Assimilating Multicycle Rupture Simulations into Probabilistic Forecasting Models

Luis Vazquez, & Thomas H. Jordan

Published August 14, 2020, SCEC Contribution #10557, 2020 SCEC Annual Meeting Poster #093 (PDF)

A general problem in earthquake forecasting is how to assimilate deterministic physical simulations into probabilistic forecasting models. Here we focus on combining long earthquake catalogs (~ 10 6 yr) from the multi-cycle Rate-State Quake Simulator (RSQSim) of Dieterich & Richards-Dinger (2010) with the time-independent Uniform California Earthquake Rupture Forecast Version 3 (UCERF3) of Field et al. (2014). Rupture statistics are compared by establishing a mapping of RSQSim ruptures into the UCERF3 rupture set, which we optimize to preserve the seismic moment. Our Bayesian approach uses the UCERF3 logic tree to construct a prior distribution of earthquake rates, which we update using an RSQSim catalog. We model the catalog as a time-independent Poisson process and adopt a multi-variate gamma distribution as the conjugate prior. We assess the efficacy of the updating schemes by logarithmic scoring of the mean forecasts against independent RSQSim catalogs, and we show how to employ the calibrated time-independent forecasts as prior distributions in the development of time-dependent forecasts that are consistent with the RSQSim event statistics.

Citation
Vazquez, L., & Jordan, T. H. (2020, 08). Assimilating Multicycle Rupture Simulations into Probabilistic Forecasting Models. Poster Presentation at 2020 SCEC Annual Meeting.

Related Projects & Working Groups
Earthquake Forecasting and Predictability (EFP)