# Study on Fluctuating Wind Characteristics and Non-Stationarity at U-Shaped Canyon Bridge Site
## 1 Introduction  
Advancements in bridge construction technology and equipment have led to the construction of an increasing number of long-span cable bridges in canyon areas. However, due to their flexible structures, long-span bridges are highly susceptible to wind effects. Accurately estimating wind characteristics is essential for studying the wind response of structures [1, 2, 3]. Long-span bridges, predominantly located in mountainous and canyon areas, are frequently impacted by strong canyon winds [4, 5]. Complex terrain and climatic conditions cause wind parameters to exhibit significant non-stationary characteristics, posing challenges to the safety and performance of wind-sensitive infrastructure such as long-span bridges, tall structures, and wind power generation facilities. Research on mountain canyon wind fields primarily relies on field measurements [6], wind tunnel tests [7], and numerical simulations [8]. Field measurements are the most direct and reliable method. Although field measurements require significant investment and time, and have certain limitations, they provide reliable and accurate data, often used to validate other methods, making them widely favored for analyzing wind field characteristics. [PERSON] et al. [9] evaluated the wind field characteristics in the Y-shaped canyon by combining windtunnel test results with field measurement data. It is found that the wind characteristics under complex terrain show significant sensitivity to the wind direction, and the local terrain has considerable influence on the wind field. [PERSON] et al. [10] introduced fractal dimensions to quantify wind parameter fluctuations, analyzed gust factors under various terrain conditions, and conducted a comparative study. [PERSON] et al. [11] used an ultrasonic anemometer to investigate the influence of wind direction on the characteristic parameters of deep canyon winds. They found significant directional variations in parameters such as the turbulence integral scale. Additionally, wind speed, turbulence intensity, and turbulence integral scale followed a lognormal distribution across all directions, while the angle of attack adhered to a normal distribution. [PERSON] et al. [12] installed five anemometers along the bridge span for long-term field measurements, revealing that the valley wind field is heavily influenced by terrain and exhibits strong non-stationarity. [PERSON] et al. [13] analyzed and compared wind characteristics in mountainous areas using data from two wind towers, one on a mountainside and the other at a canyon bottom. They found that mean wind speed, turbulence intensity, and wind power spectra could not be accurately predicted by existing norms or standards and proposed an exponential coherence model to effectively describe vertical coherence. Numerous studies have demonstrated that mountain winds exhibit non-stationary characteristics [14; 15], prompting extensive discussions on wind field non-stationarity under varying terrain conditions and its impact on structural wind resistance design. [PERSON] et al. [16] compared the non-stationarity of mountain canyon winds with normal climate winds under identical sample lengths and observation intervals. They found that when the sample length exceeded 10 min, the probability distribution of the non-stationarity index showed significant differences between the two. [PERSON] et al. [17] observed that near-surface wind fields below 10 m in hilly areas exhibited non-stationary characteristics. They also noted that stationary models tend to overestimate both turbulence intensity and turbulence integral scale. [PERSON] et al. [18] employed the statistical Augmented Dickey-Fuller (ADF) method to quantitatively assess the non-stationarity of measured wind speed samples and discovered that abrupt winds could occur in mountainous terrain. While existing studies have explored the characteristics and effects of wind fields in complex terrains from various perspectives, the applicability of current methods to non-stationary wind speed models remains limited.