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上海青浦CINRAD/SAD雷达和南汇WSR-88D雷达数据对比分析
引用本文:李哲,尹春光,郑杰,刘超. 上海青浦CINRAD/SAD雷达和南汇WSR-88D雷达数据对比分析[J]. 气象科技, 2024, 52(2): 173-185
作者姓名:李哲  尹春光  郑杰  刘超
作者单位:复旦大学大气与海洋科学系/大气科学研究院,上海 200438;上海市气象信息与技术支持中心,上海 200030
基金项目:华东区域气象科技协同创新基金项目(QYHZ202101,QYHZ202105,QYHZ202314)资助
摘    要:上海青浦CINRAD/SAD雷达和南汇WSR 88D雷达型号不同,并且采用不同的双偏振技术升级方案,实际业务运行中2部雷达存在一定的数据偏差。为了对雷达的探测性能进行定量评估,在共同探测区域遴选2022年7—9月及2023年6月共30个过程3933个时次数据,以稳定性降水与对流性降水分类并按强度分级进行对比,评估了反射率因子ZH,差分反射率ZDR,相关系数CC和差分传播相移ΦDP的水平分布特征及随方位变化趋势,雷达灵敏度随仰角变化趋势以及ZH和ZDR偏差的定量统计。结果表明:2部雷达ZH的观测结果接近,青浦CINRAD/SAD雷达的ZH,CC和ΦDP受地物及避雷针影响较大,随方位变化不稳定,青浦CINRAD/SAD雷达在低层的非气象回波滤除效果较南汇WSR 88D雷达差。2部雷达ZH和ZDR的偏差在ZH大于40 dBz的区域较大,ZH平均偏差为0.9 dB,ZDR为-0.14 dB。本文基于台风、冰雹、短时强降水和梅雨降水数据,定量化评估了上海2部S波段双偏振天气雷达数据之间的差异,为后续算法改进以及数据订正提供参考。

关 键 词:S波段双偏振雷达;灵敏度;偏差分析
收稿时间:2023-08-20
修稿时间:2023-11-28

Comparative Analysis of Shanghai Qingpu CINRAD/SAD Radar and Nanhui WSR-88D Radar Data
LI Zhe,YIN Chunguang,ZHENG Jie,LIU Chao. Comparative Analysis of Shanghai Qingpu CINRAD/SAD Radar and Nanhui WSR-88D Radar Data[J]. Meteorological Science and Technology, 2024, 52(2): 173-185
Authors:LI Zhe  YIN Chunguang  ZHENG Jie  LIU Chao
Affiliation:Department of Atmospheric and Oceanic Sciences & Institute of Atmospheric Sciences, Fudan University, Shanghai 200438;Shanghai Meteorological Information and Technical Support Center, Shanghai 200030
Abstract:The Qingpu CINRAD/SAD radar and the Nanhui WSR 88D radar, located in Shanghai, are of different models, and different dual polarisation technology upgrade schemes are adopted, so there is a certain data deviation between the two radars in actual business operation. In order to quantitatively evaluate the detection performance of the radars, analyse the main sources of differences in radar data, and improve the application of the data of the two radars in business forecasting, algorithm research and other aspects, a total of 3933 times of data in 30 processes are selected in the common detection area from July to September 2022 and June 2023. The data set includes typical weather processes such as hail, typhoons, and plum rains. The data are divided into stable precipitation and convective precipitation, and are compared according to intensity classification. We mainly use the data space matching method based on radars at different positions, the horizontal structure of reflectivity (ZH), differential reflectivity (ZDR), correlation coefficient (CC) and differential phase shift (ΦDP) and their variation trend with azimuth, the variation trend of radar sensitivity with elevation and the quantitative statistics of ZH and ZDR deviation for evaluation. The results show that the ZH observations of the two radars are close to each other. The ZDR, CC and ΦDP of the Qingpu CINRAD/SAD radar are more affected by the ground features and lightning rods, and are unstable with the change of azimuth, meanwhile, the non meteorological echo filtering effect of the Qingpu CINRAD/SAD radar is worse than that of the Nanhui WSR 88D radar in the lower layers. The Nanhui 88D radar utilises azimuth super resolution technology to obtain a more refined echo structure. The Nanhui 88D radar only installs a lightning rod on the top of the radome, which is basically not affected by the lightning rod. The radar parameters are more stable as the azimuth changes. The deviation of ZH and ZDR of the two radars is larger in the area where the ZH is greater than 40 dBz. For stable precipitation of 15-25 dBz, the deviations of the ZH and ZDR of the two radars are small. Through calculation, the average deviation of ZH is 0.9 dB and ZDR is -0.14 dB. Based on the data of typhoon, hail, short duration heavy precipitation and Meiyu precipitation, we quantitatively evaluate the differences between the two S band dual polarisation weather radars in Shanghai from different aspects, providing a reference for subsequent algorithm improvements and data correction.
Keywords:S band dual polarization radar   sensitivity   deviation analysis
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