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首页> 外文期刊>Journal of Quantitative Spectroscopy & Radiative Transfer >Retrieving latent heating vertical structure from cloud and precipitation profiles-Part II: Deep convective and stratiform rain processes
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Retrieving latent heating vertical structure from cloud and precipitation profiles-Part II: Deep convective and stratiform rain processes

机译:从云和沉淀型材中检索潜伏的加热垂直结构 - 第二部分:深入对流和层状雨水过程

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摘要

An exploratory study on physical based latent heat (LH) retrieval algorithm is conducted by parameterizing the physical linkages between observed cloud and precipitation profiles to the major processes of phase change of atmospheric water. Specifically, rain is segregated into three rain types: warm, convective, and stratiform rain, based on their dynamical and thermodynamical characteristics. As the second of series, both convective and stratiform rain LH algorithms are presented and evaluated here. For convective and stratiform rain, the major LH-related microphysical processes including condensation, deposition, evaporation, sublimation, and freezing-melting are parameterized with the aid of Cloud Resolving Model (CRM) simulations. The condensation and deposition processes are parameterized in terms of rain formation processes through the precipitation formation theory. LH associated with the freezing-melting process is relatively small and is assumed to be a fraction of total condensation and deposition LH. The evaporation and sublimation processes are parameterized for three unsaturated scenarios: rain out of the cloud body, clouds at cloud boundary and clouds and rain in downdraft region. The evaluation or self-consistency test indicates the retrievals capture the major features of LH profiles and reproduce the double peaks at right altitudes. The LH products are applicable at various stages of cloud system life cycle for high-resolution models, as well as for large-scale climate models.
机译:通过参数化观察到的云和沉淀曲线之间的物理连接来进行物理潜热(LH)检索算法对大气水相变的主要过程进行的探索性研究。具体而言,雨被分为三种雨水:温暖,对流和层状雨,基于它们的动态和热力学特性。作为第二系列的第二个,这里呈现并评估了对流和层状雨LH算法。对于对流和层状雨,主要的LH相关的微球种方法包括借助于云解析模拟(CRM)模拟来参数化包括缩合,沉积,蒸发,升华和冷冻熔化。通过降水形成理论,在雨层过程方面参数化缩合和沉积工艺。与冷冻熔点过程相关的LH相对较小,并且假设是总缩合和沉积LH的一部分。蒸发和升华过程是针对三种不饱和情景的参数化:雨水从云端,云边界和云和下降区域下雨。评估或自我一致性测试表明检索捕获LH简档的主要特征,并在右海拔地区再现双峰。 LH产品适用于云系统生命周期的各个阶段,用于高分辨率模型,以及大规模的气候模型。

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