Numerical Ocean

Numerical ocean modeling aims to simulate and predict ocean dynamics, crucial for understanding climate change and improving weather forecasting. Current research emphasizes developing computationally efficient models, employing deep learning architectures like neural operators and masked autoencoders, and leveraging graph neural networks for parameter space exploration of complex simulations. These advancements improve prediction accuracy and efficiency across various spatial and temporal scales, from short-term wave forecasting to multi-year climate projections, ultimately enhancing our understanding of ocean processes and their impact on the Earth system.