Ocean Modeling

Ocean modeling aims to simulate and predict ocean dynamics, crucial for understanding climate change and improving weather forecasting. Current research emphasizes developing more efficient and accurate models, focusing on data-driven approaches like neural operators (including Fourier Neural Operators and U-Net architectures) and machine learning techniques to enhance resolution, improve prediction accuracy at various timescales (from daily to decadal), and reduce computational costs. These advancements are significantly impacting our ability to understand and predict ocean processes, leading to better climate models and more effective management of coastal resources.