针对业务运行中雷达观测存在遮挡和雷达产品延迟,提出利用带噪声基于密度的空间聚类(density-based spatial clustering of applications with noise,DBSC AN)算法对闪电数据的聚类结果替代雷达产品,并分别利用北京三维闪电定位网(Beiji...针对业务运行中雷达观测存在遮挡和雷达产品延迟,提出利用带噪声基于密度的空间聚类(density-based spatial clustering of applications with noise,DBSC AN)算法对闪电数据的聚类结果替代雷达产品,并分别利用北京三维闪电定位网(Beijing Total Lightning System,BJTLS)和升级后的国家闪电定位网(DDW1)总闪数据,应用2σ闪电跃增算法对北京2022年6月4日和12日两次强对流致灾过程进行临近预警,对比强对流单体识别法和DBSCAN聚类法的预警效果。结果表明:两种算法和两种闪电数据均能有效预警北京地区的灾害性天气,基于BJTLS总闪数据的预警效果较优;对于BJTLS总闪数据,两种方法的预警效果相当,预警命中率、误报率、临近成功指数和平均预警提前时间依次分别为100%,11.9%,88.1%,38.9 min和100%,13.3%,86.7%,42.8 min;仅利用闪电数据并应用2σ闪电跃增算法可对灾害性天气进行临近预警,摆脱对雷达产品的依赖。展开更多
The region of Beijing-Tianjin-Hebei is covered by two different lightning detection networks： SAFIR （Systeme d＇Alerte Fondre par Interferometrie Radioelecctrique） for total lightning, including IntraCloud （IC） f...The region of Beijing-Tianjin-Hebei is covered by two different lightning detection networks： SAFIR （Systeme d＇Alerte Fondre par Interferometrie Radioelecctrique） for total lightning, including IntraCloud （IC） flashes and Cloud-to-Ground （CG） flashes, and the ADTD （ADvanced TOA and Direction system; TOA denotes time of arrival） network of China for CG lightning. Fourteen isolated hail-bearing thunderstorms in this region were examined in this study, using the data of SAFIR and ADTD. The peak of lightning frequency, for both total lightning and CG lightning, was often observed in advance of the occurrence of hailstones on the ground, with a trend of a rapid increase of lightning frequency before the hail was reported. The average lead times of the two types of lightning jump before hail events were obtained （total lightning： 32.2 min; CG： 25.4 min） through the 2a lightning jump algorithm. Additionally, in hailstorms with a high ratio of positive CG flashes, the diameter of hail was larger and the duration of hail was longer; when negative CG flashes dominated, the diameter of hail was relatively small. The comparison of the characteristics of total lightning and CG flashes in hailstorms in this study is expected to serve as a supplementary tool for hail forecasting.展开更多
文摘针对业务运行中雷达观测存在遮挡和雷达产品延迟,提出利用带噪声基于密度的空间聚类(density-based spatial clustering of applications with noise,DBSC AN)算法对闪电数据的聚类结果替代雷达产品,并分别利用北京三维闪电定位网(Beijing Total Lightning System,BJTLS)和升级后的国家闪电定位网(DDW1)总闪数据,应用2σ闪电跃增算法对北京2022年6月4日和12日两次强对流致灾过程进行临近预警,对比强对流单体识别法和DBSCAN聚类法的预警效果。结果表明:两种算法和两种闪电数据均能有效预警北京地区的灾害性天气,基于BJTLS总闪数据的预警效果较优;对于BJTLS总闪数据,两种方法的预警效果相当,预警命中率、误报率、临近成功指数和平均预警提前时间依次分别为100%,11.9%,88.1%,38.9 min和100%,13.3%,86.7%,42.8 min;仅利用闪电数据并应用2σ闪电跃增算法可对灾害性天气进行临近预警,摆脱对雷达产品的依赖。
基金Supported by the National Natural Science Foundation of China (41030960 and 41105122)Project for Integration and Application of Meteorological Key Technology by the China Meteorological Administration (CAMGJ2012M78)National Science and Technology Support Program of China (2008BAC36B04)
文摘The region of Beijing-Tianjin-Hebei is covered by two different lightning detection networks： SAFIR （Systeme d＇Alerte Fondre par Interferometrie Radioelecctrique） for total lightning, including IntraCloud （IC） flashes and Cloud-to-Ground （CG） flashes, and the ADTD （ADvanced TOA and Direction system; TOA denotes time of arrival） network of China for CG lightning. Fourteen isolated hail-bearing thunderstorms in this region were examined in this study, using the data of SAFIR and ADTD. The peak of lightning frequency, for both total lightning and CG lightning, was often observed in advance of the occurrence of hailstones on the ground, with a trend of a rapid increase of lightning frequency before the hail was reported. The average lead times of the two types of lightning jump before hail events were obtained （total lightning： 32.2 min; CG： 25.4 min） through the 2a lightning jump algorithm. Additionally, in hailstorms with a high ratio of positive CG flashes, the diameter of hail was larger and the duration of hail was longer; when negative CG flashes dominated, the diameter of hail was relatively small. The comparison of the characteristics of total lightning and CG flashes in hailstorms in this study is expected to serve as a supplementary tool for hail forecasting.
