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タイトル: Automatic hypocenter determination with the IPFx method for the 2018 Hualien earthquake sequence
著者: Yamada, Masumi
Chen, Da-Yi
著者名の別形: 山田, 真澄
キーワード: IPFx method
2018 Hualien earthquake
Automatic hypocenter determination
Earthquake early warning
発行日: 16-Jun-2022
出版者: Springer Nature
誌名: Terrestrial, Atmospheric and Oceanic Sciences
巻: 33
論文番号: 18
抄録: The extended integrated particle filter (IPFx) method is an automatic source determination algorithm designed for the Japanese earthquake early warning (EEW) system. The method improved earthquake source determination during active seismicity by incorporating the smart phase association scheme. We applied this method to the 2018 Hualien earthquake sequence and evaluated its performance by comparing it to the manual catalog. We used 1-month continuous waveforms from February 2018 at 170 stations. Owing to the higher noise level, we improved the phase association algorithm to avoid noise contamination. Out of 127 earthquakes with a seismic intensity ≥ 4, 105 were successfully detected in one month, of which 103 had good accuracy with a location error of < 30 km. The detectability of earthquakes decreased immediately following large events. The IPFx method showed good performance in detecting earthquakes with seismic intensity ≥ 4 during the 2018 Hualien earthquake sequence. The method was also applied to the 1-day continuous data on April 18, 2021, and detected 14 earthquakes with a magnitude ~ 2 that were not on the manual catalog. Currently, the Central Weather Bureau in Taiwan uses the effective epicenter method to locate earthquakes for the EEW system. However, source determination for offshore events is difficult as most of the stations are on land. We expect the IPFx method to provide better location estimates for offshore earthquakes and during the period of active seismicity. It also provides an earlier warning as it sends the first message when three stations are triggered. This new method can potentially improve the speed and accuracy of the Taiwanese EEW system.
著作権等: © The Author(s) 2022.
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
URI: http://hdl.handle.net/2433/282852
DOI(出版社版): 10.1007/s44195-022-00018-y
出現コレクション:学術雑誌掲載論文等

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