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北京层状云人工增雨数值模拟试验和机理研究
引用本文:何晖,高茜,李宏宇.北京层状云人工增雨数值模拟试验和机理研究[J].大气科学,2013,37(4):905-922.
作者姓名:何晖  高茜  李宏宇
作者单位:北京市人工影响天气办公室,北京100089;云降水物理研究与云水资源开发北京市重点实验室,北京100089
基金项目:国家自然科学基金项目41205100、41175007,公益性行业(气象)科研专项GYHY201306065、GYHY200906025,北京市气象局气象科技研发专项2012BMBKYZX01
摘    要:在中尺度WRF 模式的Morrison 双参数方案中引入了AgI 粒子与云相互作用的过程,在WRF 模式中实现了催化功能。利用加入了催化方案的中尺度模式对2008 年3 月20~21 日环北京地区一次层状云系降水过程进行模拟和催化试验。模拟自然降水与实测结果一致,分析微物理特征并在所得分析基础上进行催化试验。研究在不同催化剂量、高度和时刻进行试验对降水的影响。结果表明:以20 g 的碘化银进行催化作业,在催化后的前30min 之内,地面雨量轻微减小,最大累积减雨量为2010 t,30 min 后,净增雨量迅速增加,最大累积增雨量达到了3.4×105 t。催化开始阶段的减雨主要是由于播撒AgI 后,云水减少而雪晶增多,导致雨滴碰并云滴,云滴向雨滴自动转化过程的减少以及雪晶碰并雨滴过程的增多,然而空中增多的雪晶尚未下落到暖区融化成雨滴。而第二阶段的增雨则是空中增多的雪晶逐渐下落到暖区,雪晶融化成雨滴过程增多。AgI 的播撒率对降水量有明显影响,过量催化会使雪晶平均质量减少,下落速度锐减,从而雪融化成雨水减少,导致雨量减弱,不同催化高度和催化时间的催化结果表明在过冷水含量比较丰富而冰雪晶含量偏少的区域进行催化,增雨效果显著。

关 键 词:中尺度催化数值模式    层状云系    物理机制    催化效果
收稿时间:2012/6/25 0:00:00
修稿时间:2012/11/12 0:00:00

Numerical Simulation of Stratiform Precipitation Enhancement in Beijing Area and Its Mechanism
HE Hui,GAO Qian and LI Hongyu.Numerical Simulation of Stratiform Precipitation Enhancement in Beijing Area and Its Mechanism[J].Chinese Journal of Atmospheric Sciences,2013,37(4):905-922.
Authors:HE Hui  GAO Qian and LI Hongyu
Institution:Beijing Weather Modification Office, Beijing 100089;Key Laboratory of Beijing for Cloud, Precipitation, and Atmospheric Water Resources, Beijing 100089
Abstract:On the basis of the dynamic framework of the Weather Research and Forecasting Model (WRF) and the Morrison two-moment explicit cloud scheme, an AgI seeding scheme is developed and used to simulate stratiform precipitation during March 20-21, 2008. The simulated rainfall is similar to the observations, in which several seeding tests for different seeding amounts, seeding levels, and seeding times are examined on the basis of cloud microphysical analysis. The results show that seeding with an amount of 20 g slightly suppresses the surface rainfall in 30 min, rapidly enhances the surface rainfall after 30 min; the maximum suppressed and enhanced rainfall are 2010 t and 3.4×105 t, respectively. The microphysical mechanism of decreasing rainfall is the depletion of supercooled water and an increase in snow and ice after AgI is injected into the cloud, which lead to the decrease conversion rate of rain collide with cloud water as same as cloud water auto converse into rain water but increase conversion rate of snow collide with rain, while enhanced snow cannot fall to the warm region to melt at this time. The microphysical mechanism that increased rainfall 30 min after the seeding operation is that enhanced snow gradually fell to the warm region and melted into rain. Different seeding amounts strongly influence the surface precipitation. Overseeding will reduce the average mass of snow crystals, causing the falling speed to sharply decline; thus, the amount of snow melting into rain is reduced, decreasing rainfall. Sensitive experiments with different seeding heights and seeding times show that when seeding is conducted in areas with a high supercooled water content and low ice particle content, the surface rainfall will be increased.
Keywords:Mesoscale cloud-seeding model  Stratiform precipitation  Physical mechanism  Seeding effect
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