Comparing large ocean maps meaningfully is a difficult task, due to the spatial complexity inherent in measurements taken from the ocean. This project proposes new methods based on Wasserstein distance (WD) to address this challenge. WD, unlike traditional methods, considers how underlying distributions change over space, providing a more realistic picture. The project will develop a suite of WD analysis tools specifically designed for ocean data. Using these tools in collaboration with various CBIOMES researchers, we aim to measure the temporal evolutions of the ocean’s physical features such as climatological or simulation-based Chlorophyll-A measurements, and detect long-term changes. More generally, our tools can improve the calibration of model simulation output to real data, ultimately producing higher-quality ocean simulations.. Going hand-in-hand with new statistical tools are computational improvements, which will make it feasible to analyze massive ocean datasets whose size would have been prohibitively large only several years ago. The software and data analysis pipelines developed by our research will be openly available for other oceanographers and statisticians to use, to promote reproducibility and open research.