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首页> 外文期刊>Journal of Applied Meteorology >A Large-Droplet Mode and Prognostic Number Concentration of Cloud Droplets in the Colorado State University Regional Atmospheric Modeling System (RAMS). Part I: Module Descriptions and Supercell Test Simulations
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A Large-Droplet Mode and Prognostic Number Concentration of Cloud Droplets in the Colorado State University Regional Atmospheric Modeling System (RAMS). Part I: Module Descriptions and Supercell Test Simulations

机译:科罗拉多州立大学区域大气建模系统(RAMS)中的云滴的大滴模式和预测数集中。第一部分:模块说明和Supercell测试模拟

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摘要

The microphysics module of the version of the Regional Atmospheric Modeling System (RAMS) maintained at Colorado State University has undergone a series of improvements, including the addition of a large-cloud-droplet mode from 40 to 80 mu m in diameter and the prognostic number concentration of cloud droplets through activation of cloud condensation nuclei (CCN) and giant CCN (GCCN). The large-droplet mode was included to represent the dual modes of cloud droplets that often appear in nature. The activation of CCN is parameterized through the use of a Lagrangian parcel model that considers ambient cloud conditions lor the nucleation of cloud droplets from aerosol. These new additions were tested in simulations of a supercell thunderstorm initiatedfrom a warm, moist bubble. Model response was explored in regard to the microphysics sensitivity to the large-droplet mode, number concentrations of CCN and GCCN, size distributions of these nuclei, and the presence of nuclei sources and sinks.
机译:科罗拉多州立大学维护的区域大气建模系统(RAMS)版本的微物理学模块进行了一系列改进,包括添加了直径从40到80微米的大云滴模式和预后数通过激活云凝结核(CCN)和巨型CCN(GCCN)浓缩云滴。大液滴模式被包括来代表自然界中经常出现的云滴的双重模式。通过使用拉格朗日包裹模型对CCN的激活进行参数化,该模型考虑了环境云条件或来自气溶胶的云滴成核。这些新添加物在模拟由温暖潮湿的气泡引发的超级单体雷暴中进行了测试。探索了关于大液滴模式的微观物理敏感性,CCN和GCCN的浓度,这些原子核的大小分布以及原子核源和汇的存在的模型响应。

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