Tropical cyclone (TC) wind field models are becoming increasingly sophisticated and complex. This review systematically discusses a range of models capable of simulating TCs in terms of modifications or simplifications of the governing equation, the Navier–Stokes equations, as a starting point. The discussion focuses on linear models, which include slab models, height-resolving models, and numerical simulation methods, respectively. The linear model offers quick calculations and insights into physical mechanisms, while slab models have limitations in capturing important processes and site conditions. The height-resolving model is widely used for Monte Carlo simulations, providing realistic three-dimensional wind structures. Nonlinear simulations yield reliable results for typhoon trajectory prediction, although they require specific boundary and initial conditions. Integration of nonlinear simulation with artificial intelligence and machine learning shows promise for faster typhoon prediction. However, challenges remain in terms of data training for machine learning models. Future advancements in these areas have the potential to enhance hazard assessment and weather forecasting.

中文翻译：

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热带气旋边界层风场模拟综合评述

热带气旋 (TC) 风场模型变得越来越复杂。本综述以控制方程（纳维-斯托克斯方程）的修改或简化为起点，系统地讨论了一系列能够模拟 TC 的模型。讨论的重点是线性模型，分别包括平板模型、高度分辨模型和数值模拟方法。线性模型提供快速计算和对物理机制的洞察，而板模型在捕获重要过程和现场条件方面存在局限性。高度分辨模型广泛用于蒙特卡罗模拟，提供真实的三维风结构。非线性模拟可以为台风轨迹预测提供可靠的结果，尽管它们需要特定的边界和初始条件。非线性模拟与人工智能和机器学习的集成有望实现更快的台风预测。然而，机器学习模型的数据训练仍然存在挑战。这些领域的未来进步有可能加强灾害评估和天气预报。