IAG-IASPEI 2017

講演情報

Oral

IASPEI Symposia » S13. Earthquake source mechanics

[S13-3] Earthquake source mechanics III

2017年8月3日(木) 13:30 〜 15:00 Main Hall (Kobe International Conference Center 1F)

Chairs: Yuji Yagi (Graduate School of Life and Environmental Sciences) , Satoshi Ide (University of Tokyo)

13:30 〜 13:45

[S13-3-01] Tidal controls on earthquake size-frequency statistics

Satoshi Ide1, Suguru Yabe1, Yoshiyuki Tanaka2 (1.Dept. EPS, The University of Tokyo, Tokyo, Japan, 2.ERI, The University of Tokyo, Tokyo, Japan)

The possibility that tidal stresses can trigger earthquakes is a long-standing issue in seismology. Except in some special cases, a causal relationship between seismicity and the phase of tidal stress has been rejected on the basis of studies using many small events. However, recently discovered deep tectonic tremors are highly sensitive to tidal stress levels, with the relationship being governed by a nonlinear law according to which the tremor rate increases exponentially with increasing stress; thus, slow deformation (and the probability of earthquakes) may be enhanced during periods of large tidal stress. Here, we show the influence of tidal stress on seismicity by calculating histories of tidal shear stress during the 2-week period before earthquakes. Very large earthquakes tend to occur near the time of maximum tidal stress, but this tendency is not obvious for small earthquakes. Rather, we found that tidal stress controls the earthquake size-frequency statistics; i.e., the fraction of large events increases (i.e. the b-value of the Gutenberg-Richter relation decreases) as the tidal shear stress increases. This correlation is apparent in data from the global catalog and in relatively homogeneous regional catalogues of earthquakes in Japan. The relationship is also reasonable, considering the well-known relationship between stress and the b-value. Our findings indicate that the probability of a tiny rock failure expanding to a gigantic rupture increases with increasing tidal stress levels. This finding has clear implications for probabilistic earthquake forecasting.