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基于TRMM/PR的长江下游地基雷达一致性订正
引用本文:楚志刚,许丹,王振会,韩静,费海燕.基于TRMM/PR的长江下游地基雷达一致性订正[J].应用气象学报,2018,29(3):296-306.
作者姓名:楚志刚  许丹  王振会  韩静  费海燕
作者单位:1.南京信息工程大学气象灾害预报预警与评估协同创新中心/中国气象局气溶胶与云降水重点开放实验室, 南京 210044
基金项目:公益性行业(气象)科研专项(GYHY201306078),国家自然科学基金项目(41405026),江苏省自然科学基金项目(BK20130993),江苏省高校优势学科建设工程项目(PAPD)
摘    要:我国有近200部地基多普勒天气雷达,已经积累了近20年的观测数据,这些数据对雷达气候学研究非常重要。但由于不同雷达的标定误差不同,雷达之间存在观测值不一致性的现象(与美国的地基雷达类似),有的反射率因子差异超过了3 dB。这种不一致影响了多雷达联合降水估计的精度和雷达组网临近预报的效果。为此,采用筛选比较法对地基雷达与TRMM/PR(Tropical Rainfall Measuring Mission/Precipitation Radar)进行空间匹配和异常数据剔除,以TRMM/PR为参照计算并订正地基雷达偏差。对2013年5—9月长江下游7部S波段雷达数据订正后,结果表明:订正后7部雷达之间的平均反射率因子差异从1.8 dB降至0.5 dB,任意两部雷达之间的差异均小于1.0 dB,多雷达的观测一致性和空间连续性有明显改善。与传统的几何匹配法比较,筛选比较法订正结果相对稳定,不存在过量订正的问题。

关 键 词:天气雷达    TRMM/PR    反射率因子一致性    反射率因子订正    质量控制
收稿时间:2017/9/11 0:00:00
修稿时间:2018/3/1 0:00:00

Consistent Correction to Ground-based Radars in the Lower Reachers of the Yangtze Based on TRMM/PR Observations
Chu Zhigang,Xu Dan,Wang Zhenhui,Han Jing and Fei Haiyan.Consistent Correction to Ground-based Radars in the Lower Reachers of the Yangtze Based on TRMM/PR Observations[J].Quarterly Journal of Applied Meteorology,2018,29(3):296-306.
Authors:Chu Zhigang  Xu Dan  Wang Zhenhui  Han Jing and Fei Haiyan
Institution:1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 2100442.China Meteorological Administration Training Center, Beijing 100081
Abstract:There are almost 200 ground-based operational Doppler weather radars in China''s new generation weather radar network, accumulating a large amount of radar data continuously for nearly 20 years. These historical data from weather radars are essential for researches related to China''s radar climatology. However, reflectivity factors of two adjacent radars are often found inconsistent in observation overlap area, which is similar to the WSR-88D (Weather Surveillance Radar-1988 Doppler) in US. Some reflectivity differences are reported more than 3 dB. The fundamental cause for this problem is that different radar has different calibration error which will cause a reflectivity factor bias. Reflectivity differences of two adjacent radars will certainly reduce accuracy and precision of multiple radars joint Quantitative Precipitation Estimation and Nowcasting. Therefore, a ground-based radar correction method based on TRMM/PR (Tropical Rainfall Measuring Mission/Precipitation Radar) observations is proposed, which is named as Selective Comparison Method. Ground-based radar and TRMM/PR data are spatially matched and the abnormal values are gradually eliminated to extract an Optimal Matchup Datasets with relatively high correlation coefficient in the new method. Then the ground-based radar bias is calculated and corrected with the Optimal Matchup Datasets. The Selective Comparison Method is applied for consistency correction to seven S-band radars in the lower reaches of the Yangtze from May to September in 2013. Results show that annual reflectivity factor biases of three radars are greater than 1.5 dB among seven ground-based radars in the research area. These biases lead to some differences in adjacent radar observations and bring about a significant spatial discontinuity in multiple radar reflectivity fields. After correction, the average reflectivity differences of seven radars significantly decrease from 1.8 dB to 0.5 dB. Furthermore, all reflectivity differences between two adjacent radars are less than 1.0 dB. The reflectivity factor consistency and spatial continuity of multiple radars are greatly improved. Comparing to the traditional Geometric Matchup Method, the Selective Comparison Method performs better, and it overcomes the problem that some radars may be over-corrected. This correction method is only suitable for the quality control of historical ground-based radar data because TRMM/PR stopped its observations in 2014. Further improvements are still needed to extend this method to GPM/DPR to achieve real-time radar data processing in the future.
Keywords:weather radar  TRMM/PR  reflectivity consistency  reflectivity correction  quality control
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