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A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction

机译:用于中尺度数值天气预报的干热和浅积云参数化

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For numerical weather prediction models and models resolving deep convection, shallow convective ascents are subgrid processes that are not parameterized by classical local turbulent schemes. The mass flux formulation of convective mixing is now largely accepted as an efficient approach for parameterizing the contribution of larger plumes in convective dry and cloudy boundary layers. We propose a new formulation of the EDMF scheme (for Eddy DiffusivityMass Flux) based on a single updraft that improves the representation of dry thermals and shallow convective clouds and conserves a correct representation of stratocumulus in mesoscale models. The definition of entrainment and detrainment in the dry part of the updraft is original, and is specified as proportional to the ratio of buoyancy to vertical velocity. In the cloudy part of the updraft, the classical buoyancy sorting approach is chosen. The main closure of the scheme is based on the mass flux near the surface, which is proportional to the sub-cloud layer convective velocity scale w *. The link with the prognostic grid-scale cloud content and cloud cover and the projection on the non- conservative variables is processed by the cloud scheme. The validation of this new formulation using large-eddy simulations focused on showing the robustness of the scheme to represent three different boundary layer regimes. For dry convective cases, this parameterization enables a correct representation of the countergradient zone where the mass flux part represents the top entrainment (IHOP case). It can also handle the diurnal cycle of boundary-layer cumulus clouds (EUROCSARM) and conserve a realistic evolution of stratocumulus (EUROCSFIRE).
机译:对于数值天气预报模型和解决深对流问题的模型,浅对流上升过程是子网格过程,经典局部湍流方案没有对此参数化。对流混合的质量通量公式现在已被广泛接受,作为一种有效的方法,可以对较大的羽流对流干燥和浑浊的边界层的贡献进行参数化。我们基于单个上升气流,提出了一种新的EDMF方案(针对涡流扩散率/质量通量),可以改善干热和浅层对流云的表示,并保留平流积云在中尺度模型中的正确表示。上升气流干燥部分的夹带和减阻的定义是原始的,并且被指定为与浮力与垂直速度之比成比例。在上升气流的阴天部分,选择了经典的浮力分类方法。该方案的主要结论是基于地表附近的质量通量,它与次云层对流速度尺度w *成正比。云方案处理了具有预测网格规模的云内容和云覆盖以及对非保守变量的投影的链接。使用大涡模拟对这种新配方的验证集中于显示该方案代表三种不同边界层制度的稳健性。对于干燥对流情况,此参数设置可以正确表示反梯度带,其中质量通量部分代表顶部夹带(IHOP情况)。它也可以处理边界层积云的日循环(EUROCS ARM),并保留平流层积的现实演变(EUROCS FIRE)。

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