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基于核密度估计的经验路径模型在西北太平洋虚拟台风构建中的应用

徐晓武 陈永平 谭亚 刘畅 李尚鲁 车助镁

徐晓武,陈永平,谭亚,等. 基于核密度估计的经验路径模型在西北太平洋虚拟台风构建中的应用[J]. 海洋学报,2024,46(3):1–11 doi: 10.12284/hyxb2024014
引用本文: 徐晓武,陈永平,谭亚,等. 基于核密度估计的经验路径模型在西北太平洋虚拟台风构建中的应用[J]. 海洋学报,2024,46(3):1–11 doi: 10.12284/hyxb2024014
Xu Xiaowu,Chen Yongping,Tan Ya, et al. Application of Empirical Path Model based on kernel density estimation in the construction of synthetic typhoon in Northwest Pacific[J]. Haiyang Xuebao,2024, 46(3):1–11 doi: 10.12284/hyxb2024014
Citation: Xu Xiaowu,Chen Yongping,Tan Ya, et al. Application of Empirical Path Model based on kernel density estimation in the construction of synthetic typhoon in Northwest Pacific[J]. Haiyang Xuebao,2024, 46(3):1–11 doi: 10.12284/hyxb2024014

基于核密度估计的经验路径模型在西北太平洋虚拟台风构建中的应用

doi: 10.12284/hyxb2024014
基金项目: 国家重点研发计划项目(2023YFC3008100);浙江省基础公益研究计划项目(LGF22D060010);广州市南沙区水务局科技项目(2022-263)。
详细信息
    作者简介:

    徐晓武(1998—),男,江西省上饶市人,研究方向为海洋动力学。E-mail:1025223833@qq.com

    通讯作者:

    陈永平,男,教授,主要从事海洋动力学研究,E-mail:ypchen@hhu.edu.cn

  • 中图分类号: P447

Application of Empirical Path Model based on kernel density estimation in the construction of synthetic typhoon in Northwest Pacific

  • 摘要: 合理评估台风对沿海区域的影响程度与风险对于科学抵御台风灾害而言十分重要,而我国具有详细的台风观测记录至今也仅有60多年的历史,这使得在推算具有一定重现期的极值风速及相应的极值波高和潮位等特征参数时存在局限性,同时台风观测样本量的不足也限制了如深度学习等数据驱动型模型在台风灾害预报中的应用。因此,有必要基于实际台风行进规律构建虚拟台风以克服历史数据量不足的问题。故本文采用基于核密度估计的经验路径模型,在西北太平洋海域构建了18 671场虚拟台风,将虚拟台风的起始与终止位置、发生频数、行进速度和行进方向等参数与实际发生的台风进行统计意义上的对比分析。结果表明,基于本文方法构建的虚拟台风总体上符合西北太平洋历史台风的行进规律。通过这些虚拟台风的构建,可为中国沿海极值波浪和风暴增水研究提供数据量足够且性能可靠的虚拟台风样本数据库。
  • 图  1  虚拟台风生成流程

    Fig.  1  Flowchart of synthetic typhoon generation

    图  2  西北太平洋1959−2020年间历史台风路径

    Fig.  2  Historical typhoon tracks from 1959 to 2020 in Northwest Pacific

    图  3  台风起始参数累积分布密度拟合

    a. 台风年发生频数;b. 台风初始移速;c. 台风初始移向

    Fig.  3  Typhoon initial parameter cumulative distribution density fitting

    a. Annual frequency of typhoon occurrence; b. initial movement direction of typhoon; c. initial moving speed of typhoon

    图  4  历史台风路径(a)与随机抽取的1 520场虚拟台风路径(b)

    Fig.  4  Historical typhoon tracks (a) and randomly selected 1 520 sysnthtic typhoon tracks (b)

    图  5  历史台风与随机抽取的1 520场虚拟台风起始点对比(a)与终止点对比(b)

    Fig.  5  Comparison between historical typhoons and 1 520 randomly selected synthetic typhoons generating points (a) and disappearing points (b)

    图  6  验证站点布置

    Fig.  6  Verification stations Layout

    图  7  影响各站点的历史台风与虚拟台风的年发生频数对比(a)和台风中心风速平均值和标准差对比(b)

    Fig.  7  Comparison of annual frequency of historical typhoons and synthetic typhoons affecting each station (a) and comparison of mean and standard deviation of maximum wind speed at the center (b)

    图  8  影响M25(a)、M30(b)和M35(c)的历史台风与虚拟台风的各强度等级占比

    Fig.  8  The proportion of historical typhoons and virtual typhoons affecting M25 (a), M30 (b), and M35 (c) at different intensity levels

    图  9  12个特征点处的历史台风及虚拟台风移速的累计概率分布曲线对比

    Fig.  9  Comparison of cumulative probability distribution curves of historical and virtual typhoon movement speeds at 12 characteristic stations

    图  10  12个特征点处的历史台风及虚拟台风移向的概率密度曲线对比

    Fig.  10  Comparison of probability density curves of historical and virtual typhoon movement directions at 12 characteristic stations

    表  1  热带气旋分类标准

    Tab.  1  Standard for classification of tropical cyclones

    热带气旋类型 底层中心附近最大平均风速(10 min平均风速)/(m·s−1
    热带低压 ≥ 51
    热带风暴 41.5~50.9
    强热带风暴 32.7~41.4
    台风 24.5~32.6
    强台风 17.2~24.4
    超强台风 10.8~17.1
    下载: 导出CSV

    表  2  各分布的5%显著水平下的KS检验

    Tab.  2  KS test at 5% significance level for each distribution

    分布类型 $ {D}_{n} $ 样本量 $ {D}_{\mathrm{c}\mathrm{r}\mathrm{i}\mathrm{t},\; 0.05} $
    泊松分布
    (台风年发生频数)
    0.066 62 0.173
    伽马分布
    (台风初始移速)
    0.026 1520 0.035
    双峰分布
    (台风初始移向)
    0.015 1520 0.035
    下载: 导出CSV
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  • 收稿日期:  2023-07-12
  • 修回日期:  2023-10-20
  • 网络出版日期:  2023-12-20

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