Space- and Time-Dependent Probabilities for Earthquake Fault Systems from Numerical Simulations: Feasibility Study and First Results

Abstract

Abstract-In weather forecasting, current and past observational data are routinely assimilated into numerical simulations to produce ensemble forecasts of future events in a process termed ''model steering''. Here we describe a similar approach that is motivated by analyses of previous forecasts of the Working Group on California Earthquake Probabilities (WGCEP). Our approach is adapted to the problem of earthquake forecasting using topologically realistic numerical simulations for the strike-slip fault system in California. By systematically comparing simulation data to observed paleoseismic data, a series of spatial probability density functions (PDFs) can be computed that describe the probable locations of future large earthquakes. We develop this approach and show examples of PDFs associated with magnitude M [ 6.5 and M [ 7.0 earthquakes in California.

Complex Earthquake Cycle Simulations Using a Two-Degree-of-Freedom Spring-Block Model with a Rate- and State-Friction Law

“…However, it is still difficult to predict large earthquakes precisely, due to their complex patterns of occurrence. The recurrence times and rupture areas are variable, due to interactions between fault segments, as demonstrated by numerical simulations (WARD 1996;RUNDLE et al 2006;KATO et al 2007;AALSBURG et al 2010).…”

No Evidence of Magnitude Clustering in an Aftershock Sequence of Nano- and Picoseismicity

“…To this end, the Omori law and other empirical observations including the Gutenberg-Richter (GR) law have been used to formulate stochastic models of seismicity [13][14][15][16]. Despite some success forecasting aftershock activity and seismicity rates [17][18][19][20][21], we are, however, far away from reliably predicting the occurrence of large earthquakes ahead of time [22,23], which potentially could even be an unreachable goal [24].…”

Paleoseismology

“…Therefore, paleoseismic data have been influential in the development and testing of models that describe fault behavior over multiple rupture cycles (e.g., Rundle et al, 2006;Smith and Sandwell, 2006) and in forecasting earthquakes (e.g., Rundle et al, 2005;Van Aalsburg et al, 2010). Therefore, paleoseismic data have been influential in the development and testing of models that describe fault behavior over multiple rupture cycles (e.g., Rundle et al, 2006;Smith and Sandwell, 2006) and in forecasting earthquakes (e.g., Rundle et al, 2005;Van Aalsburg et al, 2010).…”