A prominent feature of earthquakes is their empirical laws, including memory (clustering) in time and space. Several earthquake forecasting models, such as the epidemic-type aftershock sequence (ETAS) model, were developed based on these empirical laws. Yet, a recent study  showed that the ETAS model fails to reproduce the significant long-term memory characteristics found in real earthquake catalogs. Here we modify and generalize the ETAS model to include short- and long-term triggering mechanisms, to account for the short- and long-time memory (exponents) discovered in the data. Our generalized ETAS model accurately reproduces the short- and long-term/distance memory observed in the Italian and Southern Californian earthquake catalogs. The revised ETAS model is also found to improve earthquake forecasting after large shocks.
Bibliographical noteFunding Information:
We thank the Israel Science Foundation (Grants No. 189/19), the joint China-Israel Science Foundation (Grants No. 3132/19), ONR, BSF-NSF (Grant No. 2019740), the EU H2020 project RISE, the BIU Center for Research in Applied Cryptography and Cyber Security, and DTRA (Grants No. HDTRA-1-19-1-0016) for financial support. The Italian earthquake catalog is provided by reference  and available on request from the authors. The Southern California catalog can be downloaded from the SCEDC (https://scedc. caltech.edu/research-tools/alt-2011-dd-hauksson-yang-shearer.html) .
© 2021 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.
- ETAS model
- earthquake memory