Abstract. Wave-driven fragmentation is the key mechanism shaping the Marginal Ice Zone (MIZ). Capturing this process is therefore essential for improving sea ice models, which currently do not fully capture the complex interactions between the forcing imposed by waves and the nonlinear dynamics of the resulting sea ice breakup and deformation. To investigate these interactions, we introduce a comprehensive multi-instrument dataset from a field campaign in the MIZ of the St. Lawrence Estuary, Canada, designed to characterize wave propagation and mechanical properties of sea ice under natural forcing conditions. The dataset integrates synchronized measurements from geophone arrays, wave buoys, smartphones configured as motion sensors, and unmanned aerial vehicles (UAVs), all collected during coordinated deployments across diverse ice types and sea states. Seismic data, recorded with geophone arrays, enable estimation of the ice thickness and elastic properties via active and passive wavefield analyses. Concurrently, wave buoys and smartphones capture ocean wave characteristics including amplitude, wavelength, and attenuation near ice edges. UAV imagery is processed with advanced methods to detect vertical ice displacements with sub-centimetre sensitivity, allowing extraction of wave dispersion relations in different ice conditions. Preliminary analyses demonstrate strong agreement between independent measurement methods, validating the dataset’s quality. This multi-sensor approach offers unique opportunities to improve our understanding of wave-ice interactions, wave attenuation, and fracture dynamics in situ, thus offering a valuable resource for the sea ice and oceanographic research community to gain insight in wave-induced ice break-up mechanisms under natural conditions.
Kuchly et al. (Tue,) studied this question.