Improving the Foreshock Traffic Light Systems for Real-Time Discrimination Between Foreshocks and Aftershocks
Abstract After a moderate-to-large earthquake, Civil Protection, scientists, the population, and decision makers immediately ask: “Was this the mainshock, or is a bigger event yet to come?” According to the current state of the art, the probability that an even larger event will occur within five days and 10 km after a moderate earthquake is typically 5%. Recent work proposes that a more specific answer to this question is possible (Gulia and Wiemer, 2019). The method allows real-time discrimination between foreshocks and aftershocks in well-monitored regions. However, so far, some expert judgments are required to adapt the technique to the case-specific data, such as defining the overall magnitude of completeness and the duration of the short-term aftershock incompleteness. Here, we introduce and retrospectively test an improved version of the foreshock traffic light system (FTLS) approach that successfully overcomes the aforementioned limits using the b-positive estimator (van der Elst, 2021). With these improvements, an FTLS assessment can be fully automated as early as one hour after an M ≥6 event without requiring expert judgments. We also test the updated approach on six additional sequences; the results align with the FTLS hypothesis.
Authors
- Stefan Wiemer (ORCID: https://orcid.org/0000-0002-4919-3283)
- Gianfranco Vannucci (ORCID: https://orcid.org/0000-0003-0918-0784)
- Bogdan Enescu (ORCID: https://orcid.org/0000-0003-2153-0097)
- Emanuele Biondini (ORCID: https://orcid.org/0000-0003-2305-9534)
- Laura Gulia (ORCID: https://orcid.org/0000-0002-1474-230X)
Institutions
- Kyoto University (JP)
- Istituto Nazionale di Geofisica e Vulcanologia (IT)
- ETH Zurich (CH)
- Institutul National de Cercetare si Dezvoltare pentru Fizica Pamantului (RO)
- University of Bologna (IT)
Publication Details
- Journal
- Seismological Research Letters
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1785/0220240163
- Citations
- 11
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.92