The Collaboratory for the Study of Earthquake Predictability (CSEP) aims to advance earthquake research by rigorous testing of earthquake forecast hypotheses. As in other disciplines, such hypothesis testing requires carefully designed experiments that meet certain requirements: they should be reproducible, fully transparent, and conducted within a controlled environment. CSEP has begun building infrastructure for conducting such rigorous earthquake forecasting experiments. Because past earthquake prediction experiments often have been controversial, CSEP testing centers-the secure, controlled computational environments within which experiments are conducted-have been designed to address particular issues related to transparency and exact reproducibility. Moreover, CSEP fosters collaboration among scientists developing earthquake forecast models, and the testing center concept allows multiple concurrent predictability experiments. In this paper, we share our perspective on computational earthquake science by presenting the design principles, organizational structure, and implementation details of CSEP testing centers. We describe ongoing forecast experiments in different testing regions and some of the * Correspondence to: implementation challenges encountered. We also describe the collaboration tools used for multinational software development and regional presentation websites. The need for common data exchange formats is discussed, as are potential avenues of future research within CSEP testing centers.

The Collaboratory for the Study of Earthquake Predictability (CSEP) is a global cyberinfrastructure for prospective evaluations of earthquake forecast models and prediction algorithms. CSEP's goals are to improve our understanding of earthquake predictability, advance forecasting model development, test key scientific hypotheses and their predictive power, and to improve seismic hazard assessments. Since its inception in California in 2007, the global CSEP collaboration has been conducting forecast experiments in a variety of tectonic settings and at the global scale, and now operates four testing centers on four continents to automatically and objectively evaluate models against prospective data. These experiments have provided a multitude of results that are informing operational earthquake forecasting systems and seismic hazard models, and they have provided new, and sometimes surprising, insights into the predictability of earthquakes and spurned model improvements. CSEP has also conducted pilot studies to evaluate ground-motion and hazard models. Here, we report on selected achievements from a decade of CSEP, and we present our priorities for future activities.

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The static Coulomb stress hypothesis is a widely known physical mechanism for earthquake triggering, and thus a prime candidate for physics-based Operational Earthquake Forecasting (OEF). However, the forecast skill of Coulomb-based seismicity models remains controversial, especially in comparison to empirical statistical models. A previous evaluation by the Collaboratory for the Study of Earthquake Predictability (CSEP) concluded that a suite of Coulomb-based seismicity models were less informative than empirical models during the aftershock sequence of the 1992 M w 7.3 Landers, California, earthquake. Recently, a new generation of Coulomb-based and Coulomb/statistical hybrid models were developed that account better for uncertainties and secondary stress sources. Here, we report on the performance of this new suite of models in comparison to empirical Epidemic Type Aftershock Sequences (ETAS) models during the 2010-2012 Canterbury, New Zealand, earthquake sequence. Comprising the 2010 M 7.1 Darfield earthquake and three subsequent M ≥ 5.9 shocks (including the February 2011 Christchurch earthquake), this sequence provides a wealth of data (394 M ≥ 3.95 shocks). We assessed models over multiple forecast horizons (1-day, 1-month and 1-year, updated after M ≥ 5.9 shocks). The results demonstrate substantial improvements in the Coulomb-based models. Purely physics-based models have a performance comparable to the ETAS model, and the two Coulomb/statistical hybrids perform better or as well as the corresponding statistical model. On the other hand, an ETAS model with anisotropic (fault-based) aftershock zones is just as informative. These results provide encouraging evidence for the predictive power of Coulomb-based models. To assist with model development, we identify discrepancies between forecasts and observations.