固体地球科学(S)
セッション小記号地震学
セッションIDS-SS05
タイトル和文統計および物理モデルに基づく地震活動予測
英文earthquake statistics, physics-based earthquake forecasting, and earthquake model testing
タイトル短縮名和文Under consideration
英文Under consideration
代表コンビーナ氏名和文鶴岡 弘
英文Hiroshi Tsuruoka
所属和文東京大学地震研究所
英文Earthquake Research Institute, Tokyo Univ.
共同コンビーナ 1氏名和文Schorlemmer Danijel
英文Danijel Schorlemmer
所属和文GFZ German Research Centre for Geosciences
英文GFZ German Research Centre for Geosciences
共同コンビーナ 2氏名和文平田 直
英文Naoshi Hirata
所属和文東京大学地震研究所
英文Earthquake Research Institute, the University of Tokyo
共同コンビーナ 3氏名和文Matt Gerstenberger
英文Matt Gerstenberger
所属和文GNS Science
英文GNS Science
共同コンビーナ 4氏名和文庄 建倉
英文Jiancang Zhuang
所属和文統計数理研究所
英文Institute of Statistical Mathematics
発表言語EE
スコープ和文
英文Earthquake statistics, providing major contributions to earthquake forecast and hazard models, is moving towards combinations with physics-based models. On one hand, Coulomb-based or rate and state-based models attempt to better describe stress and activity evolution for better forecasting seismicity rates, while global interseismic strain rates are combined with activity rates to improve long-term forecasts. On the other hand, hazard models are nowadays incorporating more earthquake statistics than simple Poissonian seismicity models for background seismicity. They are becoming increasingly time- dependent on various time scales beyond the established ETAS model. Statistics are included to describe temporal as well as spatial earthquake activity. The concept of earthquakes resembling a Poisson process has been challenged but still remains a cornerstone in seismic hazard analysis. Many studies have found evidence for earthquake preparations processes on various time scales. Statistical studies have indicated stress accumulations and asperity build-up over periods lasting from years to decades. Likewise, Coulomb-stress modeling revealed changes in stress states as results of previous earthquakes, moving affected areas closer to failure. These developments are creating new challenges for model testing. In this session we aim at exploring new opportunities these kind of models and model combinations offer for seismic hazard. Can hazard estimates be improved significantly by incorporating these models? Is their forecasting power sufficiently larger to warrant their inclusion? How well can future seismicity be forecast based on time-limited observations? Can the preparation process be modeled into seismic hazard? What are the limits of these models and how can we bridge the gap in the models between detailed short-term statistical observations and long-term geologic/geodetic observations? How can any of the models being tested rigorously?
発表方法口頭および（または）ポスターセッション
招待講演