Public Release: 

Pilot model forecasts complex earthquake sequences with increased accuracy

Earthquake forecasting during the complex Amatrice-Norcia seismic sequence

American Association for the Advancement of Science


IMAGE: This is the village of Amatrice, completely destroyed by the central Italy seismic sequence of August-October 2016. view more 

Credit: Credit: Marco Anzidei

Pilot Model Forecasts Complex Earthquake Sequences with Increased Accuracy: Scientists have validated a recently developed earthquake forecasting model based on observations of a complex earthquake sequence in Italy, which they say may lead to better global risk mitigation planning. The ability to accurately forecast earthquakes has remained a challenge, especially for seismic events that do not follow typical mainshock-aftershock sequences (where one large earthquake is followed by many smaller aftershocks). To date, the most widely-accepted aftershock forecasting model, the Reasenberg and Jones (R&J) model, does not account for spatial information, and assumes that earthquakes exceeding a specific magnitude produce other earthquakes (in addition to the mainshock). Researchers therefore created new clustering models called the epidemic-type aftershock sequence (ETAS) and the short-term earthquake probability (STEP) models, yet their statistical reliability is relatively unknown. In an effort to gauge such models' statistical reliability, Warner Marzocchi and colleagues analyzed the weekly earthquake forecasts (including 40 target earthquakes) that occurred during the 2016-2017 Amatrice-Norcia sequence, to test the accuracy of the operational earthquake forecasting (OEF) system, a model that combines aspects of both the ETAS and STEP models. They found that, during this specific sequence, the OEF system provided statistically reliable forecasts when compared to the observed events of the largest earthquakes in central Italy. Marzocchi et al. argue that while the model is still in its pilot phase, the OEF's "brick-by-brick" approach could change the way scientists think about earthquake predictability, and ultimately provide seismologists with the tools they need to more accurately forecast earthquakes.


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