层状冷云人工增雨可播性实时识别技术研究

A STUDY OF REAL-TIME IDENTIFICATION OF SEEDABILITY OF COLD STRATIFORM CLOUDS

该文综合分析了 4次层状冷云人工增雨过程的雷达回波、粒子测量系统 (PMS)探测资料 ,以及GPS定位资料 ,提出应以PMS的FSSP 1 0 0探头探测的云中粒子浓度以及 2D C探头探测的云中大粒子浓度作为判别云中可播性的主要技术参量 ,并发展了层状冷云飞机人工增雨实时监测指挥技术。FSSP 1 0 0探测的粒子浓度不小于 2 0 /cm3的云区才具有一定的可播性。其中 2D C探测的大粒子浓度小于 2 0 /L时 ,可确定为强可播区 ,否则为可播区。

Based on integrated analysis of the cloud data obtained by digital radar,the particle measuring system (PMS) and the global positioning system (GPS), the main cloud physical parameters used to identify cloud seedability are proposed. Only when the relevant cloud particle concentration obtained by FSSP-100 probe of PMS is larger than 20/cm3, has the cloud area certain seedability. Furthermore, when the particle concentration obtained by 2D-C probe of PMS is less than 20/L, the cloud is highly seedable and otherwise it is seedable.