基于“高影响天气”的贵阳机场协同观测技术应用研究

Application of Collaborative Observation Technology at Guiyang Airport Based on “High-Impact Weather”

摘要: 贵阳机场地处云贵高原复杂地形区，单一观测手段在覆盖范围与协同性方面均显不足。本文以“高影响天气”为主线，构建面向贵阳机场的综合立体协同观测体系：依据民航规章与ICAO标准，量化界定“本场”(基准点周边8 km)及进近着陆与起飞爬升地带(东西10 km、南北16 km矩形)的观测范围；针对探测设备布局缺陷，补建测风激光雷达、激光雨滴谱仪、翻斗式雨量桶与冰霜探测预警系统；进而为对流性、冰雪凝冻、风要素(低空风切变)和大雾四类高影响天气分别建立多设备协同观测与数据融合策略。以2025年11月13~15日辐射雾(部分雾)过程为案例的定量检验表明，相较于常规观测，协同观测使生成预警提前量由20~35 min提升至40~55 min，消散判识提前量由约10 min提升至约25 min，能见度判识误差由±200 m收窄至±70 m以内，起止时刻判识准确率由约65%升至88%以上，数据完整率由约80%升至98%以上。该方法可为同类高原复杂地形机场的航空气象保障提供借鉴。

Abstract: Guiyang Airport is located in a complex-terrain region of the Yunnan-Guizhou Plateau, where single-source observation is insufficient in both coverage and coordination. Taking high-impact weather as the main thread, this paper builds an integrated three-dimensional collaborative observation system for the airport. First, according to civil aviation regulations and ICAO standards, the observation scopes are quantified: the aerodrome area is defined as an 8 km radius around the reference point, and the approach and take-off climb area as a rectangle of 10 km (E-W) by 16 km (N-S) centered on the same point. Second, to fill the gaps of the existing equipment layout, a wind lidar, a laser disdrometer, a tipping-bucket rain gauge and a frost/ice detection and warning system were deployed. Third, collaborative observation and data fusion strategies are established respectively for four types of high-impact weather: convective weather, freezing and icing, wind elements including low-level wind shear, and fog. Verification against the radiation fog (partial fog) episode of 13~15 November 2025 shows that, compared with conventional observation, the collaborative strategy extends the lead time of fog-onset warning from 20~35 min to 40~55 min, advances dissipation identification from about 10 min to about 25 min, reduces the visibility identification error from ±200 m to within ±70 m, raises the accuracy of onset/end timing from about 65% to over 88%, and increases data completeness from about 80% to over 98%. The proposed method provides a reference for aviation meteorological support at airports with similar plateau and complex terrain.