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Slow slip events (SSEs) are important for the slip budget along a megathrust fault. Although the recurrence of weeks‐long short‐term SSEs (S‐SSEs) in southcentral Alaska has been suggested, a large amount of noise prevented us from detecting discrete events. We applied a systematic detection method to Global Navigation Satellite System data and detected 31 S‐SSEs during the 14‐year analysis period. The events mainly occurred at a depth from 35 to 45 km at a down‐dip extension of the 1964 Alaska earthquake, and the active clusters correlated with the region of the subducting Yakutat microplate. A large cumulative slip of S‐SSEs indicated a significant contribution to stress transfer along the plate interface, and its source area spatially coincided with that of the long‐term SSEs and the afterslip of the 1964 earthquake. Large and recurrent S‐SSEs are key phenomena for understanding interplate slip kinematics in this region. Plain Language Summary Slow and transient fault slips, called slow slip events (SSEs), are important phenomena accommodating plate motion during interseismic periods. However, detecting SSEs, especially short‐term SSEs (S‐SSEs) that last from days to weeks, is sometimes difficult because of their weak signals. In southcentral Alaska, previous studies have detected S‐SSEs as several discrete events synchronizing with tectonic tremors, but their spatiotemporal distribution and the features of their magnitude and duration are still unclear. We applied a systematic detection method to 14 years of daily Global Navigation Satellite System position data and successfully detected 31 S‐SSEs. We found two major groups of S‐SSEs (S‐SSE clusters) at a depth from 35 to 45 km, which corresponds to a deeper extension of the source of the 1964 Alaska earthquake. These clusters are located in the region where the Yakutat microplate subducts. Maximum cumulative slip reaches 0.27 and 0.43 m in the western and eastern clusters, respectively, and it suggests that S‐SSEs contribute to the reduction of the large amount of interplate slip in their source areas. Key Points Systematic detection identified 31 short‐term slow slip events in southcentral Alaska from 14 years of Global Navigation Satellite System data The slow slips were located at a depth from 35 to 45 km, particularly in the region where the Yakutat microplate subducts The short‐term slow slips overlap the source areas of the long‐term slow slips and the 1964 Alaska earthquake afterslip

Short‐term slow slip events accompanied by nonvolcanic deep low‐frequency tremors and deep very low frequency earthquakes in southwest Japan were investigated systematically by means of ground tilting studies. The change in tilt usually lasts for several days. By using a genetic algorithm and a least squares method, we inverted the data for tilt steps that were caused by slow slip events and were detected by at least four stations situated near the source of the tremor. Fault parameters were estimated for 54 slow slip episodes that occurred mainly in the western Shikoku, northeastern Kii, and Tokai regions from 2001 to 2008. In eastern Shikoku, two slow slip episodes were detected quantitatively for the first time. The fault geometries of all the slow slip events were located within the belt‐like distribution of tremors in the transition zone between the locked and aseismic slip zones at the plate interface of the subducting Philippine Sea Plate. The spatial extent of the fault geometry corresponds roughly to the distribution of clusters of nonvolcanic tremors and very low frequency earthquakes. The moment magnitudes ranged from 5.4 to 6.2, and the slip was ∼1 cm for each slow slip event. The rate of moment release by the detected slow slip events was 40–60% of the moment accumulation expected from the relative plate motion, and it showed regional differences. They may reflect the along‐strike variations in plate convergence and/or the characteristic size of the slow slip fault plane on the plate interface.

Slow slip events and associated non‐volcanic tremors are sensitive to oscillatory stress perturbations, such as those induced by tides or seismic surface waves. Slow slip events and tremors are thought to occur near the seismic‐aseismic transition regions of active faults, where the differencea − b = ∂μ/∂lnVbetween the sensitivity of friction to slip rate and fault state, which characterizes the stability of slip, can be arbitrarily small. We investigate the response of a velocity‐strengthening fault region to oscillatory loads through analytical approximations and spring‐slider simulations. We find that fault areas that are near velocity‐neutral at steady‐state, i.e., ∂μ / ∂lnV ≈ 0, are highly sensitive to cyclic loads: oscillatory stress perturbations in a certain range of periods induce large transient slip velocities. These aseismic transients can in turn trigger tremor activity with enhanced oscillatory modulation. In this sensitive regime, a harmonic Coulomb stress perturbation of amplitude ΔS causes a slip rate perturbation varying as eΔS/(a−b)σ, where σ is the effective normal stress. This result is in agreement with observations of the relationship between tremor rate and amplitude of stress perturbations for tremors triggered by passing seismic waves. Our model of tremor modulation mediated by transient creep does not require extremely high pore fluid pressure and provides a framework to interpret the sensitivity and phase of tidally modulated tremors observed in Parkfield and Shikoku in terms of spatial variations of friction parameters and background slip rate. Key Points Small values of a‐b lead to high sensitivity of NVTs to stress perturbations Explain exp relationship between amplitude of seismic waves and NVTs intensity The observed phase between NVTs and perturbing stresses is explained

The Superstition Hills Fault (SHF) exhibits a rich spectrum of slip modes, including M 6+ earthquakes, afterslip, quasi‐steady creep, and both triggered and spontaneous slow slip events (SSEs). Following 13 years of quiescence, creepmeters recorded 25 mm of slip during 16–19 May 2023. Additional sub‐events brought the total slip to 41 mm. The event nucleated on the northern SHF in early‐May and propagated bi‐laterally at rates on the order of kilometers per day. Surface offsets reveal a bi‐modal slip distribution, with slip on the northern section of the fault being less localized and lower amplitude compared to the southern section. Kinematic slip models confirm systematic variations in the slip distribution along‐strike and with depth and suggest that slip is largely confined to the shallow sedimentary layer. Observations and models of the 2023 SSE bear a strong similarity to previous slip episodes in 1999, 2006, and 2010, suggesting a characteristic behavior. Plain Language Summary Studying the mechanical properties and behavior of faults is essential for understanding earthquake ruptures. In this study, we investigate a recent slip event on the Superstition Hills Fault (SHF), which has a well‐documented record of slip. A notable aspect of the SHF is that it periodically undergoes “slow slip events” (SSEs), where the fault slips and releases energy without any accompanied ground shaking. During May‐July 2023, the SHF experienced a major SSE for the first time in 13 years. Our analysis shows that it was the largest documented SSE on the SHF and released equivalent energy to a magnitude 4.5 earthquake. We also find that the spatial pattern of fault slip is very similar to several previous slip events in 1999, 2006, and 2010, suggesting that the SHF has a tendency to slip in a characteristic manner. Key Points We document a recent spontaneous slow slip event (SSE) on the Superstition Hills Fault using creepmeter, Interferometric Synthetic Aperture Radar, Global Navigation Satellite System, and field measurements Over 41 mm of slip occurred from mid‐May to mid‐July 2023, with moment release corresponding to a Mw 4.5 earthquake The kinematics of the 2023 event are remarkably similar to several previous SSEs, suggesting a characteristic rupture process

We developed a model of short‐term slow slip events (SSEs) on the 3‐D subduction interface beneath Shikoku, southwest Japan, considering a rate‐ and state‐dependent friction law with a small cutoff velocity for the evolution effect. We assume low effective normal stress and small critical displacement at the SSE zone. On the basis of the hypocentral distribution of low‐frequency tremors, we set three SSE generation segments: a large segment beneath western Shikoku and two smaller segments beneath central and eastern Shikoku. Using this model, we reproduce events beneath western Shikoku with longer lengths in the along‐strike direction and with longer recurrence times compared with events beneath central and eastern Shikoku. The numerical results are consistent with observations in that the events at longer segments have longer recurrence intervals. The activity of SSEs is determined by nonuniform frictional properties at the transition zone. We also attempt to model the very low frequency (VLF) earthquakes that accompany short‐term SSEs, on a 2‐D thrust fault. We consider a local patch in which the friction parameters are varied. In the case that critical displacement is very small at the patch, fast multiple slips occur at the patch. In the case that the effective normal stress is high at the patch, the patch acts as a barrier to SSEs; when it ruptures, however, rapid slip occurs. Because the source time functions of these cases are somewhat different, it would be possible in the future to assess if either case is an appropriate model for VLF earthquakes.

The southern San Andreas fault is in its interseismic period, occasionally releasing some stored elastic strain during triggered slow slip events (SSEs) at <2.5 km depth. A distinct, shallowly exhumed gouge defines the fault and is present at SSE depths. To evaluate if this material can host SSEs, we characterize its mineralogy, microstructures, and frictional behavior with water‐saturated deformation experiments near‐in situ conditions, and we compare laboratory healing rates to natural SSEs. Our results show that slip localizes along clay surfaces in both laboratory and natural settings. The gouge is weak (coefficient of friction of ∼0.29), exhibits low healing rates (<0.001/decade), and transitions from unstable to stable behavior at slip rates above ∼1 μm/s. Healing rate and friction drop data from laboratory instabilities are comparable to geodetically‐constrained values for SSEs. Collective observations indicate this gouge could host shallow SSEs and/or localize slip facilitating dynamic rupture propagation to the surface.

We document a sequence of simultaneous short‐term and long‐term slow slip events (SSEs) at the Hikurangi subduction zone during the 2010/2011 period. The sequence of short‐term events (each ∼2–3 weeks in duration) ruptured much of the shallow plate interface (<15 km) at central and northern Hikurangi over a 6‐month period, was accompanied by microseismicity and involved patchy, irregular migration of SSE slip. We suggest that the patchy migration of the short‐term SSE is due to large‐scale (∼100–3500 km2) heterogeneities on the plate interface related to seamount subduction and sediment subduction and/or underplating. This is in contrast to a 2010/2011 long‐term SSE at the central Hikurangi margin, which evolved steadily over ∼1.5 years and ruptured much of the plate interface between 20 and 70 km depth. We suggest that the occurrence of long‐term versus short‐term SSEs at Hikurangi is related to differences in effective normal stresses and relative heterogeneity of the subduction interface. The long‐term SSE sequence began 1 year before the short‐term sequence. Coulomb stress change models suggest that the long‐term SSE may have triggered initiation of the subsequent short‐term SSE sequence. Initiation of the short‐term sequence occurred in a region just updip of or within an interseismically locked portion of the plate interface and may be located within the updip transition from seismic to aseismic behavior. Alternatively, it could be characteristic of a region undergoing partial interseismic coupling. This is in contrast to SSEs observed elsewhere in the world that typically occur within the downdip transition from seismic to aseismic behavior. Key Points Uniquely well‐constrained, simultaneous sequence of short‐term and long‐term SSEs Heterogeneous plate interface properties responsible for episodic SSE migration Best‐documented example of SSE slip updip of (or within) the locked zone

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.

Temporary slip speed increases with durations of 1–3 h were identified during short-term slow slip events in records of borehole and laser strainmeters in the Tokai region, Japan. They were found by searching for peaks of correlation coefficients between stacked strain data and ramp functions with rise times of 1 and 2 h. Although many of the strain steps were considered due to noise, some strain steps occurred with simultaneous activation of the deep tectonic tremors and shared source areas with the tremors. From 2016 to 2022, we observed five strain steps with simultaneous activation of tectonic tremors and coincidence of source locations with the tremors. Those strain steps occurred during short-term slow slip events and were temporary slip speed increases of the slow slip events. Those strain steps seemed to be related to successive occurrences with source migration of short-term slow slip events. The detrended strain steps corresponded to plate boundary slip events of moment magnitude around 5, which was consistent with the scaling law of slow earthquakes. Graphical Abstract

Over the past decade, short-term slow slip events (S-SSEs) have been detected along the entire Nankai Trough using Global Navigation Satellite System (GNSS) data. To enhance the detection of S-SSEs, we focused on the spatial and temporal coincidence of tremors and S-SSEs, a phenomenon known as episodic tremor and slip. We developed a machine learning-based method to detect S-SSEs directly from continuous seismic waveforms and applied it to seismic and geodetic data in western Shikoku, Japan. We trained a random forest regression model using statistical features extracted from continuous seismic waveforms as input variables and GNSS-derived displacement rates as target outputs. We predicted the GNSS displacement rate over a period of ~ 6 years and defined S-SSEs as periods when the predicted GNSS displacement rate increased sharply. We then estimated fault models for each detected S-SSE. The predicted displacement rates were correlated strongly with the observed displacement rates, and we identified a total of 23 S-SSEs, including 5 previously unrecognized events. The results demonstrate the effectiveness of machine learning using continuous seismic waveforms for improving S-SSE detection along the Nankai Trough. Graphical Abstract