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  • Presentation | A51O: Bridging Physics and AI: Understanding, Modeling, and Predicting Ocean-Atmosphere-Land Processes in the Indo-Pacific and Other Areas II Poster
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  • A51O-0932: Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction
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  • Board 0932‚ Hall EFG (Poster Hall)
    NOLA CC
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Author(s):
Jing-Jia Luo, NUIST Nanjing University of Information Science and Technology (First Author, Presenting Author)
Fenghua Ling, Nanjing University of Information Science and Technology
Zijie Guo, Fudan University
Lei Bai, Shanghai Artificial Intelligence Laboratory
Niklas Boers, Ecole Normale Supérieure Paris
Pumeng Lyu, Shanghai Artificial Intelligence Laboratory
Takeshi Izumo, IRD (Institut de Recherche pour le Développement) / EIO laboratory / University of French Polynesia
Sophie Cravatte, LEGOS, Université de Toulouse, (IRD, CNES, CNRS, UT)
Antonietta Capotondi, University of Colorado
Toshio Yamagata, Japan Agency for Marine-Earth Science and Technology
Wanli Ouyang, The Chinese University of Hong Kong


A breakthrough deep learning model is proposed for global three-dimensional ocean forecasting from seasonal to decadal scales.



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