## 1 Introduction  
During thunderstorms, the exchange of hot air near the surface with cold air aloft can trigger a meteorological phenomenon known as a downburst [1]. A downburst is characterized by a high-velocity downward airflow that transforms into horizontal motion upon hitting the ground (Figure 1). As the horizontal flow spreads, it can generate extremely destructive winds that may cause severe damage to engineering structures such as buildings and transmission line towers [2; 3; 4; 5]. Downbursts frequently occur in mountainous areas where the acceleration effect of wind velocity at the hilltop can exacerbate the hazards caused by these storms. Thus, studying the wind field characteristics in mountainous areas under downbursts is of great practical significance. The main research methods used to study the wind field characteristics of downbursts in mountainous regions include field measurements, wind tunnel tests, and numerical simulations. Although field measurements [6; 7; 8; 9; 10; 11] can provide authentic wind field data, the random and short-lived nature of downbursts in time and space [12] presents challenges in obtaining adequate data. Furthermore, field measurements entail significant labor and financial investment. [PERSON] [13] summarized the structure and characteristics of downbursts from field measurements and noted that mean velocity profiles obtained through the impinging jet model in wind tunnel tests are comparable to field-measured data. Given these limitations, researchers have conducted wind tunnel tests based on the impinging jet model to simulate downbursts and investigate their flow characteristics [14; 15; 16; 17]. Wind tunnel tests offer lower costs and shorter experimentation cycles while maintaining accuracy and persuasiveness compared to field measurements. However, wind tunnel tests are restricted by size and cannot provide complete information on the flow field [18], limiting their ability to replicate real-world wind fields in complex mountainous terrain. In recent years, with the rapid development of computer hardware and software, the use of CFD has become increasingly popular [18; 19]. As a result, many researchers have begun to use various CFD turbulence models to simulate the wind field of downbursts in flat areas. Based on the impinging jet model, [PERSON] and [PERSON] [20] used the Reynolds-averaged Navier-Stokes (RANS) method to study the wind characteristics of downwards in flat areas and obtained a reasonable simulation of the downburst wind field. [PERSON] and [PERSON] [21] used the Reynolds stress model (RSM) to conduct unsteady simulations of the formation and spread of downbursts. Their numerical results show that wind velocity varies greatly throughout the formation and diffusion process, with the maximum wind velocity occurring when the downward airflow hits the ground. [PERSON] et al. [22] used LES to describe the flow fields of downbursts in four different exposure areas: open air, rural areas, suburban areas, and urban areas. Their results show that the mean wind and fluctuating wind obtained by numerical simulations are consistent with field-measured data and that peak wind velocity decreases and the height corresponding to peak wind velocity increases as roughness increases. [PERSON] and [PERSON] [23] performed three-dimensional numerical simulations based on the impinging jet model and used different turbulence models such as standard \(k\)-\(\varepsilon\), renormalization group \(k\)-\(\varepsilon\) (RNG), realizable \(k\)-\(\varepsilon\), shear stress transport \(k\)-\(\omega\) (SST), RSM, and LES to study the effect of turbulence models on mean wind velocity. A comparison with experimental data shows that the simulated values of LES, REA, and RSM are more consistent with experimental data than those of the other three models.