4.7 Article

l1 Trend Filtering-Based Detection of Short-Term Slow Slip Events: Application to a GNSS Array in Southwest Japan

期刊

出版社

AMER GEOPHYSICAL UNION
DOI: 10.1029/2021JB023258

关键词

-

资金

  1. Japan Science and Technology Agency's Core Research for Evolutional Science and Technology (JST CREST) [JPMJCR1763]
  2. MEXT Project for Seismology toward Research Innovation with Data of Earthquake (STAR-E) [JPJ010217]
  3. Japan Society for the Promotion of Science (JSPS) [JP21H05205, JP21H05206, JP18K03796, JP21K03694, JP19K20222]

向作者/读者索取更多资源

A new method based on Global Navigation Satellite System (GNSS) data and sparse estimation technique was proposed to detect slow slip events (SSEs). This method achieved high accuracy in identifying candidates of event onsets and provided confidence values for the detections. By applying this method, researchers discovered new SSEs in the Nankai subduction zone and found an increase in low-frequency earthquake activity at the onsets of potential events.
The discovery of slow slip events (SSEs) based on the installation of dense geodetic observation networks has provided important clues to understanding the process of stress release and accumulation in subduction zones. Because SSEs with durations of days to weeks do not often result in sufficient displacements that can be visually inspected, refined automated detection methods are required to understand the occurrence of SSEs. In this study, we propose a new method based on which SSEs can be detected in observations derived by a Global Navigation Satellite System (GNSS) array by using l(1) trend filtering, a variation of sparse estimation, in conjunction with combined p $p$-value techniques. The sparse estimation technique and data-driven determination of hyperparameters are utilized in the proposed method to identify candidates of the event onsets. In addition, combined p $p$-value techniques are used to provide confidence values for the detections. The synthetic test demonstrated that the new method can detect 22 events of total 23 events and has only 1% false detections with the detection threshold 68%. The proposed method was then applied to daily displacements obtained at 39 GNSS stations in the Nankai subduction zone in western Shikoku, Southwest Japan. The results revealed that, in addition to all known events, new 12 events can be detected with the proposed method. Finally, we found the number of low-frequency earthquakes in the target region increased around at the onsets of potential events.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据