[SCG58-08] Detection of short-term slow slip events and estimation of their duration by using three components of GNSS data in the Nankai subduction zone, southwest Japan
Keywords:southwest Japan, GNSS, short-term slow slip event
Several methods have been developed to detect short-term slow slip events (S-SSEs) by using Global Navigation Satellite System (GNSS) data in a subduction zone (e.g., Nishimura et al., 2013; Frank, 2016; Rousset et al., 2017). In these methods, a vertical component of GNSS data hasn’t been generally used because of its worse positioning accuracy than horizontal components. However, it helps determine the location of S-SSEs to use a vertical component. Therefore, we attempt to detect S-SSEs and estimate their durations by using three components of GNSS data in the Nankai subduction zone, known as one of the most active regions of slow earthquake activities including S-SSEs.
We use daily coordinates time series at ~ 800 GNSS stations operated by the Geospatial Information Authority of Japan, Japan Coast Gard, universities, and International GNSS services, located around the Nankai subduction zone in the period from April 1, 1997, to December 31, 2019. The coordinates were estimated using GIPSY Ver 6.4 software with a strategy of precise point positioning. As preprocess of GNSS data, we first remove coseismic and postseismic effects and long-term trends including annual and semiannual oscillations. Next, to estimate candidate date and locations for S-SSEs, we improve the Geodetic Matched Filter (Rousset at al., 2017) and apply it to both vertical and horizontal coordinate data by shifting a 121-day time window. And then, we estimate rectangular fault models by applying the nonlinear inversion method (Matsu’ura and Hasegawa, 1987) to displacements estimated around the candidate date. Finally, we calculate the weighted averages of time series around the candidate date and estimate the duration by fitting a logistic function. In this step, we use the surface displacements predicted from the estimated fault as a weight.
As a preliminary result, we detected 70 S-SSEs in the Shikoku region which is a part of the Nankai subduction zone. Most of them accompanied deep low-frequency tremor activities (Maeda and Obara, 2009; Obara et al., 2010). We also detected several S-SSEs at a shallower part of the subduction zone near the trough axis. Although we cannot completely exclude a possible misdetection, the existence of such a shallow S-SSE may be supported by the spatial-temporal proximity of shallow very low frequency earthquakes (Takemura et al., 2019) and the shallow SSE (Yokota and Ishikawa, 2020). In addition, we discuss the regional difference of slow-slip activities including long-term trends of the cumulative moment, duration, and recurrence interval.
Acknowledgment
We thank the Geospatial Information Authority of Japan, Japan Coast Guard, Japan Crustal Activity Science Consortium, and International GNSS Service for providing GNSS RINEX data.
We use daily coordinates time series at ~ 800 GNSS stations operated by the Geospatial Information Authority of Japan, Japan Coast Gard, universities, and International GNSS services, located around the Nankai subduction zone in the period from April 1, 1997, to December 31, 2019. The coordinates were estimated using GIPSY Ver 6.4 software with a strategy of precise point positioning. As preprocess of GNSS data, we first remove coseismic and postseismic effects and long-term trends including annual and semiannual oscillations. Next, to estimate candidate date and locations for S-SSEs, we improve the Geodetic Matched Filter (Rousset at al., 2017) and apply it to both vertical and horizontal coordinate data by shifting a 121-day time window. And then, we estimate rectangular fault models by applying the nonlinear inversion method (Matsu’ura and Hasegawa, 1987) to displacements estimated around the candidate date. Finally, we calculate the weighted averages of time series around the candidate date and estimate the duration by fitting a logistic function. In this step, we use the surface displacements predicted from the estimated fault as a weight.
As a preliminary result, we detected 70 S-SSEs in the Shikoku region which is a part of the Nankai subduction zone. Most of them accompanied deep low-frequency tremor activities (Maeda and Obara, 2009; Obara et al., 2010). We also detected several S-SSEs at a shallower part of the subduction zone near the trough axis. Although we cannot completely exclude a possible misdetection, the existence of such a shallow S-SSE may be supported by the spatial-temporal proximity of shallow very low frequency earthquakes (Takemura et al., 2019) and the shallow SSE (Yokota and Ishikawa, 2020). In addition, we discuss the regional difference of slow-slip activities including long-term trends of the cumulative moment, duration, and recurrence interval.
Acknowledgment
We thank the Geospatial Information Authority of Japan, Japan Coast Guard, Japan Crustal Activity Science Consortium, and International GNSS Service for providing GNSS RINEX data.