Based on Doppler lidar observation data from Beijing Daxing International Airport during 2021-2022, a systematic analysis was conducted on the spatiotemporal distribution characteristics of low-level wind shear alerts. Furthermore, the relationship between lidar alerts and weather conditions was examined using 133 alert events from 2022. The results indicate significant seasonal and diurnal variations in wind shear alerts, with a peak period from April to June and a notably higher alert frequency during nighttime compared to daytime. Weather pattern classifications reveal that wind shear events associated with thunderstorms, strong winds, and fog account for approximately one-third of the total alerts. Although only 9% of alerts are triggered by temperature inversion breakdowns, they serve as important indicators for forecasting fog dissipation. Alerts induced by vertical wind speed differences tend to last longer but pose relatively minor impacts on flight safety. Case studies confirm that the lidar system can effectively detect abrupt changes in wind direction and speed caused by cold air intrusions, achieving a wind shear alert hit rate of up to 74% during strong wind events. These findings provide technical support for diagnosing the causes of wind shear, optimizing alert thresholds, and improving multi-source data integration forecasting, offering practical value for enhancing operational safety and meteorological services at the airport.