Assessing the capability of Moho recovery using gravity-curvature data through spatial and spectral inversion schemes

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ID: 327795
2026
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Abstract
Summary Gravity curvature is defined as the third-order derivatives of the gravitational potential. It has been proposed as a potential observable for future satellite gradiometry due to its enhanced sensitivity to short-wavelength components of Earth’s gravity field. Previous studies reported that gravity curvature exhibits apparently weaker spatial correlation with Moho geometry than gravity and gravity-gradient observations, raising concerns about its applicability for Moho inversion. In this study, we systematically assess the capability of gravity-curvature data for Moho recovery, with particular emphasis on the contrasting behaviors of spatial- and spectral-domain inversion schemes. The nonlinear spatial inversion is implemented using the iterative regularization, whereas the spectral inversion follows a spherical harmonic Parker-Oldenburg formulation. Synthetic and real-data tests reveal a clear methodological dependence. Spectral inversion demonstrates robust and stable performance, as it primarily exploits the inherent spectral content of the gravitational field and is insensitive to altered spatial patterns. In contrast, spatial inversion is strongly influenced by data-model correlation, with performance improving at higher observation altitudes but degrading under near-surface scenario. At satellite altitudes, with the effect of iterative stabilization, the spatial inversion yields roughly consistent performance to the spectral inversion. These findings highlight that the inversion capability of gravity curvature depends critically on the inversion framework. When spatial distribution and spectral content are properly considered, gravity curvature can provide a promising constraint for density interface inversion by enhancing sensitivity to specific spatial scales.
Reference Key
openalex_W7211933144 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Wei-Kai Li, Meng Yang, Wei Feng, Min Zhong
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Journal geophysical journal international
Year 2026
DOI
10.1093/gji/ggag363
URL
https://doi.org/10.1093/gji/ggag363
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