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Simone Mancini

Publications and source records attributed to Simone Mancini.

3 recordsLinked to original sources

On the use of high-resolution and deep-learning seismic catalogs for short-term earthquake forecasts: Potential benefits and current limitations

Enhanced earthquake catalogs provide detailed images of evolving seismic sequences. Currently, these data sets take some time to be released but will soon become available in real time. Here, we explore whether and how enhanced seismic catalogs feeding into established short-term earthquake forecasting protocols may result in higher predictive skill. We consider three enhanced catalogs for the 2016–2017 Central Italy sequence, featuring a bulk completeness lower by at least two magnitude units compared to the real-time catalog and an improved hypocentral resolution. We use them to inform a set of physical Coulomb Rate-and-State (CRS) and statistical Epidemic-Type Aftershock Sequence (ETAS) models to forecast the space-time occurrence of M3+ events during the first 6 months of the sequence. We track model performance using standard likelihood-based metrics and compare their skill against the best-performing CRS and ETAS models among those developed with the real-time catalog. We find that while the incorporation of the triggering contributions from new small magnitude detections of the enhanced catalogs is beneficial for both types of forecasts, these models do not significantly outperform their respective near real-time benchmarks. To explore the reasons behind this result, we perform targeted sensitivity tests that show how (a) the typical spatial discretizations of forecast experiments ( 2 km) hamper the ability of models to capture highly localized secondary triggering patterns and (b) differences in earthquake parameters (i.e., magnitude and hypocenters) reported in different catalogs can affect forecast evaluation. These findings will contribute toward improving forecast model design and evaluation strategies for next-generation seismic catalogs.

Journal of Geophysical Research--Solid Earth

Crustal permeability changes observed from seismic attenuation: Impacts on multi-mainshock sequences

We use amplitude ratios from narrowband-filtered earthquake seismograms to measure variations of seismic attenuation over time, providing unique insights into the dynamic state of stress in the Earth’s crust at depth. Our dataset from earthquakes of the 2016-2017 Central Apennines sequence allows us to obtain high-resolution time histories of seismic attenuation (frequency band: 0.5-30 Hz) characterized by strong earthquake dilatation-induced fluctuations at seismogenic depths, caused by the cumulative elastic stress drop after the sequence, as well as damage-induced ones at shallow depths caused by energetic surface waves. Cumulative stress drop causes negative dilatation, reduced permeability, and seismic attenuation, whereas strong-motion surface waves produce an increase in crack density, and so in permeability and seismic attenuation. In the aftermath of the main shocks of the sequence, we show that the M ≥ 3.5 earthquake occurrence vs. time and distance is consistent with fluid diffusion: diffusion signatures are associated with changes in seismic attenuation during the first days of the Amatrice, Visso-Norcia, and Capitignano sub-sequences. We hypothesize that coseismic permeability changes create fluid diffusion pathways that are at least partly responsible for triggering multi-mainshock seismic sequences. Here we show that anelastic seismic attenuation fluctuates coherently with our hypothesis.

Frontiers in Earth Science

The predictive skills of elastic Coulomb rate-and-state aftershock forecasts during the 2019 Ridgecrest, California, earthquake sequence

Operational earthquake forecasting protocols commonly use statistical models for their recognized ease of implementation and robustness in describing the short-term spatiotemporal patterns of triggered seismicity. However, recent advances on physics-based aftershock forecasting reveal comparable performance to the standard statistical counterparts with significantly improved predictive skills when fault and stress field heterogeneities are considered. Here, we perform a pseudo-prospective forecasting experiment during the first month of the 2019 Ridgecrest (California) earthquake sequence. We develop seven Coulomb rate-and-state models that couple static stress change estimates with continuum mechanics expressed by the rate-and-state friction laws. Our model parametrization supports a gradually increasing complexity; we start from a preliminary model implementation with simplified slip distributions and spatially homogeneous receiver faults to reach an enhanced one featuring optimized fault constitutive parameters, finite-fault slip models, secondary triggering effects, and spatially heterogenous planes informed by pre-existing ruptures. The data-rich environment of Southern California allows us to test whether incorporating data collected in near real-time during an unfolding earthquake sequence boosts our predictive power. We assess the absolute and relative performance of the forecasts by means of statistical tests used within the Collaboratory for the Study of Earthquake Predictability (CSEP) and compare their skills against a standard benchmark ETAS model for the short (24 hours after the two Ridgecrest mainshocks) and intermediate-term (one month). Stress-based forecasts expect heightened rates along the whole near-fault region and increased expected seismicity rates in Central Garlock Fault. Our comparative model evaluation supports that faulting heterogeneities coupled with secondary triggering effects are the most critical success components behind physics-based forecasts, but also underlines the importance of model updates incorporating near real-time available aftershock data reaching better performance than ETAS models. We explore the physical basis behind our results by investigating the localized shut down of pre-existing normal faults in the Ridgecrest near-source area.

California