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CINRAD/SAD双偏振雷达非降水回波识别技术

张林 李峰 吴蕾 孙康远

张林, 李峰, 吴蕾, 等. CINRAD/SAD双偏振雷达非降水回波识别技术. 应用气象学报, 2022, 33(6): 724-735. DOI:  10.11898/1001-7313.20220607..
引用本文: 张林, 李峰, 吴蕾, 等. CINRAD/SAD双偏振雷达非降水回波识别技术. 应用气象学报, 2022, 33(6): 724-735. DOI:  10.11898/1001-7313.20220607.
Zhang Lin, Li Feng, Wu Lei, et al. Non-precipitation identification technique for CINRAD/SAD dual polarimetric weather radar. J Appl Meteor Sci, 2022, 33(6): 724-735. DOI:  10.11898/1001-7313.20220607.
Citation: Zhang Lin, Li Feng, Wu Lei, et al. Non-precipitation identification technique for CINRAD/SAD dual polarimetric weather radar. J Appl Meteor Sci, 2022, 33(6): 724-735. DOI:  10.11898/1001-7313.20220607.

CINRAD/SAD双偏振雷达非降水回波识别技术

DOI: 10.11898/1001-7313.20220607
资助项目: 

南京气象科技创新研究院北极阁基金 BJG202203

中国气象科学研究院基本科研业务费专项资金 2021Z003

国家重点研发计划 2018YFC1506103

详细信息
    通信作者:

    李峰, 邮箱:liflif04@tom.com

Non-precipitation Identification Technique for CINRAD/SAD Dual Polarimetric Weather Radar

  • 摘要: 双偏振雷达观测特征参量(如相关系数、差分反射率等)能有效抑制地物、超折射、电磁干扰、海浪和晴空等非降水回波。在上海南汇WSR-88D双偏振雷达非降水回波识别算法基础上,对我国升级布网且纳入业务运行的CINRAD/SAD双偏振雷达数据进行算法测试、算法模块适应性改进,利用江苏、广东的双偏振雷达观测冰雹、融化层、台风降水及各种杂波个例进行算法检验评估,并在组网拼图中展示质量控制效果。结果表明:总体上算法对非降水回波的识别准确率达到95.2%,降水回波的误判率为2.6%。但对夏秋季节夜晚的大面积晴空回波算法识别准确率低于90%,有待尝试利用深度学习方法改进。
  • 图  1  降水回波与非降水回波的相关系数和差分反射率

    (a)降水回波相关系数,(b)非降水回波相关系数,(c)降水回波差分反射率,(d)非降水回波差分反射率

    Fig. 1  Correlation coefficient and differential reflectivity for precipitation echo and clutter

    (a)correlation coefficient of precipitation, (b)correlation coefficient of non-precipitation, (c)differential reflectivity of precipitation, (d)differential reflectivity of non-precipitation

    图  2  2019年9月3日01:30:19徐州CINRAD/SAD双偏振雷达观测特征参量

    (相邻距离圈间隔50 km,下同)

    Fig. 2  Parameters observed by CINRAD/SAD dual-polarimetric radar of Xuzhou at 013019 BT 3 Sep 2019

    (distance of adjacent circles is 50 km, the same hereinafter)

    图  3  WSR-88D算法对图 2个例的识别

    Fig. 3  Recognition before and after WSR-88D quality control for the case in Fig. 2

    图  4  降水回波与非降水回波的相关系数和差分反射率的水平纹理特征

    (a)降水回波相关系数纹理,(b)非降水回波相关系数纹理,(c)降水回波差分反射率纹理,(d)非降水回波差分反射率纹理

    Fig. 4  Texture features of correlation coefficient and differential reflectivity for precipitation and non-precipitation

    (a)correlation coefficient texture of precipitation, (b)correlation coefficient texture of non-precipitation, (c)differential reflectivity texture of precipitation, (d)differential reflectivity texture of non-precipitation

    图  5  CINRAD/SAD双偏振雷达观测非降水回波识别算法流程

    Fig. 5  Flow chart of non-precipitation identification algorithm on CINRAD/SAD dual-polarimetric weather radar

    图  6  质量控制前后大面积晴空回波

    Fig. 6  Reflectivity factor of large clear air before and after radar quality control

    图  7  2019年8月1日13:35徐州CINRAD/SAD双偏振雷达观测冰雹及融化层质量控制前后的反射率因子

    Fig. 7  Reflectivity factor of hailstorm and melting layer before and after radar quality control observed by CINRAD/SAD dual-polarimetric weather radar of Xuzhou at 1335 BT 1 Aug 2019

    图  8  2019年8月11日00:05盐城CINRAD/SAD双偏振雷达观测台风降水质量控制前后的反射率因子

    Fig. 8  Reflectivity factor of typhoon precipitation before and after radar quality control observed by CINRAD/SAD dual-polarimetric weather radar of Yancheng at 0005 BT 11 Aug 2019

    图  9  2019年7月30日23:03盐城CINRAD/SAD双偏振雷达观测地物、超折射、干扰杂波质量控制前后的反射率因子

    Fig. 9  Reflectivity factor of ground clutter, anomalous propagation and electromagnetic interference process before and after radar quality control observed by CINRAD/SAD dual-polarimetric weather radar of Yancheng at 2303 BT 30 Jul 2019

    图  10  2019年9月2日03:36徐州CINRAD/SAD双偏振雷达观测降水与大面积晴空混杂回波质量控制前后的反射率因子

    Fig. 10  Reflectivity factor of precipitation and large clear air process before and after radar quality control algorithm observed by CINRAD/SAD dual-polarimetric weather radar of Xuzhou at 0336 BT 2 Sep 2019

    图  11  2020年6月12日14:00江苏高邮龙卷过程6部CINRAD/SAD双偏振雷达组网拼图

    Fig. 11  Mosaic image of Gaoyou Tornado before and after quality control observed by six CINRAD/SAD dual-polarimetric weather radars at 1400 BT 12 Jun 2020

    表  1  多种个例质量控制客观评估表

    Table  1  Quality control algorithm evaluation of cases

    种类 非降水回波识别准确率/% 降水回波误判率/%
    冰雹、融化层 96.5 1.2
    台风降水 1.8
    电磁干扰、小面积晴空 99.2
    地物、超折射、电磁干扰 95.7 2.2
    大面积晴空 90.9 2.0
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-06-04
  • 修回日期:  2022-09-06
  • 网络出版日期:  2022-11-21
  • 刊出日期:  2022-11-17

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