海洋极端天气现象预测方法研究进展
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作者单位:

1.天津大学电气自动化与信息工程学院, 天津 300072;2.中国科学院自动化研究所, 北京 100190;3.中国海洋大学数学科学学院, 青岛 266100

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基金项目:

国家重点研发计划(2021YFF0704000);国家自然科学基金联合基金重点支持项目(U22A2068)。


Research on Marine Extreme Meteorology Forecast
Author:
Affiliation:

1.School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China;2.Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;3.School of Mathematical Sciences, Ocean University of China, Qingdao 266100, China

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    摘要:

    海洋极端天气对沿海地区影响重大。研究人员利用海洋大数据,结合深度学习算法,在海洋极端天气现象预测方面取得了重要进展。本文首先以典型的多尺度海洋极端天气现象——厄尔尼诺、台风及短临降雨为例,介绍了近年来主流的海洋极端天气现象预测算法,即基于模式计算的方法和基于人工智能的算法。然后分析了海洋极端天气现象智能预测的挑战和机遇,详细总结了各类方法的研究进展,并且通过数据和实验讨论了现有算法的优点和不足。最后展望了基于海洋大数据的海洋极端天气现象智能预测的发展方向。

    Abstract:

    Extreme marine weather phenomena have an important impact on the coastal area. Researchers have made great progress in marine extreme meteorology prediction with the help of marine big data and deep learning algorithms. In this paper, taking typical multi-scale marine extreme weather phenomena—El Ni?o, typhoon, short-term precipitation as examples, we firstly introduce the mainstream marine extreme meteorology forecast algorithms in recent years, which are mainly divided into numerical model-based methods and artificial intelligence-based algorithms. Then,we analyze the challenges and opportunities of marine extreme meteorology prediction, and summarize the research advances of various methods in detail. And, we discuss the advantages and disadvantages of existing algorithms through experiments. Finally, we briefly look forward to the development direction of marine intelligent meteorology prediction based on marine big data.

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刘安安,李天宝,宋丹,李文辉,孙正雅,袁春鑫.海洋极端天气现象预测方法研究进展[J].数据采集与处理,2023,38(2):231-244

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  • 收稿日期:2022-12-15
  • 最后修改日期:2023-01-13
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  • 在线发布日期: 2023-04-11