1529 / 2024-09-27 22:19:08
Neural Network Based Parameterization for Ocean Surface Boundary Layer Turbulence
Machine Learning, Ocean Boundary Layer Turbulence
摘要录用
Junhong Liang / Louisiana State University
Ocean surface boundary layer turbulence plays pivotal roles in shaping the oceanic environment and influencing Earth's climate dynamics. Despite their significance, these fine-scale ocean currents can not be simulated ocean and climate models and are approximated by simplified formulas call parameterizations. Traditionally, parameterizations are derived solely from fundamental physics principles. In this talk, I will present our recent efforts using machine learning techniques to improve those parameterizations and to apply the machine learning based parameterization to better under ocean surface boundary layer turbulence.
重要日期
  • 会议日期

    01月14日

    2025

    01月17日

    2025

  • 09月27日 2024

    初稿截稿日期

  • 12月14日 2024

    注册截止日期

主办单位
State Key Laboratory of Marine Environmental Science, Xiamen University
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