## Abstract

We present two models for estimating the probabilities of future earthquakes in California, to be tested in the Collaboratory for the Study of Earthquake Predictability (CSEP). The first is a time-independent model of adaptively smoothed seismicity that we modified from Helmstetter et al. (2007). The model provides five-year forecasts for earthquakes with magnitudes M >= 4.95. We show that large earthquakes tend to occur near the locations of small M >= 2 events, so that a high-resolution estimate of the spatial distribution of future large quakes is obtained from the locations of the numerous small events. We further assume a universal Gutenberg-Richter magnitude distribution. In retrospective tests, we show that a Poisson distribution does not fit the observed rate variability, in contrast to assumptions in current earthquake predictability experiments. We therefore issued forecasts using a better-fitting negative binomial distribution for the number of events. The second model is a time-dependent epidemic-type aftershock sequence (ETAS) model that we modified from Helmstetter et al. (2006) and that provides next-day forecasts for M >= 3.95. In this model, the forecasted rate is the sum of a background rate (proportional to the time-independent model rate) and of the expected rate of triggered events due to all prior earthquakes. Each earthquake triggers events with a rate that increases exponentially with its magnitude and decays in time according to the Omori-Utsu law. An isotropic kernel models the spatial density of aftershocks for small (M

Original language | English |
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Pages (from-to) | 1630-1648 |

Number of pages | 19 |

Journal | Bulletin of the Seismological Society of America |

Volume | 101 |

Issue number | 4 |

DOIs | |

Publication status | Published - Aug 2011 |

## Keywords

- AFTERSHOCK SEQUENCE MODEL
- POINT-PROCESS MODELS
- TRIGGERED SEISMICITY
- SOUTHERN CALIFORNIA
- MAGNITUDE
- CATALOGS
- PREDICTABILITY
- COMPLETENESS
- OCCURRENCES
- VARIABILITY