Ocean digital twins: A powerful tool for understanding and managing our oceans
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报告开始:2025年01月15日 15:35(Asia/Shanghai)

报告时间:15min

所在会场:[S32] Session 32-Digital Twins of the Ocean (DTO) and Its Applications [S32-2] Digital Twins of the Ocean (DTO) and Its Applications

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摘要

Digital twins are virtual models of physical systems used in various industries for monitoring, control, and prediction. Recently, digital twins of the ocean have been developed to simulate and predict ocean dynamics such as currents, temperature, and sea level. For example, they can help predict conditions that support decision-making in offshore energy, fisheries, and shipping. Ocean digital twins have the potential to transform fields such as marine biology, ocean engineering, and climate prediction by providing real-time insights into ocean behavior. They can revolutionize research, support sustainable development, and contribute to the blue economy. The user-friendly interfaces of these systems will allow researchers and the public to access data, visualize scenarios, and interact with simulations. This presentation will review advances in ocean modeling, data assimilation, artificial intelligence/machine learning (AI/ML), and user interface design under the UN Decade of Ocean Science, with a particular focus on how these digital twins are transforming both research and operational frameworks in marine science and industry worldwide. The development of such tools for coastal regions of Japan will also be discussed, with possible outreach activities to other parts of the world. 

关键词
ocean, digital twin
报告人
Swadhin Behera
Professor Japan Agency for Marine-Earth Science and Technology

稿件作者
Swadhin Behera Japan Agency for Marine-Earth Science and Technology
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重要日期
  • 会议日期

    01月13日

    2025

    01月17日

    2025

  • 09月27日 2024

    初稿截稿日期

  • 01月17日 2025

    注册截止日期

主办单位
State Key Laboratory of Marine Environmental Science, Xiamen University
承办单位
State Key Laboratory of Marine Environmental Science, Xiamen University
Department of Earth Sciences, National Natural Science Foundation of China
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