Seismic risk mitigation at Campi Flegrei in volcanic unrest.

Campi Flegrei is a densely populated volcanic area in Italy. Its inner caldera periodically experiences uplift and subsidence, known as bradyseism, also accompanied by seismic activity. In the last decade, with uplift rates up to 2 cm/month, about nine-thousand earthquakes were recorded.

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.

Revealing the spatiotemporal complexity of the magnitude distribution and b-value during an earthquake sequence.

The Magnitude-Frequency-Distribution (MFD) of earthquakes is typically modeled with the (tapered) Gutenberg-Richter relation. The main parameter of this relation, the b-value, controls the relative rate of small and large earthquakes. Resolving spatiotemporal variations of the b-value is critical to understanding the earthquake occurrence process and improving earthquake forecasting.

Possible origin of memory in earthquakes: Real catalogs and an epidemic-type aftershock sequence model.

Earthquakes are one of the most devastating natural disasters that plague society. Skilled, reliable earthquake forecasting remains the ultimate goal for seismologists. Using the detrended fluctuation analysis (DFA) and conditional probability (CP) methods, we find that memory exists not only in interoccurrence seismic records but also in released energy as well as in the series of the number of events per unit time.

Earthquake forecasting during the complex Amatrice-Norcia seismic sequence.

Earthquake forecasting is the ultimate challenge for seismologists, because it condenses the scientific knowledge about the earthquake occurrence process, and it is an essential component of any sound risk mitigation planning. It is commonly assumed that, in the short term, trustworthy earthquake forecasts are possible only for typical aftershock sequences, where the largest shock is followed by many smaller earthquakes that decay with time according to the Omori power law. We show that the current Italian operational earthquake forecasting system issued statistically reliable and skillful space-time-magnitude forecasts of the largest earthquakes during the complex 2016-2017 Amatrice-Norcia sequence, which is characterized by several bursts of seismicity and a significant deviation from the Omori law.

Mechanical origin of aftershocks.

Aftershocks are the most striking evidence of earthquake interactions and the physical mechanisms at the origin of their occurrence are still intensively debated. Novel insights stem from recent results on the influence of the faulting style on the aftershock organisation in magnitude and time. Our study shows that the size of the aftershock zone depends on the fault geometry.

On the earthquake predictability of fault interaction models.

Space-time clustering is the most striking departure of large earthquakes occurrence process from randomness. These clusters are usually described ex-post by a physics-based model in which earthquakes are triggered by Coulomb stress changes induced by other surrounding earthquakes. Notwithstanding the popularity of this kind of modeling, its ex-ante skill in terms of earthquake predictability gain is still unknown.

Testing for ontological errors in probabilistic forecasting models of natural systems.

Probabilistic forecasting models describe the aleatory variability of natural systems as well as our epistemic uncertainty about how the systems work. Testing a model against observations exposes ontological errors in the representation of a system and its uncertainties. We clarify several conceptual issues regarding the testing of probabilistic forecasting models for ontological errors: the ambiguity of the aleatory/epistemic dichotomy, the quantification of uncertainties as degrees of belief, the interplay between Bayesian and frequentist methods, and the scientific pathway for capturing predictability.

Spatial organization of foreshocks as a tool to forecast large earthquakes.

An increase in the number of smaller magnitude events, retrospectively named foreshocks, is often observed before large earthquakes. We show that the linear density probability of earthquakes occurring before and after small or intermediate mainshocks displays a symmetrical behavior, indicating that the size of the area fractured during the mainshock is encoded in the foreshock spatial organization. This observation can be used to discriminate spatial clustering due to foreshocks from the one induced by aftershocks and is implemented in an alarm-based model to forecast m > 6 earthquakes.