Forecasting the eddying ocean with a deep neural network

Yingzhe CuiRuohan WuXiang ZhangZiqi ZhuBo LiuJun ShiJunshi ChenHailong Liu

气象海洋与地球系统方向论文：Forecasting the eddying ocean with a deep neural network

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内容导读Reading note

分类与摘要Category & abstract

面向天气、海洋、气溶胶或地球系统模拟，强调模型预测能力与科学解释。

Evidence note

Multispheres and Earth System and Key Laboratory of Ocean dynamics/Academy of Future Ocean, Ocean University of China, Qingdao, China.2Department of Ocean Big Data and Prediction, Laoshan Laboratory, Qingdao, China.3School of Computer Science and Technology, University of Science and Technology of China, Hefei, China.4Joint Laboratory of Advanced Computing for Transparent Oceans between Laoshan Laboratory and Unive || Multispheres and Earth System and Key Laboratory of Ocean dynamics/Academy of Future Ocean, Ocean University of China, Qingdao, China.2Department of Ocean Big Data and Prediction, Laoshan Laboratory, Qingdao, China.3School of Computer Science and Technology, University of Science and Technology of China, Hefei, China.4Joint Laboratory of Advanced Computing for Transparent Oceans between Laoshan Laborator || ported by the National Natural Science Foundation of China (42325601 and 92358303 to Z.J.). Computational resources were supported by Laoshan Laboratory (No. LSKJ202300302 and No. LSKJ202300305). We thank the Mercator Océan and E.U. Copernicus Marine Service Information for providing the GLORYS reanalysis (https://doi.org/10.48670/moi-00021), GLO12v4 analysis and forecast (https://doi.org/10.48670/moi-00016) a || ents This work was supported by the National Natural Science Foundation of China (42325601 and 92358303 to Z.J.). Computational resources were supported by Laoshan Laboratory (No. LSKJ202300302 and No. LSKJ202300305). We thank the Mercator Océan and E.U. Copernicus Marine Service Information for providing the GLORYS reanalysis (https://doi.org/10.48670/moi-00021), GLO12v4 analysis and forecast (https:

Metadata

完整论文信息Full record

title: Forecasting the eddying ocean with a deep neural network
title_zh: 待补充
abstract: 待补充
abstract_zh: 待补充
keywords: AI, CFD, 学位认定 A
year: 2025
published_date: 待补充
online_date: 待补充
paper_type: Journal
publication_status: Published
volume: 待补充
issue: 待补充
pages: 待补充
article_number: 待补充
publisher: Nature
doi: 10.1038/s41467-025-57389-2
research_area: 气象海洋与地球系统
tags: AI, CFD, 学位认定 A
category: 气象海洋与地球系统
summary: 面向天气、海洋、气溶胶或地球系统模拟，强调模型预测能力与科学解释。
authors: Yingzhe Cui, Ruohan Wu, Xiang Zhang, Ziqi Zhu, Bo Liu, Jun Shi, Junshi Chen, Hailong Liu
corresponding_authors: 待补充
affiliations: 崂山实验室, 待补充
funding: 崂山实验室项目

Research area

气象海洋与地球系统

Citation

Yingzhe Cui, Ruohan Wu, Xiang Zhang, Ziqi Zhu, Bo Liu, Jun Shi, Junshi Chen, Hailong Liu, Shenghui Zhou, Liang Su, Zhao Jing, Hong An, Lixin Wu, Forecasting the eddying ocean with a deep neural network，Nature Communications，VOL 16，NO.1, March 2025.

BibTeX

@article{acsa2025_16,
  title = {Forecasting the eddying ocean with a deep neural network},
  year = {2025},
  doi = {10.1038/s41467-025-57389-2}
}