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Does precipitation susceptibility vary with increasing cloud thickness in marine stratocumulus

机译:海洋层积云中的降雨敏感性是否随云层厚度的增加而变化

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The relationship between precipitation rate and accumulation mode aerosol concentration in marine stratocumulus-topped boundary layers is investigated by applying the precipitation susceptibility metric to aircraft data obtained during the VOCALS Regional Experiment. A new method to calculate the precipitation susceptibility that incorporates non-precipitating clouds is introduced. The mean precipitation rate R over a segment of the data is expressed as the product of a drizzle fraction f and a drizzle intensity I (mean rate for drizzling columns). The susceptibility Sx is then defined as the fractional decrease in precipitation variable x Combining double low line {R, f, I} per fractional increase in the concentration of aerosols with dry diameter >0.1 ?1/4m, with cloud thickness h held fixed. The precipitation susceptibility SR is calculated using data from both precipitating and non-precipitating cloudy columns to quantify how aerosol concentrations affect the mean precipitation rate of all clouds of a given h range and not just the mean precipitation of clouds that are precipitating. SR systematically decreases with increasing h, and this is largely because Sf decreases with h while SI is approximately independent of h. In a general sense, Sf can be thought of as the effect of aerosols on the probability of precipitation, while SI can be thought of as the effect of aerosols on the intensity of precipitation. Since thicker clouds are likely to precipitate regardless of ambient aerosol concentration, we expect Sf to decrease with increasing h. The results are broadly insensitive to the choice of horizontal averaging scale. Similar susceptibilities are found for both cloud base and near-surface drizzle rates. The analysis is repeated with cloud liquid water path held fixed instead of cloud thickness. Simple power law relationships relating precipitation rate to aerosol concentration or cloud droplet concentration do not capture this observed behavior.
机译:通过将降水敏感性指标应用于VOCALS区域实验期间获得的飞机数据,研究了海洋平顶云顶边界层中降水率与累积模式气溶胶浓度之间的关系。介绍了一种结合非降水云计算降水敏感性的新方法。数据段上的平均降水率R表示为毛毛雨分数f和毛毛雨强度I(毛毛雨柱的平均率)的乘积。然后将磁化率Sx定义为降水变量x的分数降低x结合干燥直径> 0.1?1 / 4m且气溶胶厚度h保持固定的气溶胶浓度每增加分数所得到的双重低线{R,f,I}。降水敏感性SR是使用来自降水和非降水阴云列的数据计算得出的,以量化气溶胶浓度如何影响给定h范围内所有云的平均降水率,而不仅是影响正在降水的云的平均降水。 SR随着h的增加而系统地降低,这主要是因为Sf随着h的降低而SI却与h几乎无关。在一般意义上,Sf可以被认为是气溶胶对降水概率的影响,而SI可以被认为是气溶胶对降水强度的影响。由于无论环境气溶胶浓度如何,较厚的云层都有可能沉淀,因此我们预计Sf将随着h的增加而降低。结果对水平平均标度的选择大体上不敏感。对于云层基数和近地表毛毛雨率都发现了相似的敏感性。使用固定的云液体水路径而不是云厚度来重复分析。将降水速率与气溶胶浓度或云滴浓度相关的简单幂律关系无法捕获这种观察到的行为。

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