Geophysical Journal International

SummaryIn this work, a novel method has been developed to remove the north-south stripe noise in the Level-2 spherical harmonic coefficient products collected by the Gravity Recovery and Climate Experiment (GRACE) mission. The proposed method extracts the stripe noise from the Equivalent Water Height (EWH) map via the Multivariate Variational Mode Decomposition algorithm. The idea behind our method is to extract the co-frequency mode in multiple-channel series in the longitude direction. The parameters of our method are empirically determined. The investigation in a closed-loop simulation proves the improvement of our methods compared with the Singular Spectrum Analysis Spatial (SSAS) filter. Subsequently, the spatial-domain and spectral-domain investigations are conducted by using real GRACE data. Our method only suppresses stripe noise at low latitudes (30°S∼30°N) and imposes an order-dependent impact on spherical harmonic coefficients but with potential over-smoothing. Meanwhile, the well-documented water level proves that our method further reduces outliers in a time series of localized mass variations compared with the SSAS filter. More importantly, users are allowed to reduce the filtering strength of our method to preserve small-scale strong signals while suppressing stripe noise. Moreover, noise levels over the ocean at low latitudes are evaluated as well. The noise level of our method using empirical parameters is 32.48 mm of EWH, with 31.54 and 53.52 mm for SSAS and DDK6, respectively. Our work introduces a novel method to address the issue of north-south stripe noise in the spatial domain.

SummaryIn anticipation of a forthcoming scientific deep drilling initiative within the Western Alps near Balmuccia, Italy, a high-resolution seismic survey is performed at the proposed drill site. This site is situated within the Ivrea Verbano Zone (IVZ), characterized by lower-crustal materials and fragments of upper mantle rocks exposed adjacent to the Insubric Line. The 2-km-long seismic survey crosses an isolated km-scale outcrop of peridotite near the town of Balmuccia. Applying P-wave traveltime tomography, a substantial contrast in seismic velocities is identified, with velocities in the range of 1–8 km s−1. The peridotite displays velocities ranging from 6 to 8 km s−1. The higher velocities near 8 km s−1 are consistent with laboratory measurements on small-scale samples, while the low velocity areas within the peridotite body reflect the influence of fractures and faults. The mean velocity derived for the peridotite body is ca. 7 km s−1. The reflection seismic analysis reveals subvertical reflectors positioned at the peridotite boundaries mapped at the surface, converging at a depth of ca. 0.175 km b.s.l. which images a lens-like structure for the peridotite body. However, the area beneath the imaged lens and the deeper Ivrea Geophysical Body (IGB) suggested by earlier studies is not well imaged, which leaves room for other interpretations regarding the relationship of these two bodies. Prior geophysical investigations provide only approximate depth estimates for the top of the IGB, spanning between 1–3 km depth b.s.l. Although the reflection data does not exhibit a series of continuous reflectors beneath the peridotite, a prominent reflection at ca. 1.3 km depth may indicate the top of the IGB.

SummaryInduced Polarization (IP) effects can significantly affect and superimpose the inductive earth response, leading to heavily distorted data and, if overlooked, false geological interpretation. In this paper, we implemented the Levenberg-Marquardt (LM) and very fast simulated annealing (VFSA) algorithms to recover induced polarization effects from central loop transient electromagnetic (TEM) data. To incorporate the IP effect in the TEM response, we used the Cole-Cole parameterization, maximum phase angle (MPA), maximum imaginary conductivity (MIC), and Jeffrey transform of Cole-Cole parameters. The result of 1D forward calculation and inversion of synthetic TEM data revealed that the Cole-Cole parametrization is more robust and reliable than MPA, MIC, and Jeffrey transform, and that the synthetic data were well fitted and IP parameters well recovered using this model. However, the incorporation of the IP effect leads to a highly non-linear and non-unique inverse problem which requires an accurate starting model, especially for LM inversion. To evaluate the performance of our algorithm using field data, we carried out a 1D inversion of TEM data acquired along a profile that traverses a waste site located near Cologne, Germany. Furthermore, to obtain a priori information and validate the result of TEM data modeling, we conducted an electrical resistivity tomography (ERT) and time-domain IP (TDIP) survey along the TEM profile. A 2D inversion was used to retrieve the Cole-Cole parameters as input for TEM interpretation. By including the IP information, the TEM field data can be explained quantitively, and a consistent and improved interpretation of the waste body is achieved.

AbstractMining operations result in changes of the subsurface stress field that can lead to the occurrence of microseismic events. The development of strategies for forecasting and avoidance of significant events is crucial for safe and efficient operations of mines. One such example, discussed here is the observed induced microseismicity in soft rock potash mines. It is primarily driven by the rock excavations but can also be triggered by preceding events or can result from the delayed effects of plastic creep of soft rocks. Therefore, it is important from seismic hazard assessment and risk mitigation points of view to understand the statistical aspects of microseismicity in potash or other types of mines. In this study, the temporal evolution of the induced microseismicity from a potash mine in Saskatchewan is analyzed and modeled. Specifically, the epidemic type aftershock sequence (ETAS) model is used to approximate the occurrence rate of the induced mining microseismicity. The estimated parameters signify that the microseismicity displays swarm-type characteristics with limited inter-event triggering. Moreover, the Bayesian predictive framework is used to compute the probabilities of the occurrences of the largest expected events above a certain magnitude for prescribed forecasting time intervals during the evolution of the sequence. This approach for computing the probabilities allows one to incorporate fully the uncertainties of the model parameters. The Markov Chain Monte Carlo (MCMC) sampling of the posterior distribution are used to generate parameter chains to quantify their variability. Furthermore, several statistical tests are conducted to assess the credibility of the obtained retrospective forecasts compared to the observed microseismicity. The obtained results show that the developed approach can accurately forecast the number of events and intensity of the sequence. It also provides a framework for computing the probabilities for the largest expected events.

SummaryLarge-scale and high-resolution seismic modelling are very significant to simulating seismic waves, evaluating earthquake hazards, and advancing exploration seismology. However, achieving high-resolution seismic modelling requires substantial computing and storage resources, resulting in a considerable computational cost. To enhance computational efficiency and performance, recent heterogeneous computing platforms, such as Nvidia Graphics Processing Units (GPUs), natively support half-precision floating-point numbers (FP16). FP16 operations can privide faster calculation speed, lower storage requirements and greater performance enhancement over single-precision floating-point numbers (FP32), thus providing significant benefits for seismic modelling. Nevertheless, the inherent limitation of fewer 16-bit representations in FP16 may lead to severe numerical overflow, underflow, and floating-point errors during computation. In this study, to ensure stable wave equation solutions and minimize the floating-point errors, we employ a scaling strategy to adjust the computation of FP16 arithmetic operations. For optimal GPU floating-point performance, we implement a 2-way single instruction multiple data (SIMD) within the floating-point units (FPUs) of CUDA cores. Moreover, we implement an earthquake simulation solver for FP16 operations based on curvilinear grid finite-difference method (CGFDM) and perform several earthquake simulations. Comparing the results of wavefield data with the standard CGFDM using FP32, the errors introduced by FP16 are minimal, demonstrating excellent consistency with the FP32 results. Performance analysis indicates that FP16 seismic modelling exhibits a remarkable improvement in computational efficiency, achieving a speedup of approximately 1.75 and reducing memory usage by half compared to the FP32 version.

SummaryThe ratio of the magnetic power spectrum and the secular variation spectrum measured at the Earth’s surface provides a time scale τsv(l) as a function of spherical harmonic degree l. τsv is often assumed to be representative of time scales related to the dynamo inside the outer core and its scaling with l is debated. To assess the validity of this surmise and to study the time variation of the geomagnetic field $\dot{B}$ inside the outer core, we introduce a magnetic time-scale spectrum τ(l, r) that is valid for all radius r above the inner core and reduces to the usual τsv at and above the core–mantle boundary (CMB). We study τ in a numerical geodynamo model. At the CMB, we find that τ ∼ l−1 is valid at both the large and small scales, in agreement with previous numerical studies on τsv. Just below the CMB, the scaling undergo a sharp transition at small l. Consequently, in the interior of the outer core, τ exhibits different scaling at the large and small scales, specifically, the scaling of τ becomes shallower than l−1 at small l. We find that this transition at the large scales stems from the fact that the horizontal components of the magnetic field evolve faster than the radial component in the interior. In contrast, the magnetic field at the CMB must match onto a potential field, hence the dynamics of the radial and horizontal magnetic fields are tied together. The upshot is τsv becomes unreliable in estimating time scales inside the outer core. Another question concerning τ is whether an argument based on the frozen-flux hypothesis can be used to explain its scaling. To investigate this, we analyse the induction equation in the spectral space. We find that away from both boundaries, the magnetic diffusion term is negligible in the power spectrum of $\dot{B}$. However, $\dot{B}$ is controlled by the radial derivative in the induction term, thus invalidating the frozen-flux argument. Near the CMB, magnetic diffusion starts to affect $\dot{B}$ rendering the frozen-flux hypothesis inapplicable. We also examine the effects of different velocity boundary conditions and find that the above results apply for both no-slip and stress-free conditions at the CMB.

SummaryFor seismographic stations with short acquisition duration, the signal-to-noise ratios (SNRs) of ambient noise cross-correlation functions (CCFs) are typically low, preventing us from accurately measuring surface wave dispersion curves or waveform characteristics. In addition, with noisy CCFs, it is difficult to extract relatively weak signals such as body waves. In this study, we propose to use local attributes to improve the SNRs of ambient noise CCFs, which allows us to enhance the quality of CCFs for stations with limited acquisition duration. Two local attributes: local cross-correlation and local similarity, are used in this study. The local cross-correlation allows us to extend the dimensionality of daily CCFs with computational costs similar to global cross-correlation. Taking advantage of this extended dimensionality, the local similarity is then used to measure non-stationary similarity between the extended daily CCFs with a reference trace, which enables us to design better stacking weights to enhance coherent features and attenuate incoherent background noises. Ambient noise recorded by several broadband stations from the USArray in North Texas and Oklahoma, the Superior Province Rifting EarthScope Experiment in Minnesota and Wisconsin and a high-frequency nodal array deployed in the northern Los Angeles basin are used to demonstrate the performance of the proposed approach for improving the SNR of CCFs.

SummaryPassive surface-wave methods have found extensive application in near-surface investigation due to their benefits of low costs, noninvasiveness, and high accuracy. Linear arrays are usually adopted in urban environments for their convenience and efficiency. However, the distribution of noise sources in densely populated urban areas varies rapidly in time and space, making it challenging to estimate accurate dispersion spectra using a linear array. To solve this problem, we propose a polarization analysis-based azimuthal correction method. We first obtain the azimuth of each segment by calculating the correlation coefficient of three-component ambient noise data. The normalized correlation coefficient is then applied for quality control to select reliable segments. For selected segments, the overestimated velocity caused by directional sources are corrected to obtain accurate dispersion spectra. A synthetic test is conducted to demonstrate the feasibility of our method. Compared with the dispersion spectra obtained without any correction, the dispersion spectra obtained following the suggested scheme are more consistent with the theoretical dispersion curves. Two real-world examples at crossroads show the superiority of the proposed technique in obtaining higher-resolution dispersion energy and more accurate phase velocities. In addition, our approach can attenuate the artifacts and improve the dispersion measurements.

SummaryUsing forward mantle convection models starting at 140 Ma, and assimilating plate reconstructions as surface velocity boundary condition, we predict present-day mantle structure and compare them with tomography models, using geoid as an additional constraint. We explore a wide model parameter space, such as different values of Clapeyron slope and density change across 660 km, density and viscosity of the thermochemical piles at the core-mantle boundary (CMB), internal heat generation rate, and model initiation age. We also investigate the effects of different strengths of a weak layer below 660 km and weaker asthenosphere and slabs. Our results suggest that slab structures at different subduction zones are sensitive to the viscosity of the asthenosphere, strength of slabs, values of Clapeyron slope and the density and viscosity of the thermochemical piles, while different internal heat generation rates do not affect the slab structures. We find that with a moderately weak asthenosphere (1020 Pas) and strong slabs, the predicted slab structures are consistent with the tomography models, and the observed geoid is also matched well. Moreover, our models successfully reproduce the degree-2 structure of the lower mantle beneath Africa and the Pacific, also known as Large Low Shear Velocity provinces (LLSVPs). A moderate Clapeyron slope of -2.5 MPa/K at 660 km aids in slab stagnation while higher values result in massive slab accumulation at that depth, ultimately leading to slab avalanches. We also find that the convective patterns in the thermal and thermochemical cases with slightly denser LLSVPs are similar, although the geoid amplitudes are lower for the latter. However, with more dense LLSVPs, the slabs cannot perturb them and no plumes are generated. Plumes arise as thermal instabilities from the edges of the LLSVPs, when cold and viscous slabs perturb them. While our predicted plume locations are consistent with the observed hotspot locations, matching the plume structures in tomography models is difficult. These plumes are essential in fitting the finer features of the observed geoid. In longer-duration models, more voluminous subducted material reaches the CMB, which tends to erode the LLSVPs significantly, and yields a poor fit to the observed geoid. Our results suggest that with the presence of a thin, moderately weak layer below 660 km, a slightly dense LLSVP, and Clapeyron slope of -2.5 MPa/K, the velocity anomalies in seismic tomography and the long-wavelength geoid can be matched well. One of the limitations of our models is that the assimilated plate motion history may be too short to overcome arbitrary initial conditions effects. Also, assimilated true plate velocities in our models may not represent the true convective vigor of the Earth.

SummaryMode conversion of P waves at the boundary between Earth's crust and upper mantle, when analyzed using receiver functions (RFs), allows characterization of Earth structure where seismic station density is high and earthquake sources are favorably distributed. We applied two ensemble decision tree algorithms – Random Forest (RanFor) and eXtreme Gradient Boost (XGBoost) – to synthetic and real RF data to assess these machine learning techniques' potential for crustal imaging when available data are sparse. The synthetic RFs, entailing both sharp increases in seismic velocity across the Moho and gradational Moho structures, calculated with and without added random noise, correspond to idealized crustal structures: a dipping Moho, Moho offset by crustal-scale faults, anti- and synform Moho structures and combinations of these. The RanFor/XGBoost algorithm recovers input structures well regardless of event-station distributions. Useful crustal and upper mantle seismic velocities can also be determined using RanFor and XGBoost, making it possible to image crustal thickness and P and S wave velocities simultaneously from receiver functions alone. We applied the trained RanFor/XGBoost to receiver functions determined from real seismic data recorded in the contiguous U.S., producing a map of the Moho and P and S wave velocities of the lowermost crust and uppermost mantle. Use of XGBoost, which evaluates residuals between input RFs and ground-truth to update the decision tree using the gradient of a penalty function, improves the crustal thickness estimates.

SummaryDuring the inversion of seafloor topography (ST) using the backpropagation neural network (BPNN), the random selection of parameters may decrease the accuracy. To address this issue and achieve a more efficient global search, this paper introduces a genetic algorithm-backpropagation (GA-BP) neural network. Benefiting from the global search and parallel computing capabilities of the GA, this study refines the seafloor topography of the South China Sea using multi-source gravity data. The results indicate that the GA-BP model, with a root mean square (RMS) value of 126.0 m concerning ship-measured water depths. It is noteworthy that when dealing with regions characterized by sparse survey line distributions, the GA-BP neural network stronger robustness compared to BPNN, showing less sensitivity to the distribution of survey data. Furthermore, the paper explores the influence of different data preprocessing methods on the neural network inversion of sea depths. This research introduces an optimization algorithm that reduces instability during BPNN initialization, resulting in a more accurate prediction of seafloor topography.

SummaryOn 6 February 2023, an Mw 7.8 left-lateral strike-slip fault earthquake occurred on the East Anatolian Fault Zone (EAFZ) in Türkiye. This study examined the spatial variation of the stress field around Türkiye better to understand the generation process of this event. We first combined focal mechanisms around Türkiye, created a dataset consisting of 2984 focal mechanisms, and conducted stress tensor inversion. The results showed that the maximum compressional axis near the EAFZ was oriented north-south and slightly varied along the strike. Moreover, the relative magnitude of north-south compressional stress gradually increases from south to north, and the stress regime changes from a normal fault stress regime to a strike-slip fault regime. The stress change caused by the Mw 7.8 mainshock does not explain this lateral pattern, implying that this stress regime transition existed before the mainshock. This suggests that shear stress on the EAFZ was low in this southern segment because it was unfavourably oriented to the regional stress field. Previous studies have reported that the Mw 7.8 mainshock rupture started at a splay fault, first propagated through the central and northern segments and then backpropagated with a time delay toward the southern segment, where it caused a significant but relatively small slip. The preexisting along-strike shear stress variation on the fault may have contributed to the smaller and delayed coseismic slip in the southern segment than in the central and northern segments. Moreover, the mainshock rupture possibly caused stress rotation locally near the central segment where the magnitudes of the vertical and north-south compressional stresses were almost equal.

SummaryWe present a novel strategy for performing joint inversion with guided fuzzy c-means (GFCM) clustering coupling and apply it to electrical resistivity tomography (ERT) and ambient noise surface wave (ANSW) data. To accurately extract a priori clustering information, we use density peak clustering (DPC) rather than fuzzy c-means (FCM). The number and centres of resistivity and shear-wave velocity a priori clusters are extracted by DPC and then used to guide the joint inversion with the GFCM clustering coupling of ERT and ANSW data. Synthetic and field data are used to evaluate the flow and algorithm of DPC-GFCM clustering joint inversion. The results of synthetic examples show that the models recovered by the DPC-GFCM clustering joint inversion are nearly the same as the true models and are more accurate than those inverted using individual inversion and FCM-GFCM clustering joint inversion. In the field case, the depths of the stratigraphic interfaces shown in the resistivity and shear-wave velocity models inverted by DPC-GFCM clustering joint inversion are nearly consistent with those from the drilling data. In contrast, the strata recovered by the individual inversion and FCM-GFCM clustering joint inversion significantly differ from the drilling results. Both the synthetic and field examples verify the effectiveness of the DPC-GFCM clustering coupling method used for the joint inversion of ERT and ANSW data acquired from the near surface with strong heterogeneity. This novel approach can also be applied to other types of geophysical data.

SummaryAirborne magnetics have found few applications in investigating basalt-trapped areas because anomaly interferences from deep and shallow sources prevent clear identification of subjacent dyke systems. The structural positioning of dykes is of major importance in basin studies due to their role as a heat source for maturing organic matter and plumbing capacity to feed intrusive bodies and surface lava flows. Aeromagnetic data in such a scenario can outline faults and the basin framework but faces difficulties in identifying the distribution of dykes seated at different depth levels. We present a procedure that sequentially combines conventional processing techniques to identify and retrieve the magnetic anomaly content with two-dimensional (2D) properties, as expected from tabular dykes with contrasting magnetic properties with respect to the background medium. The mean direction of 2D anomalies is quantitatively evaluated by tracking the directions in which the horizontal component of the transformed anomaly mostly vanishes. The observed field is then cosine-direction filtered to retain the anomaly content along this mean direction. Once isolated, the filtered 2D content of the anomaly is interpreted with multiple thin-sheet models to determine the dyke distribution and their respective depths to the top. The inferred depths are interpreted concerning basin stratigraphic markers to recognize dykes possibly serving as a heat source for geothermal or petroleum and gas maturation, acting as compartments to aquifer systems, or determining the location of former conduits once feeding the lava flow volcanism. The developed procedure is applied to the Ponta Grossa Dyke Swarm, along its North-western continuation beneath the basalt-capped sedimentary sequences of the Palaeozoic Paraná Basin. The distribution of the dykes recognizes a sequence confined to the bottom Paleozoic formations with petroleum and gas potential, a sequence intercepting the upper layers forming the Guarani aquifer system (GAS), and dykes at different depth levels within the basalt Serra Geral traps, indicative of at least two feeding events supplying the Mesozoic surface lava flows.

SummaryDistributed acoustic sensing (DAS) enables high-density sampling of seismic wavefields at low cost compared to conventional geophones. This capability facilitates structural detection of a municipal solid waste (MSW) landfill, which is important for protecting the surrounding ecosystem. However, processing the vast amount of data from DAS array for ambient noise imaging can be computationally intensive. To address this, we employed the common-midpoint two-station (CMP-TS) analysis to enhance the efficiency of ambient noise imaging in the MSW landfill. CMP-TS analysis involves selecting pairs of traces at equal distances on both sides with the subarray midpoint as symmetry, which reduces the number of DAS array recordings for cross-correlation calculations. After positioning the DAS arrays linearly on top of the MSW landfill to automatically collect ambient noise, we used the CMP-TS analysis in the cross-correlation calculations to speed up the measurement of dispersion. The S-wave velocity structure of the study region was obtained quickly by inverting the extracted dispersion curves using the gradient optimization method. Ambient noise imaging based on CMP-TS analysis with DAS was applied to a test of an area-type MSW landfill. The resulting S-wave velocity section revealed a discontinuous low-velocity zone, validated by the high-density resistivity method. This low-velocity zone was interpreted as containing leachate from waste decomposition, and its discontinuity may be caused by excessive differences in the waste residues settling rates under compaction. Employing CMP-TS analysis in ambient noise data collected by DAS offers more cost-effective monitoring and a reliable basis for environmental pollution prevention and control.

SummaryA regional approach is developed for high-resolution gravity anomaly recovery from the full airborne gravity gradient tensor (GGT) based on the radial basis function (RBF) technique. The analytical expressions that link the full GGT to the gravity anomaly based on Poisson wavelets are developed, where the closed formulas of the associated derivatives of Poisson wavelets are deduced. Based on this approach, the gravity anomalies at a mean resolution of ∼ 0.15 km over the Kauring Test Range in Australia are recovered by using the local airborne GGT. The results show that the solution computed from the vertical component provides the best quality when a single component is used, whereas the model computed from the curvature component performs the worst. Moreover, the incorporation of two components magnifies the gravity anomalies and further improves the fit with the terrestrial and airborne gravity data, compared with the solutions computed from individual components. However, the solutions calculated by additionally merging one or more components provide comparable qualities with the models calculated by fusing two components only. Finally, the solution is computed by merging the full airborne GGT, and the standard deviation of the misfits against the terrestrial gravity data is 0.788 mGal. Further comparisons with the Fourier transformation and equivalent source method demonstrate that the proposed approach has slightly better performance. The proposed method is numerically efficient and offers a better data adaptation, which is useful for high-resolution gravity data recovery in managing huge number of gravity gradient data.

SummaryBefore inverting Moho topography, the traditional Parker-Oldenburg method requires the determination of two important hyperparameters, the average Moho depth and Moho density contrast. The selection of these two hyperparameters will directly affect the inversion results. In this paper, a new method for estimating hyperparameters is proposed which is used to improve the Parker-Oldenburg method. The new method is improved by using simulated annealing to accurately estimate the average Moho depth and Moho density contrast based on the relationship between Moho depths and corresponding gravity anomalies at seismic control points. Synthetic tests show that compared to the improved Bott's method and the trial and error method, our method reduces the error in Moho density contrast and average Moho depth by 0.83% and 1.81% respectively. In addition, compared with the trial and error method, our method greatly improves the computational efficiency. In a practical example, we apply this method to invert the Moho topography in the northern South China Sea. The inversion results show that the Moho topography in the northern South China Sea ranges from 8.2 to 33 km. The root mean squared error between our Moho topography and the seismic validation points is 0.94 km. Compared with the CRUST 1.0 model, our Moho topography is more accurate.

SummaryStrong ground shaking has the potential to generate significant dynamic strains in shallow materials such as soils and sediments, thereby inducing nonlinear site response resulting in changes in near-surface materials. The nonlinear behavior of these materials can be characterized by an increase in wave attenuation and a decrease in the resonant frequency of the soil; these effects are attributed to increased material damping and decreased seismic wave propagation velocity, respectively. This study investigates the “in-situ” seismic velocity changes and the predominant ground motion frequency evolution during the 2016 Kumamoto earthquake sequence. This sequence includes two foreshocks (Mw6, Mw6.2) followed by a mainshock (Mw7.2) that occurred 24 h after the last foreshock. We present the results of the seismic velocity evolution during these earthquakes for seismological records collected by the KiK-net (32 stations) and K-NET (88 stations) networks between 2002 and 2020. We analyze the impulse response and autocorrelation functions to investigate the nonlinear response in near-surface materials. By comparing the results of the impulse response and autocorrelation functions, we observe that a nonlinear response occurs in near-surface materials. We then quantify the velocity reductions that occur before, during, and after the mainshock using both approaches. This allows us to estimate the “in situ” shear modulus reduction for different site classes based on VS30 values (VS30 < 360 m/s, 360 <VS30 < 760 m/s, VS30 > 760 m/s). We also establish the relationships between velocity changes, shear modulus reduction, variations in predominant ground motion frequencies, and site characteristics (VS30). The results of this analysis can be applied to site-specific ground motion modeling, site response analysis, and the incorporation of nonlinear site terms into ground motion models.

SummaryEvidence that the Earth’s surface is divided into a tessellation of piece-wise rigidly translating plates is the primary observation supporting the solid-state creep-enabled convection paradigm, utilised to investigate evolution of the Earth’s mantle. Accordingly, identifying the system properties that allow for obtaining dynamically generated plates remains a primary objective in numerical global mantle convection simulations. The first challenge for analysing fluid dynamic model output for the generation of rigid plates is to identify candidate plate boundaries. Here, we utilise a previously introduced numerical tool for plate boundary detection which employs a user specified threshold (tolerance) to automatically detect candidate plate boundaries. The numerical tool is applied with different sensitivities, to investigate the nature of the surface velocity fields generated in three calculations described in earlier work. The cases examined differ by the values that they specify for the model yield stress, a parameter that can allow the formation of tightly focussed bands of surface deformation. The three calculations we examine include zones comprising possible plate boundaries that are characterised by convergence, divergence, and strike-slip behaviour. Importance of the potential plate boundaries is assessed by examining the rigidity of the inferred model generated plates. The rigidity is measured by comparing the model velocities to the rigid rotation velocities implied by the statistically determined Euler poles for each candidate plate. We quantify a lack in rigidity by calculating a deformity field based on disagreement of actual surface velocity with rotation about the Euler pole. For intermediate yield stress and boundary detection threshold value, we find that the majority of the model surface can translate almost rigidly about distinct plate Euler poles. Regions that conform poorly to large-scale region rigid translation are also obtained but we find that generally these regions can be decomposed into subsets of smaller plates with a lower tolerance value. Alternatively, these regions may represent diffuse boundary zones. To clarify the degree to which the mantle convection model behaviour shows analogues with Earth’s current-day surface motion, we apply the plate boundary detection and Euler pole calculation methods to previously published terrestrial strain-rate data. Strong parallels are found in the response of the terrestrial data and mantle convection calculations to the threshold value, such that appropriate choice of that parameter results in very good agreement between observations and convection model character. We conclude that plates generated by fluid dynamic convection models can exhibit motion that is markedly rigid, and define statistics (plateness) and fields (deformity) by which the generation of self-consistently determined plate rigidity can be quantified, as well as describing how plate recognition might be optimized. We also note that in agreement with the Earth’s current state, we obtain a dozen dominant plates in the case exhibiting the most plate-like (rigid) surface, suggesting that this approximate number of plates is perhaps intrinsic to the geometry, surface area and physical properties of Earth’s mantle.

SummaryThe mechanism responsible for the lateral expansion and uplift of the eastern Tibetan Plateau remains a topic of ongoing debate, partly due to discrepancies in the results of seismic velocity and anisotropy. In local earthquake tomography, hypocentral uncertainties can cause significant errors in the tomographic model. However, this issue has received limited attention in previous studies. In this work, we employ the weighted least-squares (WLS) method to solve the tomographic inversion problem. A power exponent coefficient, which is called weighting level, is introduced into the weighting matrix to control the relative contribution of the data with different hypocentral errors to the final tomographic result. Our data set contains high-quality Pg, Pn and Sg arrival times of local earthquakes recorded by the dense Chinese seismic network in eastern Tibet during 2008 to 2022. We comprehensively analyze the inversion results derived from the WLS inversions with different weighting levels to evaluate the robustness of isotropic velocity anomalies and azimuthal anisotropy. The most robust feature of our results is a striking low-velocity (low-Vp) zone surrounded by high-velocity (high-Vp) anomalies and fault parallel fast-velocity directions (FVDs) of azimuthal anisotropy in the lower crust beneath the western side of the Longmenshan fault zone. Taking into account many previous results of the region, we deem that the low-Vp zone reflects hot and wet upwelling flow from the deep asthenosphere, which ascends to the lower crust along the fault zone. At the NE margin of the Tibetan Plateau, significant low-Vp anomalies exist in the lower crust and the FVDs are consistent with the motion direction of the Tibetan block revealed by GPS observations. We think that lower crustal flow exists beneath NE Tibet, which controls the plateau expansion toward the northeast. A low-Vp anomaly appears at 30 km depth beneath the Sichuan Basin. However, as the weighting level increases, the amplitude of this low-Vp anomaly decreases by more than 6%, suggesting that this low-Vp anomaly has a larger uncertainty than the other features.