In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar o...In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar of China.The HCA-QPE algorithm,localized Colorado State University-Hydrometeor Identification of Rainfall(CSUHIDRO)algorithm,the Joint Polarization Experiment(JPOLE)algorithm,and the dynamic Z-R relationships based on variational correction QPE(DRVC-QPE)algorithm were evaluated with the rainfall events from March 1 to October 30,2017 in Guangdong Province.The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction,its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h-1;and the stronger the rainfall intensity,the greater the QPE improvement.Besides,the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms.This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.展开更多
In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal-spatial variability of raindrop size distributions(DSDs)in the Zhengzhou ex...In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal-spatial variability of raindrop size distributions(DSDs)in the Zhengzhou extreme rainfall event on 20 July 2021.The rain rates observed by disdrometers and rain gauges from six operational sites are in good agreement,despite significant site-to-site variations of 24-h accumulated rainfall ranging from 198.3 to 624.1 mm.The Parsivel OTT observations show prominent temporal-spatial variations of DSDs,and the most drastic change was registered at Zhengzhou Station where the record-breaking hourly rainfall of 201.9 mm over 1500-1600 LST(local standard time)was reported.This hourly rainfall is characterized by fairly high concentrations of large raindrops,and the mass-weighted raindrop diameter generally increases with the rain rate before reaching the equilibrium state of DSDs with the rain rate of about 50 mm h^(−1).Besides,polarimetric radar observations show the highest differential phase shift(K_(dp))and differential reflectivity(Z_(dr))near surface over Zhengzhou Station from 1500 to 1600 LST.In light of the remarkable temporal-spatial variability of DSDs,a reflectivity-grouped fitting approach is proposed to optimize the reflectivity-rain rate(Z-R)parameterization for radar quantitative precipitation estimation(QPE),and the rain gauge measurements are used for validation.The results show an increase of mean bias ratio from 0.57 to 0.79 and a decrease of root-mean-square error from 23.69 to 18.36 for the rainfall intensity above 20.0 mm h^(−1),as compared with the fixed Z-R parameterization.This study reveals the drastic temporal-spatial variations of rain microphysics during the Zhengzhou extreme rainfall event and warrants the promise of using reflectivity-grouped fitting Z-R relationships for radar QPE of such events.展开更多
双偏振多普勒雷达相较于业务广泛使用的单偏振雷达,可以获得水凝物相态等方面的信息,为短临预报、云降水物理研究及定量测量降水量提供了更多依据。为探索上海 WSR-88D 双偏振雷达资料在定量降水估测中的改进作用,引入双偏振参量水平反...双偏振多普勒雷达相较于业务广泛使用的单偏振雷达,可以获得水凝物相态等方面的信息,为短临预报、云降水物理研究及定量测量降水量提供了更多依据。为探索上海 WSR-88D 双偏振雷达资料在定量降水估测中的改进作用,引入双偏振参量水平反射率因子 Z h 、差分反射率因子 Z dr 、差分传播相移率 K dp 等,与自动站雨量观测数据进行比较,分别试验了R( K dp )、R( K dp ,Z dr )、R( Z h ,Z dr )三种算法,进行了单站和面上的 Z-R关系定量估测降水量试验。研究表明:在单站试验中,得到的估计值与R( K dp )的结果基本一致,与此次降水中闵行站的反射率因子 Z 和差分传播相移率K dp 一直较大有关,但从总体趋势上来看,与雨量计数据相比,这三种算法仍存在降水量估计不足的情况;进一步提出了多种 Z-R关系综合算法,在对流降水试验中,计算的显著降水区域与实际观测结果基本对应,强降水中心在对流的发展阶段和成熟阶段皆有响应,在对流成熟阶段,强降水中心的降水估计与实际观测结果较接近,但是在对流发展阶段,强降水中心的降水存在高估,说明在 35 dBZ 以上的强回波区域,算法还有待改进,需进一步研究算法的本地化和降水类型细化。展开更多
基金National Key Research and Development Program of China(2017YFC1404700,2018YFC1506905)Open Research Program of the State Key Laboratory of Severe Weather(2018LASW-B09,2018LASW-B08)+7 种基金Science and Technology Planning Project of Guangdong Province,China(2019B020208016,2018B020207012,2017B020244002)National Natural Science Foundation of China(41375038)Special Scientific Research Fund of Meteorological Public Welfare Profession of China(GHY201506006)2017-2019Meteorological Forecasting Key Technology Development Special Grant(YBGJXM(2017)02-05)Guangdong Science&Technology Plan Project(2015A020217008)Zhejiang Province Major Science and Technology Special Project(2017C03035)Scientific and Technological Research Projects of Guangdong Meteorological Service(GRMC2018M10)Natural Science Foundation of Guangdong Province(2018A030313218)
文摘In this paper,a quantitative precipitation estimation based on the hydrometeor classification(HCA-QPE)algorithm was proposed for the first operational S band dual-polarization radar upgraded from the CINRAD/SA radar of China.The HCA-QPE algorithm,localized Colorado State University-Hydrometeor Identification of Rainfall(CSUHIDRO)algorithm,the Joint Polarization Experiment(JPOLE)algorithm,and the dynamic Z-R relationships based on variational correction QPE(DRVC-QPE)algorithm were evaluated with the rainfall events from March 1 to October 30,2017 in Guangdong Province.The results indicated that even though the HCA-QPE algorithm did not use the observed rainfall data for correction,its estimation accuracy was better than that of the DRVC-QPE algorithm when the rainfall rate was greater than 5 mm h-1;and the stronger the rainfall intensity,the greater the QPE improvement.Besides,the HCA-QPE algorithm worked better than the localized CSU-HIDRO and JPOLE algorithms.This study preliminarily evaluated the improved accuracy of QPE by a dual-polarization radar system modified from CINRAD-SA radar.
基金Supported by the National Key Research and Development Program of China(2022YFC3003901)National Natural Science Foundation of China(42305087 and 42105141)+2 种基金Science and Technology Innovation Project for Ecosystem Construction of Zhengzhou Supercomputing Center in Henan Province(201400210800)Meteorological Joint Project of Henan Provincial Science and Technology(222103810094 and 232103810091)Basic Research Fund of Chinese Academy of Meteorological Sciences(451490 and 2023Z008).
文摘In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal-spatial variability of raindrop size distributions(DSDs)in the Zhengzhou extreme rainfall event on 20 July 2021.The rain rates observed by disdrometers and rain gauges from six operational sites are in good agreement,despite significant site-to-site variations of 24-h accumulated rainfall ranging from 198.3 to 624.1 mm.The Parsivel OTT observations show prominent temporal-spatial variations of DSDs,and the most drastic change was registered at Zhengzhou Station where the record-breaking hourly rainfall of 201.9 mm over 1500-1600 LST(local standard time)was reported.This hourly rainfall is characterized by fairly high concentrations of large raindrops,and the mass-weighted raindrop diameter generally increases with the rain rate before reaching the equilibrium state of DSDs with the rain rate of about 50 mm h^(−1).Besides,polarimetric radar observations show the highest differential phase shift(K_(dp))and differential reflectivity(Z_(dr))near surface over Zhengzhou Station from 1500 to 1600 LST.In light of the remarkable temporal-spatial variability of DSDs,a reflectivity-grouped fitting approach is proposed to optimize the reflectivity-rain rate(Z-R)parameterization for radar quantitative precipitation estimation(QPE),and the rain gauge measurements are used for validation.The results show an increase of mean bias ratio from 0.57 to 0.79 and a decrease of root-mean-square error from 23.69 to 18.36 for the rainfall intensity above 20.0 mm h^(−1),as compared with the fixed Z-R parameterization.This study reveals the drastic temporal-spatial variations of rain microphysics during the Zhengzhou extreme rainfall event and warrants the promise of using reflectivity-grouped fitting Z-R relationships for radar QPE of such events.
文摘双偏振多普勒雷达相较于业务广泛使用的单偏振雷达,可以获得水凝物相态等方面的信息,为短临预报、云降水物理研究及定量测量降水量提供了更多依据。为探索上海 WSR-88D 双偏振雷达资料在定量降水估测中的改进作用,引入双偏振参量水平反射率因子 Z h 、差分反射率因子 Z dr 、差分传播相移率 K dp 等,与自动站雨量观测数据进行比较,分别试验了R( K dp )、R( K dp ,Z dr )、R( Z h ,Z dr )三种算法,进行了单站和面上的 Z-R关系定量估测降水量试验。研究表明:在单站试验中,得到的估计值与R( K dp )的结果基本一致,与此次降水中闵行站的反射率因子 Z 和差分传播相移率K dp 一直较大有关,但从总体趋势上来看,与雨量计数据相比,这三种算法仍存在降水量估计不足的情况;进一步提出了多种 Z-R关系综合算法,在对流降水试验中,计算的显著降水区域与实际观测结果基本对应,强降水中心在对流的发展阶段和成熟阶段皆有响应,在对流成熟阶段,强降水中心的降水估计与实际观测结果较接近,但是在对流发展阶段,强降水中心的降水存在高估,说明在 35 dBZ 以上的强回波区域,算法还有待改进,需进一步研究算法的本地化和降水类型细化。
