USGSでポスドクをされている Margarita Segouさんのセミナーを下記のように行います。
日時：２０１５年３月１８日（水）15:00 – 16:30
会場：京都大学宇治キャンパス 地震予知研究センター新館セミナー室(200)
タイトル：Forecasting our Earthquake Predictability
*Abstract:*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. 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). My recent work provides evidence that physics-based earthquake forecast models, combining fault aging laws and the static stress triggering hypothesis, can accurately predict (80%) transient seismicity rates. 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.
In this seminar I focus on recent development on physics-based earthquake models using worldwide examples, including pre-Tohoku and post-Tohoku aftershock sequences in Japan, 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 expect higher information gains in the near future?/ and, /How these forecast models could be most effective in Japan?/
USGSでのセミナーが下記にあります。
http://earthquake.usgs.gov/regional/nca/seminars/2012-05-23/
Title: Forecasting our Earthquake Predictability
Lecturer: Dr. Margarita Segou, USGS
Date: March 18, 15:00-16:30
Place: Room 200, Research Center for Earthquake Prediction , Kyoto University Uji Campus
*Abstract:*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. 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). My recent work provides evidence that physics-based earthquake forecast models, combining fault aging laws and the static stress triggering hypothesis, can accurately predict (80%) transient seismicity rates. 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.
In this seminar I focus on recent development on physics-based earthquake models using worldwide examples, including pre-Tohoku and post-Tohoku aftershock sequences in Japan, 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 expect higher information gains in the near future?/ and, /How these forecast models could be most effective in Japan?/
© Research Center for Earthquake Hazards.
© Research Center for Earthquake Hazards.
