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In the present study, we analyze ground-motion hazard maps and hazard disaggregation in order to define areas in Italy where liquefaction triggering due to seismic activity can not be excluded. To this end, we refer to the triggering criteria (not to be confused with liquefaction susceptibility criteria, which essentially take into account soil type and depth to groundwater) proposed by the Italian Guidelines for Seismic Microzonation, which are described in the main body of the paper. However, the study can be replicated in other countries that adopt different criteria. The final goal is the definition of a screening map for all of Italy that classifies sites in terms of liquefaction triggering potential according to their seismic hazard level. The map, which is referred to with the Italian acronym MILQ – Mappa del potenziale d'Innesco della LiQuefazione (i.e., map of liquefaction triggering potential), and the associated data are freely accessible at the following web address: https://distav.unige.it/rsni/milq.php (last access: 28 April 2023). Our results can be useful to guide land-use planners in deciding whether liquefaction is a hazard that needs to be considered within the planning processes or not. Furthermore, they can serve as a guide for recommending geological and geotechnical investigations aimed at the evaluation of liquefaction hazards or, conversely, rule out further studies with consequent savings in efforts and money.

In the present study, we analyze ground-motion hazard maps and hazard disaggregation in order to define areas in Italy where liquefaction triggering due to seismic activity can not be excluded. To this end, we refer to the triggering criteria (not to be confused with liquefaction susceptibility criteria, which essentially take into account soil type and depth to groundwater) proposed by the Italian Guidelines for Seismic Microzonation, which are described in the main body of the paper. However, the study can be replicated in other countries that adopt different criteria. The final goal is the definition of a screening map for all of Italy that classifies sites in terms of liquefaction triggering potential according to their seismic hazard level. The map, which is referred to with the Italian acronym MILQ – Mappa del potenziale d'Innesco della LiQuefazione (i.e., map of liquefaction triggering potential), and the associated data are freely accessible at the following web address: https://distav.unige.it/rsni/milq.php (last access: 28 April 2023). Our results can be useful to guide land-use planners in deciding whether liquefaction is a hazard that needs to be considered within the planning processes or not. Furthermore, they can serve as a guide for recommending geological and geotechnical investigations aimed at the evaluation of liquefaction hazards or, conversely, rule out further studies with consequent savings in efforts and money.

We present the Istituto Nazionale di Geofisica e Vulcanologia Strong-Motion Data-quality (ISMDq)—a new automatic system designed to check both continuous data stream and event strong-motion waveforms before online publication. The main purpose of ISMDq is to ensure accurate ground-motion data and derived products to be rapidly shared with monitoring authorities and the scientific community. ISMDq provides data-quality reports within minutes of the occurrence of Italian earthquakes with magnitude ≥3.0 and includes a detailed daily picture describing the performance of the target strong-motion networks. In this article, we describe and discuss the automatic procedures used by ISMDq to perform its data-quality check. Before an earthquake, ISMDq evaluates the selected waveforms through the estimation of quality indexes employed to reject bad data and/or to group approved data into classes of quality that are useful to quantify the level of reliability. The quality indexes are estimated based on comparisons with the background ambient noise level performed both in the time and frequency domains. As a consequence, new high- and low-noise reference levels are derived for the overall Italian strong-motion network, for each station, and for groups of stations in the same soil categories of the Eurocode 8 (Eurocode 8 [EC8], 2003). In absence of earthquakes, 24 hr streaming of ambient noise recordings are analyzed at each station to set an empirical threshold on selected data metrics and data availability, with the goal to build a station quality archive, which is daily updated in a time span of six months. The ISMDq is accessible online (see Data and Resources) from August 2020, providing rapid open access to ∼10,000 high-quality checked automatically processed strong-motion waveforms and metadata, relative to more than 160 Italian earthquakes with magnitude in the 3.0–5.2 range. Comparisons between selected strong-motion data automatically processed and then manually revised corroborate the reliability of the proposed procedures.

We present Rapid Assessment of MOmeNt and Energy Service (RAMONES), a service for disseminating through a web interface, the estimates of seismic moment (M0) and radiated energy (ER) for earthquakes occurring in central Italy with local magnitudes above 1.7. The service is based on a fully-automatic procedure developed for downloading and processing open seismological data from the European Integrated Data Archive, Italian Civil Protection repository, and Incorporated Research Institutions for Seismology (IRIS). In its actual configuration, RAMONES uses the seismic catalog generated through the event webservice of the Italian Institute of Geophysics and Volcanology (compliant with International Federation of Digital Seismograph Networks standards) to guide the data download. The concept of RAMONES is to estimate M0 and ER from features extracted directly from recordings, namely the S-wave peak displacement (PDS) and the integral of the squared velocity (IV2S) evaluated over the S-wave window at local distances. A data set composed of 6515 earthquakes recorded in central Italy between 2008 and 2018 was used to calibrate the attenuation models relating M0 to PDS and ER to IV2S, including station corrections. The calibration values for M0 and ER were extracted from the source spectra obtained by applying a decomposition approach to the Fourier amplitude spectra known as the generalized inversion technique. To test the capabilities of RAMONES, we validate the attenuation models by performing residual analysis over about 60 earthquakes occurring in 2019 that were used for the spectral decomposition analysis but not considered in the calibration phase. Since January 2020, a testing operational phase has been running, and RAMONES has analyzed about 800 earthquakes by September 2020. The distribution of the source parameters and their relevant scaling relationships are automatically computed and disseminated in the form of maps, parametric tables, figures, and reports available through the RAMONES web interface.

Landslides are a major threat for population and urban areas. Persistent Scatterer Interferometry (PSI) is a powerful tool for identifying landslides and monitoring their evolution over long periods and has proven to be very useful especially in urban areas, where a sufficient number of PS can be generated. In this study, we applied PS interferometry to investigate the landslide affecting Santo Stefano d’Aveto (Liguria, NW Italy) by integrating classic interferometric techniques with cross-correlation analysis of PS time-series and with geological and geotechnical field information. We used open-source software and packages to process Synthetic Aperture Radar (SAR) images from the Copernicus Sentinel-1A satellite for both ascending and descending orbits over the period 2015–2021 and calculate both the vertical motion and the E-W horizontal displacement. By computing the cross-correlation of the PS time-series, we identified three families of PS with a similarity greater than 0.70. The cross-correlation analysis allowed subdividing the landslide in different sectors, each of which is characterized by a specific type of movement. The geological meaning of this subdivision is still a matter of discussion but it is presumably driven by the geomorphological setting of the area and by the regional tectonics.

SUMMARYThe 2016–2017 central Italy earthquake sequence began with the first main shock near the town of Amatrice on August 24 (Mw 6.0), and was followed by two subsequent large events near Visso on October 26 (Mw 5.9) and Norcia on October 30 (Mw 6.5), plus a cluster of four events with Mw > 5.0 within few hours on 18 January 2017. The affected area had been monitored before the sequence started by the permanent Italian National Seismic Network (RSNC), and was enhanced during the sequence by temporary stations deployed by the National Institute of Geophysics and Volcanology and the British Geological Survey. By the middle of September, there was a dense network of 155 stations, with a mean separation in the epicentral area of 6–10 km, comparable to the most likely earthquake depth range in the region. This network configuration was kept stable for an entire year, producing 2.5 TB of continuous waveform recordings.Here we describe how this data was used to develop a large and comprehensive earthquake catalogue using the Complete Automatic Seismic Processor (CASP) procedure. This procedure detected more than 450 000 events in the year following the first main shock, and determined their phase arrival times through an advanced picker engine (RSNI-Picker2), producing a set of about 7 million P- and 10 million S-wave arrival times. These were then used to locate the events using a non-linear location (NLL) algorithm, a 1-D velocity model calibrated for the area, and station corrections and then to compute their local magnitudes (ML). The procedure was validated by comparison of the derived data for phase picks and earthquake parameters with a handpicked reference catalogue (hereinafter referred to as ‘RefCat’). The automated procedure takes less than 12 hr on an Intel Core-i7 workstation to analyse the primary waveform data and to detect and locate 3000 events on the most seismically active day of the sequence. This proves the concept that the CASP algorithm can provide effectively real-time data for input into daily operational earthquake forecasts,The results show that there have been significant improvements compared to RefCat obtained in the same period using manual phase picks. The number of detected and located events is higher (from 84 401 to 450 000), the magnitude of completeness is lower (from ML 1.4 to 0.6), and also the number of phase picks is greater with an average number of 72 picked arrival for a ML = 1.4 compared with 30 phases for RefCat using manual phase picking. These propagate into formal uncertainties of ±0.9 km in epicentral location and ±1.5 km in depth for the enhanced catalogue for the vast majority of the events. Together, these provide a significant improvement in the resolution of fine structures such as local planar structures and clusters, in particular the identification of shallow events occurring in parts of the crust previously thought to be inactive. The lower completeness magnitude provides a rich data set for development and testing of analysis techniques of seismic sequences evolution, including real-time, operational monitoring of b-value, time-dependent hazard evaluation and aftershock forecasting.

The Transantarctic Mountains (TAM) separate the Mesozoic to recent West Antarctic rift system (WARS) from a wide and depressed triangular sector of East Antarctica spanning from 100° E to 160° E in longitude and from the Oates, George V and Adelie coastlines to 85° S in latitude. The sub-ice bedrock of this sector shows a basin and range style topography comprising two major basins of continental proportions -the Wilkes Basin and the Aurora Basin complex- and many smaller basins such as the Adventure, Concordia, Aurora and Vostok trenches. Most of these basins and trenches exhibit a triangular shape with the acutest angle pointing approximatively to a single pole towards the South, giving a fan shaped pattern of significant dimensions. We name here this region as the East Antarctic Fan shaped Basin Province (EAFBP). To the West, this province is limited by the intraplate Gamburtsev Mountains (GM).Origins and inter-relationships between these four fundamental Antarctic tectonic units (WARS, TAM, EAFBP, GM) are still poorly understood and strongly debated. In the EAFBP, very little is known about the mechanism generating the basins, their formation time, whether they are all coeval and if and how they relate to Australia basins before Antarctica-Australia rifting. Present genetic hypotheses for some of the basins span from continental rifting to a purely flexural origin or a combination of the two. Also, post-tectonic erosional and depositional processes may have had a significant impact on the present-day topographic configuration.Here we investigate the possibility that the EAFBP is the result of a single genetic mechanism: a wide fan-shaped intra-continental extension around a pivot point at about 135° E, 85° S that occurred at the Mesozoic-Cenozoic transition. We discuss evidence from the sub-ice topography and potential field airborne and satellite data.We have used international community-based Antarctic compilations in public domain, including BedMachine (Morlighem et al., 2020), AntGG (Scheinert et al., 2016) and ADMAP 2.0 (Golynsky et al., 2018). We have applied image segmentation techniques to the rebounded sub-ice topography to automatically trace the first order shape of the sub-ice basins. Then we have fitted the edges of the basins by maximum circles and we have estimated the best Euler pole identified by their intersection. Potential field anomalies have been taken into account in order to enlighten major discontinuities not revealed by the sub-ice topography.Software simulations of the EAFBP opening in the frame of global plate tectonics reconstructions indicate that it may be inserted in the frame of the later phase of the Antarctica-Australia rifting, giving constraints on timing that allow us to date the EAFBP opening at the Mesozoic-Cenozoic transition.The reconnaissance of the EAFBP as the result of a continental-scale fan-shaped extension may have deep implications on global and regional tectonics plate reconstructions, plate deformation assumptions and new tectonic evolutionary models of WARS, TAM and GM.

An application of the Complete Automatic Seismic Processor (CASP) for seismic monitoring is presented. Its integrated and iterative fully automatic procedure is able to achieve complete data analysis and significantly rapid elaborations. Its performance in real-time seismic monitoring and alerting is tested in the Trentino region (NE Italy) for the period 1st March 2018 – 31st August 2019. CASP precisely and accurately located 386 seismic events, with local magnitudes in the -0.8–3.4 range, and produced a seismic catalogue with a magnitude of completeness around 1.1. Automatic earthquake solutions, with average horizontal and vertical errors of 1.1 and 1.5 km, are very similar to those included in a manually revised reference catalogue. In addition, 146 detected events are located in the area of the local porphyry quarries. CASP alerts are delivered as Short Message Service (SMS), Telegram and e-mail messages within an average time of just over two minutes from the earthquake origin time. These alerts contain earthquake source parameters, ground shaking levels and instrumental intensities. CASP reliability, promptness and robustness permit to civil protection and decision makers to perform a monitoring primarily dedicated to emergency management, in order to evaluate both seismic sources and their effects (peak ground acceleration) at local targets, such as more inhabited territories and critical infrastructures (dams and hydropower plants).

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.

Abstract. Background: Climate factors may offer a stronger explanation of the variations in suicide rates compared with economic variables, even in the case of patients admitted involuntarily. Aims: We assessed the role of temperature as a determinant of the increased prevalence of suicide attempts (SA). Method: The sample comprised all cases of hospitalization for SA at the Psychiatric Clinic of the IRCCS Ospedale Policlinico San Martino between August 2013 and July 2018. For ambient temperature, data were provided by the Meteorological Observatory of the University of Genoa. Results: We noted a peak in suicides that was typically found in late spring and early summer due to global warming. Limitations: Other environmental/psychological factors contributing to the onset of an acute clinical event were not considered. The cross-sectional design of the study is another limitation. Conclusion: Further studies are needed to clarify the impact of climatic factors on suicide behavior and implement early intervention and preventive strategies for mental health.

The monitoring of sea wave parameters, such as the significant wave height, represents a fundamental issue for several economic activities. The use of buoy networks is nowadays a standard approach in sea wave monitoring. However, due to their maintenance costs, both a widespread coverage of monitored areas and the acquisition of continual stream of data appear problematic in any coastal area. In this work, we present an automatic procedure for the near real-time monitoring of the significant sea wave height through microseism recordings. The procedure relies on a set of empirical prediction relations that are calibrated on existing datasets of hindcast sea wave heights, which were computed from wave modeling in the Mediterranean basin. This automatic procedure is developed and tested for monitoring the sea wave height along the Ligurian coast, covering an area of almost 5000 km2. On average, our predictions are found to be within a few centimeters from the reference hindcast data, thus showing the overall reliability of the procedure. The accuracy of our procedure has been also confirmed by the good agreement between the predicted significant sea wave heights and the sea wave heights measured at two buoys in the Ligurian Sea, with differences that, on average, are within 20 cm. Compared to conventional monitoring systems based on wave measuring buoys, the procedure proposed in this work allows the minimization of data acquisition interruption due to instrumental breakage, and a widespread, uniform monitoring of sea areas, particularly in the proximity of the shoreline, where structures and infrastructures are more exposed to sea storms.

Understanding the dynamics of faulting is a crucial target in earthquake source physics (Yoo et al., 2010). To study earthquake dynamics it is indeed necessary to look at the source complexity from different perspectives; in this regard, useful information is provided by the seismic moment (M0), which is a static measure of the earthquake size, and the seismic radiated energy (ER), which is connected to the rupture kinematics and dynamics (e.g. Bormann & Di Giacomo 2011a). Studying spatial and temporal evolution of scaling relations between scaled energy (i.e., e = ER/M0) versus the static measure of source dimension (M0) can provide valuable indications for understanding the earthquake generation processes, single out precursors of stress concentrations, foreshocks and the nucleation of large earthquakes (Picozzi et al., 2019). In the last ten years, seismology has undergone a terrific development. Evolution in data telemetry opened the new research field of real-time seismology (Kanamori 2005), which targets are the rapid determination of earthquake location and size, the timely implementation of emergency plans and, under favourable conditions, earthquake early warning. On the other hand, the availability of denser and high quality seismic networks deployed near faults made possible to observe very large numbers of micro-to-small earthquakes, which is pushing the seismological community to look for novel big data analysis strategies. Large earthquakes in Italy have the peculiar characteristic of being followed within seconds to months by large aftershocks of magnitude similar to the initial quake or even larger, demonstrating the complexity of the Apennines’ faults system (Gentili and Giovanbattista, 2017). Picozzi et al. (2017) estimated the radiated seismic energy and seismic moment from P-wave signals for almost forty earthquakes with the largest magnitude of the 2016-2017 Central Italy seismic sequence. Focusing on S-wave signals recorded by local networks, Bindi et al. (2018) analysed more than 1400 earthquakes in the magnitude ranges 2.5 ≤ Mw ≤ 6.5 of the same region occurred from 2008 to 2017 and estimated both ER and M0, from which were derived the energy magnitude (Me) and Mw for investigating the impact of different magnitude scales on the aleatory variability associated with ground motion prediction equations. In this work, exploiting first steps made in this direction by Picozzi et al. (2017) and Bindi et al. (2018), we derived a novel approach for the real-time, robust estimation of seismic moment and radiated energy of small to large magnitude earthquakes recorded at local scales. In the first part of the work, we describe the procedure for extracting from the S-wave signals robust estimates of the peak displacement (PDS) and the cumulative squared velocity (IV2S). Then, exploiting a calibration data set of about 6000 earthquakes for which well-constrained M0 and theoretical ER values were available, we describe the calibration of empirical attenuation models. The coefficients and parameters obtained by calibration were then used for determining ER and M0 of a testing dataset

The earthquake swarm that took place in 2012–2015 in the Upper Ubaye Valley (the most active seismic zone in the French Alps) is peculiar for two reasons: (1) it occurred a few kilometers from a previous swarm (active in 2003–2004); (2) it was initiated by an M L 4.3 shock and reactivated, more than two years later, by another M L 4.8 shock with an identical epicenter but a deeper focus. We present here the corresponding data set of ∼13,000 events, of which ∼3000 were relocated using a double‐difference algorithm. The swarm extends north‐northwest–south‐southeast (N165°E) over a distance of 11 km, but daily snapshots along a 2.5 yr period allow us to identify transverse faults whose activity was often ephemeral. Focal mechanisms for 13 M L ≥3 events confirm the complexity of the swarm geometry, although the fault plane for the two “mainshocks” is very consistent (N156°E–N160°E strike, 52°–55°SW dip), with clear normal faulting and a slight dextral strike‐slip component. Most foci were located in the 4–11‐km depth range, within the crystalline basement. Taking into account the source sizes for the two “mainshocks”, the hydraulic diffusivity of 0.05 m 2 s −1 found for the 2003–2004 swarm is shown to fit reasonably well the 2012 data, but not the 2014 reactivation sequence. Throughout the article, we discuss the difficult issue of the identification of “foreshocks” and “aftershocks” within such a sequence, even though a swarm, per se, makes this terminology inadequate. As previously suggested by other authors, between a foreshock–mainshock–aftershock sequence and an earthquake swarm also exists a whole gamut of seismic activity which makes this dichotomy much more complex than anticipated.

The use of microseisms with appropriate predictive laws is a reliable method for estimating such sea-wave parameters as period and significant height. Through the use of opportune predictive laws calibrated with measurements obtained from wave buoys, it is possible to determine the significant height of the wave as a function of the spectral energy-content of the microseism. In this paper we will present a procedure that utilises microseisms recorded by a micro network of five seismic stations to predict the significant height of waves, and its uncertainty, along the western Ligurian coast (Italy). The calibration and validation of the procedure was performed using wave measurements obtained from a wave buoy off Capo Mele (Imperia, Italy) over a two and a half year period. The differences between the significant heights measured by the wave buoy and the empirical predictions were less than 10 cm (corresponding to 10% of the mean measured value) for 47% of the data and less than 20 cm (corresponding to 20% of the mean measured value) for 72%.

In this work, we test a fully automatic procedure to obtain local earthquake tomography (LET), starting from seismic waveforms and applying the capability of the automatic phase picker and locator engine “RSNI‐Picker” (Spallarossa et al. , 2014), which is based on a multistep iterative procedure working on P and S arrival times. This code is currently operating as part of the Earthquake Monitoring System at the University of Genoa (RSNI designates the regional seismic network of northwestern Italy). In particular, we compare P ‐ and S ‐wave tomographic results obtained using this fully automatic procedure for picking and locations with those based on data from accurate manual picking and revised locations. We use a dataset of 409 earthquakes that occurred in the Trentino region (Northeastern Italy) in the 1994–2007 period. The highly variable waveform qualities (e.g., signal‐to‐noise ratio), mainly due to recording stations equipped with different types of sensors and digitizers (including both one‐component narrowband stations and three‐component broadband seismic stations), ensure a severe test for the automatic procedure. The comparison of the two 3D velocity propagation models for the Trentino region (i.e., LET images) from the automatic and manual procedures, shows maximum differences of 0.54 and 0.34 km/s for P and S waves, respectively (if we consider 90% of all the computed absolute velocities, as a reference percentage). The automatic LET shows velocity anomaly distributions and reliability patterns (e.g., resolution diagonal element [RDE] values) similar to those obtained using the manual procedure; 90% of RDE differences are lower than 0.15. The results obtained by testing the RSNI‐Picker engine suggest it can be used to automatically process large amounts of seismic recordings in order to identify P and S wavepicks for reliable LET analysis.

A historical set of daily meteorological data collected at the Hanbury Botanical Gardens (Liguria, northwestern Italy) from 1900 to 1940 was recovered from five manually entered registers. They were digitised and statistically analysed to check their reliability and study their trends and variations. In particular, air temperature, precipitation and their extreme values were considered, together with wind direction, sea state, sky conditions and relative humidity. The results show a decreasing trend in mean annual temperature of approximately 0.2 °C/decade due to a decrease in maximum air temperature. Annual cumulative precipitation increased by 65.2 mm/decade over the study period. The data analysis showed a summer temperature decrease in 1912 and a severe drought in 1921. Moreover, the years with most days with extreme temperatures were associated to the negative phases of the North Atlantic oscillation (NAO). During the study period, SW winds were prevailing. Sky conditions followed seasonal trends, while slight sea was the most frequent sea state.

The present work aims to suggest an innovative solution for seismic monitoring stations’ endurance. These stations are characterized by many different problems, such as lightning vulnerability, energy independence and noises disturbance. The suggested technology, for this type of application, is an improved bladeless turbo-expander patented by Nikola Tesla in the early 20th century, the Tesla turbine.

Since the beginning of the 1980s, when Mandelbrot observed that earthquakes occur on ‘fractal’ self-similar sets, many studies have investigated the dynamical mechanisms that lead to self-similarities in the earthquake process. Interpreting seismicity as a self-similar process is undoubtedly convenient to bypass the physical complexities related to the actual process. Self-similar processes are indeed invariant under suitable scaling of space and time. In this study, we show that long-range dependence is an inherent feature of the seismic process, and is universal. Examination of series of cumulative seismic moment both in Italy and worldwide through Hurst’s rescaled range analysis shows that seismicity is a memory process with a Hurst exponent H ≈ 0.87. We observe that H is substantially space- and time-invariant, except in cases of catalog incompleteness. This has implications for earthquake forecasting. Hence, we have developed a probability model for earthquake occurrence that allows for long-range dependence in the seismic process. Unlike the Poisson model, dependent events are allowed. This model can be easily transferred to other disciplines that deal with self-similar processes.

The aim of this work is to describe the seismicity of Northwestern Italy from the very detailed picture provided by 30 years of accurate instrumental recordings coming from the Regional Seismic Network of Northwestern Italy (RSNI—University of Genoa). In an attempt to provide, for the first time, a comprehensive view of the seismicity in the area, this study describes the main characteristics of the database collected by the RSNI network. The seismicity is spread almost over the entire area, but it is mainly concentrated in the Northern Apennines and in the western sector of the Alps. The seismicity of the area is superficial: It is almost confined to the first 20 km of depth. Only a few deeper events are located in a small area southwest of the city of Turin, down to a depth of 80 km, and below the Northern Apennines down to 60–70-km depth. The majority of the earthquakes in this sector of the Italian peninsula are of low magnitude; nevertheless, the areas where the highest magnitude earthquakes took place during the last three decades are the Northern Apennines and the lower Piedmont, on land, and the Ligurian Sea, offshore. They are indeed the areas where the most damaging historical earthquakes have occurred, giving emphasis, if necessary, to the importance of continuous seismic monitoring.

The study presents a detailed analysis of the swarm that occurred in the area surrounding Sampeyre (Piedmont, Italy) during the period October–November 2010. The crisis caught the attention of seismologists because of its intense seismic productivity that has never been observed in the past. During the swarm, 550 earthquakes were recorded and located by the Regional Seismic network of Northwestern Italy — RSNI ( http://www.distav.unige.it/geofisica/ ) in the study area. However, including the micro-seismicity (mainly, earthquakes of magnitude lower than 0) detected through an STA/LTA- (short-term average/long-term average) based algorithm, the number of events goes up to approximately 3250. Among all these events, approximately two hundred exceeded a local magnitude ( M l ) of 1.0 but only two earthquakes exceeded M l = 3.0, reaching up to M l = 3.2. Following a general description of the swarm evolution, the study presents the results of a waveform similarity analysis and double-difference relocation, aimed at identifying groups of earthquakes belonging to common genetic sources. A statistical analysis of the resulting earthquake families has revealed a variation of the scaling exponent ( b -value) of the Gutenberg and Richter size-frequency model with depth. In particular, our results have evidenced a slightly higher b -value at shallower depths where a distinct family of earthquakes was identified through seismogram cross-correlation. This may reflect variability in the distribution of fractures in the rock volume involved in the swarm.

Summary In the context of the environmental monitoring of the Concordia wreck removal project, measurements of currents, winds and sea level height were made along the eastern coast of the Giglio Island, Tyrrhenian Sea (Italy), during 2012–2013. The aim of the study was to investigate the effect of atmospheric forcing and periodic sea-level changes on the coastal currents. Normalised Cross-Correlation Function analysis allowed us to correlate these observations. A marked inter-seasonal variability was found in both current and local wind velocity observations but a significant level of correlation between the data was only found during strong wind events. Current and wind directions appeared to be uncorrelated and current measurements showed a predominant NW–SE direction, presumably linked to the shape and orientation of Giglio Island itself. During strong winds from the SSE, current flow was towards the NNW but it suddenly switched from the NNW to the SE at the end of wind events. The results show that, at Giglio Island, currents are principally dominated by the general cyclonic Tyrrhenian circulation, and, secondly, by strong wind events. The sea level had no effects on the current regime.

ISMD is the real time INGV Strong Motion database. During the recent August-September 2016 Amatrice, Mw 6.0, seismic sequence, ISMD represented the main tool for the INGV real time strong motion data sharing. Starting from August 24th, the main task of the web portal was to archive, process and distribute the strong-motion waveforms recorded by the permanent and temporary INGV accelerometric stations, in the case of earthquakes with magnitude ≥ 3.0, occurring in the Amatrice area and surroundings. At present (i.e. September 30th, 2016), ISMD provides more than 21.000 strong motion waveforms freely available to all users. In particular, about 2.200 strong motion waveforms were recorded by the temporary network installed for emergency in the epicentral area by SISMIKO and EMERSITO working groups. Moreover, for each permanent and temporary recording site, the web portal provide a complete description of the necessary information to properly use the strong motion data.

According to the most common interpretation, the Apennines developed in Neogene and Quaternary times in the hanging wall of a west directed subduction zone. Seismic tomography is the most powerful tool to investigate large volume of Earth at depth, and it has been extensively applied to shed light on the geometry and shape of the subduction under the Italian peninsula. The various experiments were able to display the slab under the Southern Apennines, but even the most recent tomographic images were non-uniquely interpretable and left open questions about the characteristics of the subduction in the Northern-Central sector of the chain. We here present the results of an improved inversion experiment focused on the Northern and Central Apennines. The results do not show any pronounced subduction slab and the most evident anomaly is a low velocity body extending down to 100 km depth, located in a relatively small area under the western Tuscany. On the basis of accurate synthetic tests, we assess that, if established, a subduction like geometry should be visible in our tomographic images. We then conclude that no subduction is imaged in the Northern and Central Apennines. We thus interpret this anomaly as an asthenospheric flow. However, we cannot exclude that our result is due to intrinsic limitations of the methodology. In fact in response to the original question about the capability of local earthquake tomography to settle the matter about subduction, we underline that the absence of deep earthquakes to illuminate the model from below, the existence of seismic gaps in some sectors of the area under study even at shallow depth and the non uniqueness of interpretation of the tomographic images make local tomography unable to give alone definitive information on the deep structure of the Northern and Central Apennines.

Reliable automatic procedure for lo- cating earthquake in quasi-real time is strongly needed for seismic warning system, earthquake preparedness, and producing shaking maps. The reliability of an automatic location algorithm is influenced by several factors such as errors in picking seismic phases, network geometry, and velocity model uncertainties. The main purpose of this work is to investigate the performances of different automatic procedures to choose the most suitable one to be applied for the quasi-real-time earthquake locations in northwestern Italy. The reliability of two automatic-picking algorithms (one based on the Characteristic Function (CF) analysis, CF picker, and the other one based on the Akaike Information Criterion (AIC), AIC picker) and two location methods ("Hypoellipse" and "NonLinLoc" codes) is analysed by com- paring the automatically determined hypocentral coordinates with reference ones. Reference loca- tions are computed by the "Hypoellipse" code considering manually revised data and tested us- ing quarry blasts. The comparison is made on a

We present a thermo-rheological study of the Adriatic crust in the central Po plain (Northern Italy), which records the convergence of the Alpine and Apennine external fronts. The present thermal regime of the crust is inferred from geological and geophysical data from oil exploration. A set of temperature data from 37 deep boreholes (bottom hole, drill stem, and production test temperatures) is used to estimate undisturbed formation temperatures down to 6-7 km of depth. Best quality data are used to estimate upper crustal geotherms, which are subdivided into four groups taking into considerations the following factors: i) presence/absence of relevant fluid circulation, ii) conductive thermal refraction, iii) recent sedimentation, and iv) other disturbing tectonothermal processes (e.g., recent tectonics). Assuming average corrections for temperature data affected by recent sedimentation effects, geotherms fall within the same range and provide a homogeneous thermal signal. Temperature measurements in the upper ~7 km are used to constrain a 1-D thermal model at the crustal scale. The best fitting geotherm gives a thermal gradient of ~23 ± 5 mK m-1 (over 7 km of depth), a surface heat flow of ~46 ± 9 mW m-2, and an estimated Moho temperature of 620 ± 80 °C. Using the estimated crustal structure and composition and the best-fitting geotherm, a representative strength envelope is obtained. For hydrostatic and supra-hydrostatic pore pressures, the calculated total crustal strength of this sector of the Adria microplate (not including the upper mantle contribution) is in the 1.8-2.5 TN m-1 range. Considering also the lithospheric mantle contribution, the total lithospheric strength is estimated to be between 23 (wet peridotite) and 39 (dry peridotite) TN m-1.

A revised seismic catalogue (1994–2007) for the central–eastern Alps (N Italy) is presented. 396 earthquake relocations, for local magnitudes in the 1.2–5.3 range, are performed using a 3D crustal velocity structure and probabilistic locations. The location procedure is validated by computing a set of 41 quarry shot solutions and all the results, both about shots and seismic events, are compared with those obtained using the routine location procedure. Results are shown for five contiguous seismotectonic domains, as supported by geological and geophysical evidence (e.g., fault systems, crustal tomography, focal mechanisms types). Earthquake hypocentres are mostly located in the upper crust (0–15 km of depth), in good agreement with thermo-rheological models about the brittle–ductile transitions (8–9 km of depth) and total crustal strengths (1.0–2.0 TN m − 1 ). Epicentres are clustered and/or aligned along present-day active geological structures. The proposed seismotectonic model shows dominant compression along the Giudicarie and Belluno–Bassano–Montello thrusts, with strain partitioning along the dominant right-lateral strike-slip faults of the Schio–Vicenza domain. The present-day deformation of the Southern Alps and the internal Alpine chain is compatible with Adria indentation and the related crustal stress distribution.

Online Material: Tables of information regarding the parameters used in the automatic picking procedure; figures illustrating the quality of picks. The vast volumes of seismic data being recorded by both permanent and temporary networks operating all over the world provide exciting opportunities for studying the Earth’s interior and earthquake source characteristics. As a result, the development of efficient computer algorithms and procedures capable of automatically extracting and processing such long streams of data is one of the most challenging issues facing modern seismological research. Valoroso et al. (2013) obtained an extraordinary degree of detail in the anatomy of the normal‐fault system of the l’Aquila earthquake after processing around 64,000 aftershocks (extracted, picked, and located) via an automated procedure. Spectral analysis of K‐NET and KiK‐net data in Japan was carried out by Oth et al. (2011) on the basis of more than 67,000 records analyzed via an automated procedure that included phase picking, earthquake location, and coda identification. The key elements of any automatic procedure devoted to exploiting the full potential of travel‐time‐based methods such as earthquake location and seismic tomography are (1) arrival‐time determination, (2) quality assessment, and (3) outlier detection. In recent decades, several new automatic picking algorithms have been developed, with the aim of processing large amounts of data for (near‐) real‐time seismic signal analysis. These algorithms are generally classified according to the adopted phase‐detection scheme: (1) short term average to long term average ratio (STA/LTA)‐based algorithms (Allen, 1978, 1982; Baer and Kradolfer, 1987; Lomax et al. , 2012), (2) autoregressive methods (Leonard and Kennet, 1999; Sleeman and van Eck, 1999; Leonard, 2000; Kuperkoch et al. , 2012), (3) Akaike information criterion (AIC; Akaike, 1974)‐based algorithms (Maeda, 1985; Turino et al. , 2010), (4) methods based on neural networks (Dai and MacBeth, 1995; Zhao and Takano, 1999; Gentili and Michelini, 2006 …

Structure and properties of the Adriatic crust were determined from local earthquake tomography around the Giudicarie fault zone (central-eastern Southern Alps, Italy). Tomographic results, based on well-suited 436 revised earthquakes (period 1994–2007), have a resolution comparable to the scale of regional geological domains and tectonic structures. The observed strong velocity anomalies correlate well with lithological variations corresponding to different geological domains (particularly magmatic complexes at depth) and with high fracturing and/or presence of fluids along active fault systems (South Giudicarie and Valsugana– Bassano del Grappa–Montello thrusts).

S U M M A R Y In this study, microseism recordings from a near coast seismic station and concurrent significant sea wave heights (H 1 3 ) are analysed to calibrate an empirical relation for predicting sea wave height in the Ligurian Sea. The study stems from the investigation of the damaging sea storms occurred in the Ligurian Sea between 2008 October and November. Analysing data collected in this time frame allows identification of two types of microseism signal, one associated to the local sea wave motion and one attributable to a remote source area. The former is dominated by frequencies greater than 0.2 Hz and the latter by frequencies between 0.07 and 0.14 Hz. Moreover, comparison of microseism spectrogram and significant sea wave heights reveals a strong correlation in that the spectral energy content of microseism results proportional to the sea wave height observed in the same time window. Hence, an extended data set including also observations from January to December 2011 is used to calibrate an empirical predictive relation for sea wave height whose functional form is a modified version of the classical definition of H 1 3 . By means of a Markov chain Monte Carlo algorithm we set up a procedure to investigate the inverse problem and to find a set of parameter values for predicting sea wave heights from microseism.

[1] This work presents seismic strain rate maps for the Western Alps and Northern Apennines (northern Italy) as derived from an earthquake catalog collecting both historical and instrumental data. Strain rates are calculated on the basis of the rate of seismic moment release using the Anderson method. Unlike previous applications, which determined the total strain rate associated with specific seismogenic sources, we have employed an innovative zoneless approach based on a spatially smoothed seismicity method. In addition, a Monte Carlo simulation procedure is applied to allow for uncertainty in the input data (e.g., magnitude to moment conversion, seismogenic thickness, maximum earthquake magnitude). Strain rate maps are developed by summing the moments of the earthquakes reported in the catalog and by using two different earthquake recurrence relations. Our results indicate that deformation rates are quite high, ranging from about 2 to 12 × 10−9 yr−1 in the Northern Apennines and from 0.5 to 6 × 10−9 yr−1 in the Western Alps. These values, however, are ∼1 order less than those derived from Global Positioning System measurements, suggesting that a portion of the recent deformation in northwestern Italy is related to aseismic processes. The discrepancies between seismic and geodetic strain rates may also indicate that the record of seismicity may not provide a sufficient time window for assessment of secular rates of moment release (or secular deformation rates) and rates of recurrence of large magnitude earthquakes in the study area.

We investigate the P wave velocity structure and the Vp/Vs ratio beneath the Italian peninsula down to 100 and 60 km depth respectively by seismic travel time tomography. We invert data provided by the International Seismological Centre (ISC) (1997–2005), making use of some alternative strategies for the travel time approach in a well constrained and worldwide adopted code (SIMULPS). Resolution for the different layers is discussed and sensitivity analyses are performed through test inversions to explore the resolution characteristics of the model at different spatial scales. The resulting tomographic images provide a detailed sketch of the P wave anomalies, clearly showing, among the other features, the shape of the Ivrea body in the Western Alps, the upwelling of the oceanic crust in the Ligurian Sea and the slab under the Calabrian arc. They are less informative for the Vp/Vs ratio. Nevertheless, some features are very interesting and deserve further investigation like the anomalous decrease of the Vp/Vs ratio under the Ligurian Sea or the variations of the Vp/Vs ratio calculated in the first 10 km depth of the Apenninic region with respect to the lower values of the Alpine region at the same depth. The tomographic cross sections reveal a continuous superposition of two kinds of crusts (transitional over Adriatic) all along the peninsula but do not show any slab, intended as a clear, vertical downgoing high velocity material in either the northern or central Apennines.

Seismotectonic studies concern themselves with understanding the distribution of earthquakes in space, time, size and style. Therefore, the better these parameters are known, the most correct the association of any seismic event with the faulting structure that caused it will result. The use of accurate location methods is especially required when dealing with very complex areas, where several faulting systems or relatively small seismogenic structures exist. In fact, even though routinely determined epicentres are capable of revealing the rough picture of the seismicity, they are not suitable for studies of the fine structure of the causative fault, as their location uncertainties are often larger than the source dimension itself. In this work the probabilistic approach of the “Non Linear Localization” has been used to compute precise locations for earthquakes occurred in the last twenty years nearby the Saorge–Taggia line, a complex fault system situated in Western Liguria, close to the border between Italy and France. Together with the Breil–Sospel–Monaco and the Peille–Laghet faults, this line is responsible for the seismic activity of the area. The seismotectonic study is completed through a local tomographic study and the analysis of the focal mechanisms computed for an enlarged area. The results show that the seismicity associated with this fault system is confined within the first 10 km depth. Many clusters of seismic events are identified along the Saorge–Taggia line. The existence of a not previously mapped branch perpendicular to the Saorge–Taggia line is also recognized. Although its position may suggest it to be the continuation of the Breil–Sospel–Monaco fault system towards NE, our finding would rather suggest no association with the fault. The overall results confirm the complexity of the area; in particular the hypothesis that the Saorge–Taggia system may represent the eastward limit of a subalpine crustal block comprised within the Nice Arc, the named fault and a thrust front which is supposed to be located 20 km offshore find a confirm in the shallow depth of the seismic events. In addition we propose that the western limit of the block, located along the Nice arc, could be instead shifted where the Peille–Laghet fault lays.