Supersaturation calculation in large eddy simulation models for prediction of the droplet number concentration
Supersaturation calculation in large eddy simulation models for prediction of the droplet number concentration
复制标题
大涡模拟模型中的过饱和度计算用于预测液滴数浓度
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
F. Burnet
中科院分区：
文献类型：
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作者：
O. Thouron;J. Brenguier;F. Burnet
抽象的。描述了一种新的参数化方案，用于计算LES模式中的过饱和度，该方案专门针对云凝结核（CCN）激活的模拟和液滴数浓度的预测。该计划进行了测试，对目前的参数化的框架中的中-NH LES模式。结果表明，基于对流上升气流中CCN激活参数化的饱和度调整方案高估了云核中的液滴浓度，而无法模拟由于多云和晴朗空气混合而产生的云顶过饱和度。过饱和诊断方案通过考虑云核中已经凝结的水的存在来减轻这些人为因素，但它对云顶的过饱和波动太敏感，并在云顶混合期间产生虚假的CCN激活。所提出的伪预测方案显示出与云核中的诊断方案类似的性能，但显著减轻了云顶处的CCN激活。
Abstract. A new parameterization scheme is described for calculation of supersaturation in LES models that specifically aims at the simulation of cloud condensation nuclei (CCN) activation and prediction of the droplet number concentration. The scheme is tested against current parameterizations in the framework of the Meso-NH LES model. It is shown that the saturation adjustment scheme, based on parameterizations of CCN activation in a convective updraft, overestimates the droplet concentration in the cloud core, while it cannot simulate cloud top supersaturation production due to mixing between cloudy and clear air. A supersaturation diagnostic scheme mitigates these artefacts by accounting for the presence of already condensed water in the cloud core, but it is too sensitive to supersaturation fluctuations at cloud top and produces spurious CCN activation during cloud top mixing. The proposed pseudo-prognostic scheme shows performance similar to the diagnostic one in the cloud core but significantly mitigates CCN activation at cloud top.