Abstract
Using global navigation satellite system (GNSS) data to detect millimeter-order signals of short-term slow slip events (S-SSEs) and to estimate their source parameters, especially duration, is challenging because of low signal-to-noise ratio. Although the duration of S-SSEs in the Nankai subduction zone has been estimated using tiltmeters, its regional variation has never been quantitatively studied. We developed an S-SSE detection method to estimate both the fault model and duration with their errors based on the detection methods developed by previous studies and applied it to a 23-year period of GNSS data in the Nankai subduction zone. We extracted S-SSE signals by calculating correlation coefficients between the GNSS time series and a synthetic template representing the time evolution of an S-SSE and by computing the average of correlation coefficients weighted by the predicted S-SSE signals. We enhanced the signals for duration estimation by stacking GNSS time series weighted by displacements calculated from the estimated fault model. By applying the developed method, we detected 284 S-SSEs from 1997 to 2020 in the Nankai subduction zone from Tokai to Kyushu and discussed their regional characteristics. The results include some newly detected S-SSEs, including events accompanying very low-frequency earthquakes and repeating earthquakes in offshore Kyushu. Our study provides the first geodetic evidence for synchronization of S-SSEs and other seismic phenomena in offshore Kyushu. We estimated the cumulative slip and duration, and their error carefully. We also estimated the average slip rate by dividing the cumulative slip by the cumulative duration. This study clarified that the average slip rate in western Shikoku was approximately twice as that in eastern Shikoku and Kyushu. These regional differences were statistically significant at the 95% confidence interval. Multiple factors can influence the regional characteristics of S-SSEs, and we speculate that the subducting plate interface geometry is one of the dominant factors.Graphical
Highlights
Slow slip events (SSEs) are transient aseismic fault slip events occurring in a transition zone between seismogenic and stable creep zones (Obara and Kato 2016)
Correlation coefficients between global navigation satellite system (GNSS) time series and a synthetic template, and weighting by displacements predicted from assumed faults are key processes in extracting small transient signals from noisy observed data
We detected short-term SSE (S-SSE) synchronizing with Very low-frequency earthquake (VLFE) and Repeating earthquake (RE) in offshore Kyushu
Summary
Introduction Slow slip events (SSEs) are transient aseismic fault slip events occurring in a transition zone between seismogenic and stable creep zones (Obara and Kato 2016). We calculated the weighted stacking of the horizontal GNSS coordinates in a 121day time window, with the center date being the date of the detected event (Fig. 5a). Where uds,i is the displacement computed from the estimated fault assuming an event duration of d days, σs,i is the noise level of the GNSS time series of component i at station s , σis the average of σs,i , and Ad is a constant depending on the duration. We extracted an event which had a correlation coefficient, to the stacked time series, larger than 0.4 in order to retain a significant signal of transient displacement caused by S-SSEs. We regarded the events satisfying the above three criteria as S-SSEs and further categorized them into classes 1 and 2 based on a reduction of chi-square calculated in the fault model estimation process. We computed the 70% confidence intervals (that is, an interval between 15 and 85th percentiles) for each frequency distribution (Fig. 5c) and used it as the duration error
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
