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人工智能技术在数值天气预报中的应用

孙健 曹卓 李恒 钱思萌 王昕 闫力敏 薛巍

孙健, 曹卓, 李恒, 等. 人工智能技术在数值天气预报中的应用. 应用气象学报, 2021, 32(1): 1-11. DOI: 10.11898/1001-7313.20210101. DOI: 10.11898/1001-7313.20210101
引用本文: 孙健, 曹卓, 李恒, 等. 人工智能技术在数值天气预报中的应用. 应用气象学报, 2021, 32(1): 1-11. DOI: 10.11898/1001-7313.20210101. DOI: 10.11898/1001-7313.20210101
Sun Jian, Cao Zhuo, Li Heng, et al. Application of artificial intelligence technology to numerical weather prediction. J Appl Meteor Sci, 2021, 32(1): 1-11. DOI:  10.11898/1001-7313.20210101
Citation: Sun Jian, Cao Zhuo, Li Heng, et al. Application of artificial intelligence technology to numerical weather prediction. J Appl Meteor Sci, 2021, 32(1): 1-11. DOI:  10.11898/1001-7313.20210101

人工智能技术在数值天气预报中的应用

DOI: 10.11898/1001-7313.20210101
资助项目: 

国家重点研发计划 2017YFA0604500

国家重点研发计划 2016YFA0602100

详细信息
    通信作者:

    孙健, sunjian@cma.gov.cn

Application of Artificial Intelligence Technology to Numerical Weather Prediction

  • 摘要: 当前,人工智能迎来第3次发展浪潮并在多个领域大数据分析中取得巨大成功,这为人工智能技术与数值天气预报结合提供了契机。已有大量研究尝试将人工智能技术用于数值天气预报的初值生成、预报和产品应用过程中,涉及观测资料预处理、资料同化、模式积分、后处理以及高性能计算,通过误差估计、参数估计和局部代理等手段使预报结果,得到改进且计算速度大幅提升,展示出良好的应用前景,一些神经网络模型也表现出纯数据驱动预报的可能性,在短时强对流天气、降水以及气候预测中已有较为理想的应用实例。然而,人工智能技术在数值天气预报中的应用与发展仍面临一些挑战,主要包括深度学习的弱解释性、不确定性分析以及两者的耦合等,除了应对这些挑战,未来两者的深度结合还需要在理论指导下的人工智能模型设计、高时空分辨率人工智能预报模型设计以及使用更多新型人工智能技术等方面深入探索。
  • 图  1  数值天气预报过程示意图

    Fig. 1  Workflow of numerical weather prediction

    图  2  人工智能技术组成

    Fig. 2  Components of artificial intelligence technology

    图  3  基于人工智能模型的天气预报流程

    Fig. 3  Weather prediction workflow based on artificial intelligence models

    表  1  人工智能技术在数值天气预报中的应用

    Table  1  Artificial intelligence applications to numerical weather prediction

    功能 模块 人工智能技术 目标 效果
    初值生成 观测资料处理及质量控制 贝叶斯方案、全卷积网络、极限学习机等 观测偏差纠正[43]、雷达及卫星图像资料预处理[44-45] 提高观测资料质量,优化高分辨率图像资料分割、资料填补等
    资料同化 随机森林、深度神经网络、支持向量机等 同化算法参数优化[46]、部分替代资料同化方法[47]、聚焦观测区域[48] 提高同化质量,提高同化速度,更好利用高分辨率资料等
    预报 模式积分 深度神经网络、卷积网络、随机森林等 模式代理[49]、替代物理过程参数化方案[50-53]、参数校正[54-55] 提高模式计算速度,优化次网格物理过程的表示,提高参数校正效果与速度等
    产品应用 后处理 随机森林、深度神经网络、卷积神经网络等 确定性及集合预报结果后处理[56-58]、替代集合预报[59-60] 后处理偏差订正、质量更好、效率更高等
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  • 收稿日期:  2020-08-25
  • 修回日期:  2020-11-02
  • 刊出日期:  2021-01-31

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