人工增雨(雪)三要素潜力指标分析及业务应用

对2015—2016年秋冬季4次小雨过程云中液水含量、地面降水量和近地面大气细颗粒物浓度PM_2.5三要素观测资料统计，得到47个数据组个例，根据冷云催化和天气动力学原理，在对47例增雨(雪)潜力定性分析基础上，结合大气污染数值模拟结果对三要素关联性进一步综合分析，探讨和研究了三要素组合的潜力量化指标。即地面未降水时作业潜力指标为：1.5>N>0.1,PM_2.5<78;2.5>N>1.5,PM_2.5<86;N>2.5,PM_2.5<93。地面降水时的作业潜力指标为：1.5>N>0.1,R<1.9,PM_2.5<78;2.5>N>1.5,R<2.6,PM_2.5<86;N>2.5,R<2.8,PM_2.5<93(其中N、R、PM_2.5分别为小时云中液水含量、地面降水量和近地面细颗粒物浓度)。采用C#.net编程技...

Research on Artificial Precipitation (Snow)Three-factor Potential Indicators and Its Application

By statistically classifying cloud liquid water, surface rainfall and near surface PM_2.5 concentration during four light rain cases in Autumn and winter from 2015 to 2016, 47 data combination cases are derived. According to the principle of cold cloud catalytic and weather dynamics, as well as the quantitative analysis on the artificial enhancement of 47 cases, combine with the air pollution simulation, the relationship and enhancement potential indication of the three factors are analyzed. C#.net programming is used to develop the platform, which is operationally applied. The potential indicators of artificial precipitation (snow) in 28 light rainfall cases from 2018 to 2019 are analyzed and verified in this method. The platform timely outputs potential results. The accuracy rate reaches 86%. The results provide an important basis for decision making of artificial precipitation (snow) operations in pollutant air conditions. Verifying light rain case on 13 April 2019 in this method, the expected results are achieved.