Identification and Analysis of Wind Shear Within the Transiting Frontal System at Xining International Airport Using Lidar

The principal factor contributing to the restricted accuracy of wind shear detection resides in the rapid oscillations of the wind field and the intricate characteristics of wind shear. The abrupt alterations in wind speed and direction over a short span pose a formidable challenge for conventional detection techniques to precisely capture and expeditiously analyze this phenomenon. In this study, three algorithms were employed to analyze wind shear within the frontal system at Xining International Airport on 5 April 2023, and the same analytical approach was applied to three additional paradigmatic cases. Initially, the slope characteristics of the Lidar signal were utilized to ascertain the existence and intensity of wind shear by assessing the rate of variation of the wind field parameters along a specific trajectory. Secondly, the S-factor algorithm was applied to detect wind shear. This algorithm revolves around particular mathematical relationships and statistical measures within the wind field data. By taking into account multiple variables and their mutual interactions, an S-factor value was computed to signify the strength of wind shear. Furthermore, an enhanced F-factor algorithm was found upon scrutinizing the identical wind field data, as they all detected a substantial intensification in wind shear intensity prior to and after the issuance of the voice report. This evinces that despite the differences in sensitivity, all three algorithms are able to capture the general trend of wind shear fluctuations during the passage of the frontal system.