Geophysical Journal International

SummaryThe precise extraction of tidal signals from non-stationary gravity observations is a central challenge in geophysics, where accuracy is often limited by mode mixing in data preprocessing algorithms. This study evaluates the performance of the Time-Varying Filter-based Empirical Mode Decomposition (TVF-EMD) method to address this issue. We employed a progressive validation pipeline: the method was first verified on simulated signals, then rigorously tested against a high-fidelity benchmark from a superconducting gravimeter (SG), and finally applied to one month of continuous data from an Atom Gravimeter (AG) at the Yilan station. Results demonstrate that TVF-EMD dramatically suppresses mode mixing, with the energy of transient spikes in its residual being an order of magnitude lower than that from the conventional Ensemble Empirical Mode Decomposition (EEMD) method. The tidal signal reconstructed by TVF-EMD achieved the highest cross-correlation coefficient and the smallest root mean square error when compared to the theoretical gravity tide. Subsequent harmonic analysis confirmed that TVF-EMD yielded the lowest errors across all major tidal constituents. These findings validate TVF-EMD as a superior preprocessing framework for tidal analysis, particularly for enhancing the reliability of geophysical parameter inversion from short-duration records obtained with next-generation quantum sensors.

SummaryStructural boundaries are often the features of most interest geologically, but imaging them can be difficult due to wavefield scattering and interference caused by the sharp velocity contrasts. One example of this is the apparent Rayleigh-wave anisotropy (1-psi anisotropy) that has been observed near major structural boundaries using seismic arrays. The cause of the apparent anisotropy is the interference between the incident surface wave and waves scattered from velocity discontinuities. In this study, we first investigate the sensitivity of apparent anisotropy measurements to lateral boundary sharpness through 2D full waveform simulations. We demonstrate that 1-psi anisotropy can vary based on boundary sharpness, station spacing, and period of surface waves. We show that a misfit defined using triple-difference travel times, i.e. the difference in double-difference travel times between station pairs with opposite propagation directions, well characterizes the apparent anisotropy. The sensitivity kernel for this triple-difference misfit can be constructed using the adjoint method. We show that triple-difference travel times are mainly sensitive to velocity contrasts rather than absolute velocities, in contrast to double-difference travel times. With sensitivity kernels constructed, we demonstrate how triple-difference travel times can be combined with double-difference travel times into a tomography inversion. We show that by including triple-difference travel times, seismic inversions converge faster and resolve boundary and average structure better in early iterations, compared to using double-difference travel times alone. Recent advancements in dense array experiments could facilitate the application of this method to better delineate tectonic and basin structural boundaries.