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首页> 外文期刊>Quarterly Journal of the Royal Meteorological Society >Modelling the diurnal cycle of deep precipitating convection over land with cloud-resolving models and single-column models.
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Modelling the diurnal cycle of deep precipitating convection over land with cloud-resolving models and single-column models.

机译:使用云解析模型和单列模型对陆地上的深度降水对流的昼夜周期进行建模。

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摘要

An idealized case-study has been designed to investigate the modelling of the diurnal cycle of deep precipitating convection over land. A simulation of this case was performed by seven single-column models (SCMs) and three cloud-resolving models (CRMs). Within this framework, a quick onset of convective rainfall is found in most SCMs, consistent with the results from general-circulation models. In contrast, CRMs do not predict rainfall before noon. A joint analysis of the results provided by both types of model indicates that convection occurs too early in most SCMs, due to crude triggering criteria and quick onsets of convective precipitation. In the CRMs, the first clouds appear before noon, but surface rainfall is delayed by a few hours to several hours. This intermediate stage, missing in all SCMs except for one, is characterized by a gradual moistening of the free troposphere and an increase of cloud-top height. Later on, convective downdraughts efficiently cool and dry the boundary layer (BL) in the CRMs. This feature is also absent in most SCMs, which tend to adjust towards more unstable states, with moister (and often more cloudy) low levels and a drier free atmosphere. This common behaviour of most SCMs with respect to deep moist convective processes occurs even though each SCM simulates a different diurnal cycle of the BL and atmospheric stability. The scatter among the SCMs results from the wide variety of representations of BL turbulence and moist convection in these models. Greater consistency is found among the CRMs, despite some differences in their representation of the daytime BL growth, which are linked to their parametrizations of BL turbulence and/or resolution.
机译:设计了一个理想的案例研究,以研究陆地上深度降水对流的昼夜循环模型。通过七个单列模型(SCM)和三个云解析模型(CRM)对这种情况进行了模拟。在此框架内,大多数SCM中都发现了对流降雨的快速爆发,这与全环流模型的结果一致。相反,CRM不能在中午之前预测降雨量。对这两种类型的模型提供的结果进行的联合分析表明,由于粗略的触发标准和对流降水的快速开始,大多数SCM中对流发生得太早。在CRM中,第一场云出现在中午之前,但是地表降雨延迟了几个小时到几个小时。除一个以外的所有SCM中都缺少的这一中间阶段,其特征是自由对流层逐渐变湿和云顶高度增加。后来,对流下沉有效地冷却和干燥了CRM中的边界层(BL)。在大多数SCM中也没有此功能,这些SCM趋向于向更加不稳定的状态调整,具有低潮(通常更多云)的低水平和干燥的大气。即使每个SCM模拟BL的昼夜周期和大气稳定性,大多数SCM在深湿对流过程中也会出现这种常见行为。在这些模型中,SCM之间的分散是由于BL湍流和湿对流的各种表示形式造成的。尽管CRM在白天BL增长的表示上存在一些差异,这与CRM BL湍流和/或分辨率的参数化有关,但在CRM中发现了更高的一致性。

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