# Wind Characteristics in Mountainous Valleys Obtained through Field Measurement
## 1 Introduction
Although numerical simulation has been widely studied and applied, the setting of inlet wind speed conditions, the selection of the terrain calculation area, and the transition form of terrain boundary are not standardized, leading to insufficient rationality of the calculation results. Field measurements are the most effective method to obtain wind field characteristics, especially the power spectrum, turbulence intensity, turbulence integration scale, and gust factor in pulsating wind characteristics. To study the characteristics of wind, from early on, researchers have collected wind observations. The most reliable and representative Davenport spectrum was obtained by statistically analyzing nearly 100 strong wind records at different locations and different heights around the world [18; 19]. [PERSON] et al. compared wind speed data measured by Doppler sodars with those measured by anemometers mounted on towers and checked the validity of the Doppler sodars. [PERSON] et al. used Doppler radars and [PERSON] et al. used GPS dropsondes to measure wind characteristics near the eye walls of tropical cyclones at altitudes higher than 2000 m [20; 21; 22; 23; 24; 25]. [PERSON] et al. obtained multiple wind speed measurements on the Great Naruto Bridge and Akashi Strait Bridge in Japan and obtained the maximum wind speed over 10 min for typhoons and the maximum wind speed over 10 min for monsoons. After, they conducted correlation studies based on the measured data and compared the findings with the longitudinal pulsating wind empirical formula proposed by [PERSON] [26]. [PERSON] and [PERSON] measured three hurricanes in the Gulf of Mexico at heights of 5 and 10 m using a two-dimensional propeller anemometer and a three-dimensional ultrasonic anemometer. The wind characteristic parameters, such as mean wind speed and direction, turbulence intensity, and turbulence integral scale when the hurricane passed, were obtained [27]. [PERSON] et al. used the long-term wind speed and acceleration monitoring data from Hardanger Bridge to study the relationship between wind load and response processes [28]. [PERSON] et al. obtained the wind field characteristics of Tamil Nadu, India using a Doppler sodars (sound detection and ranging) system [29]. [PERSON] et al. obtained observations of the urban wind island effect [30]. [PERSON] et al. obtained the characteristics of wind based on the data obtained from two wind poles located on a hillside and the bottom of a valley [31]. To reliably obtain statistical wind characteristics,Wang et al. incorporated two anemometers into a structural health monitoring system (SHMS) to extensively collect wind data to monitor the wind environment at the site of the Runyon Suspension Bridge (RSB) [32]. [PERSON] et al. investigated the wind characteristics of the Donghai Bridge site and discussed the mean and turbulent wind characteristics based on six years of field monitoring data [33]. [PERSON] et al. installed nine anemometers on the 325 m high Beijing Meteorological Tower to systematically analyze the recorded thunderstorm flows [34]. When constructing a bridge in a deep canyon, [PERSON] et al. installed five sets of anemometers on the bridge catwalk to provide an overall analysis of the wind characteristics of the bridge [35]. In this study, we obtained wind observations on a river beach and at the height of the main beam of the bridge using one set of 3D Doppler sodars and two sets of 2D anemometers. And the Doppler radar system was developed by ART (Atmospheric Research & Technology). The 2D ultrasonic anemometer was manufactured by the British company Gill Instruments Limited. Wind data were obtained over a long period. The terrain of the bridge site is quite special. It is a typical mountain pass with river beach terrain, also known as horn-shaped terrain. There are limitations to the research of this terrain.