首页> 外文期刊>Quarterly Journal of the Royal Meteorological Society >Modelling convective processes during the suppressed phase of a Madden-Julian oscillation: Comparing single-column models with cloud-resolving models
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Modelling convective processes during the suppressed phase of a Madden-Julian oscillation: Comparing single-column models with cloud-resolving models

机译:对Madden-Julian振荡抑制阶段的对流过程进行建模:将单列模型与云解析模型进行比较

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The role of convective processes in moistening the atmosphere during suppressed periods of the suppressed phase of a Madden-Julian oscillation is investigated in cloud-resolving model (CRM) simulations, and the impact of moistening on the subsequent evolution of convection is assessed as part of a Global Energy and Water Cycle Experiment Cloud System Study (GCSS) intercomparison project. The ability of single-column model (SCM) versions of a number of state-of-the-art climate and numerical weather prediction models to capture these convective processes is also evaluated. During the suppressed periods, the CRMs are found to simulate a maximum moistening around 3 km, which is associated with a predominance of shallow convection. All SCMs produce adequate amounts of shallow convection during the suppressed periods, comparable to that seen in CRMs, but the relatively drier SCMs have higher precipitation rates than the relatively wetter SCMs and CRMs. The relatively drier SCMs dry, rather than moisten,the lower troposphere below the melting level. During the transition periods, convective processes act to moisten the atmosphere above the level at which mean advection changes from moistening to drying, despite an overall drying effect for the column. The SCMs capture some essence of this moistening at upper levels. A gradual transition from shallow to deep convection is simulated by the CRMs and the wetter SCMs during the transition periods, but the onset of deep convection is delayed in the drier SCMs. This results in lower precipitation rates for these SCMs during the active periods, although much better agreement exists between the models at this time.
机译:在云解析模型(CRM)模拟中研究了对流过程在Madden-Julian振荡抑制相的抑制期中的增湿过程中的作用,并评估了增湿对随后对流演变的影响。全球能源和水循环实验云系统研究(GCSS)比较项目。还评估了许多最新气候和数值天气预报模型的单列模型(SCM)版本捕获这些对流过程的能力。在抑制期间,发现CRM可以模拟3 km附近的最大湿度,这主要与浅对流有关。与在CRM中所见的情况相比,所有SCM在抑制期间都产生了足够数量的浅对流,但是相对较干燥的SCM与相对较湿的SCM和CRM相比,降水量较高。相对较干燥的SCM在融化水平以下将对流层下层干燥而不是变湿。在过渡期间,对流过程的作用是使大气湿润,使其​​高于对流从湿润变为干燥的平均水平,尽管该柱具有整体干燥效果。 SCM在较高级别捕获了这种润湿的本质。 CRM和较湿的SCM在过渡期间模拟了从浅对流逐渐过渡到深对流的过程,但较干燥的SCM延迟了深对流的发生。尽管目前模型之间存在更好的一致性,但是这导致活动期间这些SCM的降水率较低。

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