On the selection of prognostic moments in parametrization schemes for drop sedimentation
On the selection of prognostic moments in parametrization schemes for drop sedimentation
复制标题
关于液滴沉降参数化方案中预测时刻的选择
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
C. Lüpkes
中科院分区：
文献类型：
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作者：
U. Wacker;C. Lüpkes
摘要
云微物理过程的常见参数化模型使用凝结物质量密度和/或粒子数密度作为预报属性。然而，粒径分布的其他矩同样可被选作预测之用。本研究涉及分别具有一个和两个预报矩的液滴集合沉降参数化模型。光谱分辨模型定义了参考解。液态水含量、液滴数密度和降雨率的垂直廓线演变强烈依赖于参数化模型中预报矩的选择。在具有单个预报矩的模型中，其垂直廓线被所有其他矩复制。建议选择物理相关性最强的矩进行预测。在具有两个预报矩的模型中，所有矩的垂直廓线都不同。预报矩的阶数应选择接近相关性最高的矩的阶数。否则会出现较大误差。例如，如果从例如数密度和质量密度诊断雷达反射率，那么模拟的与观测的雷达反射率（相对于直径的6阶矩）的比较并不能很好地说明其他属性的质量。此外，只有预测质量密度时才能满足质量守恒。
Abstract Common parametrizationmodels for cloud microphysical processes use condensate mass density and/or particle number density as prognostic properties. However, other moments of the particle size distribution can likewise be chosen for prediction. This study deals with parametrization models with one and two, respectively, prognostic moments for the sedimentation of drop ensembles. The spectral resolving model defines the reference solution. The evolution of the vertical profiles of liquid water content, drop number density and rain rate strongly depend on the choice of the prognostic moments in the parametrizationmodels. Inmodels with a single prognostic moment, its vertical profile is copied by all other moments. The moment of most physical pertinence is recommended for prediction. In models with two prognostic moments, the vertical profiles of all moments differ. The orders of the prognostic moments should be chosen close to the order of moments of highest relevance. Otherwise large errors occur. For example, comparison of modelled versus observed radar reflectivity (6th moment with respect to diameter) does not tell much about the quality of other properties if reflectivity is diagnosed from for example, number density and mass density. Furthermore, mass conservation is fulfilled only if mass density is forecasted.