## 1 Introduction  
Plateau airports are defined as airports located at altitudes of 2438 m (8000 feet) or higher. The construction and operation of these airports play a crucial role in enhancing external transportation, driving economic and social development, and improving the local quality of life. As of December 2023, China operates 25 plateau airports, the largest number in the world. Most of these airports are situated on or around the Qinghai-Tibet Plateau, where the combined effects of atmospheric circulation, intense solar radiation, and high terrain result in highly variable and sensitive meteorological conditions [1, 2], particularly in the wind field. The complexity and variability of wind fields significantly impact aircraft takeoffs and landings, often leading to return flights, alternate landings, or even unsafe incidents due to wind shear and turbulence. Therefore, strengthening wind field monitoring and forecasting capabilities at plateau airports is critical for enhancing flight safety and operational efficiency.  
Doppler wind lidar (DWL) emits pulse beams and receives backscattered signals from aerosol particles, using the Doppler effect to measure wind speed [3]. It is especially effective for wind field monitoring under clear-sky conditions [4; 5]. Numerous comparative validation studies have been conducted between DWL, radiosondes [6], and wind profilers [7; 8] across various weather conditions, consistently demonstrating strong agreement in wind measurements [9]. DWL is known for its high measurement accuracy, three-dimensional scanning capabilities, and fast response times. One of its critical applications is the development of wind shear identification algorithms based on radial wind speed. However, due to the varying meteorological conditions that lead to low-level wind shear, studies have found differences in wind shear identification rates across different weather scenarios, such as convective systems, cold fronts, and inversion layers [10; 11; 12; 13]. These variations are linked to the algorithms used and are closely related to the detection range of DWL under changing weather conditions. [PERSON] et al. [14] specifically noted that the detection range of DWL along the glide path is approximately 6-7 km; and that DWL can be applied to regions with similar climates and aerosol concentrations. An analysis of DWL detection performance in the Sichuan Basin showed that seasonal variations in aerosol concentrations significantly affect the detection range [15]. Other research has demonstrated that the Qinghai-Tibet Plateau, with its low water vapor content and fewer aerosol particles, results in weaker returned laser pulse signals and lower signal-to-noise ratios, which limit the detection range of DWL. This reduces the sensitivity and resolution of the DWL, ultimately affecting the accuracy and reliability of the results [16; 17]. Therefore, understanding the detection performance of DWL under various weather conditions is essential for improving its environmental adaptability and advancing its application. Based on this, the present study conducts an objective quantitative analysis of the detection performance and influencing factors of DWL at Lhasa Gonggar Airport (hereafter referred to as Gonggar Airport).