第47回統計地震学セミナー / The 47th Statistical Seismology Seminar

The last decade dense seismological networks around the world provide the opportunity to study more aftershock sequences in seismically active areas across the world such as California (San Andreas Fault), Japan, New Zealand (Canterbury Fault, Christchurch) and continental rift systems (Corinth Gulf, Greece). The importance behind that is evident; the 2008 M7.9 Sichuan event continues having catastrophic aftershocks (2013 Lushan M6.6) after five years. The above provide the necessary motivation for geophysicists to develop short and long-term earthquake forecasts for providing to scientists and the public authoritative information on seismic hazard and answer ultimately the question When the next big earthquake will occur. Static and dynamic triggering are often described as the two primary mechanisms for earthquake clustering in time and space. Recent studies have provided evidence that physics-based earthquake forecast models, combining fault aging laws and the static stress triggering hypothesis, can accurately predict (80%) transient seismicity rates. Static triggering plays an important role in spatial clustering at distances 2-3 rupture lengths away from the seismic source whereas dynamic triggering studies usually focus on larger distances (>1000 km). But how dependent are our calculations on our incomplete knowledge of the ambient stress of a region? What are the implications behind the time dependent fault behavior? The last two questions are the key for reducing the uncertainties of physical forecast models. Quite often the development of such quantitative and testable models is followed by extensive statistical performance evaluation, which is critical for understanding their merits and pitfalls.

In this seminar I focus on recent development on physics-based earthquake models using worldwide examples and how they compare with statistical models. Furthermore, I discuss how we can reduce their uncertainties and sketch the future of our scientific predictability. Is it possible to hope on higher information gains in the near future? and, How these forecast models could be most effective in Japan?