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Highlights
• We show the first observations of seismo-acoustic tremor at Oldoinyo Lengai, the world's only active carbonatite volcano.
• We observe significant changes in seismic and acoustic tremor properties and their correlation in one year of data collection.
• Using satellite-based thermal data, we identify different volcanic processes (degassing, lava pond dynamics and spattering).
Abstract
We analyze volcanic tremor from Oldoinyo Lengai, Tanzania, which is currently the only active volcano on Earth producing carbonatitic lavas. Here, we use data from the recent SEISVOL deployment and focus on a co-located seismic and infrasound station about 200 m below the summit. We show the very first observations of seismo-acoustic tremor caused by carbonatitic eruptions. This seismo-acoustic tremor is highly variable throughout the ∼one year of data which we characterize by analyzing its seismic amplitude, duration, recurrence, dominant seismic frequency and harmonics. Frequency gliding occurs frequently and over short (minutes to hours) to long time scales (hours to days) and likely reflects different time-dependent mechanisms, such as evenly-spaced repeating events with a change in inter-event times, crater dynamics that alter resonators, and dike intrusions. Seismic and acoustic wavefields correlate well for stronger eruptive sequences but are only partially coherent which suggests that high-frequency seismic tremor (up to 25 Hz) may be caused by the low viscosity of the carbonatitic melt and not by ground-coupled airwaves. In addition, the comparison between seismic-acoustic and satellite InfraRed thermal data allows us to infer different volcanic activity styles which partially alternate throughout the year: intrusive activity and the construction of hornitos, degassing, activity from a lava pond, and varying styles of extrusive activity, in particular spattering. Our study provides important insights into the eruption dynamics of this peculiar volcano which suggests shallow melt storage within the crater floor.
PolarCAP – A deep learning approach for first motion polarity classification of earthquake waveforms
(2022)
Highlights
• We present PolarCAP, a deep learning model that can classify the polarity of a waveform with a 98% accuracy.
• The first-motion polarity of seismograms is a useful parameter, but its manual determination can be laborious and imprecise.
• We demonstrate that in several cases the model can assign trace polar-ity more accurately than a human analyst.
Abstract
The polarity of first P-wave arrivals plays a significant role in the effective determination of focal mechanisms specially for smaller earthquakes. Manual estimation of polarities is not only time-consuming but also prone to human errors. This warrants a need for an automated algorithm for first motion polarity determination. We present a deep learning model - PolarCAP that uses an autoencoder architecture to identify first-motion polarities of earth-quake waveforms. PolarCAP is trained in a supervised fashion using more than 130,000 labelled traces from the Italian seismic dataset (INSTANCE) and is cross-validated on 22,000 traces to choose the most optimal set of hyperparameters. We obtain an accuracy of 0.98 on a completely unseen test dataset of almost 33,000 traces. Furthermore, we check the model generalizability by testing it on the datasets provided by previous works and show that our model achieves a higher recall on both positive and negative polarities.
In this study, we determine spectral characteristics and amplitude decays of wind turbine induced seismic signals in the far field of a wind farm (WF) close to Uettingen/Germany. Average power spectral densities (PSD) are calculated from 10 min time segments extracted from (up to) 6-months of continuous recordings at 19 seismic stations, positioned along an 8 km profile starting from the WF. We identify 7 distinct PSD peaks in the frequency range between 1 Hz and 8 Hz that can be observed to at least 4 km distance; lower-frequency peaks are detectable up to the end of the profile. At distances between 300 m and 4 km the PSD amplitude decay can be described by a power law with exponent b. The measured b-values exhibit a linear frequency dependence and range from b = 0.39 at 1.14 Hz to b = 3.93 at 7.6 Hz. In a second step, the seismic radiation and amplitude decays are modeled using an analytical approach which approximates the surface-wave field. Since we observe temporally varying phase differences between seismograms recorded directly at the base of the individual wind turbines (WTs), source-signal phase information is included in the modeling approach. We show that phase differences between source signals have significant effects on the seismic radiation pattern and amplitude decays. Therefore, we develop a phase-shift-elimination-method to handle the challenge of choosing representative source characteristics as an input for the modeling. To optimize the fitting of modeled and observed amplitude decay curves, we perform a grid search to constrain the two model parameters, i.e., the seismic shear wave velocity and quality factor. The comparison of modeled and observed amplitude decays for the 7 prominent frequencies shows very good agreement and allows to constrain shear velocities and quality factors for a two-layer model of the subsurface. The approach is generalized to predict amplitude decays and radiation patterns for WFs of arbitrary geometry.
The Alpine orogeny is characterized by tectonic sequences of subduction and collision accompanied by break-off events and possibly preceded by a flip of subduction polarity. The tectonic evolution of the transition to the Eastern Alps has thus been under debate. The dense SWATH-D seismic network as a complementary experiment to the AlpArray seismic network provides unprecedented lateral resolution to address this ongoing discussion. We analyze the shear-wave splitting of this data set including stations of the AlpArray backbone in the region to obtain new insights into the deformation at depth from seismic anisotropy. Previous studies indicate two-layer anisotropy in the Eastern Alps. This is supported by the azimuthal pattern of the measured fast axis direction across all analyzed stations. However, the temporary character of the deployment requires a joint analysis of multiple stations to increase the number of events adding complementary information of the anisotropic properties of the mantle. We, therefore, perform a cluster analysis based on a correlation of energy tensors between all stations. The energy tensors are assembled from the remaining transverse energy after the trial correction of the splitting effect from two consecutive anisotropic layers. This leads to two main groups of different two-layer properties, separated approximately at 13°E. We identify a layer with a constant fast axis direction (measured clockwise with respect to north) of about 60° over the whole area, with a possible dip from west to east. The lower layer in the west shows N–S fast direction and the upper layer in the east shows a fast axis of about 115°. We propose two likely scenarios, both accompanied by a slab break-off in the eastern part. The continuous layer can either be interpreted as frozen-in anisotropy with a lithospheric origin or as an asthenospheric flow evading the retreat of the European slab that would precede the break-off event. In both scenarios, the upper layer in the east is a result of a flow through the gap formed in the slab break-off. The N–S direction can be interpreted as an asthenospheric flow driven by the retreating European slab but might also result from a deep-reaching fault-related anisotropy.
In this study, we determine spectral characteristics and amplitude decays of wind turbine induced seismic signals in the far field of a wind farm (WF) close to Uettingen, Germany. Average power spectral densities (PSDs) are calculated from 10 min time segments extracted from (up to) 6 months of continuous recordings at 19 seismic stations, positioned along an 8 km profile starting from the WF. We identify seven distinct PSD peaks in the frequency range between 1 and 8 Hz that can be observed to at least 4 km distance; lower-frequency peaks are detectable up to the end of the profile. At distances between 300 m and 4 km the PSD amplitude decay can be described by a power law with exponent b. The measured b values exhibit a linear frequency dependence and range from b=0.39 at 1.14 Hz to b=3.93 at 7.6 Hz. In a second step, the seismic radiation and amplitude decays are modeled using an analytical approach that approximates the surface wave field. Since we observe temporally varying phase differences between seismograms recorded directly at the base of the individual wind turbines (WTs), source signal phase information is included in the modeling approach. We show that phase differences between source signals have significant effects on the seismic radiation pattern and amplitude decays. Therefore, we develop a phase shift elimination method to handle the challenge of choosing representative source characteristics as an input for the modeling. To optimize the fitting of modeled and observed amplitude decay curves, we perform a grid search to constrain the two model parameters, i.e., the seismic shear wave velocity and quality factor. The comparison of modeled and observed amplitude decays for the seven prominent frequencies shows very good agreement and allows the constraint of shear velocities and quality factors for a two-layer model of the subsurface. The approach is generalized to predict amplitude decays and radiation patterns for WFs of arbitrary geometry.
Constraining the architecture of complex 3D volcanic plumbing systems within active rifts, and their impact on rift processes, is critical for examining the interplay between faulting, magmatism and magmatic fluids in developing rift segments. The Natron basin of the East African Rift System provides an ideal location to study these processes, owing to its recent magmatic-tectonic activity and ongoing active carbonatite volcanism at Oldoinyo Lengai. Here, we report seismicity and fault plane solutions from a 10-month temporary seismic network spanning Oldoinyo Lengai, Naibor Soito volcanic field and Gelai volcano. We locate 6827 earthquakes with ML -0.85 to 3.6, which are related to previous and ongoing magmatic and volcanic activity in the region, as well as regional tectonic extension. We observe seismicity down to ~17 km depth north and south of Oldoinyo Lengai and shallow seismicity (3 - 10 km) beneath Gelai, including two swarms. The deepest seismicity (~down to 20 km) occurs above a previously imaged magma body below Naibor Soito. These seismicity patterns reveal a detailed image of a complex volcanic plumbing system, supporting potential lateral and vertical connections between shallow- and deep-seated magmas, where fluid and melt transport to the surface is facilitated by intrusion of dikes and sills. Focal mechanisms vary spatially. T-axis trends reveal dominantly WNW-ESE extension near Gelai, while strike-slip mechanisms and a radial trend in P-axes are observed in the vicinity of Oldoinyo Lengai. These data support local variations in the state of stress, resulting from a combination of volcanic edifice loading and magma-driven stress changes imposed on a regional extensional stress field. Our results indicate that the southern Natron basin is a segmented rift system, in which fluids preferentially percolate vertically and laterally in a region where strain transfers from a border fault to a developing magmatic rift segment.
Highlights
• Full automatized analysis of teleseismic XKS shear wave splitting.
• Rapid analysis of large seismological data sets.
• Automated window selection and quality classification.
• Application to the USArray Transportable Array including expansion to Alaska.
• Improved statistical evidence and objectivity of derived effective splitting.
Abstract
Recent technological advances have led to community wide use of large-scale seismic experiments which produce seismic data on previously impossible scales. Standard processing procedures thus require automatization to facilitate a fast and objective analysis of the data. Among these, XKS-splitting is an important tool to derive first insights into the Earth's deformation regimes at depth by studying seismic anisotropy. Most often, shear-wave splitting is interpreted to represent crystallographic preferred orientation (CPO) of mantle minerals like olivine as dominating feature and can thus be used as a proxy of mantle flow processes. Here, we introduce an addition to the MATLAB®-based SplitRacer tool box (Reiss and Rümpker 2017) which automatizes the entire XKS-splitting procedure. This is achieved by the automatization of 1) choosing a time window based on spectral analyses and 2) categorization of results based on three different XKS-splitting methods (energy minimization, rotation correlation and splitting intensity). This provides effective and objective results for splitting as well as null-measurement results. This extension allows to use SplitRacer without a graphical interface and introduces a bootstrapping statistics as error estimate of the single layer joint splitting method. The procedures are designed to allow a fast and more objective analysis of a vast amount of data, as produced by recent seismic deployments (e.g. USArray, AlpArray). We test this automatization by applying the analysis to the USArray data set, which has approximately 1900 stations with between two to fifteen years of data. We can reproduce the general pattern of the results from former studies with the more objective automatic analysis. Based on a joint-splitting approach, we approximate the splitting effect at individual stations by a single anisotropic layer. As we include null-measurements as well as a larger data set as previous studies, we can provide improved statistical evidence for these effective splitting parameters.
Previous investigation of seismic anisotropy indicates the presence of a simple mantle flow regime beneath the Turkish-Anatolian Plateau and Arabian Plate. Numerical modeling suggests that this simple flow is a component of a large-scale global mantle flow associated with the African superplume, which plays a key role in the geodynamic framework of the Arabia-Eurasia continental collision zone. However, the extent and impact of the flow pattern farther east beneath the Iranian Plateau and Zagros remains unclear. While the relatively smoothly varying lithospheric thickness beneath the Anatolian Plateau and Arabian Plate allows progress of the simple mantle flow, the variable lithospheric thickness across the Iranian Plateau is expected to impose additional boundary conditions on the mantle flow field. In this study, for the first time, we use an unprecedented data set of seismic waveforms from a network of 245 seismic stations to examine the mantle flow pattern and lithospheric deformation over the entire region of the Iranian Plateau and Zagros by investigation of seismic anisotropy. We also examine the correlation between the pattern of seismic anisotropy, plate motion using GPS velocities and surface strain fields. Our study reveals a complex pattern of seismic anisotropy that implies a similarly complex mantle flow field. The pattern of seismic anisotropy suggests that the regional simple mantle flow beneath the Arabian Platform and eastern Turkey deflects as a circular flow around the thick Zagros lithosphere. This circular flow merges into a toroidal component beneath the NW Zagros that is likely an indicator of a lateral discontinuity in the lithosphere. Our examination also suggests that the main lithospheric deformation in the Zagros occurs as an axial shortening across the belt, whereas in the eastern Alborz and Kopeh-Dagh a belt-parallel horizontal lithospheric deformation plays a major role.
During the first two days of August 2016 a seismic crisis occurred on Brava, Cabo Verde, which – according to observations based on a local seismic network – was characterized by more than a thousand volcano-seismic signals. Brava is considered an active volcanic island, although it has not experienced any historic eruptions. Seismicity significantly exceeded the usual level during the crisis. We report on results based on data from a temporary seismic-array deployment on the neighbouring island of Fogo at a distance of about 35 km. The array was in operation from October 2015 to December 2016 and recorded a total of 1343 earthquakes in the region of Fogo and Brava; 355 thereof were localized. On 1 and 2 August we observed 54 earthquakes, 25 of which could be located beneath Brava. We further evaluate the observations with regards to possible precursors to the crisis and its continuation. Our analysis shows a significant variation in seismicity around Brava, but no distinct precursory pattern. However, the observations suggest that similar earthquake swarms commonly occur close to Brava. The results further confirm the advantages of seismic arrays as tools for the remote monitoring of regions with limited station coverage or access.
During the first two days of August 2016 a seismic crisis occurred on Brava, Cape Verde, which – according to observations based on a local seismic network – was characterized by more than thousand volcano–seismic signals. Brava is considered an active volcanic island, although it has not experienced any historic eruptions. Seismicity significantly exceeded the usual level during the crisis. We report on results based on data from a temporary seismic–array deployment on the neighbouring island of Fogo at a distance of about 35 km. The array was in operation from October 2015 to December 2016 and recorded a total of 1343 earthquakes, 355 thereof were localized. On 1 and 2 August we observed 54 earthquakes, 25 of which could be located beneath Brava. We further evaluate the observations with regards to possible precursors to the crisis and its continuation. Our analysis shows a migration of seismicity around Brava, but no distinct precursory pattern. However, the observations suggest that similar earthquake swarms commonly occur close to Brava. The results further confirm the advantages of seismic arrays as tools for the remote monitoring of regions with limited station coverage or access.