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SUMMARY Applications of machine learning in seismology have greatly improved our capability of detecting earthquakes in large seismic data archives. Most of these efforts have been focused on continental shallow earthquakes, but here we introduce an integrated deep-learning-based workflow to detect deep earthquakes recorded by a temporary array of ocean-bottom seismographs (OBSs) and land-based stations in the Tonga subduction zone. We develop a new phase picker, PhaseNet-TF, to detect and pick P- and S-wave arrivals in the time–frequency domain. The frequency-domain information is critical for analysing OBS data, particularly the horizontal components, because they are contaminated by signals of ocean-bottom currents and other noise sources in certain frequency bands. PhaseNet-TF shows a much better performance in picking S waves at OBSs and land stations compared to its predecessor PhaseNet. The predicted phases are associated using an improved Gaussian Mixture Model Associator GaMMA-1D and then relocated with a double-difference package teletomoDD. We further enhance the model performance with a semi-supervised learning approach by iteratively refining labelled data and retraining PhaseNet-TF. This approach effectively suppresses false picks and significantly improves the detection of small earthquakes. The new catalogue of Tonga deep earthquakes contains more than 10 times more events compared to the reference catalogue that was analysed manually. This deep-learning-enhanced catalogue reveals Tonga seismicity in unprecedented detail, and better defines the lateral extent of the double-seismic zone at intermediate depths and the location of four large deep-focus earthquakes relative to background seismicity. It also offers new potential for deciphering deep earthquake mechanisms, refining tomographic models, and understanding of subduction processes. 

SUMMARY We present a new 3-D radially anisotropic seismic velocity model EARA2024 of the crust and mantle beneath East Asia and the northwestern Pacific using adjoint full-waveform inversion tomography. We construct the EARA2024 model by iteratively minimizing the waveform similarity misfit between the synthetic and observed waveforms from 142 earthquakes recorded by about 2000 broad-band stations in East Asia. Compared to previous studies, this new model renders significantly improved images of the subducted oceanic plate in the upper mantle, mantle transition zone, and uppermost lower mantle along the Kuril, Japan, Izu-Bonin and Ryukyu Trenches. Complex slab deformation and break-offs are observed at different depths. Moreover, our model provides new insights into the origins of intraplate volcanoes in East Asia, including the Changbaishan, Datong-Fengzhen, Tengchong and Hainan volcanic fields. 

Summary The contiguous United States has been well instrumented with broadband seismic stations due to the development of the EarthScope Transportable Array. Previous studies have provided various 3D seismic wave speed models for the crust and upper mantle with improved resolution. However, discrepancies exist among these models due to differences in both data sets and tomographic methods, which introduce uncertainties on the imaged lithospheic structure beneath North America. A further model refinement using the best data coverage and advanced tomographic methods such as full-waveform inversion (FWI) is expected to provide better seismological constraints. Initial models have significant impacts on the convergence of FWIs. However, how to select an optimal initial model is not well investigated. Here, we present a data-driven initial model selection procedure for the contiguous US and surrounding regions by assessing waveform fitting and misfit functions between the observations and synthetics from candidate models. We use a data set of waveforms from 30 earthquakes recorded by 5,820 stations across North America. The results suggest that the tested 3D models capture well long-period waveforms while showing discrepancies in short-periods especially on tangential components. This observation indicates that the smaller-scale heterogeneities and radial anisotropy in the crust and upper mantle are not well constrained. Based on our test results, a hybrid initial model combining S40RTS or S362ANI in the mantle and US.2016 for Vsv and CRUST1.0 for Vsh in the crust is compatible for future FWIs to refine the lithospheric structure of North America. 

Abstract Although transformational faulting in the rim of the metastable olivine wedge is hypothesized as a triggering mechanism of deep-focus earthquakes, there is no direct evidence of such rim. Variations of thebvalue – slope of the Gutenberg-Richter distribution – have been used to decipher triggering and rupture mechanisms of deep earthquakes. However, detection limits prevent full understanding of these mechanisms. Using the Japan Meteorological Agency catalog, we estimatebvalues of deep earthquakes in the northwestern Pacific Plate, clustered in four regions with unsupervised machine learning. Theb-value analysis of Honshu and Izu deep seismicity reveals a kink at magnitude 3.7–3.8, where thebvalue abruptly changes from 1.4–1.7 to 0.6–0.7. The anomalously highbvalues for small earthquakes highlight enhanced transformational faulting, likely catalyzed by deep hydrous defects coinciding with the unstable rim of the metastable olivine wedge, the thickness of which we estimate at$$\sim$$ $~$1 km. 

The 410‐ and 660‐km discontinuities define the top and bottom of the mantle transition zone (MTZ). The properties of these mineralogical phase transformation interfaces provide critical constraints on the dynamics, temperature, and composition of the MTZ. Triplicated body waves that bottom near these discontinuities carry rich information about them. To streamline the modeling of upper‐mantle triplications recorded at regional distances (13°–30°), we have developed a (Fast) Message Passing Interface (MPI)‐accelerated 1D (Tr)iplication Waveform (I)nversion (P)ackage (FastTrip). With triplication waveform data as input, FastTrip uses a global search method to output a set of acceptable 1D velocity models. Quantitative estimation of the model uncertainties can be further derived based on the range of acceptable models. FastTrip supports central processing unit (CPU) parallel acceleration (15,000 models within 2 hr with 100 CPUs) and is portable to other inversion problems that can be described by a relatively small number of model parameters. 

Abstract The lithospheric structure of the contiguous US and surrounding regions offers clues into the tectonic history, including interactions between subducting slabs and cratons. In this paper, we present a new radially anisotropic shear wave speed model of the upper mantle (70–410 km) of the contiguous US and surrounding regions, constrained by seismic full‐waveform inversion. The new model (named CUSRA2021) utilizes frequency‐dependent travel time measurements, from 160 earthquake events recorded by 5,280 stations. The data coverage in eastern US is improved by incorporating more intraplate earthquakes. The final model exhibits clear and detailed shear wave speed anomalies correlating well with tectonic units such as North America Craton (high‐Vs), Cascadia subduction zones (high‐Vs), Columbia Plateau (low‐Vs), Basin and Range (low‐Vs), etc. In particular, the detailed structure of the North America Craton beneath Illinois basin is revealed. The depth of high‐Vs anomaly beneath the North America Craton correlates well with S‐to‐P receiver function and SH reflection results. Besides, the radial anisotropy in the Craton lithosphere shows a layering structure, which may relate to the process of lithospheric accretion and the origin of mid‐lithosphere discontinuities.