Ambient-noise multicomponent multimodal dispersion characteristics in thick sedimentary basins

Ambient noise cross-correlations enable the extraction of multimodal surface waves, yet resolving their complex dispersion characteristics is essential for robust subsurface imaging. Using dense array data from the North China Plain, we resolve multicomponent multimodal Rayleigh and Love wave dispersion with unprecedented detail. The results reveal several distinct dispersion characteristics, including stronger excitation of higher modes on horizontal components, opposite polarity of the first higher mode on the ZR-RZ component, and a switching of the dominant Rayleigh mode between vertical and horizontal components at low frequencies. We also identify and confirm mode kissing between fundamental and first higher Rayleigh modes and guided P modes arising from normal mode and leaky mode coupling. These dispersion characteristics are primarily controlled by the shallow low-velocity sediments, which govern frequency-dependent mode excitation, polarity, and energy partitioning. Integrating these multicomponent multimodal observations improves the physical interpretability and reliability of subsurface imaging.