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Role of eyewall and rainband eddy forcing in tropical cyclone intensification

机译:眼镜和雨筋涡流强迫热带气旋强化的作用

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摘要

While turbulence is commonly regarded as a flow feature pertaining to the planetary boundary layer (PBL), intense turbulent mixing generated by cloud processes also exists above the PBL in the eyewall and rainbands of a tropical cyclone (TC). The in-cloud turbulence above the PBL is intimately involved in the development of convective elements in the eyewall and rainbands and consists of a part of asymmetric eddy forcing for the evolution of the primary and secondary circulations of a TC. In this study, we show that the Hurricane Weather Research and Forecasting (HWRF) model, one of the operational models used for TC prediction, is unable to generate appropriate sub-grid-scale (SGS) eddy forcing above the PBL due to a lack of consideration of intense turbulent mixing generated by the eyewall and rain-band clouds. Incorporating an in-cloud turbulent-mixing parameterization in the vertical turbulent-mixing scheme notably improves the HWRF model's skills in predicting rapid changes in intensity for several past major hurricanes. While the analyses show that the SGS eddy forcing above the PBL is only about one-fifth of the model-resolved eddy forcing, the simulated TC vortex inner-core structure, secondary overturning circulation, and the model-resolved eddy forcing exhibit a substantial dependence on the parameterized SGS eddy processes. The results highlight the importance of eyewall and rainband SGS eddy forcing to numerical prediction of TC intensification, including rapid intensification at the current resolution of operational models.
机译:虽然湍流通常被认为是与行星边界层(PBL)有关的流动特征,但是云过程产生的强烈湍流混合也存在于热带气旋(TC)的眼罩和雨带中的PBL上方。 PBL上方的云湍流紧密地涉及眼镜和雨带中的对流元素的发展,并且由一部分不对称涡流强迫TC的初级循环的演变。在这项研究中,我们表明,由于缺乏,飓风天气研究和预测(HWRF)模型,用于TC预测的操作模型之一,无法产生适当的子网格级(SGS)涡流,由于缺乏眼罩和雨带云产生强烈湍流混合的考虑。在垂直湍流混合方案中纳入云湍流混合参数化显着提高了HWRF模型的技能,以预测几个过去主要飓风的强度快速变化。虽然分析表明,在PBL上方的SGS涡流强制迫使模型分辨涡流的五分之一,模拟的TC涡流内核结构,次要倾覆循环和模型分辨涡流迫使表现出实质性依赖在参数化的SGS辅助进程上。结果突出了眼罩和Rainband SGS涡流强迫TC强化的数值预测的重要性,包括在运行模型的当前分辨率下的快速强化。

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