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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Influence of cloud condensation and giant cloud condensation nuclei on the development of precipitating trade wind cumuli in a large eddy simulation
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Influence of cloud condensation and giant cloud condensation nuclei on the development of precipitating trade wind cumuli in a large eddy simulation

机译:云凝结和大云的影响凝结核的发展沉淀信风堆积在一个大的涡流模拟

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To investigate the effects of both cloud condensational nuclei (CCN) and giant CCN (GCCN), the Regional Atmospheric Modeling System was used to investigate the effects of various CCN and GCCN concentrations on the development of precipitating trade wind cumuli in a large eddy simulation (LES) framework. The sounding to initialize the LES was taken from the Rain in Cumulus over the Ocean Experiment archive for11 January 2005. Several sensitivity experiments were performed in which two levels of CCN (GCCN) concentrations were used: 100 (0.01) and 1000 (0.1) cm-3 corresponding to low and high values, respectively. Both CCN and GCCN can affect the precipitation processes. With low GCCN concentration, raising the CCN concentration from low to high reduced the precipitation rate as well as the accumulated precipitation due to the presence of a large number of small cloud droplets that are inefficient in forming drizzle. However, GCCN can have a greater response in increasing the precipitation rate and accumulation when the cloud system has a high CCN concentration. The total cloud coverage (TCC) was reduced for the higher CCN concentration experiments because of the susceptibility of evaporation of cloud droplets in the upper parts of the cloud as a result of entrainment. On the other hand, the TCC was increased for the higher GCCN concentration experiments. For this trade wind cumuli case, the time- and domain-averaged albedo changed very slightly with increased [CCN] and/or [GCCN] because of a compensating increase/decrease among the optical depth, liquid water path, cloud coverage, and cloud droplet concentration.
机译:调查两个云的影响收缩核(CCN)和巨人CCN (GCCN),使用区域大气建模系统调查各种CCN的影响GCCN浓度的发展沉淀信风堆积在一个大的涡流模拟(LES)框架。初始化莱斯从雨中积云在海洋实验档案看重2005年1月。进行两个层次的CCN (GCCN)使用浓度:100(0.01)1000人(0.1) cm-3对应低和高值,分别。降水过程。浓度,提高CCN浓度低到高减少了降水率积累沉淀造成的存在大量小云液滴形成细雨中效率低下。然而,GCCN可以有一个更大的反应增加了降水率和当云系统积累CCN很高浓度。减少对CCN的浓度就越高实验的易感性云滴的蒸发上部分云的诱导作用的结果。另一方面,太极拳组增加的更高GCCN浓度实验。风堆积情况下,时间和domain-averaged与(CCN)增加反照率变化非常小和/或GCCN由于补偿增加/减少光学深度,液体水道路、云覆盖,和云滴浓度。

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