The preparatory process of the 2023 Mw 7.8 Türkiye earthquake.

To verify the existence of a preparatory process for the 6 February 2023, Mw 7.8 Kahramanmaras earthquake, southern Türkiye, we analyze the temporal evolution of seismic catalog information for ~ 7500 earthquakes with magnitudes ML ≥ 1.5, which occurred along the main segments of the East Anatolian Fault (EAF) since 2014. We find the EAF fault segments showing different temporal patterns in the proportion of nonclustered seismicity, which we interpret as temporal variation of coupling. We also study the evolution of the b-value, fractal dimension and energy rate. These seismic features show for the Amanos and Pazarcik fault segments a long-term trend during the period 2020-2022 that might correspond to a quiescence phase. The latter is followed by a change in earthquakes clustering and characteristics that starts about eight months before the Mw 7.8 Kahramanmaras event. Our observations confirm the existence of a long-lasting preparatory phase for the 2023, Mw 7.8 Kahramanmaras earthquake and can stimulate new investigations on the East Anatolian Fault mechanic. Intercepting when a fault starts deviating from its steady behavior, might be the key for identifying the preparatory phase of large earthquakes and mitigate seismic risk.

On catching the preparatory phase of damaging earthquakes: an example from central Italy.

How, when and where large earthquakes are generated remain fundamental unsolved scientific questions. Intercepting when a fault system starts deviating from its steady behavior by monitoring the spatio-temporal evolution and dynamic source properties of micro-to-small earthquakes can have high potential as tool for identifying the preparatory phase of large earthquakes. We analyze the seismic activity that preceded the Mw 6.3 earthquake that hit L'Aquila on 6 April 2009 in central Italy, and we show that the seismic catalog information can be transformed into features allowing us to track in a statistical framework the spatio-temporal evolution of seismicity. Features associated to foreshocks show different patterns from the background seismicity that occurred in the previous years. We show that features ensemble allows to clearly capture the activation phase of the main event. Nonetheless, foreshocks share similar clustering properties of previous seismic sequences not culminating in large earthquakes, and thus generating questions on their use as potential precursor for earthquake sequences prone to evolve into catastrophic sequences.

A comprehensive suite of earthquake catalogues for the 2016-2017 Central Italy seismic sequence.

The protracted nature of the 2016-2017 central Italy seismic sequence, with multiple damaging earthquakes spaced over months, presented serious challenges for the duty seismologists and emergency managers as they assimilated the growing sequence to advise the local population. Uncertainty concerning where and when it was safe to occupy vulnerable structures highlighted the need for timely delivery of scientifically based understanding of the evolving hazard and risk. Seismic hazard assessment during complex sequences depends critically on up-to-date earthquake catalogues-i.e., data on locations, magnitudes, and activity of earthquakes-to characterize the ongoing seismicity and fuel earthquake forecasting models. Here we document six earthquake catalogues of this sequence that were developed using a variety of methods. The catalogues possess different levels of resolution and completeness resulting from progressive enhancements in the data availability, detection sensitivity, and hypocentral location accuracy. The catalogues range from real-time to advanced machine-learning procedures and highlight both the promises as well as the challenges of implementing advanced workflows in an operational environment.

Detecting long-lasting transients of earthquake activity on a fault system by monitoring apparent stress, ground motion and clustering.

Damaging earthquakes result from the evolution of stress in the brittle upper-crust, but the understanding of the mechanics of faulting cannot be achieved by only studying the large ones, which are rare. Considering a fault as a complex system, microearthquakes allow to set a benchmark in the system evolution. Here, we investigate the possibility to detect when a fault system starts deviating from a predefined benchmark behavior by monitoring the temporal and spatial variability of different micro-and-small magnitude earthquakes properties. We follow the temporal evolution of the apparent stress and of the event-specific residuals of ground shaking. Temporal and spatial clustering properties of microearthquakes are monitored as well. We focus on a fault system located in Southern Italy, where the Mw 6.9 Irpinia earthquake occurred in 1980. Following the temporal evolution of earthquakes parameters and their time-space distribution, we can identify two long-lasting phases in the seismicity patterns that are likely related to high pressure fluids in the shallow crust, which were otherwise impossible to decipher. Monitoring temporal and spatial variability of micro-to-small earthquakes source parameters at near fault observatories can have high potential as tool for providing us with new understanding of how the machine generating large earthquakes works.

Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability.

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 AlpArray Seismic Network: A Large-Scale European Experiment to Image the Alpine Orogen.

The AlpArray programme is a multinational, European consortium to advance our understanding of orogenesis and its relationship to mantle dynamics, plate reorganizations, surface processes and seismic hazard in the Alps-Apennines-Carpathians-Dinarides orogenic system. The AlpArray Seismic Network has been deployed with contributions from 36 institutions from 11 countries to map physical properties of the lithosphere and asthenosphere in 3D and thus to obtain new, high-resolution geophysical images of structures from the surface down to the base of the mantle transition zone. With over 600 broadband stations operated for 2 years, this seismic experiment is one of the largest simultaneously operated seismological networks in the academic domain, employing hexagonal coverage with station spacing at less than 52 km. This dense and regularly spaced experiment is made possible by the coordinated coeval deployment of temporary stations from numerous national pools, including ocean-bottom seismometers, which were funded by different national agencies. They combine with permanent networks, which also required the cooperation of many different operators. Together these stations ultimately fill coverage gaps. Following a short overview of previous large-scale seismological experiments in the Alpine region, we here present the goals, construction, deployment, characteristics and data management of the AlpArray Seismic Network, which will provide data that is expected to be unprecedented in quality to image the complex Alpine mountains at depth.