Accurate precipitation forecasting on the Qinghai-Tibet Plateau (QTP) remains a significant challenge due to complex terrain and nonlinear atmospheric dynamics. This study evaluates an XGBoost-SHAP framework for 24 h precipitation forecasting at Maqu Station, leveraging multi-source observations from 2020 to 2022. Vertical profile analyses via microwave radiometer (MWR) indicate that moisture is predominantly confined to altitudes below 4 km (AGL), with Integrated Water Vapor (IWV) and Liquid Water Path (LWP) typically varying between 0–15 mm and 0–2.5 mm, respectively. The optimized XGBoost model achieves an annual R² of 0.872 and a Root Mean Square Error (RMSE) of 1.609 mm, showing improved statistical consistency compared with standard Random Forest baselines. While the framework maintains robust performance for winter stratiform precipitation (RMSE = 0.32 mm), predictive variance increases during summer convective periods (RMSE = 3.26 mm). SHAP diagnostic analysis identifies Dew Point Temperature (DPT) as a consistent year-round predictor. Feature sensitivity analysis further reveals shifting seasonal driving mechanisms: spring precipitation appears sensitive to mid-tropospheric geopotential height, whereas summer forecasts are more strongly modulated by 500 hPa specific humidity and lower-level water vapor density. Overall, the XGBoost-SHAP framework serves as a transparent and physically plausible diagnostic tool for examining seasonal moisture–dynamic coupling. While these site-specific results are encouraging, they represent a localized empirical baseline; further cross-site validation is required to assess regional generalizability.

Low-level wind shear (LLWS) poses a critical threat to aviation safety, especially at high-altitude airports located in valley environments. However, the formation mechanisms of LLWS with low-level jets (LLJs) remain poorly understood under high-altitude valley conditions. In this study, high-resolution Doppler lidar observations collected during March–April 2024 were used to investigate the characteristics of low-level wind fields, LLJs, and LLWS, as well as their relationship in an airport environment. The results reveal pronounced diurnal variations in the low-level circulation, with easterly winds dominating from early morning to late morning, westerly winds prevailing in the afternoon, and southerly winds occurring at night. LLJ events exhibit a strong diurnal cycle, with the highest frequency occurring during 02:00–10:00 LT, and jet cores are mainly distributed between 200 and 300 m. The observed LLJs are predominantly easterly, with typical maximum wind speeds of 8–10 m s⁻¹. The development of LLJs is related to enhanced LLWS, although the temporal correspondence between LLJ intensity and LLWS evolution varies among individual events. The vertical shear structure is closely related to LLJ characteristics, including jet core height and wind speed distribution. Case analyses further demonstrate that the spatial evolution of LLWS follows the directional migration of LLJs, with the high wind-speed region shifting from easterly sectors in the morning to westerly sectors in the afternoon and southerly sectors at night. These findings provide new observational insights into LLJ-related LLWS processes under high-altitude valley environments and contribute to improved understanding of low-level wind hazards in complex airport environments.