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This dataset is an accompaniment to the paper titled Statistics of bubble plumes generated by breaking surface waves, by Derakhti et al, in the Journal of Geophysical Research: Oceans. It includes extensive observations from arrays of freely drifting SWIFT buoys and shipboard systems, enabling concurrent high-resolution measurements of wind, waves, and bubble plumes. This dataset allowed us to examine the dependence of the penetration depth and fractional surface area (e.g., whitecap coverage) of bubble plumes generated by breaking surface waves on various wind and wave parameters over a wide range of sea state conditions in the North Pacific Ocean, including storms with sustained winds up to 22 m s-1 and significant wave heights up to 10 m.  Notably, this study provides the first field evidence of a direct relation between bubble plume penetration depth and whitecap coverage, suggesting that the volume of bubble plumes could be estimated by remote sensing techniques. 

Abstract We examine the dependence of the penetration depth and fractional surface area (e.g., whitecap coverage) of bubble plumes generated by breaking surface waves on various wind and wave parameters over a wide range of sea state conditions in the North Pacific Ocean, including storms with sustained winds up to 22 m s⁻¹and significant wave heights up to 10 m. Our observations include arrays of freely drifting SWIFT buoys together with shipboard systems, which enabled concurrent high‐resolution measurements of wind, waves, bubble plumes, and turbulence. We estimate bubble plume penetration depth from echograms extending to depths of more than 30 m in a surface‐following reference frame collected by downward‐looking echosounders integrated onboard the buoys. Our observations indicate that mean and maximum bubble plume penetration depths exceed 10 and 30 m beneath the surface during high winds, respectively, with plume residence times of many wave periods. They also establish strong correlations between bubble plume depths and wind speeds, spectral wave steepness, and whitecap coverage. Interestingly, we observe a robust linear correlation between plume depths, when scaled by the total significant wave height, and the inverse of wave age. However, scaled plume depths exhibit non‐monotonic variations with increasing wind speeds. Additionally, we explore the dependencies of the combined observations on various non‐dimensional predictors used for whitecap coverage estimation. This study provides the first field evidence of a direct relation between bubble plume penetration depth and whitecap coverage, suggesting that the volume of bubble plumes could be estimated by remote sensing.