第46回統計地震学セミナー / The 46th Statistical Seismology Seminar

Date&Time
2015年1月27日(火)
/ 27 January, 2015 (Tuesday) 15:00 –

Admission Free,No Booking Necessary

Place
統計数理研究所 セミナー室4 D312B
/ Room D312B @ The Institute of Statistical Mathematics
区切り線
Speaker1
Takao Kumazawa
(The institute of statistical mathematics)
Title
"Predicting Offshore Swarm Rate by Volumetric Strain Changes in Izu Peninsula, Japan"
Abstract
The eastern offshore of Izu peninsula is one of the well known volcanic active regions in Japan, where magma intrusions have been observed several times since 1980s monitored by strain-meters located nearby. Major swarm activities have been synchronously associated with coseismic and preseismic significant sizes of volumetric strain changes (Earthquake Research Committee, 2010).  We investigated the background seismicity changes during these earthquake swarms using the nonstationary ETAS model (Kumazawa and Ogata, 2013, 2014), and have found the followings. The volumetric strain change data, modified by removing the effect of earth tides and precipitation as well as removing coseismic jumps, have much higher cross-correlations to the background rates of the ETAS model than to the whole seismicity rate change of the ETAS. Furthermore the strain changes precede the background seismicity by lag of about half a day. This relation suggests an enhanced prediction of earthquakes in this region using volumetric strain measurements. Thus we propose an extended ETAS model where the background seismicity rate is predicted by the time series of preceding volumetric strain changes. Our numerical results for Izu region show consistent outcomes throughout the major swarms.
区切り線
Speaker2
Wang Ting
(University of Otago, New Zealand)
Title
"Marked point process modeling with missing data in volcanic eruption records"
Abstract
Despite ongoing efforts to compile new data, eruption records, particularly those of earlier time periods, are pervasively incomplete. The probability of missing an ancient eruption is much higher than a recent eruption. We consider modeling both the times and sizes of the eruptions using a marked point process. We propose to model the marks (the sizes of the events) as having a time-varying distribution which takes the higher proportion of missing smaller events in earlier records into consideration. We then estimate the proportion of detected events over time based on the assumption that the most recent record is complete and that the record of eruptions with the largest size in the considered catalog is complete. With this information, we can then estimate the true intensity of volcanic eruptions.