PhyOceanCast: Global Ocean Forecasting with Physics-Informed Diffusion
Qixiu Li, Xiang Zhu, Xiaoyong Li, Xiaolong Xu
Abstract
Ocean dynamics drive global climate patterns and extreme weather events, making accurate spatiotemporal forecasting essential for climate monitoring and marine operations. Traditional Global Ocean Forecasting Systems (GOFSs) offer high accuracy predictions, yet remain computationally expensive and fail to fully leverage growing historical data. Recent deep learning models have achieved notable success, but still face three fundamental challenges: (1) they homogenize ocean variables despite strong physical coupling via
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