In this presentation, I will introduce the Functional Data Analysis approach proposed by Yarger et al. for analyzing the Argo dataset. The Argo dataset represents a contemporary oceanographic collection providing unparalleled global coverage of temperature and salinity measurements in the upper 2000 meters of the ocean. This data was gathered through the Argo project using floats—devices that periodically ascend from depths of two kilometers while recording temperature and salinity measurements, creating what we refer to as 'profiles'. Yarger et al. treated each profile as functional data, considering measurements as a function of depth for a specific time and location. I will discuss both the strengths and weaknesses of their approach and share my thoughts on the Argo dataset towards the end of the presentation.