SUMMARY
The Gulf of Guinea exhibits a continuous emission of narrow-band and long-period signals (16, 26 and 27 s) on teleseismic records, yet the underlying excitation mechanism remains unclear. ...This study establishes a connection between these tremors and the vibration of thin, decoupled crustal plates at unexplored volcanoes in the gulf. We first formulate the damped plate oscillation equation, by incorporating the vibration of the thin surface crustal plate and magma flow in the subsurface sill. The findings reveal that a fundamental-mode vibration with a period of several dozen seconds can be induced by a crustal plate that is less than 1.0 km thick but extends over tens of kilometres in both length and width, given a subsurface sill depth exceeding 10.0 cm. The thin plate hypothesis also allows for excitation of a few overtone modes, but such waves in higher frequencies diminish over long distances, leaving only the monotonous fundamental-mode vibration at teleseismic stations. The long duration of Guinea tremors at each recurrence is attributed to the presence of low viscosity basaltic magma, which influences the damping factor. Direct wave loads at the shallow gulf serve as the primary vibration source, accounting for seasonal variations and recurring patterns. Sporadic energy bursts may also occur due to large storms. Radiation patterns of Guinea tremors are linked to the geometric structure of the thin plate. Our theoretical estimates of tremor spectra closely align with observed data, confirming the model’s accuracy in capturing reported Guinea tremor characteristics. This study provides valuable insights into the origins of very long-period tremors at continental volcanoes.
SUMMARY
This study examines the feature space of seismic waveforms often used in machine learning applications for seismic event detection and classification problems. Our investigation centres on ...the southern Alaska region, where the seismic record captures diverse seismic activity, notably from the calving of marine-terminating glaciers and tectonic earthquakes along active plate boundaries. While the automated discrimination of earthquakes and glacier quakes is our nominal goal, this data set provides an outstanding opportunity to explore the general feature space of regional seismic phases. That objective has applicability beyond ice quakes and our geographic region of study. We make a noteworthy discovery that features rooted in the spectral content of seismic waveforms consistently outperform statistical and temporal features. Spectral features demonstrate robust performance, exhibiting resilience to class imbalance while being minimally impacted by factors such as epicentral distance and signal-to-noise ratio. We also conduct experiments on the transferability of the model and find that transferability primarily depends on the appearance of the waveforms. Finally, we analyse misclassified events and find examples that are identified incorrectly in the original regional catalogue.
SUMMARY
Earthquakes come in clusters formed of mostly aftershock sequences, swarms and occasional foreshock sequences. This clustering is thought to result either from stress transfer among faults, a ...process referred to as cascading, or from transient loading by aseismic slip (pre-slip, afterslip or slow slip events). The ETAS statistical model is often used to quantify the fraction of clustering due to stress transfer and to assess the eventual need for aseismic slip to explain foreshocks or swarms. Another popular model of clustering relies on the earthquake nucleation model derived from experimental rate-and-state friction. According to this model, earthquakes cluster because they are time-advanced by the stress change imparted by the mainshock. This model ignores stress interactions among aftershocks and cannot explain foreshocks or swarms in the absence of transient loading. Here, we analyse foreshock, swarm and aftershock sequences resulting from cascades in a Discrete Fault Network model governed by rate-and-state friction. We show that the model produces realistic swarms, foreshocks and aftershocks. The Omori law, characterizing the temporal decay of aftershocks, emerges in all simulations independently of the assumed initial condition. In our simulations, the Omori law results from the earthquake nucleation process due to rate and state friction and from the heterogeneous stress changes due to the coseismic stress transfers. By contrast, the inverse Omori law, which characterizes the accelerating rate of foreshocks, emerges only in the simulations with a dense enough fault system. A high-density complex fault zone favours fault interactions and the emergence of an accelerating sequence of foreshocks. Seismicity catalogues generated with our discrete fault network model can generally be fitted with the ETAS model but with some material differences. In the discrete fault network simulations, fault interactions are weaker in aftershock sequences because they occur in a broader zone of lower fault density and because of the depletion of critically stressed faults. The productivity of the cascading process is, therefore, significantly higher in foreshocks than in aftershocks if fault zone complexity is high. This effect is not captured by the ETAS model of fault interactions. It follows that a foreshock acceleration stronger than expected from ETAS statistics does not necessarily require aseismic slip preceding the mainshock (pre-slip). It can be a manifestation of a cascading process enhanced by the topological properties of the fault network. Similarly, earthquake swarms might not always imply transient loading by aseismic slip, as they can emerge from stress interactions.
SUMMARY
Time-lapse seismic monitoring using full-wavefield methods aims to accurately and robustly image rock and fluid changes within a reservoir. These changes are typically small and localized. ...Quantifying the uncertainty related to these changes is crucial for decision making, but traditional methods that use pixel by pixel uncertainty quantification with large models are computationally infeasible. We exploit the structure of the time-lapse seismic problem for fast wavefield computations using a numerically exact local acoustic solver. This allows us to perform a Bayesian inversion using a Metropolis–Hastings algorithm to sample our posterior distribution. We address the well-known dimensionality problem in global optimization using an image compression technique. We run our numerical experiments using a single shot and a single frequency, however we show that various frequencies converge to different local minima. In addition, we test our framework for both uncorrelated and correlated noise, and we retrieve different histograms for each noise type. Through our numerical examples we show the importance of defining quantities of interest in order to setup an appropriate uncertainty quantification framework involving choosing the number of degrees of freedom and model parametrization that best approximate the problem. To our knowledge, there is no work in the literature studying the time-lapse problem using stochastic full-waveform inversion.
In July 2020, a Mw 7.8 earthquake initiated directly to the east of Simeonof Island offshore of the Alaska Peninsula. The earthquake ruptured the eastern part of the Shumagin Gap, a region devoid of ...large earthquakes over the last century and characterized by low geodetic coupling. Here, we investigate the rupture kinematics of the earthquake using a joint inversion of high‐rate GNSS and strong‐motion data. We find that the rupture was focused between depths of 30–45 km, starting east of the Shumagin Islands and rupturing downdip towards the northwest, with little slip west of 160°W. Early postseismic observations indicate that the entirety of the Shumagin Gap at depths between 40–60 km ruptured with aseismic afterslip and aftershocks. Historically, this earthquake resembles the Shumagin Islands earthquake of 1917, indicating that a possible rupture asperity exists to explain low interseismic coupling and repeating ~M7.5–8 earthquakes.
Plain Language Summary
A large Mw 7.8 earthquake occurred in July 2020 in the Aleutian Islands near a part of the subduction zone that is not locked, the Shumagin Gap. A fully locked fault will be more susceptible to large earthquakes since deformation is not released slowly over time. We model how the earthquake slipped using both observations of displacement and velocity nearby. We find that the July 2020 earthquake ruptured mainly the unlocked portion of the subduction zone and did not rupture into regions that are highly locked. This peculiar pattern of slip was also seen previously in 1917, indicating that the structure of the fault zone in the area may be conducive to earthquakes and some interseismic locking is occurring to allow for M7.5–8 earthquakes every century.
Key Points
The Simeonof Island earthquake ruptured a region of low interseismic coupling in the Shumagin Gap
Early postseismic deformation indicates slip along the whole width of the Shumagin Gap between 40 and 60 km
The Simeonof Island earthquake resembles the 1917 earthquake, indicating a potential rupture asperity within a highly creeping region
SUMMARY
In a recent work, we applied the every earthquake a precursor according to scale (EEPAS) probabilistic model to the pseudo-prospective forecasting of shallow earthquakes with magnitude $M\ ...5.0$ in the Italian region. We compared the forecasting performance of EEPAS with that of the epidemic type aftershock sequences (ETAS) forecasting model, using the most recent consistency tests developed within the collaboratory for the study of earthquake predictability (CSEP). The application of such models for the forecasting of Italian target earthquakes seems to show peculiar characteristics for each of them. In particular, the ETAS model showed higher performance for short-term forecasting, in contrast, the EEPAS model showed higher forecasting performance for the medium/long-term. In this work, we compare the performance of EEPAS and ETAS models with that obtained by a deterministic model based on the occurrence of strong foreshocks (FORE model) using an alarm-based approach. We apply the two rate-based models (ETAS and EEPAS) estimating the best probability threshold above which we issue an alarm. The model parameters and probability thresholds for issuing the alarms are calibrated on a learning data set from 1990 to 2011 during which 27 target earthquakes have occurred within the analysis region. The pseudo-prospective forecasting performance is assessed on a validation data set from 2012 to 2021, which also comprises 27 target earthquakes. Tests to assess the forecasting capability demonstrate that, even if all models outperform a purely random method, which trivially forecast earthquake proportionally to the space–time occupied by alarms, the EEPAS model exhibits lower forecasting performance than ETAS and FORE models. In addition, the relative performance comparison of the three models demonstrates that the forecasting capability of the FORE model appears slightly better than ETAS, but the difference is not statistically significant as it remains within the uncertainty level. However, truly prospective tests are necessary to validate such results, ideally using new testing procedures allowing the analysis of alarm-based models, not yet available within the CSEP.
Recordings by Japan's dense seismic network in the days and weeks before the 2011 Mw 9.0 Tohoku-Oki earthquake provide an opportunity to interrogate what caused the dynamic rupture of one of the ...largest earthquakes on record. Using a method to extract small earthquakes that are often obscured by overlapping seismic waves, Kato et al. (p. 705, published online 19 January) identified over a thousand small repeating earthquakes that migrated slowly toward the hypocenter of the main rupture. Based on the properties of these foreshocks, the plate interface experienced two sequences of slow slip, the second of which probably contributed a substantial amount of stress and may have initiated the nucleation of the main shock. Many large earthquakes are preceded by one or more foreshocks, but it is unclear how these foreshocks relate to the nucleation process of the mainshock. On the basis of an earthquake catalog created using a waveform correlation technique, we identified two distinct sequences of foreshocks migrating at rates of 2 to 10 kilometers per day along the trench axis toward the epicenter of the 2011 moment magnitude (Mw) 9.0 Tohoku-Oki earthquake in Japan. The time history of quasi-static slip along the plate interface, based on small repeating earthquakes that were part of the migrating seismicity, suggests that two sequences involved slow-slip transients propagating toward the initial rupture point. The second sequence, which involved large slip rates, may have caused substantial stress loading, prompting the unstable dynamic rupture of the mainshock. PUBLICATION ABSTRACT
3-D frequency-domain full waveform inversion (FWI) is applied on North Sea wide-azimuth ocean-bottom cable data at low frequencies (≤10 Hz) to jointly update vertical wave speed, density and quality ...factor Q in the viscoacoustic VTI approximation. We assess whether density and Q should be viewed as proxy to absorb artefacts resulting from approximate wave physics or are valuable for interpretation in the presence of soft sediments and gas cloud. FWI is performed in the frequency domain to account for attenuation easily. Multiparameter frequency-domain FWI is efficiently performed with a few discrete frequencies following a multiscale frequency continuation. However, grouping a few frequencies during each multiscale step is necessary to mitigate acquisition footprint and match dispersive shallow guided waves. Q and density absorb a significant part of the acquisition footprint hence cleaning the velocity model from this pollution. Low Q perturbations correlate with low-velocity zones associated with soft sediments and gas cloud. However, the amplitudes of the Q perturbations show significant variations when the inversion tuning is modified. This dispersion in the Q reconstructions is however not passed on the velocity parameter suggesting that cross-talks between first-order kinematic and second-order dynamic parameters are limited. The density model shows a good match with a well log at shallow depths. Moreover, the impedance built a posteriori from the FWI velocity and density models shows a well-focused image with however local differences with the velocity model near the sea bed where density might have absorbed elastic effects. The FWI models are finally assessed against time-domain synthetic seismogram modelling performed with the same frequency-domain modelling engine used for FWI.
Supraglacial debris affects glacier mass balance as a thin layer enhances surface melting, while a thick layer reduces it. While many glaciers are debris‐covered, global glacier models do not account ...for debris because its thickness is unknown. We provide the first globally distributed debris thickness estimates using a novel approach combining sub‐debris melt and surface temperature inversion methods. Results are evaluated against observations from 22 glaciers. We find the median global debris thickness is ∼0.15 ± 0.06 m. In all regions, the net effect of accounting for debris is a reduction in sub‐debris melt, on average, by 37%, which can impact regional mass balance by up to 0.40 m water equivalent (w.e.) yr‐1. We also find recent observations of similar thinning rates over debris‐covered and clean ice glacier tongues is primarily due to differences in ice dynamics. Our results demonstrate the importance of accounting for debris in glacier modeling efforts.
Plain Language Summary
Many glaciers around the world have a layer of debris (boulders, rocks, and sand) covering the underlying ice over much of the glacier surface, yet global glacier models do not account for debris because the debris thickness is unknown. Here we provide the first estimates of debris thickness for debris‐covered glaciers globally and show the debris substantially reduces regional glacier mass loss. We also find that recent observations that debris‐covered and clean ice glaciers are thinning at similar speeds is primarily due to differences in how glaciers flow. Our results fundamentally advance our ability to account for debris in glacier reconstructions, landscape evolution models, hazard assessments, and glacier projections of glacier runoff and their contribution to sea‐level rise.
Key Points
We produce the first distributed global debris thickness estimates
Accounting for debris significantly reduces regional glacier mass loss
The similar thinning rates of debris‐covered and clean ice glaciers in High Mountain Asia is primarily caused by differences in ice dynamics
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