Improving the Rapidity of Magnitude Estimation for Earthquake Early Warning Systems for Railways

To improve the performance of earthquake early warning (EEW) systems, we propose an approach that utilizes the time-dependence of P-wave displacements to estimate the earthquake magnitude (M) based on the relationship between M and the displacement. The traditional seismological understanding posits that this relationship achieves statistical significance when the displacement reaches its final peak value, resulting in the adoption of time-constant coefficients. However, considering the potential for earlier establishment of the relationship's significance than conventionally assumed, we analyze waveforms observed in Japan and determine the intercept in the relationship as a function of time from the P-wave onset. We demonstrate that our approach reduces the underestimation of M in the initial P-wave stages compared to the conventional technique. Consequently, we find a significant rise in the number of earlier warnings in the Japanese railway EEW system. Due to the inherent trade-off between the immediacy and accuracy of alarm outputs, the proposed method unavoidably leads to an increase in the frequency of alerts. Nonetheless, if deemed acceptable by system users, our approach can contribute to EEW performance improvement.

Fast and full characterization of large earthquakes from prompt elastogravity signals

Prompt ElastoGravity Signals are light-speed gravity-induced signals recorded before the arrival of seismic waves. They have raised interest for early warning applications but their weak amplitudes close to the background seismic noise have questioned their actual potential for operational use. A deep-learning model has recently demonstrated its ability to mitigate this noise limitation and to provide in near real-time the earthquake magnitude (M w ). However, this approach was efficient only for large earthquakes (M w ≥ 8.3) of known focal mechanism. Here we show unprecedented performance in full earthquake characterization using the dense broadband seismic network deployed in Alaska and Western Canada. Our deep-learning model provides accurate magnitude and focal mechanism estimates of M w ≥ 7.8 earthquakes, 2 minutes after origin time (hence the tsunamigenic potential). Our results represent a major step towards the routine use of prompt elastogravity signals in operational warning systems, and demonstrate its potential for tsunami warning in densely-instrumented areas.

Universal neural networks for real-time earthquake early warning trained with generalized earthquakes

Deep learning enhances earthquake monitoring capabilities by mining seismic waveforms directly. However, current neural networks, trained within specific areas, face challenges in generalizing to diverse regions. Here, we employ a data recombination method to create generalized earthquakes occurring at any location with arbitrary station distributions for neural network training. The trained models can then be applied universally with different monitoring setups for earthquake detection and parameter evaluation from continuous seismic waveform streams. This allows real-time Earthquake Early Warning (EEW) to be initiated at the very early stages of an occurring earthquake. When applied to substantial earthquake sequences across Japan and California (US), our models reliably report most earthquake locations and magnitudes within 4 seconds of the initial P-wave arrival, with mean errors of 2.6-7.3 km and 0.05-0.32, respectively. The generalized neural networks facilitate global applications of real-time EEW, eliminating complex empirical configurations typically required by traditional methods.

Fault size-dependent fracture energy explains multiscale seismicity and cascading earthquakes

Earthquakes vary in size over many orders of magnitude, often rupturing in complex multifault and multievent sequences. Despite the large number of observed earthquakes, the scaling of the earthquake energy budget remains enigmatic. We propose that fundamentally different fracture processes govern small and large earthquakes. We combined seismological observations with physics-based earthquake models, finding that both dynamic weakening and restrengthening effects are non-negligible in the energy budget of small earthquakes. We established a linear scaling relationship between fracture energy and fault size and a break in scaling with slip. We applied this scaling using supercomputing and unveiled large dynamic rupture earthquake cascades involving >700 multiscale fractures within a fault damage zone. We provide a simple explanation for seismicity across all scales with implications for comprehending earthquake genesis and multifault rupture cascades.

Real-Time Seismic Intensity Measurements Prediction for Earthquake Early Warning: A Systematic Literature Review

With the gradual development of and improvement in earthquake early warning systems (EEWS), more accurate real-time seismic intensity measurements (IMs) methods are needed to assess the impact range of earthquake intensities. Although traditional point source warning systems have made some progress in terms of predicting earthquake source parameters, they are still inadequate at assessing the accuracy of IMs predictions. In this paper, we aim to explore the current state of the field by reviewing real-time seismic IMs methods. First, we analyze different views on the ultimate earthquake magnitude and rupture initiation behavior. Then, we summarize the progress of IMs predictions as they relate to regional and field warnings. The applications of finite faults and simulated seismic wave fields in IMs predictions are analyzed. Finally, the methods used to evaluate IMs are discussed in terms of the accuracy of the IMs measured by different algorithms and the cost of alerts. The trend of IMs prediction methods in real time is diversified, and the integration of various types of warning algorithms and of various configurations of seismic station equipment in an integrated earthquake warning network is an important development trend for future EEWS construction.

Instantaneous tracking of earthquake growth with elastogravity signals

Rapid and reliable estimation of large earthquake magnitude (above 8) is key to mitigating the risks associated with strong shaking and tsunamis¹. Standard early warning systems based on seismic waves fail to rapidly estimate the size of such large earthquakes^2–5. Geodesy-based approaches provide better estimations, but are also subject to large uncertainties and latency associated with the slowness of seismic waves. Recently discovered speed-of-light prompt elastogravity signals (PEGS) have raised hopes that these limitations may be overcome^6,7, but have not been tested for operational early warning. Here we show that PEGS can be used in real time to track earthquake growth instantaneously after the event reaches a certain magnitude. We develop a deep learning model that leverages the information carried by PEGS recorded by regional broadband seismometers in Japan before the arrival of seismic waves. After training on a database of synthetic waveforms augmented with empirical noise, we show that the algorithm can instantaneously track an earthquake source time function on real data. Our model unlocks ‘true real-time’ access to the rupture evolution of large earthquakes using a portion of seismograms that is routinely treated as noise, and can be immediately transformative for tsunami early warning.

A deep learning model trained on prompt elastogravity signal (PEGS) recorded by seismometers in Japan predicts in real time the final magnitude of large earthquakes faster than methods based on elastic waves.

Source time functions of earthquakes based on a stochastic differential equation

Source time functions are essential observable quantities in seismology; they have been investigated via kinematic inversion analyses and compiled into databases. Given the numerous available results, some empirical laws on source time functions have been established, even though they are complicated and fluctuated time series. Theoretically, stochastic differential equations, including a random variable and white noise, are suitable for modeling complicated phenomena. In this study, we model source time functions as the convolution of two stochastic processes (known as Bessel processes). We mathematically and numerically demonstrate that this convolution satisfies some of the empirical laws of source time functions, including non-negativity, finite duration, unimodality, a growth rate proportional to [Formula: see text], [Formula: see text]-type spectra, and frequency distribution (i.e., the Gutenberg-Richter law). We interpret this convolution and speculate that the stress drop rate and fault impedance follow the same Bessel process.

Earthquake breakdown energy scaling despite constant fracture energy

In the quest to determine fault weakening processes that govern earthquake mechanics, it is common to infer the earthquake breakdown energy from seismological measurements. Breakdown energy is observed to scale with slip, which is often attributed to enhanced fault weakening with continued slip or at high slip rates, possibly caused by flash heating and thermal pressurization. However, seismologically inferred breakdown energy varies by more than six orders of magnitude and is frequently found to be negative-valued. This casts doubts about the common interpretation that breakdown energy is a proxy for the fracture energy, a material property which must be positive-valued and is generally observed to be relatively scale independent. Here, we present a dynamic model that demonstrates that breakdown energy scaling can occur despite constant fracture energy and does not require thermal pressurization or other enhanced weakening. Instead, earthquake breakdown energy scaling occurs simply due to scale-invariant stress drop overshoot, which may be affected more directly by the overall rupture mode – crack-like or pulse-like – rather than from a specific slip-weakening relationship.

Earthquake breakdown energy is commonly interpreted as a proxy for fracture energy but is observed to scale with magnitude. Here the authors show that a scale-independent stress overshoot, as seen in the 3D dynamic earthquake rupture simulations, leads to comparable scaling despite constant fault fracture energy.

What controls the remobilization and deformation of surficial sediment by seismic shaking? Linking lacustrine slope stratigraphy to great earthquakes in South-Central Chile

Remobilization and deformation of surficial subaqueous slope sediments create turbidites and soft sediment deformation structures, which are common features in many depositional records. Palaeoseismic studies have used seismically-induced turbidites and soft sediment deformation structures preserved in sedimentary sequences to reconstruct recurrence patterns and - in some cases - allow quantifying rupture location and magnitude of past earthquakes. However, current understanding of earthquake-triggered remobilization and deformation lacks studies targeting where these processes take place, the subaqueous slope and involving direct comparison of sedimentary fingerprint with well-documented historical earthquakes. This study investigates the sedimentary imprint of six megathrust earthquakes with varying rupture characteristics in 17 slope sediment cores from two Chilean lakes, Riñihue and Calafquén, and evaluates how it links to seismic intensity, peak ground acceleration, bracketed duration and slope angle. Centimetre-scale stratigraphic gaps ranging from ca 1 to 20 cm - caused by remobilization of surficial slope sediment - were identified using high-resolution multi-proxy core correlation of slope to basin cores, and six types of soft sediment deformation structures ranging from ca 1 to 25 cm thickness using high-resolution three-dimensional X-ray computed tomography data. Stratigraphic gaps occur on slope angles of ≥2.3°, whereas deformation already occurs from slope angle 0.2°. The thickness of both stratigraphic gaps and soft sediment deformation structures increases with slope angle, suggesting that increased gravitational shear stress promotes both surficial remobilization and deformation. Seismic shaking is the dominant trigger for surficial remobilization and deformation at the studied lakes. Total remobilization depth correlates best with bracketed duration and is highest in both lakes for the strongest earthquakes (M _w ca 9.5). In lake Riñihue, soft sediment deformation structure thickness and type correlate best with peak ground acceleration providing the first field-based evidence of progressive soft sediment deformation structure development with increasing peak ground acceleration for soft sediment deformation structures caused by Kelvin-Helmholtz instability. The authors propose that long duration and low frequency content of seismic shaking favours surficial remobilization, whereas ground motion amplitude controls Kelvin-Helmholtz instability-related soft sediment deformation structure development.

Resolution and uncertainties in estimates of earthquake stress drop and energy release

Our models and understanding of the dynamics of earthquake rupture are based largely on estimates of earthquake source parameters, such as stress drop and radiated seismic energy. Unfortunately, the measurements, especially those of small and moderate-sized earthquakes (magnitude less than about 5 or 6), are not well resolved, containing significant random and potentially systematic uncertainties. The aim of this review is to provide a context in which to understand the challenges involved in estimating these measurements, and to assess the quality and reliability of reported measurements of earthquake source parameters. I also discuss some of the ways progress is being made towards more reliable parameter measurements. At present, whether the earthquake source is entirely self-similar, or not, and which factors and processes control the physics of the rupture remains, at least in the author's opinion, largely unconstrained. Detailed analysis of the best recorded earthquakes, using the increasing quantity and quality of data available, and methods less dependent on simplistic source models is one approach that may help provide better constraints. This article is part of the theme issue 'Fracture dynamics of solid materials: from particles to the globe'.

High-temporal-resolution quasideterministic dynamics of granular stick-slip

We report high-temporal-resolution observations of the spontaneous instability of model granular materials under isotropic and triaxial compression in fully drained conditions during laboratory tests representative of earthquakes. Unlike in natural granular materials, in the model granular materials, during the first stage of the tests, i.e., isotropic compression, a series of local collapses of various amplitudes occurs under random triggering cell pressures. During the second stage, i.e., shearing under triaxial compression, the model granular samples exhibit very large quasiperiodic stick-slip motions at random deviatoric triggering stresses. These motions are responsible for very large stress drops that are described by power laws and are accurate over more than 3 decades in logarithmic space. Then, we identify the quasideterministic nature of these stick-slip events, assuming that they are fully controlled by the cell pressure and solid fraction. Finally, we discuss the potential mechanisms that could explain these intriguing behaviors and the possible links with natural earthquakes.

Asymmetric Damage Avalanche Shape in Quasibrittle Materials and Subavalanche (Aftershock) Clusters

Crackling dynamics is characterized by a release of incoming energy through intermittent avalanches. The shape, i.e., the internal temporal structure of these avalanches, gives insightful information about the physical processes involved. It was experimentally shown recently that progressive damage toward compressive failure of quasibrittle materials can be mapped onto the universality class of interface depinning when considering scaling relationships between the global characteristics of the microcracking avalanches. Here we show, for three concrete materials and from a detailed analysis of the acoustic emission waveforms generated by microcracking events, that the shape of these damage avalanches is strongly asymmetric, characterized by a very slow decay. This remarkable asymmetry, at odds with mean-field depinning predictions, could be explained, in these quasibrittle materials, by retardation effects induced by enhanced viscoelastic processes within a fracture process zone generated by the damage avalanche as it progresses. It is associated with clusters of subavalanches, or aftershocks, within the main avalanche.

Seismogeodetic P-wave Amplitude: No Evidence for Strong Determinism

Whether the final properties of large earthquakes can be inferred from initial observations of rupture (deterministic rupture) is valuable for understanding earthquake source processes and is critical for operational earthquake and tsunami early warning. Initial (P-wave) characteristics of small to moderate earthquakes scale with magnitude, yet observations of large to great earthquakes saturate, resulting in magnitude underestimation. Whether saturation is inherent to earthquake dynamics or rather is due to unreliable observation of long-period signals with inertial seismic instrumentation is unclear. Seismogeodetic methods are better suited for broadband observation of large events in the near-field. In this study, we investigate the deterministic potential of seismogeodetically derived P-wave amplitude using a dataset of 14 medium-to-great earthquakes around Japan. Our results indicate that seismogeodetic P-wave amplitude is not a reliable predictor of magnitude, opposing the notion of strong determinism in the first few seconds of rupture.

Hierarchical interlocked orthogonal faulting in the 2019 Ridgecrest earthquake sequence

A nearly 20-year hiatus in major seismic activity in southern California ended on 4 July 2019 with a sequence of intersecting earthquakes near the city of Ridgecrest, California. This sequence included a foreshock with a moment magnitude (M _w) of 6.4 followed by a M _w 7.1 mainshock nearly 34 hours later. Geodetic, seismic, and seismicity data provided an integrative view of this sequence, which ruptured an unmapped multiscale network of interlaced orthogonal faults. This complex fault geometry persists over the entire seismogenic depth range. The rupture of the mainshock terminated only a few kilometers from the major regional Garlock fault, triggering shallow creep and a substantial earthquake swarm. The repeated occurrence of multifault ruptures, as revealed by modern instrumentation and analysis techniques, poses a formidable challenge in quantifying regional seismic hazards.

Frequent observations of identical onsets of large and small earthquakes

Every gigantic earthquake begins as a tiny rock failure at almost a point, followed by successive slip of the complex fault system, before radiating strong shaking from a vast rupture area extending over hundreds of kilometres. Whether the growth process of the rupture of a large earthquake is predictable and whether it produces observable signatures different from that of smaller events^1-5 are fundamental questions related to the potential for earthquake early warning and probabilistic forecasting. Inspired by a recent discovery that large earthquakes might have seismic waves, and probably rupture processes, that are almost identical to those of smaller events^6-8, we show that such similarity characterized by large cross-correlation is a common feature of earthquakes in the Tohoku-Hokkaido subduction zone, Japan. A systematic comparison of 15 years of high-sensitivity seismograph records for approximately 100,000 events reveals 80 extremely similar and 390 very similar pairs of large (moment magnitude M > 4.5) and small (M < 4.0) earthquakes, co-located within about 100 metres. An extremely high similarity is observed for pairs of subduction-type earthquakes (170 of 899 large events) separated by a long period of up to 15 years, whereas for pairs of other types of large earthquakes only the foreshocks and aftershocks are similar. This frequently occurring similarity between different-sized subduction-type earthquakes suggests repeated cascading rupture processes in a widespread hierarchical structure^9-12 along the plate interface and indicates a specific but probabilistically limited predictability of the final size of the earthquake (that is, the location and a set of possible sizes of an earthquake are well predicted, but its final size is not at all well constrained).

Characterizing large earthquakes before rupture is complete

Whether earthquakes of different sizes are distinguishable early in their rupture process is a subject of debate. Studies have shown that the frequency content of radiated seismic energy in the first seconds of earthquakes scales with magnitude, implying determinism. Other studies have shown that recordings of ground displacement from small to moderate-sized earthquakes are indistinguishable, implying a universal early rupture process. Regardless of how earthquakes start, events of different sizes must be distinguishable at some point. If that difference occurs before the rupture duration of the smaller event, this implies some level of determinism. We show through analysis of a database of source time functions and near-source displacement records that, after an initiation phase, ruptures of M7 to M9 earthquakes organize into a slip pulse, the kinematic properties of which scale with magnitude. Hence, early in the rupture process-after about 10 s-large and very large earthquakes can be distinguished.

Geodetic Observations of Weak Determinism in Rupture Evolution of Large Earthquakes

The moment evolution of large earthquakes is a subject of fundamental interest to both basic and applied seismology. Specifically, an open problem is when in the rupture process a large earthquake exhibits features dissimilar from those of a lesser magnitude event. The answer to this question is of importance for rapid, reliable estimation of earthquake magnitude, a major priority of earthquake and tsunami early warning systems. Much effort has been made to test whether earthquakes are deterministic, meaning that observations in the first few seconds of rupture can be used to predict the final rupture extent. However, results have been inconclusive, especially for large earthquakes greater than M w 7. Traditional seismic methods struggle to rapidly distinguish the size of large-magnitude events, in particular near the source, even after rupture completion, making them insufficient to resolve the question of predictive rupture behavior. Displacements derived from Global Navigation Satellite System data can accurately estimate magnitude in real time, even for the largest earthquakes. We employ a combination of seismic and geodetic (Global Navigation Satellite System) data to investigate early rupture metrics, to determine whether observational data support deterministic rupture behavior. We find that while the earliest metrics (~5 s of data) are not enough to infer final earthquake magnitude, accurate estimates are possible within the first tens of seconds, prior to rupture completion, suggesting a weak determinism. We discuss the implications for earthquake source physics and rupture evolution and address recommendations for earthquake and tsunami early warning.

The limits of earthquake early warning: Timeliness of ground motion estimates

The basic physics of earthquakes is such that strong ground motion cannot be expected from an earthquake unless the earthquake itself is very close or has grown to be very large. We use simple seismological relationships to calculate the minimum time that must elapse before such ground motion can be expected at a distance from the earthquake, assuming that the earthquake magnitude is not predictable. Earthquake early warning (EEW) systems are in operation or development for many regions around the world, with the goal of providing enough warning of incoming ground shaking to allow people and automated systems to take protective actions to mitigate losses. However, the question of how much warning time is physically possible for specified levels of ground motion has not been addressed. We consider a zero-latency EEW system to determine possible warning times a user could receive in an ideal case. In this case, the only limitation on warning time is the time required for the earthquake to evolve and the time for strong ground motion to arrive at a user's location. We find that users who wish to be alerted at lower ground motion thresholds will receive more robust warnings with longer average warning times than users who receive warnings for higher ground motion thresholds. EEW systems have the greatest potential benefit for users willing to take action at relatively low ground motion thresholds, whereas users who set relatively high thresholds for taking action are less likely to receive timely and actionable information.