A completeness analysis of the national seismic network of Italy

We present the first detailed study of earthquake detection capabilities of the Italian National Seismic Network and of the completeness threshold of its earthquake catalog. The network in its present form started operating on 16 April 2005 and is a significant improvement over the previous networks. For our analysis, we employed the PMC method as introduced by Schorlemmer and Woessner (2008). This method does not estimate completeness from earthquakes samples as traditional methods, mostly based on the linearity of earthquake-size distributions. It derives detection capabilities for each station of the network and synthesizes them into maps of detection probabilities for earthquakes of a given magnitude. Thus, this method avoids the many assumptions about earthquake distributions that traditional methods make. The results show that the Italian National Seismic Network is complete at M=2.9 for the entire territory excluding the islands of Sardinia, Pantelleria, and Lampedusa. At the M=2.5 level, which is the reporting threshold level of the Italian Civil Protection, the network may miss events in southern parts of Apulia and the western part of Sicily. The stations are connected through many different telemetry links to the operational datacenter in Rome. Scenario computations show that no significant drop in completeness occurs if one of the three major links fail, indicating a well-balanced network setup

A completeness analysis of the national seismic network of Italy

We present the first detailed study of earthquake detection capabilities of the Italian National Seismic Network and of the completeness threshold of its earthquake catalog. The network in its present form started operating on 16 April 2005 and is a significant improvement over the previous networks. For our analysis, we employed the PMC method as introduced by Schorlemmer and Woessner (2008). This method does not estimate completeness from earthquakes samples as traditional methods, mostly based on the linearity of earthquake-size distributions. It derives detection capabilities for each station of the network and synthesizes them into maps of detection probabilities for earthquakes of a given magnitude. Thus, this method avoids the many assumptions about earthquake distributions that traditional methods make. The results show that the Italian National Seismic Network is complete at $M=2.9$ for the entire territory excluding the islands of Sardinia, Pantelleria, and Lampedusa. At the $M=2.5$ level, which is the reporting threshold level of the Italian Civil Protection, the network may miss events in southern parts of Apulia and the western part of Sicily. The stations are connected through many different telemetry links to the operational datacenter in Rome. Scenario computations show that no significant drop in completeness occurs if one of the three major links fail, indicating a well-balanced network setup

Earthquake detection capability of the Swiss Seismic Network

A reliable estimate of completeness magnitudes is vital for many seismicity- and hazard-related studies. Here we adopted and further developed the Probability-based Magnitude of Completeness (PMC) method. This method determines network detection completeness (MP) using only empirical data: earthquake catalogue, phase picks and station information. To evaluate the applicability to low- or moderate-seismicity regions, we performed a case study in Switzerland. The Swiss Seismic Network (SSN) at present is recording seismicity with one of the densest networks of broad-band sensors in Europe. Based on data from 1983 January 1 to 2008 March 31, we found strong spatio-temporal variability of network completeness: the highest value of MP in Switzerland at present is 2.5 in the far southwest, close to the national boundary, whereas MP is lower than 1.6 in high-seismicity areas. Thus, events of magnitude 2.5 can be detected in all of Switzerland. We evaluated the temporal evolution of MP for the last 20 yr, showing the successful improvement of the SSN. We next introduced the calculation of uncertainties to the probabilistic method using a bootstrap approach. The results show that the uncertainties in completeness magnitudes are generally less than 0.1 magnitude units, implying that the method generates stable estimates of completeness magnitudes. We explored the possible use of PMC: (1) as a tool to estimate the number of missing earthquakes in moderate-seismicity regions and (2) as a network planning tool with simulation computations of installations of one or more virtual stations to assess the completeness and identify appropriate locations for new station installations. We compared our results with an existing study of the completeness based on detecting the point of deviation from a power law in the earthquake-size distribution. In general, the new approach provides higher estimates of the completeness magnitude than the traditional one. We associate this observation with the difference in the sensitivity of the two approaches in periods where the event detectability of the seismic networks is low. Our results allow us to move towards a full description of completeness as a function of space and time, which can be used for hazard-model development and forecast-model testing, showing an illustrative example of the applicability of the PMC method to regions with low to moderate seismicit

CSEP Progress Report

CSEP Progress Repor

Sub-TeV hadronic interaction model differences and their impact on air showers

In the sub-TeV regime, the most widely used hadronic interaction models disagree significantly in their predictions of particle spectra from cosmic ray induced air showers. We investigate the nature and impact of model uncertainties, focussing on air shower primaries with energies around the transition between high and low energy hadronic interaction models, where the dissimilarities are largest and which constitute the bulk of the interactions in air showers.Comment: Proceedings of the 51 International Symposium on Multiparticle Dynamics (ISMD2022

Simultaneous Dependence of the Earthquake-Size Distribution on Faulting Style and Depth

We analyze two high-quality Southern Californian earthquake catalogues, one with focal mechanisms, to statistically model and test for dependencies of the earthquake-size distribution, the b values, on both faulting style and depth. In our null hypothesis, b is assumed constant. We then develop and calibrate one model based only on faulting style, another based only on depth dependence and two models that assume a simultaneous dependence on both parameters. We develop a new maximum-likelihood estimator corrected for the degrees of freedom to assess models' performances. Our results show that all models significantly reject the null hypothesis. The best performing is the one that simultaneously takes account of depth and faulting style. Our results suggest that differential stress variations in the Earth's crust systematically influence b values and that this variability should be considered for contemporary seismic hazard studies

Look-Ahead Benchmark Bias in Portfolio Performance Evaluation

Performance of investment managers are evaluated in comparison with benchmarks, such as financial indices. Due to the operational constraint that most professional databases do not track the change of constitution of benchmark portfolios, standard tests of performance suffer from the "look-ahead benchmark bias," when they use the assets constituting the benchmarks of reference at the end of the testing period, rather than at the beginning of the period. Here, we report that the "look-ahead benchmark bias" can exhibit a surprisingly large amplitude for portfolios of common stocks (up to 8% annum for the S&P500 taken as the benchmark) -- while most studies have emphasized related survival biases in performance of mutual and hedge funds for which the biases can be expected to be even larger. We use the CRSP database from 1926 to 2006 and analyze the running top 500 US capitalizations to demonstrate that this bias can account for a gross overestimation of performance metrics such as the Sharpe ratio as well as an underestimation of risk, as measured for instance by peak-to-valley drawdowns. We demonstrate the presence of a significant bias in the estimation of the survival and look-ahead biases studied in the literature. A general methodology to test the properties of investment strategies is advanced in terms of random strategies with similar investment constraints.Comment: 16 pages, 1 table, 4 figure

Setting up an earthquake forecast experiment in Italy

We describe the setting up of the first earthquake forecasting experiment for Italy within the Collaboratory for the Study of Earthquake Predictability (CSEP). CSEP conducts rigorous and truly prospective forecast experiments for different tectonic environments in several forecast testing centers around the globe; forecasts are issued for a future period and also tested only against future observations to avoid any possible bias. As such, experiments need to be completely defined. This includes exact definitions of the testing area, of learning data for the forecast models, and of observation data against which forecasts will be tested to evaluate their performance. Here we present the rules, as taken from the Regional Earthquake Likelihood Models experiment and extended or changed for the Italian experiment. We also present characterizations of learning and observational catalogs that describe the completeness of these catalogs and illuminate inhomogeneities of magnitudes between these catalogs. A particular focus lies on the stability of earthquake recordings of the observational network. These catalog investigations provide guidance for CSEP modelers for developing earthquakes forecasts for submission to the forecast experiment in Italy

On the Testing of Seismicity Models

Recently a likelihood-based methodology has been developed by the Collaboratory for the Study of Earthquake Predictability (CSEP) with a view to testing and ranking seismicity models. We analyze this approach from the standpoint of possible applications to hazard analysis. We arrive at the conclusion that model testing can be made more efficient by focusing on some integral characteristics of the seismicity distribution. This is achieved either in the likelihood framework but with economical and physically reasonable coarsening of the phase space or by choosing a suitable measure of closeness between empirical and model seismicity rate in this space.Comment: To appear at Acta Geophysic