| Popis: |
Earthquakes are one of the most devastating natural disasters that plague society. Skilled, reliable earthquake forecasting remains the ultimate goal for seismologists. Using the detrended fluctuation analysis (DFA) and conditional probability (CP) methods we find that memory exists not only in inter-occurrence seismic records, but also in released energy as well as in the series of the number of events per unit time. Analysis of a stan- dard Epidemic Type Aftershock Sequences (ETAS) earthquake model indicates that the empirically observed earthquake memory can be reproduced only for a narrow range of model’s parameters. This finding, therefore provides tight constraints on the model’s parameters and can serve as a testbed for existing earthquake forecast- ing models. Furthermore, we show that by implementing DFA and CP results, the ETAS model can significantly improve the short term forecasting rate for the real (Italian) earthquake catalog. |
