The horizontal turbulence parameterization is vital for the intensity and structure forecasting of tropical cyclone (TC) in numerical weather prediction (NWP) models. The default two-dimensional (2D) standard Smagorinsky model with a single universal constant in Weather and Research Forecasting (WRF) model has been proven to be over dissipative for TC, leading to underprediction of TC intensity. This study provides the first attempt to implement the physically based 2D dynamic Smagorinsky model (DSM) for horizontal turbulence parameterization in WRF model for TC forecasts. The DSM dynamically computes the Smagorinsky coefficient as a function of the resolved flow during the simulation, avoiding the need to prescribe the coefficient a prior. The test results of the DSM in a TC NWP model show that the DSM can significantly improve the wind intensity forecasts compared to the standard Smagorinsky model.

中文翻译：

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热带气旋模拟中水平湍流参数化的动态斯马戈林斯基模型


水平湍流参数化对于数值天气预报（NWP）模型中热带气旋（TC）的强度和结构预报至关重要。天气和研究预报 (WRF) 模型中默认的具有单一通用常数的二维 (2D) 标准 Smagorinsky 模型已被证明对 TC 具有过度耗散性，导致对 TC 强度的低估。本研究首次尝试在 TC 预报的 WRF 模型中实现基于物理的二维动态 Smagorinsky 模型 (DSM)，用于水平湍流参数化。 DSM 在模拟过程中动态计算 Smagorinsky 系数作为解析流的函数，从而无需事先指定系数。 DSM在TC NWP模式中的测试结果表明，与标准Smagorinsky模式相比，DSM可以显着改善风强预报。