Underwater mixing plays a critical role in regulating Earth’s climate by distributing heat, nutrients, and dissolved gases throughout the ocean. This mixing is largely driven by the breaking of internal waves, which are generated by wind and tides. However, many ocean models cannot resolve the wave breaking that drives mixing and must instead rely on simplified representations called parameterizations. One such model is the Generalized Finescale Parameterization (GFP), which infers mixing rates from measurements of the internal wave field. While effective, and an improvement on past parameterizations, the current GFP has two major limitations: it neglects energy sources beyond wind forcing and omits the equatorial ocean, where wave dynamics differ substantially. This project aims to improve the GFP by incorporating additional energy sources, such as tidal flows, and by incorporating unique wave dynamics at equatorial latitudes. These enhancements will provide a more complete understanding of the drivers of ocean mixing, reduce key uncertainties in climate models, and offer new insight into the energetic pathways that lead to mixing. The project also supports education and training through undergraduate mentorship and participation in an international oceanographic summer school. To construct an improved parameterization, the project will analyze historical mooring and Argo float datasets to identify a minimal set of spectral parameters that capture spatiotemporal scales of