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高原气象  2017, Vol. 36 Issue (5): 1276-1289    DOI: 10.7522/j.issn.1000-0534.2016.00116
论文     
北京地区一次降雪过程的人工催化数值模拟研究
师宇1,2, 楼小凤3,4, 单云鹏5, 胡非1,2
1. 中国科学院大气物理研究所大气边界层物理和大气化学国家重点实验室, 北京 100029;
2. 中国科学院大学, 北京 100049;
3. 中国气象科学研究院灾害天气国家重点试验室, 北京 100081;
4. 中国气象科学研究院/中国气象局云雾物理试验室, 北京 100081;
5. Division of atmospheric science, Desert Research Institute, Reno, NV 89512, USA
Numerical Simulation of Rain Enhancement Seeding of a Snowfall Case in Beijing Area
SHI Yu1,2, LOU Xiaofeng3,4, SHAN Yunpeng5, HU Fei1,2
1. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. State Key Laboratory of Disaster Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China;
4. Key Laboratory for Cloud Physics of China Meteorological Administration, Beijing 100081, China;
5. Division of atmospheric science, Desert Research Institute, Reno, NV 89512, USA
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摘要: 利用中尺度气象模式WRF的双参数显示云物理方案,开展冬季冷性层状云降水过程的数值模拟和人工增雨催化数值试验。模拟个例为2013年3月19日北京地区的一次典型降水过程,在分析模拟得到的云中水成物和上升速度分布的基础上设计不同催化试验,研究不同催化时刻(云体发展期、云体成熟期)和三种催化剂量对地面降水、云中水成物浓度、动力场和热力场以及微物理转化过程的影响。模拟试验结果表明:模拟的自然降水分布和实测结果较为一致;不同的催化试验都可以使地面雨量增加,在云体发展期以107个·kg-1剂量进行催化的效果最佳;引入人工冰晶后催化区域水汽和过冷云水含量明显减少、冰晶和雪的含量有所增加、催化区域上升气流明显增强,温度提高;催化后40 min时雪的增长主要依靠其凝华增长、冰晶向雪的自动转化、雪和云滴之间的碰冻以及冰晶和雪之间的碰并;催化后200 min,催化云中各种微物理过程对雪的贡献高于自然云,催化前期消耗了过冷云水,此时云中雪和云滴之间的碰冻对雪的贡献非常微弱,雪的增长主要依靠凝华增长以及雪和冰晶的相互作用。
关键词: 云降水物理数值模拟人工增雨催化试验    
Abstract: In recent years, the drought situation in Beijing area is very serious, especially in the winter.How to effectively utilize the water resources in the air and carry out rain enhancement operation is important.Rain enhancement operation in winter is also likely to be used to remove fog and haze, and furthermore to improve air quality and visibility.Cloud models have been used in weather modification to formulate cloud-seeding hypotheses, assessments of the cloud-seeding potential or "seed ability".In this study, the numerical simulations of a snowfall case was carried out by using the two-moment explicit cloud scheme (nssl) of WRF model.The nssl scheme can predict the particle number concentration and mixing ratio of cloud water, rain, ice, snow, graupel and hail.For the snowfall case in Beijing on 19 March 2013, several seeding tests were designed to study the effects of different seeding time and seeding rate on cloud processes and precipitation amounts.The experimental results showed that all seeding tests could increase rainfall amount.When seeding with an amount of 1×107 kg-1 in cloud developing period, the rain enhancement effect was the best.The water vapor and supercooled cloud water mixing ratio in seeding area decreased after seeding, meanwhile the mixing ratios of ice and snow increased.The updraft and temperature of this area also increased.In 40 min after seeding, snow mixing ratios mainly grew through microphysical processes of deposition, the automatic conversion of ice to snow, snow accretion of cloud droplets, the collision between ice and snow.In 200 min after seeding, microphysical conversion processes of snow sources in the catalytic clouds were all higher than the natural clouds.Because of the consumption of supercooled cloud water in seeding clouds, the accretion process between cloud droplets and snow was very small.The snow mixing ratio mainly increased through terms of snow deposition and the interaction between snow and ice.The research results are helpful to understand the seeding effects on the macro and micro-processes of winter stratiform clouds, which will provide the basis for the rainfall enhancement field operations.
Key words: Cloud precipitation physics    Numerical simulation    Artificial precipitation    Seeding experiment
收稿日期: 2016-09-18 出版日期: 2017-10-20
:  P481  
基金资助: 国家自然科学基金项目(41275148,11472272,41675137)
通讯作者: 楼小凤.E-mail:louxf@camscma.cn     E-mail: louxf@camscma.cn
作者简介: 师宇(1993-),女,山西大同人,博士研究生,主要从事大气物理和大气环境研究,E-mail:shiyu@mail.iap.ac.cn
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引用本文:

师宇, 楼小凤, 单云鹏, 胡非. 北京地区一次降雪过程的人工催化数值模拟研究[J]. 高原气象, 2017, 36(5): 1276-1289.

SHI Yu, LOU Xiaofeng, SHAN Yunpeng, HU Fei. Numerical Simulation of Rain Enhancement Seeding of a Snowfall Case in Beijing Area. PLATEAU METEOROLOGY, 2017, 36(5): 1276-1289.

链接本文:

http://www.gyqx.ac.cn/CN/10.7522/j.issn.1000-0534.2016.00116        http://www.gyqx.ac.cn/CN/Y2017/V36/I5/1276

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