Large‐scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid‐scale turbulence and convection—such as that they adjust instantaneously to changes in resolved‐scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary‐layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large‐scale models. Here we lay the theoretical foundations for an extended eddy‐diffusivity mass‐flux (EDMF) scheme that has explicit time‐dependence and memory of subgrid‐scale variables and is designed to represent all subgrid‐scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross‐sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large‐scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time‐dependent life cycle.

中文翻译：

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统一表示亚网格尺度湍流和对流的扩展涡扩散质量通量方案


大规模天气预报和气候模型开始达到千米的水平分辨率，在现有的次网格尺度湍流和对流参数化方案中做出的常见假设（例如它们会立即根据解析尺度动力学的变化进行调整）不再适用是有道理的。此外，通过不连续的不同参数化方案（每个方案都有自己的参数集）来表示边界层湍流、浅对流和深层对流的常见做法，促进了大型模型中可调节参数的激增。在这里，我们为扩展的涡扩散性质量通量（EDMF）方案奠定了理论基础，该方案具有明确的时间依赖性和亚网格尺度变量的记忆，旨在表示所有亚网格尺度的湍流和对流，从边界层动力学到深层对流，统一方式。该方案中的连贯上升和下降气流被表示为预测羽流，它们与环境相互作用，并可能通过夹带和脱滞相互影响。环境中各向同性的湍流通过扩散通量来表示，扩散率是从湍流动能预算中获得的，该预算始终在羽流和环境之间分配湍流动能。上升气流和下降气流的横截面积满足预测连续性方程，该方程允许羽流覆盖大型网格盒的可变和任意大的部分，并具有由其自身内部动力学控制的生命周期。 提出了相对简单的闭合参数初步建议，并证明可以成功模拟浅对流，包括依赖时间的生命周期。