摘要
江淮对流云是安徽省夏季开展人工增雨作业的主要作业对象,不同于经过严格试验设计的随机试验,大多采用非随机的地面火箭、高炮或者烟炉的作业方式。由于对流云存在生命期较短局地性强、自然变差较大等特点,对其作业效果进行客观、科学、定量的效果评估存在一定困难。利用安徽省国家级地面气象站降水量日值数据和覆盖目标区的SA多普勒雷达资料,将区域历史回归分析统计检验方法和播云多普勒雷达识别追踪及物理检验方法相结合对2012年6月28—30日江淮对流云增雨作业效果进行个例分析。结果表明,作业后目标区绝对增雨37.2 mm,相对增雨65.18%,统计显著度α<0.1;基于雷达探测基数据识别追踪作业单元,选取合适对比单元,对比分析作业单元与对比单元作业前后雷达回波参量的变化差异给出了对应统计检验结果的物理证据。
Convective clouds in Yangtze-Huaihe Region are the main seeding objects of precipitation en- hancement experiments in Anhui Province in summer. Unrandomized seeding operations are usually adopt ed using rocket launchers, artilleries or ground generators, rather than the randomized trials through strict test design due to some limited condition. Convective clouds have characteristics of short life span and con- siderable large local and natural variations, which add great difficulties to the objective, scientific and quantitative evaluation of the operation effects. Based on daily rainfall data of national ground stations of Anhui Province and SA Doppler Radar data of the operation areas, this paper makes a case study on the seeding effects of convective clouds in Yangtze-Huaihe Region from 28 to 30 June 2012 with combination of regional historical regression statistical analysis and physical test method using Doppler Radar identifica- tion and track of cloud seeding. The results indicate that the rainfall of target area increases 37.2 mm and obtains an enhancement rate of 65. 19% after seeding, with a significant level a〈0. 1. We identify and track seeded units according to the radar data, define appropriate control units and then compare the radar echo parameters of seeded units and control units before and after operation to give physical evidence of the operation effects.
出处
《气象》
CSCD
北大核心
2016年第2期238-245,共8页
Meteorological Monthly
基金
国家自然科学基金面上项目(41375135)
公益性行业(气象)科研专项(GYHY201306040和GYHY201406033)共同资助
关键词
对流云
增雨作业
统计检验
物理检验
convective cloud, precipitation enhancement, statistical evaluation, physical test
作者简介
贾烁，从事云降水与人工影响天气研究．Email：jia91shuo@163．com
通信作者：姚展予，从事云降水与人工影响天气研究．Email：yaozy@cams．cma．gov．cn
