基于云雷达反射率因子的云宏观参量反演

Retrieval on Macro- physical Parameters of Cloud Based on the Reflectivity Factor of Cloud Radar

针对2012年7月23日云南腾冲的一次混合型层状云降水过程,联合35 GHz多普勒偏振云雷达、雨滴谱仪和探空仪进行联合观测与分析,根据Z—q_r(雷达反射率因子—雨水含量)的关系式,反演雨水含量(q_r)、云水含量(q_c)以及空气垂直速度(w)。结果表明:在较强回波区,云水含量为0.5~0.8 g·kg^(-1),雨水含量为0.2 g·kg^(-1),空气垂直速度为0.6~1.0 m·s^(-1),对应时段的小时雨量较大;通过云水含量与雨水含量、雨水含量与雷达反射率因子的散点图,分别得到各自的拟合公式。当云水含量<0.8 g·kg^(-1)时,直接通过拟合公式得到的云宏观参量的精度较好。

The wet physical process is commonly known as the mutual transformation between the cloud water,water vapor and ice under the dynamic and thermal process influences. The traditional observation instruments are difficult to get the mesoscale circulation information,meanwhile the parameters such as cloud water content,rain water content and air vertical motion are not directly detected by these instruments. However,the incorporation of macrophysical parameters and the coherence of physical variables in the initial field of numerical weather prediction are very important to the non-hydrostatic equilibrium explicit cloud model with high resolution less than 10 km,it is still a difficult problem in cloud analysis field for a long time. Based the observation data from 35 GHz cloud radar,raindrop spectrometer and radiosonde,the macrophysical parameters of rain water content,cloud water content and air vertical speed in a mixed stratiform cloud rainfall process occurred in Tengchong of Yunnan Province on 23 July 2012 were simulated by using the fitting relationship between the reflectivity factor of cloud radar and rain water content. The results show that the main spatial distribution characteristics of the cloud water content,rain water content and air vertical motion were consistent with the reflectivity factor of radar.The cloud water content and rain water content in strong echo area were 0. 5-0. 8 g·kg^-1 and 0. 12 g·kg^-1 ,respectively,the air vertical motion speed was 0.6-1.0 m·s^-1,and the corresponding rainfall intensity was larger. When the precipitation weakened,the rain water content decreased accordingly,and the vertical movement of air also slowed,while the change of cloud water content was not obvious. When the cloud water content was less than 0. 8 g·kg^-1 ,the precision of cloud macro-parameters directly obtained by the fitting equation was better.