Spatiotemporal slip distributions associated with the 2018–2019 Bungo Channel long-term slow slip event inverted from GNSS data

Long-term slow slip events (L-SSEs) have repeatedly occurred beneath the Bungo Channel in southwestern Japan with durations of several months to a couple of years, with a recurrence interval of approximately 6 years. We estimated the spatiotemporal slip distributions of the 2018–2019 Bungo Channel L-SSE by inverting processed GNSS time series data. This event was divided into two subevents, with the first on the southwest side of the Bungo Channel from 2018.3 to 2018.7 and the second beneath the Bungo Channel from 2018.8 to 2019.4. Tectonic tremors became active on the downdip side of the L-SSE occurrence region when large slow slips took place beneath the Bungo Channel. Compared with the previous Bungo Channel L-SSEs, this spatiotemporal slip pattern and amount were similar to those of the 2002–2004 L-SSE. However, the slip expanded in the northeast and southwest directions in the latter half of the second subevent. The maximum amount of slip, the maximum slip velocity, the total released seismic moment, and the moment magnitude of the 2018–2019 L-SSE were estimated to be 28 cm, 54 cm/year, $$4.4 \times 10^{19}$$ 4.4 × 10 19 Nm, and 7.0, respectively, all of which were the largest among the 1996–1998, 2002–2004, 2009–2011, and 2018–2019 L-SSEs.

Spatiotemporal Slip Distributions Associated with the 2018-2019 Bungo Channel Long-Term Slow Slip Event Inverted from GNSS Data

Long-term slow slip events (L-SSEs) have occurred beneath the Bungo Channel with durations of several months to a couple of years repeatedly with a recurrence interval of approximately six years. We estimated the spatiotemporal slip distributions of the 2018–2019 Bungo Channel L-SSE inverted from processed GNSS time series data. This event was divided into two subevents, with the first on the southwest side of the Bungo Channel from 2018.3 to 2018.7 and the second beneath the Bungo Channel from 2018.8 to 2019.4. Tectonic tremors became active on the downdip side of the L-SSE occurrence region when large slow slips took place beneath the Bungo Channel. Compared with the previous Bungo Channel L-SSEs, this spatiotemporal slip pattern and amount were similar to those of the 2003 L-SSE. However, the slip expanded in the northeast-southwest direction in the latter half of the second subevent. We also found that the total duration of the two subevents was 1.0 year, which was the shortest among the four recent L-SSEs beneath the Bungo Channel identified using GNSS time series data. The maximum amount of slip, the maximum slip velocity, the total released seismic moment, and the moment magnitude of the 2018–2019 L-SSE were estimated to be 27 cm, 53 cm/year, 4.1×1019 Nm, and 7.0, respectively, all of which were the largest among the four L-SSEs.

The Intra-Tidal Characteristics of Tidal Front and Their Spring–Neap Tidal and Seasonal Variations in Bungo Channel, Japan

The intra-tidal variations of a tidal front in Bungo Channel, Japan and their dependence on the spring–neap tidal cycle and month were analyzed utilizing high-resolution (~2 km) hourly sea surface temperature (SST) data obtained from a Himawari-8 geostationary satellite from April 2016 to August 2020. A gradient-based front detection method was utilized to define the position and intensity of the front. Similar to previous ship-based studies, SST data were utilized to identify tidal fronts between a well-mixed strait and its surrounding stratified area. The hourly SST data confirmed the theoretical intra-tidal movement of the tidal front, which is mainly controlled by tidal current advection. Notably, the intensity of the front increases during the ebb current phase, which carries the front toward the stratified area, but decreases during the flood current phase that drives the front in the opposite direction. Due to a strong dependence on tidal currents, the intra-tidal variations appear in a fortnight cycle, and the fortnightly variations of the front are dependent on the month in which the background stratification and residual current changes occur. Additionally, tidal current convergence and divergence are posited to cause tidal front intensification and weakening.

Estimation of frictional properties and slip evolution on a long-term slow slip event fault with the ensemble Kalman filter: numerical experiments

Summary A variety of slow slip events at subduction zones have been observed. They can be stress meters for monitoring the stress state of megathrust faults during their earthquake cycles. In this study, we focus on long-term slow slip events (LSSEs) recurring at downdip portions of megathrust faults among such slow earthquakes. Data analyses and simulation studies of LSSEs have so far been executed independently. In atmosphere and ocean sciences, data assimilations that optimally combine data analyses and simulation studies have been developed. We develop a method for estimating frictional properties and monitoring slip evolution on an LSSE fault, with a sequential data assimilation method, the ensemble Kalman filter (EnKF). We executed numerical twin experiments for the Bungo Channel LSSE fault in southwest Japan to validate the method. First, based on a rate- and state-dependent friction law, we set a rate-weakening circular LSSE patch on the rate-strengthening flat plate interface, whose critical nucleation size is larger than that of the patch, and reproduced the observed Bungo Channel LSSEs with recurrence times of approximately 7 yr and slip durations of 1 yr. Then, we synthesized the observed data of surface displacement rates at uniformly distributed stations with noises from the simulated slip model. Using our EnKF method, we successfully estimated the frictional parameters and the slip rate evolution after a few cycles. Secondly, we considered the effect of the megathrust fault existing in the updip portion of the LSSE fault, as revealed by kinematic inversion studies of Global Navigation Satellite System (GNSS) data and added this locked region with a slip deficit rate in the model. We estimated the slip rate on the locked region only kinematically, but the quasi-dynamic equation of motion in each LSSE fault cell includes the stress term arising from the locked region. Based on this model, we synthesized the observed surface displacement rate data for the actual distribution of GNSS stations and executed EnKF estimations including the slip rate on the locked region. The slip rate on the locked region could be quickly retrieved. Even for the actual distribution of GNSS stations, we could successfully estimate frictional parameters and slip evolution on the LSSE fault. Thus, our twin numerical experiments showed the validity of our EnKF method, although we need further studies for actual GNSS data analyses.