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  • 1
    Publication Date: 2013-06-08
    Description: Among scoring methods employed to determine the performance of probability predictions, the log-likelihood method is the most common and useful. Although the log-likelihood score evaluates the comprehensive power of forecasts, we need to further evaluate the topical predictive powers of respective factors of seismicity, such as total numbers, occurrence times, locations, and magnitudes. For this purpose, we used the conditional- or marginal-likelihood function based on the observed events. Such topical scores reveal both strengths and weaknesses of a forecasting model and suggest the necessary improvements. We applied these scores to the probability forecasts during the devastating period of March 2011, during which the M w  9.0 Off the Pacific Coast of Tohoku-Oki earthquake struck. However, the evaluations did not suggest that any of the prospective forecast models were consistently satisfactory. Hence, we undertook two additional types of retrospective forecasting experiments to investigate the reasons, including the possibility that the seismicity rate pattern has changed after the M  9 mega-earthquake. In addition, our experiments revealed a technical difficulty in the one-day forecasting protocol adopted by the Collaboratory for the Study of Earthquake Predictability (CSEP). Results of further experiments lead us to recommend specific modifications to the CSEP protocols, leading to real-time forecasts and their evaluations.
    Print ISSN: 0037-1106
    Electronic ISSN: 1943-3573
    Topics: Geosciences , Physics
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  • 2
    Publication Date: 2018
    Description: 〈span〉〈div〉ABSTRACT〈/div〉We present a prototype of a real‐time system for automatic aftershock forecasting in Japan. Using real‐time seismicity data from the High Sensitivity Seismograph Network of the National Research Institute for Earth Science and Disaster Resilience (NIED), the system automatically generates rapid aftershock forecasts. The system starts to issue a time‐dependent forecast about 3 hrs after a mainshock and keeps updating it hourly. The forecast includes the estimated occurrence probabilities of earthquakes with magnitudes equal to or greater than a mainshock. Because an official procedure for aftershock forecasting in Japan does not provide aftershock probabilities in the first week after a large earthquake, this rapid response of the system after a mainshock can complement the existing procedure. We demonstrate the system’s performance for the cases of three inland earthquakes that occurred after the establishment of the system in April 2017. We also discuss the potential usefulness of our procedure for forecasting large earthquakes by conducting a retrospective forecast test for the 2016 Kumamoto foreshock–mainshock–aftershock sequence based on the real‐time seismicity data. Our monitoring system is useful for providing continuous timely information on time‐dependent aftershock probabilities.〈/span〉
    Print ISSN: 0895-0695
    Electronic ISSN: 1938-2057
    Topics: Geosciences
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  • 3
    Publication Date: 2018
    Description: 〈span〉〈div〉ABSTRACT〈/div〉We present a prototype of a real‐time system for automatic aftershock forecasting in Japan. Using real‐time seismicity data from the High Sensitivity Seismograph Network of the National Research Institute for Earth Science and Disaster Resilience (NIED), the system automatically generates rapid aftershock forecasts. The system starts to issue a time‐dependent forecast about 3 hrs after a mainshock and keeps updating it hourly. The forecast includes the estimated occurrence probabilities of earthquakes with magnitudes equal to or greater than a mainshock. Because an official procedure for aftershock forecasting in Japan does not provide aftershock probabilities in the first week after a large earthquake, this rapid response of the system after a mainshock can complement the existing procedure. We demonstrate the system’s performance for the cases of three inland earthquakes that occurred after the establishment of the system in April 2017. We also discuss the potential usefulness of our procedure for forecasting large earthquakes by conducting a retrospective forecast test for the 2016 Kumamoto foreshock–mainshock–aftershock sequence based on the real‐time seismicity data. Our monitoring system is useful for providing continuous timely information on time‐dependent aftershock probabilities.〈/span〉
    Print ISSN: 0895-0695
    Electronic ISSN: 1938-2057
    Topics: Geosciences
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  • 4
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    Seismological Society of America (SSA)
    Publication Date: 2017-06-28
    Description: Although the unconditional probability of a major earthquake in an area is extremely small, the probability can increase in the presence of anomalies that act as potential precursors. Precursor-like anomalies of only a single type may not sufficiently enhance the probability of a large earthquake, but the probability can be substantially increased using the multielements prediction formula when independent precursor-like anomalies of plural types are observed at the same time. Despite some illustrative applications for successful predictions in the late 1970s, this idea has seldom been applied for more than 40 yrs. This is because of the scarcity of remarkable anomalies preceding large earthquakes and a lack of extensive statistical studies on anomalies relative to large earthquakes, which prevents stable assessment estimates of probability gains. This article aims to provide an outlook for future study on these issues. I focus on evaluating the probability gains of a large earthquake using anomalies of seismic activity based on statistical diagnostic analysis. Specifically, I illustrate the evaluation methods with reference to seismic activity before the 2016 M  7.3 Kumamoto earthquakes. Furthermore, I discuss outlooks using similar and extended approaches in seismicity and other monitoring fields.
    Print ISSN: 0895-0695
    Electronic ISSN: 1938-2057
    Topics: Geosciences
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  • 5
    Publication Date: 2016-12-02
    Description: Real-time aftershock forecasting is important to reduce seismic risks after a damaging earthquake. The main challenge is to prepare forecasts based on the data available in real time, in which many events, including large ones, are missing and large hypocenter determination errors are present due to the automatic detection process of earthquakes before operator inspection and manual compilation. Despite its practical importance, the forecast skill of aftershocks based on such real-time data is still in a developmental stage. Here, we conduct a forecast test of large inland aftershock sequences in Japan using real-time data from the High Sensitivity Seismograph Network (Hi-net) automatic hypocenter catalog (Hi-net catalog), in which earthquakes are detected and determined automatically in real time. Employing the Omori–Utsu and Gutenberg–Richter models, we find that the proposed probability forecast estimated from the Hi-net catalog outperforms the generic model with fixed parameter values for the standard aftershock activity in Japan. Therefore, the real-time aftershock data from the Hi-net catalog can be effectively used to tailor forecast models to a target aftershock sequence. We also find that the probability forecast based on the Hi-net catalog is comparable in performance to the one based on the latest version of the manually compiled hypocenter catalog of the Japan Meteorological Agency when forecasting large aftershocks with M 〉3.95, despite the apparent inferiority of the automatically determined Hi-net catalog. These results demonstrate the practical usefulness of our forecasting procedure and the Hi-net automatic catalog for real-time aftershock forecasting in Japan. Online Material: Figures and tables showing detailed forecast results for all considered aftershock sequences and all forecast time frames.
    Print ISSN: 0037-1106
    Electronic ISSN: 1943-3573
    Topics: Geosciences , Physics
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