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Clustering algorithms can be applied to seismic catalogs to automatically classify earthquakes upon the similarity of their attributes, in order to extract information on seismicity processes and faulting patterns out of large seismic datasets. We describe here a Python open-source software for density-based clustering of seismicity named seiscloud, based on the pyrocko library for seismology. Seiscloud is a tool to dig data out of large local, regional, or global seismic catalogs and to automatically recognize seismicity clusters, characterized by similar features, such as epicentral or hypocentral locations, origin times, focal mechanisms, or moment tensors. Alternatively, the code can rely on user-provided distance matrices to identify clusters of events sharing indirect features, such as similar waveforms. The code can either process local seismic catalogs or download selected subsets of seismic catalogs, accessing different global seismicity catalog providers, perform the seismic clustering over different steps in a flexible, easily adaptable approach, and provide results in form of declustered seismic catalogs and a number of illustrative figures. Here, the algorithm usage is explained and discussed through an application to Northern Chile seismicity.

The 2021 volcanic eruption at La Palma, Canary Islands, was the island’s most voluminous historical eruption. Little is known about this volcano’s feeding system. During the eruption, seismicity was distributed in two clusters at ~10-14 km and ~33-39 km depth, separated by an aseismic zone. This gap coincides with the location of weak seismic swarms in 2017-2021 and where petrological data have implied pre-eruptive magma storage. Here we use seismological methods to understand the seismic response to magma transfer, with 8,488 hypocentral relocations resolving small-scale seismogenic structures, and 156 moment tensors identifying stress heterogeneities and principal axes flips. Results suggest a long-lasting preparatory stage with the progressive destabilisation of an intermediate, mushy reservoir, and a co-eruptive stage with seismicity controlled by the drainage and interplay of two localised reservoirs. Our study provides new insights into the plumbing system that will improve the monitoring of future eruptions in the island. In a new study, the authors use seismological methods to understand the eruption of La Palma 2021. Results suggest a preparatory phase of de-stabilisation of a mushy reservoir, and a co-eruptive phase with seismicity controlled by the drainage and interplay of two reservoirs.

The 2013 seismic sequence at the Castor injection platform offshore Spain, including three earthquakes of magnitude 4.1, occurred during the initial filling of a planned Underground Gas Storage facility. The Castor sequence is one of the most important cases of induced seismicity in Europe and a rare example of seismicity induced by gas injection into a depleted oil field. Here we use advanced seismological techniques applied to an enhanced waveform dataset, to resolve the geometry of the faults, develop a greatly enlarged seismicity catalog and record details of the rupture kinematics. The sequence occurred by progressive fault failure and unlocking, with seismicity initially migrating away from the injection points, triggered by pore pressure diffusion, and then back again, breaking larger asperities loaded to higher stress and producing the largest earthquakes. Seismicity occurred almost exclusively on a secondary fault, located below the reservoir, dipping opposite from the reservoir bounding fault. The 2013 Castor seismic sequence, offshore Spain, is a rare example of seismicity induced by gas storage operations. Here we show that early seismicity marked the progressive failure of a fault in response to pore pressure diffusion, while later larger earthquakes resulted by the failure of loaded asperities.

Determining outline, volume and effusion rate during an effusive volcanic eruption is crucial as it is a major controlling factor of the lava flow lengths, the prospective duration and hence the associated hazards. We present for the first time a multi-sensor thermal-and-topographic satellite data analysis for estimating lava effusion rates and volume. At the 2021 lava field of Cumbre Vieja, La Palma, we combine VIIRS + MODIS thermal data-based effusion rate estimates with DSMs analysis derived from optical tri-stereo Pléiades and TanDEM-X bi-static SAR-data. This multi-sensor-approach allows to overcome limitations of single-methodology-studies and to achieve both, high-frequent observation of the relative short-term effusion rate trends and precise total volume estimates. We find a final subaerial-lava volume of 212 × 10 6 ± 13 × 10 6 m 3 with a MOR of 28.8 ± 1.4 m 3 /s. We identify an initially sharp eruption-rate-peak, followed by a gradually decreasing trend, interrupted by two short-lived-peaks in mid/end November. High eruption rate accompanied by weak seismicity was observed during the early stages of the eruption, while during later stage the lava effusion trend coincides with seismicity. This article demonstrates the geophysical monitoring of eruption rate fluctuations, that allows to speculate about changes of an underlying pathway during the 2021 Cumbre Vieja eruption.

Earthquakes with submarine foci are generally located with high uncertainties, and their focal mechanisms are poorly resolved, due to the confinement of the monitoring network onshore and the consequent poor azimuthal coverage. The use of amphibious networks, combining ocean-bottom seismometers (OBSs) and land stations, helps to reduce the epicentral distance and the azimuth gap, thus better constraining the hypocentral locations and decreasing the focal mechanism uncertainties. A second important factor in improving the location accuracy for offshore seismicity is the use of a suitable velocity model. The objective of this paper is to study how the combination of an amphibious network with 3D crustal models can improve offshore earthquake hypocenter locations and focal mechanisms. The study area is SW Iberia near Cape St. Vincent, which generated some of the most striking earthquakes and tsunamis in Europe in past centuries, such as the 1755 Lisbon earthquake (Imax = X). We deployed an array of six broadband OBSs 200 km offshore Cape St. Vincent to study the seismicity of the region for a period of 8 months. During this period, we detected 52 earthquakes, the largest with magnitude M (mbLg) ≈ 5. Thirty-eight earthquakes are relocated using land stations in Iberia and North Africa and the OBS array with different velocity models. Focal mechanisms and moment tensors are computed for a data set of seven earthquakes based on first-motion polarities, body-wave amplitude spectra and waveform cross-correlation. We show that if we include offshore OBS data and consider accurate 3D velocity models to locate earthquakes, the focal parameter uncertainties decrease substantially, thus improving the depth constraint. We also show that the locations and focal mechanisms obtained using the amphibious network agree with the regional stress pattern in the SW Iberia region.

Accurate and automated locations of microseismic events are desirable for many seismological and industrial applications. The analysis of microseismicity is particularly challenging because of weak seismic signals with low signal-to-noise ratio. Traditional location approaches rely on automated picking, based on individual seismograms, and make no use of the coherency information between signals at different stations. This strong limitation has been overcome by full-waveform location methods, which exploit the coherency of waveforms at different stations and improve the location robustness even in presence of noise. However, the performance of these methods strongly depend on the accuracy of the adopted velocity model, which is often quite rough; inaccurate models result in large location errors. We present an improved waveform stacking location method based on source-specific station corrections. Our method inherits the advantages of full-waveform location methods while strongly mitigating the dependency on the accuracy of the velocity model. With this approach the influence of an inaccurate velocity model on the results is restricted to the estimation of travel times solely within the seismogenic volume, but not for the entire source-receiver path. We finally successfully applied our new method to a realistic synthetic dataset as well as real data.

Repeating earthquakes, or repeaters, affecting overlapping rupture patches with a similar focal mechanism, have important implications to track fault slip rates, aseismic deformation, slow earthquakes and earthquake nucleation processes. They are often detected based on highly similar waveforms. Here, we discuss earthquakes with highly anti-correlated waveforms, denoting a reversed seismogenic process at the same or a neighbouring location, which we refer to as true and quasi anti-repeaters. We first report a range such observations in different environments, including volcano seismicity, intermediate depth seismicity and injection-induced microseismicity. Then, we review conceptual models proposed to explain them. True and quasi anti-repeaters can be robustly identified via a three-component single station or distributed network data. They are key indicators for stress perturbation transients or local stress heterogeneities. Since most of these observations were explained as the response to fluid migration processes, they may help to identify and track fluid movements in the subsurface.

An earthquake swarm affected the Bransfield Strait, Antarctica, a unique rift basin in transition from intra-arc rifting to ocean spreading. The swarm, counting ~85,000 volcano-tectonic earthquakes since August 2020, is located close to the Orca submarine volcano, previously considered inactive. Simultaneously, geodetic data reported up to ~11 cm northwestward displacement over King George Island. We use a broad variety of geophysical data and methods to reveal the complex migration of seismicity, accompanying the intrusion of 0.26–0.56 km 3 of magma. Strike-slip earthquakes mark the intrusion at depth, while shallower normal faulting the ~20 km long lateral growth of a dike. Seismicity abruptly decreased after a Mw 6.0 earthquake, suggesting the magmatic dike lost pressure with the slipping of a large fault. A seafloor eruption is likely, but not confirmed by sea surface temperature anomalies. The unrest documents episodic magmatic intrusion in the Bransfield Strait, providing unique insights into active continental rifting.

In December 2017, a triplet earthquake sequence of Mw 5.8–6.1 occurred near Hojedk, southeast Iran. The sequence was not destructive, but occurred in a highly seismically active region that previously experienced the 1981–1998 Sirch-Golbaf earthquake sequence and destructive 2003 Mw 6.6 Bam earthquake. We apply a waveform inversion method based on the modeling of regional seismic broadband data to derive the point source and kinematic rupture parameters of the triplet and its five significant aftershocks. The choice of an earthquake source model with a reduced number of parameters and a sequential inversion process with several iterations result in unique and stable earthquake source solutions. Within the inversion process, we combine the modeling of low- and high-frequency seismological data to retrieve the moment tensor and the kinematic source parameters. Synthetic seismogram and spectra are generated for an accurate regional velocity model. Our results suggest that the triplet ruptured a segmented fault system, with centroid locations aligned along a single lineament. Estimation of rupture directivity suggests the activation of SE-NW structure. In conclusion, we suggest that the triplet was associated with the failure of one or more aligned blind thrust faults, oriented SE-NW and dipping to the NE, in a restraining bend between strike-slip faults in a region that is a part of the greater system of the present continental shortening in Iran.

Induced seismicity is one of the main factors that reduces societal acceptance of deep geothermal energy exploitation activities, and felt earthquakes are the main reason for closure of geothermal projects. Implementing innovative tools for real-time monitoring and forecasting of induced seismicity was one of the aims of the recently completed COSEISMIQ project. Within this project, a temporary seismic network was deployed in the Hengill geothermal region in Iceland, the location of the nation’s two largest geothermal power plants. In this paper, we release raw continuous seismic waveforms and seismicity catalogues collected and prepared during this project. This dataset is particularly valuable since a very dense network was deployed in a seismically active region where thousand of earthquakes occur every year. For this reason, the collected dataset can be used across a broad range of research topics in seismology ranging from the development and testing of new data analysis methods to induced seismicity and seismotectonics studies.Measurement(s)Seismic waveforms (seismograms) • Seismicity (Origin time, location and magnitude of earthquakes)Technology Type(s)Seismic stations (velocity sensors) • SeisComP data acquisition and processing system