Numerical Diffusion and Turbulent Mixing in Convective Self-Aggregation

IF 4.4 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of Advances in Modeling Earth Systems Pub Date : 2024-05-12 DOI:10.1029/2023MS004151
L. Silvestri, M. Saraceni, P. Bongioannini Cerlini
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Abstract

Convective Self-Aggregation (CSA) is a common feature of idealized numerical simulations of the tropical atmosphere in Radiative-Convective Equilibrium (RCE). However, at coarse grid resolution where deep convection is not fully resolved, the occurrence of this phenomenon is extremely sensitive to subgrid-scale processes. This study examines the role of mixing and entrainment, provided by the turbulence model and the implicit numerical diffusion. The study compares the results of two models, WRF and SAM, by varying turbulence models, initial conditions, and horizontal spatial resolution. At a coarse grid resolution of 3 km, the removal of turbulent mixing prevents CSA in models with low numerical diffusivity but is preserved in models with high numerical diffusivity. When the horizontal grid resolution is refined to 1 km, CSA can only be achieved by increasing explicit turbulent mixing, even with a small amount of shallow clouds. Therefore, the sensitivity of CSA to horizontal grid resolution is not primarily caused by the decrease in shallow clouds. The analysis of the total water path spectrum suggests that the amplitude of initial humidity perturbations introduced by convection in the free troposphere is the key factor. This amplitude is regulated by turbulent mixing and diffusion at small scales. Prior to the onset of CSA, increased mixing makes updrafts more sensitive to the dryness of the free troposphere, which strengthens the moisture-convection feedback. This leads to an increased distance between convective cores and a stronger humidity perturbation in the free troposphere, which can destabilize the RCE state.

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对流自聚集中的数值扩散和湍流混合
对流自聚集(CSA)是处于辐射对流平衡(RCE)状态的热带大气理想化数值模拟的一个常见特征。然而,在粗网格分辨率下,深层对流无法完全解析,这种现象的发生对子网格尺度过程极为敏感。本研究探讨了湍流模型和隐式数值扩散所提供的混合和夹带作用。研究通过改变湍流模型、初始条件和水平空间分辨率,比较了 WRF 和 SAM 两种模型的结果。在 3 公里的粗网格分辨率下,去除湍流混合可防止低数值扩散率模型中的 CSA,但在高数值扩散率模型中却得以保留。当水平网格分辨率细化到 1 千米时,即使有少量浅层云,也只能通过增加显式湍流混合来实现 CSA。因此,CSA 对水平网格分辨率的敏感性主要不是由浅层云的减少引起的。对总水路谱的分析表明,自由对流层对流引入的初始湿度扰动幅度是关键因素。这一振幅受小尺度湍流混合和扩散的调节。在 CSA 开始之前,混合的增加使上升气流对自由对流层的干燥度更加敏感,从而加强了湿度-对流反馈。这导致对流核心之间的距离增大,自由对流层的湿度扰动增强,从而破坏 RCE 状态的稳定。
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来源期刊
Journal of Advances in Modeling Earth Systems
Journal of Advances in Modeling Earth Systems METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
11.40
自引率
11.80%
发文量
241
审稿时长
>12 weeks
期刊介绍: The Journal of Advances in Modeling Earth Systems (JAMES) is committed to advancing the science of Earth systems modeling by offering high-quality scientific research through online availability and open access licensing. JAMES invites authors and readers from the international Earth systems modeling community. Open access. Articles are available free of charge for everyone with Internet access to view and download. Formal peer review. Supplemental material, such as code samples, images, and visualizations, is published at no additional charge. No additional charge for color figures. Modest page charges to cover production costs. Articles published in high-quality full text PDF, HTML, and XML. Internal and external reference linking, DOI registration, and forward linking via CrossRef.
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