Falcone, Giuseppe

In this paper we deal with statistical features of earthquakes, seeking possible correlations between the G-R magnitude distribution and the short-term clustering in an area of the Central Apennines, Italy, where significant seismicity with earthquakes exceeding magnitude 6.0 has been repeatedly observed from 1990 to the present. For this purpose, a recently developed version of the ETAS model, incorporating a threedimensional spatial triggering kernel, has been adopted. Our analysis has been carried out representing the b-value and the probability of independence of events on six vertical cross-sections suitably related to the seismic structures that are considered responsible of the seismicity observed in the study area. The results of the statistical analysis of the seismicity in the study area have shown a clear distinction between the western normal low-angle fault system, characterized by eastward dip, and the eastern normal fault systems, with westward dip. In the former (Etrurian Fault System; EFS) we found seismicity with a high b-value and high probability of independence, i.e., a scarce capacity of producing clusters and strong aftershock sequences. The eastern fault systems of our study area are distinguishable in two main distinct systems, which generated two strong seismic sequences in 1997 and 2016-2017. In the former (Colfiorito) sequence the seismicity showed a very low b-value and a modest probability of independence, while in the latter (Central Italy) sequence the bvalue was significantly higher and the probability of independence had extremely low values (manifesting a high level of clustering). The much higher b-value of the EFS than the other extensional sources could be caused by its peculiar seismotectonic role of discontinuity at the base of the normal active faulting, and its reduced capacity of accumulating stress. This circumstance may be interpreted by a difference in the rheological properties of these fault systems, possibly also in relation to their present status in the earthquake cycle and the presence of strong aftershock sequences.

One important aspect of the seismicity is the spatiotemporal clustering; hence, the distinction between independent and triggered events is a critical part of the analysis of seismic catalogs. Stochastic declustering of seismicity allows a probabilistic distinction between these two kinds of events. Such an approach, usually performed with the epidemic‐type aftershock sequence (ETAS) model, avoids the bias in the estimation of the frequency–magnitude distribution parameters if we consider a subset of the catalog, that is, only the independent or the triggered events. In this article, we present a framework to properly include the probabilities of any event to be independent (or triggered) both in the temporal variation of the seismic rates and in the estimation of the b‐value of the Gutenberg–Richter law. This framework is then applied to a high‐definition seismic catalog in the central part of Italy covering the period from April 2010 to December 2015. The results of our analysis show that the seismic activity from the beginning of the catalog to March 2013 is characterized by a low degree of clustering and a relatively high b‐value, whereas the following period exhibits a higher degree of clustering and a smaller b‐value.

In this paper, we gather and take stock of the results produced by the Operational Earthquake Forecasting (OEF) system in Italy, during its first 10 yr of operativity. The system is run in real-time: every midnight and after each ML 3.5 + event, it produces the weekly forecast of earthquakes expected by an ensemble model in each cell of a spatial grid covering the entire Italian territory. To e v aluate the performance skill of the OEF-Italy forecasts, we consider here standard tests of the Collaboratory for the Study of Earthquake Predictability, which have been opportunely adapted to the case of the overlapped weekly OEF forecasts; then we also adopt new performance measures borrowed from other research fields, like meteorology, specific to validate alarm-based systems by a binary criterion (forecast: yes/no; occurrence: yes/no). Our final aim is to: (i) investigate possible weaknesses and room for improvements in the OEF-Italy stochastic modelling, (ii) provide performance measures that could be helpful for stakeholders who act through a boolean logic (making an action or not) and (iii) highlight possible features in the Italian tectonic seismic activity.

In this paper, we carry out a comparison analysis of the Epidemic Type Aftershock Sequence (ETAS) model for the earthquake process, embedded with the three main exponential-type distributions adopted in practical applications to describe the magnitudes of seismic events, that are, the Gutenberg–Richter (GR), the tapered Gutenberg–Richter (TGR) and the CHaracteristic (CH) frequency–magnitude distributions (FMDs). The first law is a pure-power decreasing function, while both the other two introduce a more rapid decay in the tail of the distribution: a soft taper in the TGR model and a sharp cut-off in the CH one. To perform the comparison, we first investigate some theoretical features of the ETAS model with CH-distributed magnitudes (ETAS-CH), which have not been deeply analysed in the literature as much as for ETAS-TGR and ETAS-GR. In particular, we explicitly compute the branching ratio, we analyse its asymptotics in relation to its parameters, and we derive the proper stability conditions. We then move to the comparison among the three ETAS-GR, ETAS-TGR and ETAS-CH processes, to highlight differences and similarities. This is done by carrying out both a theoretical analysis, mainly focused on the three models’ branching ratios and the relative sensitivity, and a simulation analysis of realistic synthetic catalogues to compare the processes’ numbers, events’ magnitude distribution and temporal evolution. The results we obtained show that the ETAS-TGR and ETAS-CH processes have very similar features. They both have also less restrictive non-explosion conditions than for ETAS-GR; in fact, differently from this latter case, their branching ratios exist for any value of the parameters and are lower than the one of ETAS-GR, to which they converge for large magnitudes.

We estimate the b-value parameter of the Gutenberg–Richter law for earthquake magnitudes in the early stage of the Costa Marchigiana (Italy) seismic sequence, starting on 2022 November 9, with an ML 5.7 event in the Adriatic sea. In particular, we estimate both the completeness magnitude Mc and the b-value within the first 4 and 7 d after the initial strong event in the sequence. Our work represents a practical example of b-value estimation in ‘true’ real time, that is, during the seismic sequence, and its possible interpretation in terms of short-term forecasting. We highlight some critical issues to consider both in estimating/intepreting the b-value, and in evaluating the real time estimation of Mc. These issues are mainly due to the fact that preliminary catalogues available in real time are quite different from the revised ones, which are usually delivered after a few months. The criticalities are linked to the raw data recorded at an early-stage, an unreliable evaluation of the Mc with statistical approaches, the Short Term Aftershock Incompleteness entailed after the initial strong event, and the magnitude binning. Our results show that real time estimation of the b-value can give insights into the evolution of an ongoing seismic sequence, when attention is paid to data quality and quantity.

Operational Earthquake Forecasting (OEF) aims to deliver timely and reliable forecasts that may help to mitigate seismic risk during earthquake sequences. In this paper, we build the first OEF system for the State of Israel, and we evaluate its reliability. This first version of the OEF system is composed of one forecasting model, which is based on a stochastic clustering Epidemic Type Earthquake Sequence (ETES) model. For every day of the forecasting time period, January 1, 2016 - November 15, 2020, the OEF-Israel system produces a weekly forecast for target earthquakes with local magnitudes greater than 4.0 and 5.5 in the entire State of Israel. Specifically, it provides space-time-dependent seismic maps of the weekly probabilities, obtained by using a fixed set of the model’s parameters, which are estimated through the maximumlikelihood technique based on a learning period of about 32 years (1983–2015). According to the guidance proposed by the Collaboratory for the Study of Earthquake Predictability (CSEP), we also perform the N- and S-statistical tests to verify the reliability of the forecasts. Results show that the OEF system forecasts a number of events comparable to the observed one, and also captures quite well the spatial distribution of the real catalog with the exception of two target events that occurred in low seismicity regions.

Short term aftershock incompleteness (STAI) can strongly bias any analysis built on the assumption that seismic catalogs have a complete record of events. Despite several attempts to tackle this issue, we are far from trusting any data set in the immediate future of a large shock occurrence. Here, we introduce RESTORE (REal catalogs STOchastic REplenishment), a Python toolbox implementing a stochastic gap-filling method, which automatically detects the STAI gaps and reconstructs the missing events in the space-time-magnitude domain. The algorithm is based on empirical earthquake properties and relies on a minimal number of assumptions about the data. Through a numerical test, we show that RESTORE returns an accurate estimation of the number of missed events and correctly reconstructs their magnitude, location, and occurrence time. We also conduct a real-case test, by applying the algorithm to the urn:x-wiley:23335084:media:ess2915:ess2915-math-0001 6.2 Amatrice aftershocks sequence. The STAI-induced gaps are filled and missed earthquakes are restored in a way which is consistent with data. RESTORE, which is made freely available, is a powerful tool to tackle the STAI issue, and will hopefully help to implement more robust analyses for advancing operational earthquake forecasting and seismic hazard assessment.

In recent years, new approaches for developing earthquake rupture forecasts (ERFs) have been proposed to be used as an input for probabilistic seismic hazard assessment (PSHA). Zone- based approaches with seismicity rates derived from earthquake catalogs are commonly used in many countries as the standard for national seismic hazard models. In Italy, a single zone- based ERF is currently the basis for the official seismic hazard model. In this contribution, we present eleven new ERFs, including five zone-based, two smoothed seismicity-based, two fault- based, and two geodetic-based, used for a new PSH model in Italy. The ERFs were tested against observed seismicity and were subject to an elicitation procedure by a panel of PSHA experts to verify the scientific robustness and consistency of the forecasts with respect to the observations. Tests and elicitation were finalized to weight the ERFs. The results show a good response to the new inputs to observed seismicity in the last few centuries. The entire approach was a first attempt to build a community-based set of ERFs for an Italian PSHA model. The project involved a large number of seismic hazard practitioners, with their knowledge and experience, and the development of different models to capture and explore a large range of epistemic uncertainties in building ERFs, and represents an important step forward for the new national seismic hazard model.

The application of a physics-based earthquake simulator to Central Italy allowed the compilation of a synthetic seismic catalogue spanning 100 000 yr, containing more than 300 000 M ≥ 4.0 simulated earthquakes, without the limitations that real catalogues suffer in terms of completeness, homogeneity and time duration. The seismogenic model upon which we applied the simulator code was derived from version 3.2.1 of the Database of Individual Seismogenic Sources (DISS; http://diss.rm.ingv.it/diss/), selecting, and modifying where appropriate, all the fault systems that are recognized in the portion of Central Italy considered in this study, with a total of 54 faults. Besides tectonic stress loading and static stress transfer as in the previous versions, the physical model on which the latest version of our simulation algorithm is based also includes the Rate and State constitutive law that helps to reproduce Omori’s law. One further improvement in our code was also the introduction of trapezoidalshaped faults that perform better than known faults. The resulting synthetic seismic catalogue exhibits typical magnitude, space and time features which are comparable to those in real observations. These features include the total seismic moment rate, the earthquake magnitude distribution, and the short- and medium-term earthquake clustering. A typical aspect of the observed seismicity in Central Italy, aswell as across thewhole Italian landmass and elsewhere, is the occurrence of earthquake sequences characterized by multiple main shocks of similar magnitude. These sequences are different from the usual earthquake clusters and aftershock sequences, since they have at least two main shocks of similar magnitude. Therefore, special attentionwas devoted to verifyingwhether the simulated catalogue includes this notable aspect. For this purpose, we developed a computer code especially for this work to count the number of multiple events contained in a seismic catalogue under a quantitative definition. We found that the last version of the simulator code produces a slightly larger number of multiple events than the previous versions, but not as large as in the real catalogue. A possible reason for this drawback is the lack of components such as pore-pressure changes due to fluid-diffusion in the adopted physical model.

We develop an ensemble earthquake rate model that provides spatially variable time-independent (Poisson) long-term annual occurrence rates of seismic events throughout Italy, for magnitude bin of 0.1 units from Mw ≥4.5 in spatial cells of 0.1° x 0.1°. We weighed seismic activity rates of smoothed seismicity and fault-based inputs to build our earthquake rupture forecast model, merging it into a single ensemble model. Both inputs adopt a tapered Gutenberg-Richter relation with a single b-value and a single corner magnitude estimated by earthquakes catalog. The spatial smoothed seismicity was obtained using the classical kernel smoothing method with the inclusion of magnitude dependent completeness periods applied to the Historical (CPTI15) and Instrumental seismic catalogs. For each seismogenic source provided by the Database of the Individual Seismogenic Sources (DISS), we computed the annual rate of the events above Mw4.5, assuming that the seismic moments of the earthquakes generated by each fault are distributed according to the tapered Gutenberg-Richter relation with the same parameters of the smoothed seismicity models. Comparing seismic annual rates of the catalogs with those of the seismogenic sources, we realized that there is a good agreement between these rates in Central Apennines zones, whereas the seismogenic rates are higher than those of the catalogs in the north east and south of Italy. We also tested our model against the strong Italian earthquakes (Mw5.5+), in order to check if the total number (N-test) and the spatial distribution (S-test) of these events was compatible with our model, obtaining good results, i.e. high p-values in the test. The final model will be a branch of the new Italian seismic hazard map.