The squall line is a band- or line-shaped mesoscale convective system formed by the lateral alignment of individual thunderstorms. Its associated thunderstorm gales and strong vertical wind shear pose a serious threat to aviation safety and can easily lead to flight abnormalities or even accidents. Xining Airport is located in the northeastern part of Qinghai Xizang Plateau. The heterogeneity of the thermal and dynamic properties of the complex underlying surfaces results in greater complexity and uncertainty in the occurrence, development, and evolution mechanisms of squall lines in this region. On 2023-08-09, Xining Airport was affected by squall line weather, resulting in widespread flight delays, a large number of stranded passengers, and the return or diversion of 9 flights, which severely compromised flight safety and on-time performance. Therefore, in-depth study of the fine-scale wind field structure of squall lines at plateau airports is of urgent practical significance and application value for enhancing the forecasting and early warning capabilities for such aviation hazardous weather and ensuring aviation safety.

Wind light detection and ranging (LiDAR) images, combined with multi-source data from the automatic weather observing system (AWOS) and Doppler weather radar (DWR), were used to conduct an in-depth analysis of the fine-scale structure of the squall line transiting Xining Airport on 2023-08-09. High-resolution wind LiDAR revealed the three-dimensional fine-scale wind field structure of the squall line. AWOS provided surface meteorological elements with high temporal resolution. DWR tracked the macro-structure, movement path, and reflectivity characteristics of the squall line system. Through multi-source data integration, the 3-D wind field structural characteristics, evolution patterns, and their correlation with changes in surface meteorological elements during the entire squall line transit process were systematically analyzed.

The squall line event was jointly influenced by the northward shift of the subtropical high and westerly trough. The mid- to low-level shear line provided dynamic lifting, while the low-level southeast airflow supplied abundant water vapor. The warm-moist low-level and dry-cold mid-to-upper-level environment generated a potentially unstable stratification (Fig.2). The squall line moved from northeast to southwest, exhibiting notable characteristics such as a sharp rise in air pressure, sudden increase in wind speed, and abrupt temperature drop (Fig.3). DWR showed that the squall line echoes moved from the northeast to the southwest, with a distinct gust front at the leading edge. As the system evolved, the gust front on the eastern side moved away and weakened, while a new gust front formed at the forefront of the strong echoes on the western side, and an inflow notch appeared at the rear (Fig.4). Wind LiDAR revealed the three-dimensional fine-scale structure of the gust front over the complex terrain of the plateau airport. Horizontally, it showed a wedge-shaped structure with significant convergent wind shear and small-scale vortices at the leading edge, and divergent gale at the rear (Fig.5). Vertically, it displayed a rearward-tilted nose-like structure extending up to 1500 m, with an upwind region and turbulent mixing in the upper part (Fig.7). During the thunderstorm dissipation stage, a divergence zone and strong directional wind shear induced by a microburst occurred northwest of the airport (Fig.6).

Refined wind LiDAR observations and analysis revealed a 3-D structural model of the plateau squall line gust front characterized by a “horizontal wedge-vertical nose” configuration. By combining the complementary advantages of wind LiDAR and DWR, key characteristics such as gust fronts, small-scale vortices, low-level wind shear, and microbursts—difficult to detect using conventional observation methods—were successfully captured during squall line transit. This provides an important basis and reference for enhancing early warnings of aviation hazardous weather and developing minute-level warning technologies using wind LiDAR.