Earthquake Forecasting and Geosciences Drive Cyberinfrastructure

Earthquakes exemplify emergent phenomena that arise from nonlinear, multiscale interactions within complex natural systems. The proper use of system-level models to make valid scientific inferences about earthquakes requires an iterative process of model formulation and verification, simulation-based predictions, validation against observations, and data assimilation to improve the models, which reinitiates the inference cycle at a higher level. We have developed a cyberfacility for seismic hazard analysis on NSF’s open-science computing resources, dubbed PetaSHA, that enables earthquake scientists to work outward on this “inference spiral” with an improved arsenal of data and model analysis tools. The PetaSHA computational platforms have been designed to vertically integrate the high-performance hardware, scalable software, and scientific expertise needed to execute the key computational pathways of seismic hazard analysis. These platforms are still evolving towards petascale capability, but they have already delivered major advances in earthquake system science: the time-dependent, uniform California earthquake rupture forecast (UCERF); high-resolution simulations of large earthquakes on the San Andreas fault system, including the TeraShake and ShakeOut simulations; the first full-3D waveform tomography of regional crustal structure; and a physics-based probabilistic seismic hazard model, CyberShake, that uses simulations to predict how source directivity, rupture complexity, and basin effects control strong ground motions. This presentation will highlight how the future demands of earthquake system science will continue to drive cyberinfrastructure requirements and high-performance computing.