Evaluation of static stress change forecasting with prospective and blind tests

Mathematics – Probability

Scientific paper

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Earthquake Interaction, Forecasting And Prediction, Statistical Seismology, Dynamics: Seismotectonics

Scientific paper

Controversy and uncertainty about the physics of earthquake triggering mean that stress interactions are rarely incorporated into formal probabilistic forecasts. Statistical methods capture and predict complex features in short-term aftershock forecasts, but we ultimately want to understand the physics behind earthquake triggering. In this paper, we show two fully prospective static stress forecasts that have failed to reproduce spatial patterns of microseismicity. We demonstrate that these failures are not the result of complex main shock ruptures, but are instead caused in part by secondary triggering as deduced from an epidemic type aftershock sequence (ETAS) based stochastic declustering calculation. Prospective testing highlights difficulties in validating physics-based forecasts using microseismicity that can evolve rapidly in time and space. We therefore turn to a global catalogue of larger potentially triggered earthquakes. Prior study with this database found that M≥ 5 earthquakes after main shocks had a ratio of stress-increased to total number of events of 61 per cent, a barely significant result relative to the null value of 50 ± 4.6 per cent. The initial study included every catalogue event; our conclusions from the prospective tests cause us to revisit this choice and to conduct a systematic study of test-event selection. Free parameters include main shock and aftershock magnitude thresholds, as well as calculated probability that aftershocks are background events. We find a mean ratio of stress-increased to total number of events of ˜70 per cent across the test parameter range, with high values greater than 80 per cent. The most important parameter is triggered-event magnitude. We therefore conclude that the static stress change hypothesis is significantly more consistent with observation of large earthquake clustering than random chance.

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