Slow slip events (SSEs) at subduction zone plate boundaries sometimes trigger earthquake swarms and megathrust earthquakes. The causal relationship between SSEs and seismicity has been studied worldwide, but the epidemic-type aftershock-sequence (ETAS) model, which is a standard statistical model of seismicity, does not explicitly consider the seismicity-triggering effect of SSEs. Therefore, if an SSE occurs at a plate boundary, probabilistic earthquake forecasts based on the ETAS model fail to predict observed seismicity. Here, we constructed a statistical model named the SSE-modulated ETAS model by incorporating SSE moment rates estimated from observation data from the global navigation satellite system into the original ETAS model. Our model assumes a linear or power-law relationship between the SSE moment rates and seismicity rates and estimates its proportionality constant as a new ETAS parameter. We applied this new model to three SSEs and M 2.5 or greater earthquakes in the shallow part of the Hikurangi Trench, New Zealand. The results show that it is better than the original ETAS model, giving a significant reduction in the Akaike information criterion. In addition, we examined the functional forms (e.g., lag time and power exponent) of the equation relating the moment rate of the SSEs to the seismicity rate. The results imply that, in addition to SSE-induced stress changes, crustal fluid migration may be related to SSE-induced seismicity. We also examine the influence of SSEs on aftershock productivity. Our model can improve short-term forecasts of seismicity associated with SSEs and is useful for quantifying characteristics of the seismicity.

Understanding the interaction between tectonic plates from geodetic data is relevant to the assessment of seismic hazard. To shed light on that prevalently slow aseismic interaction, we developed a new static-slip inversion strategy, the ELADIN (ELastostatic ADjoint INversion) method, that uses the adjoint elastostatic equations to compute the gradient of the cost function. To handle plausible slip constraints, ELADIN is a 2-step inversion algorithm. First it finds the slip that best explains the data without any constraint, and then refines the solution by imposing the constraints through a Gradient Projection Method. To obtain a selfsimilar, physically-consistent slip distribution that accounts for sparsity and uncertainty in the data, ELADIN reduces the model space by using a von Karman regularization function that controls the wavenumber content of the solution, and weights the observations according to their covariance using the data precision matrix. Since crustal deformation is the result of different concomitant interactions at the plate interface, ELADIN simultaneously determines the regions of the interface subject to both stressing (i.e., coupling) and relaxing slip regimes. For estimating the resolution, we introduce a mobile checkerboard that allows to determine lower-bound fault resolution zones for an expected slip-patch size and a given stations array. We systematically test ELADIN with synthetic inversions along the whole Mexican subduction zone and use it to invert the 2006 Guerrero Slow Slip Event (SSE), which is one of the most studied SSEs in Mexico. Since only 12 GPS stations recorded the event, careful regularization is thus required to achieve reliable solutions. We compared our preferred slip solution with two previously published models and found that our solution retains their most reliable features. In addition, although all three SSE models predict an upward slip penetration invading the seismogenic zone of the Guerrero seismic gap, our resolution analysis indicates that this penetration might not be a reliable feature of the 2006 SSE.

The triggering of large earthquakes on a fault hosting aseismic slip or, conversely, the triggering of slow slip events (SSE) by passing seismic waves involves seismological questions with important hazard implications. Just a few observations plausibly suggest that such interactions actually happen in nature. In this study we show that three recent devastating earthquakes in Mexico are likely related to SSEs, describing a cascade of events interacting with each other on a regional scale via quasi-static and/or dynamic perturbations. Such interaction seems to be conditioned by the transient memory of Earth materials subject to the “traumatic” stressing produced by the seismic waves of the great 2017 (Mw8.2) Tehuantepec earthquake, which strongly disturbed the aseismic slip beating over a 650 km long segment of the subduction plate interface. Our results imply that seismic hazard in large populated areas is a short-term evolving function of seismotectonic processes that are often observable.

Slow slip events (SSEs) along subduction zones play an important role in accommodating relative plate motion. SSEs interplay with large megathrust earthquakes and other slow earthquakes, including low frequency and very low frequency earthquakes. The Kanto and Tokai regions of central Japan host frequent slow and large earthquakes, with significant differences in slip behavior along the subduction zones in the Suruga Trough, Sagami Trough, and Japan Trench. In this study, we conducted a systematic search to estimate the fault models and durations of short-term SSEs using continuous Global Navigation Satellite System (GNSS) data collected from 1994 to 2020. We detected 179 potential SSEs with moment magnitudes of 5.3–7.0 and durations of 0–80 days from the time series. Along the Sagami Trough, two shallow regions at a depth of 10–20 km host Mw ≥ 6.5 SSEs off of the Boso Peninsula and accommodate most of the relative plate motion aseismically. Some SSEs also occur on the deep plate interface down to ~50 km without low frequency tremors (LFTs). Along the Japan Trench, the cumulative slip of the SSEs exhibits a bi-modal depth distribution to avoid the large slip areas of past megathrust earthquakes at 30–40 km depth. The shallow SSEs are in the same depth range (10–30 km) as LFTs, but are spatially separate from LFTs along the trench. The detected SSEs have limited temporal correlations with other slow earthquakes and earthquake swarms, which suggests that many factors control the genesis of slow and regular earthquakes.