The Macroscopic Entrainment Processes of Simulated Cumulus Ensemble. Part II: Testing the Entraining-Plume Model
The Macroscopic Entrainment Processes of Simulated Cumulus Ensemble. Part II: Testing the Entraining-Plume Model
复制标题
模拟积云系综的宏观夹带过程。
DOI：
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发表时间：
1997
期刊：
影响因子：
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通讯作者：
A. Arakawa
中科院分区：
文献类型：
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作者：
Chichung Lin;A. Arakawa
本文第一部分指出，在积云参数化云模式（CMCP）中，如Arakawa-Schubert参数化中的谱积云集合模式，忽略下降云气的贡献似乎是一种可以接受的热带深对流简化。由于谱积云集合模式中的每个子集合形式上类似于卷流，后者使用云分辨模式（CRM）的模拟数据进行了研究。作者首先遵循华纳的分析程序。用一个非降水试验的资料表明，该模式不能同时预报CRM所模拟的云的平均液态水廓线和云顶高度。然而，云的活动元素的平均属性，其特征是强烈的上升气流，可以描述为一个夹带羽相似的顶部高度。作者利用沉淀实验的数据，对这一现象进行了分析。
Abstract According to Part I of this paper, it seems that ignoring the contribution from descendent cloud air in a cloud model for cumulus parameterization (CMCP), such as the spectral cumulus ensemble model in the Arakawa–Schubert parameterization, is an acceptable simplification for tropical deep convection. Since each subensemble in the spectral cumulus ensemble model is formally analogous to an entraining plume, the latter is examined using the simulated data from a cloud-resolving model (CRM). The authors first follow the analysis procedure of Warner. With the data from a nonprecipitating experiment, the authors show that the entraining-plume model cannot simultaneously predict the mean liquid water profile and cloud top height of the clouds simulated by the CRM. However, the mean properties of active elements of clouds, which are characterized by strong updrafts, can be described by an entraining plume of similar top height. With the data from a precipitating experiment, the authors examine the spec...