2021 Fiscal Year Final Research Report
Study on comprehensive probability forecast of large earthquake
Project/Area Number |
17H00727
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Research Category |
Grant-in-Aid for Scientific Research (A)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Statistical science
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Research Institution | The Institute of Statistical Mathematics |
Principal Investigator |
Ogata Yosihiko 統計数理研究所, 大学共同利用機関等の部局等, 名誉教授 (70000213)
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Project Period (FY) |
2017-04-01 – 2021-03-31
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Keywords | 時空間階層ベイズETASモデル / 確率予測 / 日本内陸部直下型地震の予測 / 関東直下の予測 / 確率利得の時空間応答関数 / 多項目複合確率予測 / オンライン予測 |
Outline of Final Research Achievements |
We established the prototype of multi-factor probability forecasting including spatio-temporal ETAS models. In particular, we constructed 2- and 3-dimensional spatio-temporal hierarchical Bayesian ETAS models for entire inland areas and the Tokyo metropolitan area, respectively. We were able to implement not only short-term forecasts for these areas but also long-term forecasts for inland damage earthquakes. We have obtained new statistical models for predicting the probability of an exceptionally larger earthquake within each earthquake group (foreshock probability), as well as we have obtained the real-time aftershock probability prediction that can provide the probability of a major earthquake chain. The ETAS-based "relative quiescence" of aftershock activity provides a spatio-temporal response function for the probability gain of a large subsequent earthquake in and around the vicinity of the main shock. These can now be implemented in online forecasting.
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Free Research Field |
統計地震学
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Academic Significance and Societal Importance of the Research Achievements |
地震の確率予測は社会的・工学的に多様な需要がある。地震発生の有無だけでなく、多様な想定シナリオごとの確率を付加する点で、緊急地震速報などの防災対策の高度化と社会的な災害損失の縮小へ貢献する。すなわち。防災関係筋や一般への情報発信において、多くの予測方式を考慮し試行実験をすることで、限られた種類だけの予測による偏りを避けることができる。特に、現時点までの政府地震本部の予測は活断層のみに基づく日本内陸部直下型地震の予測計画は大きく遅れており、関連する予測モデルの開発も殆ど進んでいない。ここで取り分け本研究の直下型地震予測モデル、特に関東直下の予測モデルは極めて重要であると考える。
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