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  • 1
    Publication Date: 2022-12-05
    Description: To explore the dynamic mechanism of continental rifting within a convergent setting, we determine the first P wave radial anisotropic tomography beneath the Woodlark rift in southeastern Papua New Guinea, which develops within the obliquely colliding zone between the Australian and southwest Pacific plates. The rift zone is depicted as localized low‐velocity anomalies with positive radial anisotropy, which rules out a dominant role of active mantle upwelling in promoting the rift development and favors passive rifting with decompression melting as main processes. Downwelling slab relics in the upper mantle bounding the rift zone are revealed based on observed high‐velocity anomalies and negative radial anisotropy, which may contribute to the ultra‐high pressure rock exhumations and rift initiation. Our observations thus indicate that the Woodlark rift follows a passive model and is mainly driven by slab pull from the northward subduction of the Solomon plate.
    Description: Plain Language Summary: The Woodlark rift in Papua New Guinea develops within the shear zone between the Australian and southwest Pacific plates and is one of the youngest and most rapidly extending continental rifts in the world. In this work, we analyze teleseismic P wave arrivals to study both 3‐D velocity and radial anisotropy structures of the upper mantle, offering new evidence to understand rift initiation under a generally convergent setting. Slab remnants in the upper mantle bordering the rift zone are detected and sinking into the deeper mantle. Downwelling of these slab segments may induce small scale return flows in the mantle and contribute to exhumation of the ultra‐high pressure rocks and rift development. Significant low‐velocity anomalies are revealed beneath the rift zone and have consistently positive radial anisotropy, which indicates a dominant strain in the horizontal plane and supports a passive rifting model, where mantle material is brought to shallower depths simply as a result of the extension of the lithosphere and melt is produced due to the lowered melting point at reduced pressure (decompression melting). Tensional stresses transferred from slab pull of the northward Solomon subduction are probably driving the rifting.
    Description: Key Points: P wave radial anisotropic structure beneath the young and highly extended Woodlark rift is constrained from teleseismic tomography. Downwelling of slab relics bordering the rift zone may contribute to ultra‐high pressure rock exhumation and rift development. Slab‐pull drives rift initiation and induces decompression melting in the upper mantle under the rift zone by horizontal stress transfer.
    Description: National Natural Science Foundation of China (NSFC) http://dx.doi.org/10.13039/501100001809
    Description: National Science Foundation (NSF) http://dx.doi.org/10.13039/100000001
    Description: MEXT | Japan Society for the Promotion of Science (JSPS) http://dx.doi.org/10.13039/501100001691
    Description: Alexander von Humboldt‐Stiftung (Humboldt‐Stiftung) http://dx.doi.org/10.13039/100005156
    Description: https://doi.org/10.7914/SN/XD_1999
    Description: https://doi.org/10.7914/SN/ZN_2010
    Keywords: ddc:551 ; Woodlark rift ; radial anisotropy ; decompression melting ; slab‐pull ; slab downwelling ; ultra‐high pressure rock
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2021-11-24
    Description: Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significantly outperform classical approaches and even achieve human-like performance under certain circumstances. However, as most studies differ in the datasets and exact evaluation tasks studied, it is yet unclear how the different approaches compare to each other. Furthermore, there are no systematic studies how the models perform in a cross-domain scenario, i.e., when applied to data with different characteristics. Here, we address these questions by conducting a large-scale benchmark study. We compare six previously published deep learning models on eight datasets covering local to teleseismic distances and on three tasks: event detection, phase identification and onset time picking. Furthermore, we compare the results to a classical Baer-Kradolfer picker. Overall, we observe the best performance for EQTransformer, GPD and PhaseNet, with EQTransformer having a small advantage for teleseismic data. Furthermore, we conduct a cross-domain study, in which we analyze model performance on datasets they were not trained on. We show that trained models can be transferred between regions with only mild performance degradation, but not from regional to teleseismic data or vice versa. As deep learning for detection and picking is a rapidly evolving field, we ensured extensibility of our benchmark by building our code on standardized frameworks and making it openly accessible. This allows model developers to easily compare new models or evaluate performance on new datasets, beyond those presented here. Furthermore, we make all trained models available through the SeisBench framework, giving end-users an easy way to apply these models in seismological analysis.
    Type: Article , NonPeerReviewed
    Format: text
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  • 3
    Publication Date: 2021-11-23
    Description: Machine Learning (ML) methods have seen widespread adoption in seismology in recent years. The abilityof these techniques to efficiently infer the statistical properties of large datasets often provides significantimprovements over traditional techniques when the number of data are large(»millions of examples). Withthe entire spectrum of seismological tasks, e.g., seismic picking and detection, magnitude and source propertyestimation, ground motion prediction, hypocentre determination; among others, now incorporating ML ap-proaches, numerous models are emerging as these techniques are further adopted within seismology. To evaluatethese algorithms, quality controlled benchmark datasets that contain representative class distributions are vital.In addition to this, models require implementation through a common framework to facilitate comparison.Accessing these various benchmark datasets for training and implementing the standardization of models iscurrently a time-consuming process, hindering further advancement of ML techniques within seismology. Thesedevelopment bottlenecks also affect ’practitioners’ seeking to deploy the latest models on seismic data, withouthaving to necessarily learn entirely new ML frameworks to perform this task. We present SeisBench as a soft-ware package to tackle these issues. SeisBench is an open-source framework for deploying ML in seismology.SeisBench standardises access to both models and datasets, whilst also providing a range of common processingand data augmentation operations through the API. Through SeisBench, users can access several seismologicalML models and benchmark datasets available in the literature via a single interface. SeisBench is built to beextensible, with community involvement encouraged to expand the package. Having such frameworks availablefor accessing leading ML models forms an essential tool for seismologists seeking to iterate and apply the nextgeneration of ML techniques to seismic data.
    Type: Article , NonPeerReviewed
    Format: text
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  • 4
    Publication Date: 2021-07-03
    Description: The Klyuchevskoy Volcanic Group is a cluster of the world's most active subduction volcanoes, situated on the Kamchatka Peninsula, Russia. The volcanoes lie in an unusual off‐arc position within the Central Kamchatka Depression (CKD), a large sedimentary basin whose origin is not fully understood. Many gaps also remain in the knowledge of the crustal magmatic plumbing system of these volcanoes. We conducted an ambient noise surface wave tomography, to image the 3‐D shear wave velocity structure of the Klyuchevskoy Volcanic Group and CKD within the surrounding region. Vertical component cross correlations of the continuous seismic noise are used to measure interstation Rayleigh wave group and phase traveltimes. We perform a two‐step surface wave tomography to model the 3‐D Vsv velocity structure. For each inversion stage we use a transdimensional Bayesian Monte Carlo approach, with coupled uncertainty propagation. This ensures that our model provides a reliable 3‐D velocity image of the upper 15 km of the crust, as well as a robust assessment of the uncertainty in the observed structure. Beneath the active volcanoes, we image small slow velocity anomalies at depths of 2–5 km but find no evidence for magma storage regions deeper than 5 km—noting the 15 km depth limit of the model. We also map two clearly defined sedimentary layers within the CKD, revealing an extensive 8 km deep sedimentary accumulation. This volume of sediments is consistent with the possibility that the CKD was formed as an Eocene‐Pliocene fore‐arc regime, rather than by recent (〈2 Ma) back‐arc extension.
    Description: Plain Language Summary: The Klyuchevskoy Volcanic Group is a cluster of 13 volcanoes on the Kamchatkan corner of the Pacific ring of fire. The volcanoes regularly produce large eruptions, but good knowledge of the magma plumbing system beneath the surface is still lacking. Why the Klyuchevskoy Volcanic Group volcanoes lie in the location they do, in a large low‐lying depression, is also unexplained. We undertook a seismic experiment and used the data to produce a 3‐D velocity image of the subsurface beneath the volcanoes and the depression. We found that small regions of slow seismic velocity are located beneath the active volcanoes, at 2–5 km depth below sea level. This slower velocity is probably caused by magma lying within the porous fracture spaces in this rock. The seismic velocities are much faster beneath the dormant volcanoes, suggesting they have no magma beneath them. With our velocity image, we also find that the Central Kamchatka Depression is very deep, filled with over 8 km of sediments. This supports an idea that the sediments accumulated as a fore‐arc basin over many millions of years, since 40 Ma, when the active line of volcanoes was found 100 km to the west.
    Description: Key Points: Three‐dimensional shear velocity structure of the Klyuchevskoy area was determined using coupled transdimensional Monte Carlo inversions. Slow velocity anomalies suggest magma storage beneath active volcanoes at 2–5 km depth (below sea level) but not in the midcrust. Sediments filling the Central Kamchatka Depression are 8 km deep, consistent with an origin of the depression as a fore‐arc basin.
    Description: European Union Horizon 2020 Research and Innovation Programme http://dx.doi.org/10.13039/501100007601
    Description: Russian Ministry of Education and Science http://dx.doi.org/10.13039/501100003443
    Description: Alexander von Humboldt Foundation http://dx.doi.org/10.13039/100005156
    Keywords: 551.1 ; tomography ; Central Kamchatka Depression ; transdimensional ; Bayesian ; ambient noise ; Klyuchevskoy Volcanic Group
    Type: article
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  • 5
    Publication Date: 2021-07-03
    Description: We study the crustal structure of Sri Lanka by analyzing data from a temporary seismic network deployed in 2016–2017 to shed light on the amalgamation process from a geophysical perspective. Rayleigh wave phase dispersion curves from ambient noise cross correlation and receiver functions were jointly inverted using a transdimensional Bayesian approach. The Moho depths in Sri Lanka range between 30 and 40 km, with the thickest crust (38–40 km) beneath the central Highland Complex (HC). The thinnest crust (30–35 km) is found along the west coast, which experienced crustal thinning associated with the formation of the Mannar Basin. VP/VS ratios lie within a range of 1.60–1.82 and predominantly favor a felsic to intermediate bulk crustal composition with a significant silica content of the rocks. A major intracrustal (18–27 km), slightly westward dipping (∼4.3°) interface with high VS (∼4 km/s) underneath is prominent in the central HC, continuing into the western Vijayan Complex (VC). The discontinuity might have been part of the respective units prior to the collision and could be an indicator for the proposed tilting of the Wanni Complex/HC crustal sections. It might also be related to the deep crustal HC/VC thrust contact with the VC as an indenting promontory of high VS. A low‐velocity zone in the central HC could have been caused by fluid influx generated by the thrusting process.
    Description: Key Points: Sri Lanka has mostly isostatically compensated 30–40 km thick crust. VP/VS ratios are between 1.60 and 1.82 and predominantly favor a felsic to intermediate bulk crustal composition. A midcrustal westward dipping interface could be related to the thrust contact between the Highland Complex and the Vijayan Complex.
    Keywords: 551.1 ; 551.8 ; Sri Lanka ; crustal structure
    Type: article
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  • 6
    Publication Date: 2021-07-03
    Description: Subduction zone processes and the resulting geometries at depth are widely studied by large‐scale geophysical imaging techniques. The subsequent interpretations are dependent on information from surface exposures of fossil subduction and collision zones, which help to discern probable lithologies and their structural relationships at depth. For this purpose, we collected samples from Holsnøy in the Bergen Arcs of western Norway, which constitutes a well‐preserved slice of continental crust, deeply buried and partially eclogitized during Caledonian collision. We derived seismic properties of both the lower crustal granulite‐facies protolith and the eclogite‐facies shear zones by performing laboratory measurements on cube‐shaped samples. P and S wave velocities were measured in three perpendicular directions, along the principal fabric directions of the rock. Resulting velocities agree with seismic velocities calculated using thermodynamic modeling and confirm that eclogitization causes a significant increase of the seismic velocity. Further, eclogitization results in decreased VP/VS ratios and, when associated with deformation, an increase of the seismic anisotropy due to the crystallographic preferred orientation of omphacite that were obtained from neutron diffraction measurements. The structural framework of this exposed complex combined with the characteristic variations of seismic properties from the lower crustal protolith to the high‐pressure assemblage provides the possibility to detect comparable structures at depth in currently active settings using seismological methods such as the receiver function method.
    Description: Key Points: Eclogitization of continental crust increases seismic velocities (isotropic averages up to 8.21 km/s) and decreases VP/VS ratios by ~0.04. Eclogitization coeval with deformation causes a high P wave anisotropy of up to 9%. Shear zone formation coeval with eclogitization causes changes of the seismic response of the structure.
    Description: Deutsche Forschungsgemeinschaft (DFG) http://dx.doi.org/10.13039/501100001659
    Keywords: 551.1 ; subducted continental crust ; seismic properties
    Type: article
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  • 7
    Publication Date: 2022-03-25
    Description: A new seismic model for crust and upper mantle of the south Central Andes is derived from full waveform inversion, covering the Pampean flat subduction and adjacent Payenia steep subduction segments. Focused crustal low‐velocity anomalies indicate partial melts in the Payenia segment along the volcanic arc, whereas weaker low‐velocity anomalies covering a wide zone in the Pampean segment are interpreted as remnant partial melts. Thinning and tearing of the flat Nazca slab is inferred from gaps in the slab along the inland projection of the Juan Fernandez Ridge. A high‐velocity anomaly in the mantle below the flat slab is interpreted as relic Nazca slab segment, which indicates an earlier slab break‐off triggered by the buoyancy of the Juan Fernandez Ridge during the flattening process. In Payenia, large‐scale low‐velocity anomalies atop and below the re‐steepened Nazca slab are associated with the re‐opening of the mantle wedge and sub‐slab asthenospheric flow, respectively.
    Description: Plain Language Summary: Taking advantage of the abundant information recorded in seismic waveforms, we imaged the seismic structure of the crust and upper mantle beneath central Chile and western Argentina, where the oceanic Nazca slab is subducting beneath the South American plate. The subducted Nazca slab is almost flat at a depth of 100–150 km in the north of the study area below the Pampean region, where the Juan Fernandez seamount ridge is subducting as part of the Nazca slab. The slab steepens again in the south in the Payenia region. Our model reveals pronounced low‐velocity anomalies within the Pampean flat slab along the inland projection of the Juan Fernandez Ridge, indicating that the Pampean flat slab is thinned or even torn apart. A high‐velocity anomaly is imaged beneath the flat slab, representing a former slab segment that was broken off during the slab flattening process and was overridden by the advancing young slab. Our model suggests a causal relationship between the oceanic ridge subduction and the flat slab formation. In the Payenia region, the slab re‐steepening resulted in the re‐establishment of the mantle wedge and induced hot mantle flow below the slab, which are characterized by low‐velocity anomalies in the model.
    Description: Key Points: A new seismic model for the crust and upper mantle beneath central Chile and western Argentina is presented. Thinning and tearing within the Pampean flat slab is detected along the inland projection of the Juan Fernandez Ridge. A relic slab is imaged beneath the Pampean flat slab, reflecting slab break‐off during the flattening process.
    Description: Freie Universität Berlin—China Scholarship Council
    Description: European Research Council
    Description: European Cooperation in Science and Technology (COST) http://dx.doi.org/10.13039/501100000921
    Description: Swiss National Supercomputing Center (CSCS)
    Keywords: ddc:551.1 ; ddc:622.1592
    Language: English
    Type: doc-type:article
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  • 8
    Publication Date: 2022-04-21
    Description: To constrain seismic anisotropy under and around the Alps in Europe, we study SKS shear wave splitting from the region densely covered by the AlpArray seismic network. We apply a technique based on measuring the splitting intensity, constraining well both the fast orientation and the splitting delay. Four years of teleseismic earthquake data were processed, from 723 temporary and permanent broad-band stations of the AlpArray deployment including ocean-bottom seismometers, providing a spatial coverage that is unprecedented. The technique is applied automatically (without human intervention), and it thus provides a reproducible image of anisotropic structure in and around the Alpine region. As in earlier studies, we observe a coherent rotation of fast axes in the western part of the Alpine chain, and a region of homogeneous fast orientation in the Central Alps. The spatial variation of splitting delay times is particularly interesting though. On one hand, there is a clear positive correlation with Alpine topography, suggesting that part of the seismic anisotropy (deformation) is caused by the Alpine orogeny. On the other hand, anisotropic strength around the mountain chain shows a distinct contrast between the Western and Eastern Alps. This difference is best explained by the more active mantle flow around the Western Alps. The new observational constraints, especially the splitting delay, provide new information on Alpine geodynamics. © 2021 The Author(s) 2021. Published by Oxford University Press on behalf of The Royal Astronomical Society.
    Description: Published
    Description: 1996–2015
    Description: 1T. Struttura della Terra
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 9
    Publication Date: 2022-02-11
    Description: Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significantly outperform classical approaches, achieving human-like performance under certain circumstances. However, as studies differ in the datasets and evaluation tasks, it is unclear how the different approaches compare to each other. Furthermore, there are no systematic studies about model performance in cross-domain scenarios, that is, when applied to data with different characteristics. Here, we address these questions by conducting a large-scale benchmark. We compare six previously published deep learning models on eight data sets covering local to teleseismic distances and on three tasks: event detection, phase identification and onset time picking. Furthermore, we compare the results to a classical Baer-Kradolfer picker. Overall, we observe the best performance for EQTransformer, GPD and PhaseNet, with a small advantage for EQTransformer on teleseismic data. Furthermore, we conduct a cross-domain study, analyzing model performance on data sets they were not trained on. We show that trained models can be transferred between regions with only mild performance degradation, but models trained on regional data do not transfer well to teleseismic data. As deep learning for detection and picking is a rapidly evolving field, we ensured extensibility of our benchmark by building our code on standardized frameworks and making it openly accessible. This allows model developers to easily evaluate new models or performance on new data sets. Furthermore, we make all trained models available through the SeisBench framework, giving end-users an easy way to apply these models.
    Description: This work was supported by the Helmholtz Association Initiative and Networking Fund on the HAICORE@KIT partition. J. Münchmeyer acknowledges the support of the Helmholtz Einstein International Berlin Research School in Data Science (HEIBRiDS). The authors thank the Impuls-und Vernetzungsfonds of the HGF to support the REPORT-DL project under the grant agreement ZT-I-PF-5-53. This work was also partially supported by the project INGV Pianeta Dinamico 2021 Tema 8 SOME (CUP D53J1900017001) funded by Italian Ministry of University and Research “Fondo finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese, legge 145/2018.” Open access funding enabled and organized by Projekt DEAL.
    Description: Published
    Description: e2021JB023499
    Description: 3T. Fisica dei terremoti e Sorgente Sismica
    Description: JCR Journal
    Keywords: seismic phase recognition ; deep learnig ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 10
    Publication Date: 2022-02-10
    Description: The Joint Task Force, Science Monitoring And Reliable Telecommunications (JTF SMART) Subsea Cables, is working to integrate environmental sensors for ocean bottom temperature, pressure, and seismic acceleration into submarine telecommunications cables. The purpose of SMART Cables is to support climate and ocean observation, sea level monitoring, observations of Earth structure, and tsunami and earthquake early warning and disaster risk reduction, including hazard quantification. Recent advances include regional SMART pilot systems that are the first steps to trans-ocean and global implementation. Examples of pilots include: InSEA wet demonstration project off Sicily at the European Multidisciplinary Seafloor and water column Observatory Western Ionian Facility; New Caledonia and Vanuatu; French Polynesia Natitua South system connecting Tahiti to Tubaui to the south; Indonesia starting with short pilot systems working toward systems for the Sumatra-Java megathrust zone; and the CAM-2 ring system connecting Lisbon, Azores, and Madeira. This paper describes observing system simulations for these and other regions. Funding reflects a blend of government, development bank, philanthropic foundation, and commercial contributions. In addition to notable scientific and societal benefits, the telecommunications enterprise’s mission of global connectivity will benefit directly, as environmental awareness improves both the integrity of individual cable systems as well as the resilience of the overall global communications network. SMART cables support the outcomes of a predicted, safe, and transparent ocean as envisioned by the UN Decade of Ocean Science for Sustainable Development and the Blue Economy. As a continuation of the OceanObs’19 conference and community white paper (Howe et al., 2019, doi: 10.3389/fmars.2019.00424), an overview of the SMART programme and a description of the status of ongoing projects are given.
    Description: Published
    Description: 775544
    Description: 3A. Geofisica marina e osservazioni multiparametriche a fondo mare
    Description: JCR Journal
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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