FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution

• URL: http://arxiv.org/abs/2506.03210v1
• Date: Tue, 03 Jun 2025 00:52:31 GMT
• Title: FuXi-Ocean: A Global Ocean Forecasting System with Sub-Daily Resolution
• Authors: Qiusheng Huang, Yuan Niu, Xiaohui Zhong, Anboyu Guo, Lei Chen, Dianjun Zhang, Xuefeng Zhang, Hao Li,
• Abstract summary: FuXi-Ocean is the first data-driven global ocean forecasting model achieving six-hourly predictions at eddy-resolving 1/12deg spatial resolution.<n>The model architecture integrates a context-aware feature extraction module with a predictive network employing stacked attention blocks.<n>FuXi-Ocean demonstrates superior skill in predicting key variables, including temperature, salinity, and currents, across multiple depths.
• Score: 10.627782397713856
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Accurate, high-resolution ocean forecasting is crucial for maritime operations and environmental monitoring. While traditional numerical models are capable of producing sub-daily, eddy-resolving forecasts, they are computationally intensive and face challenges in maintaining accuracy at fine spatial and temporal scales. In contrast, recent data-driven approaches offer improved computational efficiency and emerging potential, yet typically operate at daily resolution and struggle with sub-daily predictions due to error accumulation over time. We introduce FuXi-Ocean, the first data-driven global ocean forecasting model achieving six-hourly predictions at eddy-resolving 1/12{\deg} spatial resolution, reaching depths of up to 1500 meters. The model architecture integrates a context-aware feature extraction module with a predictive network employing stacked attention blocks. The core innovation is the Mixture-of-Time (MoT) module, which adaptively integrates predictions from multiple temporal contexts by learning variable-specific reliability , mitigating cumulative errors in sequential forecasting. Through comprehensive experimental evaluation, FuXi-Ocean demonstrates superior skill in predicting key variables, including temperature, salinity, and currents, across multiple depths.

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