Accurate Mediterranean Sea forecasting via graph-based deep learning.

ABSTRACT: Accurate ocean forecasting systems are essential for understanding marine dynamics, which play a crucial role in sectors such as shipping, aquaculture, environmental monitoring, and coastal risk management. Traditional numerical solvers, while effective, are computationally expensive and time-consuming. Recent advancements in machine learning have revolutionized weather forecasting, offering fast and energy-efficient alternatives. Building on these advancements, we introduce SeaCast, a neural network designed for high-resolution regional ocean forecasting. SeaCast employs a graph-based framework to effectively handle the complex geometry of ocean grids and integrates external forcing data tailored to the regional ocean context. Our approach is validated through experiments at a high horizo

SUBMITTER: Holmberg D 

PROVIDER: S-EPMC12748638 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature