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ABSTRACT Variants of the Epidemic‐Type Aftershock Sequence (ETAS) and Short‐Term Earthquake Probabilities (STEP) models have been used for earthquake forecasting and are entered as forecast models in the purely prospective Collaboratory Study for Earthquake Predictability (CSEP) experiment. Previous analyses have suggested the ETAS model offered the best forecast skill for the first several years of CSEP. Here, we evaluate the prospective forecasting ability of the ETAS and STEP one‐day forecast models for California from 2013 to 2017, using super‐thinned residuals and Voronoi residuals. We find very comparable performance of the two models, with slightly superior performance of the STEP model compared to ETAS according to most metrics. 

One of most universal statistical properties of earthquakes is the tendency to cluster in space and time. Yet while clustering is pervasive, individual earthquake sequences can vary markedly in duration, spatial extent, and time evolution. In July 2014, a prolific earthquake sequence initiated within the Sheldon Wildlife Refuge in northwest Nevada, USA. The sequence produced 26 M4 earthquakes and several hundred M3s, with no clear mainshock or obvious driving force. Here we combine a suite of seismological analysis techniques to better characterize this unusual earthquake sequence. High-precision relocations reveal a clear, east dipping normal fault as the dominant structure that intersects with a secondary, subvertical cross fault. Seismicity occurs in burst of activity along these two structures before eventually transitioning to shallower structures to the east. Inversion of hundreds of moment tensors constrain the overall normal faulting stress regime. Source spectral analysis suggests that the stress drops and rupture properties of these events are typical for tectonic earthquakes in the western US. While regional station coverage is sparse in this remote study region, the timely installation of a temporary seismometer allows us to detect nearly 70,000 earthquakes over a 40-month time period when the seismic activity is highest. Such immense productivity is difficult to reconcile with current understanding of crustal deformation in the region and may be facilitated by local hydrothermal processes and earthquake triggering at the transitional intersection of subparallel fault systems. 

Abstract The development of new earthquake forecasting models is often motivated by one of the following complementary goals: to gain new insights into the governing physics and to produce improved forecasts quantified by objective metrics. Often, one comes at the cost of the other. Here, we propose a question-driven ensemble (QDE) modeling approach to address both goals. We first describe flexible epidemic-type aftershock sequence (ETAS) models in which we relax the assumptions of parametrically defined aftershock productivity and background earthquake rates during model calibration. Instead, both productivity and background rates are calibrated with data such that their variability is optimally represented by the model. Then we consider 64 QDE models in pseudoprospective forecasting experiments for southern California and Italy. QDE models are constructed by combining model parameters of different ingredient models, in which the rules for how to combine parameters are defined by questions about the future seismicity. The QDE models can be interpreted as models that address different questions with different ingredient models. We find that certain models best address the same issues in both regions, and that QDE models can substantially outperform the standard ETAS and all ingredient models. The best performing QDE model is obtained through the combination of models allowing flexible background seismicity and flexible aftershock productivity, respectively, in which the former parameterizes the spatial distribution of background earthquakes and the partitioning of seismicity into background events and aftershocks, and the latter is used to parameterize the spatiotemporal occurrence of aftershocks.