拉萨贡嘎国际机场一次干季乱流天气过程测风激光雷达预警应用研究分析

A Study on the Detection Characteristics of Wind-Measuring Lidar during a Turbulence Event in the Dry Season at Lhasa Gongga International Airport

摘要: 2026年4月24日下午，拉萨贡嘎国际机场发生了十余起航空器报告的低空风切变事件，其影响在近年运行中较为罕见。本文利用跑道两端部署的Molas 3D三维扫描测风激光雷达的多模式探测数据、地面自动观测站10 m风资料及航空器空中报告，对该次过程进行了系统复盘分析。结果表明：(1) 地面自观监测到的跑道端点风场变化与航空器报告相比滞后，难以满足预警时效性要求；(2) 激光雷达PPI径向速度图清晰捕捉到进近通道内多个正负速度对的出现与移动，与航空器报告的空间位置和发生时刻吻合良好；(3) DBS风廓线显示，16时至19时跑道上空交替出现超过4 m/s的上升与下沉气流，低层垂直交换显著增强，为风切变的发生提供了有利的动量交换条件；(4) 基于单一3˚仰角PPI数据重构的下滑道迎头风速廓线，能够定量反映进近通道内顺风超标区域和风速突变位置，以空间尺度 ≥ 600 m且单位距离(600 m)风速变化量的绝对值 ≥ 2.5 m/s (中度)或≥4.5 m/s (强烈)作为分级预警阈值，可有效覆盖大部分复飞航班，其中4.5 m/s阈值对应ICAO强烈风切变标准的下限。本研究验证了测风激光雷达在高高原河谷机场风切变监测预警中的工程应用价值，所提出的风切变识别指标可为后续业务化预警提供参考依据。

Abstract: On the afternoon of 24 April 2026, more than ten low-level wind shear incidents were reported by aircraft at Lhasa Gongga International Airport, representing an abnormal weather phenomenon rarely encountered in recent operational years. Based on the multimodal observation data of Molas 3D scanning LiDAR (wind light detection and ranging) installed at both runway ends, 10-meter wind records from automatic surface observation stations, and aircraft pilot reports, this paper systematically analyzes the wind shear event process. The results show that: (1) Wind field variations observed by ground automatic stations lag aircraft reports, which cannot meet the timeliness requirement for operational wind shear early warning; (2) PPI (Lidar Plan Position Indicator) radial velocity images clearly capture the generation and migration of multiple positive and negative velocity pairs within the approach corridor, which are highly consistent with the spatial positions and occurrence times recorded by aircraft reports; (3) DBS (Doppler Beam Swinging) wind profiles indicate that alternating updrafts and downdrafts exceeding 4 m/s prevailed over the runway from 16:00 to 19:00. The remarkable enhancement of low-level vertical exchange provided favorable momentum conditions for wind shear development; (4) The glide-path headwind profile reconstructed from 3˚ elevation-angle PPI data can quantitatively identify wind-speed-exceeding areas and abrupt wind variation positions in the approach segment. Taking spatial scale (≥600 m) and unit-distance (600 m) wind speed variation (≥2.5 m/s for moderate, ≥4.5 m/s for severe) as identification criteria, the proposed method can effectively cover most wind shear-induced go-around cases. The severe threshold of 4.5 m/s corresponds to the lower bound of ICAO’s severe wind shear criterion. This study verifies the practical application capability of LiDAR in wind shear monitoring and early warning at high-altitude valley airports. The optimized wind shear identification indices can provide technical references for future operational early warning services.