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Macroscopic impacts of cloud and precipitation processes on maritime shallow convection as simulated by a large eddy simulation model with bin microphysics

机译:利用bin微物理学的大型涡模拟模型模拟云和降水过程对海洋浅层对流的宏观影响

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摘要

This paper discusses impacts of cloud and precipitation processeson macrophysical properties of shallow convective clouds as simulatedby a large eddy model applying warm-rain bin microphysics. Simulationswith and without collision–coalescence are considered with cloud condensationnuclei (CCN) concentrations of 30, 60, 120, and 240 mg. Simulationswith collision–coalescence include either the standard gravitationalcollision kernel or a novel kernel that includes enhancements dueto the small-scale cloud turbulence. Simulations with dropletcollisions were discussed in Wyszogrodzki et al. (2013) focusingon the impact of the turbulent collision kernel. The current paperexpands that analysis and puts model results in the context ofprevious studies. Despite a significant increase of the drizzle/rainwith the decrease of CCN concentration, enhanced by the effects ofthe small-scale turbulence, impacts on the macroscopic cloud fieldcharacteristics are relatively minor. Model results show a systematicshift in the cloud-top height distributions, with an increasingcontribution of deeper clouds for stronger precipitating cases. Weshow that this is consistent with the explanation suggested inWyszogrodzki et al. (2013); namely, the increase of drizzle/rainleads to a more efficient condensate offloading in the upperparts of the cloud field. A second effect involves suppression ofthe cloud droplet evaporation near cloud edges in low-CCN simulations,as documented in previous studies (e.g., Xue and Feingold, 2006).We pose the question whether the effects of cloud turbulence ondrizzle/rain formation in shallow cumulican be corroborated by remote sensingobservations, for instance, from space. Although a clear signal isextracted from model results, we argue that the answer is negativedue to uncertainties caused by the temporal variability of theshallow convective cloud field, sampling and spatial resolution ofthe satellite data, and overall accuracy of remote sensing retrievals.
机译:本文讨论了云和降水过程对浅层对流云宏观物理特性的影响,这是通过应用暖雨箱微物理学的大型涡流模型模拟得出的。在有和没有碰撞-聚结的情况下进行模拟时,云凝结核(CCN)的浓度分别为30、60、120和240 mg。具有碰撞-聚结的模拟包括标准重力碰撞内核或新颖的内核,该内核由于小规模的云湍流而具有增强功能。 Wyszogrodzki等人讨论了液滴碰撞的仿真。 (2013年)专注于湍流碰撞核的影响。当前论文扩展了该分析并将模型结果置于先前研究的背景下。尽管随着小尺度湍流的影响,小雨/雨水随着CCN浓度的降低而显着增加,但对宏观云场特征的影响相对较小。模型结果表明,云顶高度分布发生了系统性变化,对于更强的降水情况,深层云的贡献增加。我们证明这与Wyszogrodzki等人提出的解释是一致的。 (2013);也就是说,细雨/雨水的增加导致云场上部的冷凝水更有效地卸载。第二个影响是在低CCN模拟中抑制云边缘附近的云滴蒸发,如先前的研究所述(例如,Xue和Feingold,2006年)。我们提出了一个问题,即云湍流是否对浅积丘中的降雨/雨水形成有影响?例如由太空的遥感观测所证实。尽管从模型结果中得出了清晰的信号,但我们认为答案是负面的,原因是不确定性是由浅对流云场的时间变化,卫星数据的采样和空间分辨率以及遥感检索的整体准确性引起的。

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