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A prominent feature of earthquakes is their empirical laws including memory(clustering) in time and space. Several earthquake forecasting models, like theEpidemicType Aftershock Sequence (ETAS) model, were developed based onearthquake empirical laws. Yet, a recent study showed that the ETAS model failsin reproducing significant long-term memory characteristics found in realearthquake catalogs. Here we modify and generalize the ETAS model to includeshort- and long-term triggering mechanisms, to account for the short- andlong-time memory (exponents) recently discovered in the data. Our generalizedETAS model reproduces accurately the short- and long-term/distance memoryobserved in the Italian and South California earthquake catalogs. The revisedETAS model is also found to significantly improve earthquake forecasting.

Improved Earthquake Forecasting Model Based on Long-term Memory in Earthquake