The research community is rapidly moving towards the development of an earthquake forecast technology based on the use of complex, system-level earthquake fault system simulations. Using these topologically and dynamically realistic simulations, it is possible to develop ensemble forecasting methods similar to that used in weather and climate research. To effectively carry out such a program, one needs 1) a topologically realistic model to simulate the fault system; 2) data sets to constrain the model parameters through a systematic program of data assimilation; 3) a computational technology making use of modern paradigms of high performance and parallel computing systems; and 4) software to visualize and analyze the results. In particular, we focus attention on a new version of our code Virtual California (version 2001) in which we model all of the major strike slip faults in California, from the Mexico-California border to the Mendocino Triple Junction. Virtual California is a “backslip model”, meaning that the long term rate of slip on each fault segment in the model is matched to the observed rate. We use the historic data set of earthquakes larger than magnitude M > 6 to define the frictional properties of 650 fault segments (degrees of freedom) in the model. To compute the dynamics and the associated surface deformation, we use message passing as implemented in the MPICH standard distribution on a Beowulf clusters consisting of >10 cpus. We also will report results from implementing the code on significantly larger machines so that we can begin to examine much finer spatial scales of resolution, and to assess scaling properties of the code. We present results of simulations both as static images and as mpeg movies, so that the dynamical aspects of the computation can be assessed by the viewer. We compute a variety of statistics from the simulations, including magnitude-frequency relations, and compare these with data from real fault systems. Finally, we report recent results on use of Virtual California for probabilistic earthquake forecasting. These methods have the advantage that system-level fault interactions are explicitly included, as well as laboratory-based friction laws.

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