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Slow Slip Events (SSEs) are episodic slip events that play a significant role in the moment budget along subduction megathrust. They share many similarities with regular earthquakes, and have been observed in major subduction regions like, for example, Cascadia, Japan, Mexico, New Zealand. They show striking regularity, suggesting that it might be possible to forecast their size and timing, but the prediction of their extension and exact timing is still yet to come. They certainly are a great natural system to study how friction works at scale of the order of hundreds or thousands of km, and their recurrence time being much shorter than that of regular earthquakes, they give us the possibility to study multiple cycles and test their predictability. Here we focus on the Cascadia region, where SSEs recur every about 1 or 2 years, depending on the latitude. We use a catalog containing dozens of SSEs derived from the study of GPS position time series during the time span ranging from 2007 to 2017. The data show a clear segmentation with a few major patches interacting with one another, a behavior that recalls that of a discrete body system. We use both classical embedding theory and Extreme Value Theory applied to the study of dynamical systems to show that, where the Signal to Noise Ratio is sufficiently high, a low-dimensional (< 5) non-linear chaotic system is more appropriate to describe the dynamics than a stochastic system. We calculate major properties of the strange attractor like its correlation and instantaneous dimension, its instantaneous extremal index and a possible range for the metric entropy of the system. This knowledge is important for the determination of the predictability of the system, since it is related to the rate at which two trajectories in the phase space diverge. We further validate our results with a fuzzy inference system model to check the predictability of the slip and slip rate. In conclusion, SSEs in Cascadia can be described as a deterministic, albeit chaotic, system rather than as a random process. As SSEs might be regarded as earthquakes in slow motion, regular earthquakes might be similarly chaotic and predictable. [ABSTRACT FROM AUTHOR]

On 14 November 2016, the Northern part of New Zealand's South Island was struck by the Mw7.8 Kaikōura earthquake, an event of unprecedented geometric complexity rupturing at least 21 segments of the contractional North Canterbury and of the Marlborough fault systems. Geological, geodetic, tsunami and seismic data reveal puzzling features as well as observational difficulties of the event leading to competing views on its key features, such as the role played by the Hikurangi subduction interface, the exact rupture sequence, and the higher than expected local tsunami. We present a dynamic rupture model of the 2016 Mw 7.8 Kaikōura earthquake to unravel the event's riddles in a physics-based manner and provide insights on the mechanical viability of competing hypotheses proposed to explain them. The event is modeled using the open-source software SeisSol (www.seissol.org), based on a arbitrary high-order accurate DERivative Discontinuous Galerkin method (ADER-DG). We verify our model with strong ground-motions, high rate GPS, long-period teleseismic and tsunami data. Our model reproduces key characteristics of the event and constraints puzzling features inferred from high-quality observations including a large gap separating surface rupture traces, the possibility of significant slip on the subduction interface, the non-rupture of the Hope fault, and slow apparent rupture speed. We show that a rupture cascade sequentially breaking the Papatea and Kekerengu faults is dynamically consistent with regional stress estimates and a crustal fault network geometry inferred from seismic and geodetic data. A coseismically triggered tsunami caused by the rare occurrence of an earthquake starting on-land and crossing to two faults off-shore matches local tide gauge data.We find, that such complex rupture cascade links the crustal fault system when operating at low apparent friction thanks to the combined effects of overpressurized fluids, low dynamic friction and stress concentrations induced by deep fault creep. Understanding the physical conditions that allow rupture cascades on complex fault systems advances our ability to quantify earthquake hazard, especially to evaluate the possibility of extreme events on real fault networks. [ABSTRACT FROM AUTHOR]