板内地震
地质学
地震学
厚板
地幔(地质学)
结壳
俯冲
大地测量学
地球物理学
构造学
作者
Ritsuko S. Matsu’ura,Hiroto Tanaka,Mitsuko Furumura,T Takahama,Akemi Noda
摘要
ABSTRACT A new equation for predicting Japanese instrumental seismic intensities at arbitrary surface sites in Japan for Mw 5.4–8.7 and distances ranging from 10 to 1000 km was derived from approximately 30,000 observed intensities for various types of earthquakes. The equation incorporates the differences in the subsurface characteristics immediately beneath each site using VS30. The equation can also predict the abnormal intensities (which are indispensable in Japan) due to subducting slabs using the depth of the slab surface beneath each site from the Crustal Activity Modeling Program standard plate model. The prediction equation can be applied to five source types: Pacific Ocean plate (PAC) interplate, PAC intraplate, very shallow crustal, shallow (≤50 km) Philippine Sea plate (PHS) intraplate, and intermediate-depth (>50 km) PHS intraplate earthquakes. Although the equation is applicable at various magnitudes and distances, the standard deviations (σ) are 0.5–0.6, which are smaller than those of other equations with narrower distance ranges. Smaller σ values were achieved by the inversion of 29,837 Japanese instrumental seismic intensities from 68 selected earthquakes of five source types with a common site effect at each station. A deep Mw 7.9 earthquake that occurred at a depth of 680 km in 2015 near the Ogasawara Islands and subjected all of Japan to long-duration shaking due to waves propagating through the mantle was effectively employed to constrain the VS30 term of the equation. The equations for PAC interplate and very shallow earthquakes were validated by seven earthquakes that were not used for the inversion; the standard deviations for these earthquakes fell in the range of 0.41–0.53. The formula for very shallow crustal earthquakes is also able to predict the intensities of PHS interplate earthquakes. Hence, this equation is useful not only for engineering applications but also for historical seismology to distinguish the source types of ancient earthquakes.
科研通智能强力驱动
Strongly Powered by AbleSci AI