Identification and Forecasting of Typical Wind Shear and Shear Line Based on Two-Dimensional Wind Field

Abstract

The forecasting of clear-air wind shear presents a significant challenge in aviation meteorology. To improve the accuracy of wind shear identification and forecasting using coherent Doppler wind lidar, this study proposes an advanced method for identifying and forecasting wind shear and shear line. The method first performs point-by-point sliding traversal of potential wind shear along the radial and tangential direction based on retrieved two-dimensional wind vector. Subsequently, shear points are identified and extracted by the wind vector, and spatial clustering analysis is applied to reconstruct low-level wind shear line. Finally, the movement of wind shear line is forecasted with the average wind vector in the guidance region of shear line segments. This study simulated two simplified wind shear scenarios that retain key wind field features: gust front passage and divergent airflow. It compared the identification and forecasting performance of wind shear and shear line based on radial speed and two-dimensional wind vector. Results demonstrated that under controlled kinematic conditions, the two-dimensional wind vector method provides more accurate identification and improved forecast precision. The proposed method effectively identified and forecasted shear lines induced by gust front and severe convection in the airport field experiments. This study provides technical support for airport low-level wind shear early warning and flight safety assurance.