Analysis of Tools Used to Quantify Droplet Clustering in Clouds
Analysis of Tools Used to Quantify Droplet Clustering in Clouds
复制标题
用于量化云中液滴聚集的工具分析
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
R. Lawson
中科院分区：
文献类型：
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作者：
B. Baker;R. Lawson
沿沿着一条穿过云的近似水平线观察到的云滴的间距可以用各种技术来分析，以揭示小尺度上的结构，有时称为聚类，如果这种结构存在的话。已经应用了一些技术，还提出了其他一些技术，但尚未严格界定和应用。在本文中，技术进行了研究和评价，使用合成液滴间距数据。对于本研究所模拟的小尺度结构（聚类）类型，最有前途的分析方法是使用功率谱和捕捞统计量的组合。标准偏差和置信区间的功率谱，对相关函数，和修改后的捕鱼统计。聚类指数和体积平均对相关性被证明是有用的正规化形式的捕捞统计。
Abstract The spacing of cloud droplets observed along an approximately horizontal line through a cloud may be analyzed using a variety of techniques to reveal structure on small scales, sometimes called clustering, if such structure exists. A number of techniques have been applied and others have been suggested but not yet rigorously defined and applied. In this paper techniques are studied and evaluated using synthetic droplet spacing data. For the type of small-scale structure (clustering) modeled in this study, the most promising analysis approach is to use a combination of the power spectrum and the fishing statistic. Standard deviations and confidence intervals are determined for the power spectrum, the pair correlation function, and a modified fishing statistic. The clustering index and the volume-averaged pair correlation are shown to be less usefully normalized forms of the fishing statistic.