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The spectral element method is currently the method of choice for computing accurate synthetic seismic wavefields in realistic 3-D earth models at the global scale. However, it requires significantly more computational time, compared to normal mode-based approximate methods. Source stacking, whereby multiple earthquake sources are aligned on their origin time and simultaneously triggered, can reduce the computational costs by several orders of magnitude. We present the results of synthetic tests performed on a realistic radially anisotropic 3-D model, slightly modified from model SEMUCB-WM1 with three component synthetic waveform 'data' for a duration of 10 000 s, and filtered at periods longer than 60 s, for a set of 273 events and 515 stations. We consider two definitions of the misfit function, one based on the stacked records at individual stations and another based on station-pair cross-correlations of the stacked records. The inverse step is performed using a Gauss–Newton approach where the gradient and Hessian are computed using normal mode perturbation theory. We investigate the retrieval of radially anisotropic long wavelength structure in the upper mantle in the depth range 100–800 km, after fixing the crust and uppermost mantle structure constrained by fundamental mode Love and Rayleigh wave dispersion data. The results show good performance using both definitions of the misfit function, even in the presence of realistic noise, with degraded amplitudes of lateral variations in the anisotropic parameter ξ. Interestingly, we show that we can retrieve the long wavelength structure in the upper mantle, when considering one or the other of three portions of the cross-correlation time series, corresponding to where we expect the energy from surface wave overtone, fundamental mode or a mixture of the two to be dominant, respectively. We also considered the issue of missing data, by randomly removing a successively larger proportion of the available synthetic data. We replace the missing data by synthetics computed in the current 3-D model using normal mode perturbation theory. The inversion results degrade with the proportion of missing data, especially for ξ , and we find that a data availability of 45 per cent or more leads to acceptable results. We also present a strategy for grouping events and stations to minimize the number of missing data in each group. This leads to an increased number of computations but can be significantly more efficient than conventional single-event-at-a-time inversion. We apply the grouping strategy to a real picking scenario, and show promising resolution capability despite the use of fewer waveforms and uneven ray path distribution. Source stacking approach can be used to rapidly obtain a starting 3-D model for more conventional full-waveform inversion at higher resolution, and to investigate assumptions made in the inversion, such as trade-offs between isotropic, anisotropic or anelastic structure, different model parametrizations or how crustal structure is accounted for. [ABSTRACT FROM AUTHOR]

Moho determination is an important issue in studying the Earth's interior structure. In accordance with the isostasy-compensation hypothesis in geodesy, it is possible to recover regional or global Moho by employing gravimetric data. The nonlinear property is one of the main difficulties in solving the inverse problem of isostasy. To effectively address this issue, we propose an improved iterative inversion method that combines 3-D integration and linear regularization to achieve an approximate nonlinear solution. To estimate the contributions of different components in the gravity-gradient tensor from the Gravity field and steady-state Ocean Circulation Explorer (GOCE), other than the vertical component, we additionally develop two joint inversion scenarios that utilize diagonal horizontal components and all five non-vertical components. The validating experiments are implemented in Qinghai–Tibet Plateau and its near zone. Simulations and applications illustrate that horizontal responses of Moho undulation are also significant. Yet the off-diagonal components provide minimal contributions, adding only 0.25 km of bias to the joint inversion results. Truncation effects serve as the primary source of systematic errors, resulting in ∼1 km error in vertical inversion results and ∼2.3 km error in joint inversion results. Then, the gravimetric Moho results are compared with CRUST1.0, and they show a generally strong correlation. Differences are obvious at the northern and eastern margins of the plateau. It is maybe due to the local changes in crust–mantle density contrasts. Upwelling of asthenospheric materials and fluid flow in the middle-lower crust are the two main factors. Based on high-precision satellite gravimetry, our study could provide new insights into the tectonic structure of Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]

The presence of seismic anisotropy at the base of the Earth's mantle is well established, but there is no consensus on the deformation mechanisms in lower mantle minerals that could explain it. Strong anisotropy in magnesium post-perovskite (pPv) has been invoked, but different studies disagree on the dominant slip systems at play. Here, we aim to further constrain this by implementing the most recent results from atomistic models and high-pressure deformation experiments, coupled with a realistic composition and a 3-D geodynamic model, to compare the resulting deformation-induced anisotropy with seismic observations of the lowermost mantle. We account for forward and reverse phase transitions from bridgmanite (Pv) to pPv. We find that pPv with either dominant (001) or (010) slip can both explain the seismically observed anisotropy in colder regions where downwellings turn to horizontal flow, but only a model with dominant (001) slip matches seismic observations at the root of hotter large-scale upwellings. Allowing for partial melt does not change these conclusions, while it significantly increases the strength of anisotropy and reduces shear and compressional velocities at the base of upwellings. [ABSTRACT FROM AUTHOR]

SUMMARY: The accuracy and sampling rate of a coseismic displacement and velocity waveform can be improved by fusing Global Navigation Satellite System (GNSS) and strong motion (SM) sensor data with a multirate Kalman filter. However, many studies have shown that the noise in GNSS coseismic waveforms includes coloured noise, and it is challenging to obtain proper GNSS and SM fusion results if the GNSS coloured noise is not accurately represented. In this paper, we propose a coloured noise multirate Kalman filter, which uses a stochastic model for modelling the GNSS coloured noise to achieve an accurate fusion of data from GNSS and SM for different sampling rates. In addition, we also propose an estimation method for the multirate Kalman filter stochastic model under coloured noise to achieve the optimal adaptive fusion of GNSS and SM data. After the reliability of the proposed method was confirmed using Monte Carlo simulations and earthquake engineering data tests, the proposed method was applied to data collected from the 2019 Mw 7.1 Ridgecrest earthquake and 2016 Mw 7.8 Kaikoura earthquake. The test results show that the proposed method can effectively fuse GNSS and SM data and accurately obtain broadband coseismic displacement and velocity waveforms. [ABSTRACT FROM AUTHOR]