Modeling Multivariable Associations and Inter-Eddy Interactions: A Dual-Graph Learning Framework for Mesoscale Eddy Trajectory Forecasting
Year: 2025
Type: article
Abstract: The precise forecasting of mesoscale eddy trajectories holds significant importance for understanding their mechanisms in driving global oceanic mass and heat transport. However, mesoscale eddies are influenced by numerous stochastic and uncertain factors, leading to substantial fluctuations in their attribute variables. Additionally, the trajectories of eddies are related to historical trends and interact with surrounding eddies. These render the accurate forecasting of mesoscale eddy trajectories a formidable challenge. This study proposes a novel dynamic forecasting framework for eddies’ trajectories, termed EddyGnet, a dual graph neural network framework that synergistically models the complex multivariable association and the spatiotemporal eddy association. In this framework, the dynamic association among eddy attribute variables is first explored by a multivariable association graph (MAG) learning module. Subsequently, the spatial and temporal association among eddies are concurrently analyzed using a spatiotemporal eddy association graph (STEAG) learning module. Finally, a decayed volatility loss function is designed to properly handle the complex and variable data features and improve the forecasting performance. The experimental results on the eddy dataset verify the effectiveness of our proposed EddyGnet, demonstrating superior predictive accuracy and stability compared with existing classical methods. The findings advance the mechanistic understanding of eddy dynamics and provide a transferable paradigm for geoscientific spatiotemporal modeling.
Source: Remote Sensing
DOI: 10.3390/rs17142524
Authors: Yanling Du, Bin Zhang, Jian Wang, Zhenli Qian, Wei Song
Institution: Shanghai Ocean University
Language: English
Subfield: Oceanography
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $3,258
OpenAlex ID: W4412515291