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利用深度学习填补双偏振雷达回波遮挡

尹晓燕 胡志群 郑佳锋 左园园 皇甫江 朱永杰

尹晓燕, 胡志群, 郑佳锋, 等. 利用深度学习填补双偏振雷达回波遮挡. 应用气象学报, 2022, 33(5): 581-593. DOI:  10.11898/1001-7313.20220506..
引用本文: 尹晓燕, 胡志群, 郑佳锋, 等. 利用深度学习填补双偏振雷达回波遮挡. 应用气象学报, 2022, 33(5): 581-593. DOI:  10.11898/1001-7313.20220506.
Yin Xiaoyan, Hu Zhiqun, Zheng Jiafeng, et al. Filling in the dual polarization radar echo occlusion based on deep learning. J Appl Meteor Sci, 2022, 33(5): 581-593. DOI:  10.11898/1001-7313.20220506.
Citation: Yin Xiaoyan, Hu Zhiqun, Zheng Jiafeng, et al. Filling in the dual polarization radar echo occlusion based on deep learning. J Appl Meteor Sci, 2022, 33(5): 581-593. DOI:  10.11898/1001-7313.20220506.

利用深度学习填补双偏振雷达回波遮挡

DOI: 10.11898/1001-7313.20220506
资助项目: 

国家重点研发计划 2019YFC1510304

广东省重点领域研发计划 2020B1111200001

中国气象局大气探测重点开放实验室开放课题 U2021Z05

河北省省级科技计划 19275408D

青年科学基金项目 42105141

详细信息
    通信作者:

    胡志群, 邮箱:huzq@cma.gov.cn

Filling in the Dual Polarization Radar Echo Occlusion Based on Deep Learning

  • 摘要: 广州S波段双偏振天气雷达低仰角多方位存在遮挡,高仰角也存在部分遮挡。基于卷积神经网络等深度学习方法,构建垂直填补(vertical echo-filling,VEF)和水平填补(horizontal echo-filling,HEF)网络架构,基于两种架构,利用无遮挡区的反射率因子ZH、差分反射率ZDR,差传播相移率KDP构建训练集,填补遮挡区的ZHZDR。针对仅0.5°仰角存在遮挡的区域,基于VEF架构,利用上层多个仰角、径向、距离库的三维数据,分距离段训练垂直填补模型。针对遮挡仰角较高的区域,则基于HEF架构,利用同一仰角左右相邻的多个径向、距离库的数据,分遮挡径向训练水平填补模型。根据解释方差、平均绝对偏差和相关系数3个指标和3个个例,对模型效果进行评估。结果表明:ZH填补模型的解释方差最大为0.92,平均绝对偏差最小为1.69 dB,相关系数最高为0.96;ZDR填补模型的解释方差最大为0.92,平均绝对偏差最小为0.12 dB,相关系数最高为0.96。利用该研究构建的深度学习填补架构,可有效填补偏振雷达遮挡区域回波,提高雷达数据质量。
  • 图  1  通过地理高程数据计算的广州CINRAD/SAD雷达0.5°仰角(a)和1.5°仰角(b)遮挡系数

    (相邻距离圈相距30 km)

    Fig. 1  Occlusion coefficient of 0.5° elevation(a) and 1.5° elevation(b) of Guangzhou CINRAD/SAD calculated from geographic elevation data

    (the distance between adjacent rings is 30 km)

    图  2  VEF(a)和HEF(b)网络架构

    Fig. 2  VEF(a) and HEF(b) network architecture

    图  3  ZHZDR垂直填补模型不同距离训练模型的估算值和真实值散点图

    (色标为高斯核密度估计值)

    Fig. 3  Plots of predicted and observed echo reflectivity of each section with ZH and ZDR vertical echo-filling models

    (color mark denotes Gaussian kernel density estimation)

    图  4  ZHZDR水平填补模型不同填补径向数的模型估算值和真实值散点图

    (色标为高斯核密度估计值)

    Fig. 4  Plots of predicted and observed echo reflectivity of different fill radial numbers with ZH and ZDR horizontal echo-filling models

    (color mark denotes Gaussian kernel density estimation)

    图  5  2019年8月25日11:36模型填补效果对比0.5°仰角PPI图

    (红色椭圆内为明显遮挡区域,下同)
    (a)ZH真实值,(b)ZH估算值,(c)ZDR真实值,(d)ZDR估算值

    Fig. 5  PPI images of echo-filling result comparison of 0.5° elevation at 1136 UTC 25 Aug 2019

    (red ellipse denotes the obvious blocked area, the same as in after)
    (a)observed ZH, (b)predicted ZH, (c)observed ZDR, (d)predicted ZDR

    图  6  2020年6月6日08:54模型填补效果对比0.5°仰角PPI图

    (a)ZH真实值,(b)ZH估算值,(c)ZDR真实值,(d)ZDR估算值

    Fig. 6  PPI images of echo-filling result comparison of 0.5° elevation at 0854 UTC 6 Jun 2020

    (a)observed ZH, (b)predicted ZH, (c)observed ZDR, (d)predicted ZDR

    图  7  2019年5月8日03:54模型填补效果对比0.5°仰角PPI图

    (a)ZH真实值,(b)ZH估算值,(c)ZDR真实值,(d)ZDR估算值

    Fig. 7  PPI images of echo-filling result comparison of 0.5° elevation at 0354 UTC 8 May 2019

    (a)observed ZH, (b)predicted ZH, (c)observed ZDR, (d)predicted ZDR

    表  1  ZHZDR垂直填补模型不同距离段评估结果

    Table  1  Evaluation of each section in ZH and ZDR vertical echo-filling models

    填补量 距离段/km 解释方差 平均绝对偏差/dB 相关系数
    ZH [20, 54) 0.9116 1.7947 0.9572
    [54, 68) 0.9155 1.7251 0.9634
    [68, 88) 0.8956 1.7210 0.9526
    [88, 120] 0.8206 2.2630 0.9208
    ZDR [20, 54) 0.8762 0.1520 0.9240
    [54, 68) 0.8564 0.1204 0.8971
    [68, 88) 0.8538 0.1228 0.9083
    [88, 120] 0.8308 0.1440 0.8683
    下载: 导出CSV

    表  2  ZHZDR水平填补模型不同填补径向数的评估结果

    Table  2  Evaluation of different fill radial numbers in ZH and ZDR horizontal echo-filling models

    填补量 遮挡径向数 解释方差 平均绝对偏差/dB 相关系数
    ZH 3 0.9228 1.6973 0.9615
    5 0.8342 2.1143 0.9227
    ZDR 3 0.9254 0.1189 0.9639
    5 0.8542 0.1275 0.9333
    下载: 导出CSV

    表  3  2019年8月25日11:36无遮挡区回波填补不同距离段评估结果

    Table  3  Evaluation of echo-filling of each section in the unblocked area at 1136 UTC 25 Aug 2019

    填补量 距离段/km 解释方差 平均绝对偏差/dB 相关系数
    ZH [20, 54) 0.9031 1.0245 0.9567
    [54, 68) 0.9094 1.0267 0.9632
    [68, 88) 0.8250 2.0311 0.9102
    [88, 120] 0.7851 2.1401 0.8816
    ZDR [20, 54) 0.9015 0.0315 0.9211
    [54, 68) 0.9242 0.0309 0.9012
    [68, 88) 0.8240 0.0353 0.8743
    [88, 120] 0.7789 0.0328 0.8674
    下载: 导出CSV

    表  4  2020年6月6日08:54无遮挡区回波填补不同距离段的评估结果

    Table  4  Evaluation of echo-filling of each section in the unblocked area at 0854 UTC 6 Jun 2020

    填补量 距离段/km 解释方差 平均绝对偏差/dB 相关系数
    ZH [20, 54) 0.9311 1.4654 0.9457
    [54, 68) 0.9594 2.0431 0.9341
    [68, 88) 0.8950 2.1143 0.9019
    [88, 120] 0.8854 2.3496 0.8942
    ZDR [20, 54) 0.9592 0.0312 0.9732
    [54, 68) 0.9321 0.0207 0.9643
    [68, 88) 0.9034 0.0236 0.9325
    [88, 120] 0.8811 0.0413 0.9078
    下载: 导出CSV

    表  5  2019年5月8日03:54无遮挡区回波填补不同距离段的评估结果

    Table  5  Evaluation of echo-filling of each section in the unblocked area at 0354 UTC 8 May 2019

    填补量 距离段/km 解释方差 平均绝对偏差/dB 相关系数
    ZH [20, 54) 0.9330 1.0309 0.9681
    [54, 68) 0.9121 1.0331 0.9616
    [68, 88) 0.9345 2.0154 0.9473
    [88, 120] 0.8708 2.3480 0.9126
    ZDR [20, 54) 0.9865 0.0333 0.9618
    [54, 68) 0.9618 0.0243 0.9679
    [68, 88) 0.9097 0.0251 0.9402
    [88, 120] 0.8602 0.0381 0.9231
    下载: 导出CSV
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