Spatiotemporal Characterization of the Shallow Subsurface Using Dense-Array Ambient Noise Tomography at Cape Modern, Utah

Abstract

We deployed 500 seismic nodes across 257 locations at Cape Modern, Utah, over several months to characterize temporal velocity variations in the shallow subsurface using ambient-noise tomography. Because of the nature of ambient noise and minor changes in the sensor locations, the available ray paths were modified during the acquisition. A Voronoi tessellation-based path resampling strategy mitigated azimuthal bias from heterogeneous station distributions, achieving quasi-uniform ray-path coverage. Spatial mapping of velocity changes reveals lateral heterogeneity in the evolution of relative velocity change (dv/v), with velocity perturbations varying across the study domain and spatial patterns reflecting underlying variations in material properties and subsurface structure. Analysis of continuous data systematically reveals dv/v decreases followed by gradual recovery, with frequency dependence (0.5–1.2 s) indicating a shallow subsurface origin. Integration with environmental monitoring identified thermoelastic forcing as the dominant mechanism, with calculated velocity change variation matching observations (0.6% for 25°C seasonal variation). The 90–100-day delay between air temperature and velocity response aligns with thermal diffusion timescales. At shorter periods (0.5–0.8 s), high-velocity regions showed rapid recovery (60–95 days), whereas low-velocity zones exhibited extended recovery (90–130 days), reflecting thermal conductivity differences. The absence of systematic correlation at longer periods (0.8–1.2 s) indicates thermal decoupling of deeper intervals. This study demonstrates the monitoring capability of a dense array for spatially resolving heterogeneous subsurface thermoelastic responses.