深圳机场2020~2025年低能见度天气统计特征及成因分析

Statistical Characteristics and Cause Analysis of Low Visibility Weather at Shenzhen Airport during 2020~2025

摘要: 本文基于2020~2025年机场天气报告数据，采用统计分析、天气学诊断等方法，对能见度 < 1000米的低能见度天气过程开展系统研究。结果表明：近六年机场共出现低能见度天气13次，年际分布不均，偶数年频次显著高于奇数年，且发生于冬末至初春(1~3月)，18~00 UTC为高发时段，峰值为20 UTC。低能见度天气以平流雾为主(84.6%)，锋面雾为辅(15.4%)，最低能见度达200米，对航班起降安全构成显著影响。平流雾形成依赖低空暖湿气流输送、近地面饱和湿度(温度露点差 ≤ 1℃)、弱南风(1~3 m/s)及稳定逆温层；锋面雾伴随冷锋过境，具有突发性强、持续时间短、消散快、范围小的特征。数值预报对地面风场和湿度的预报偏差，是导致平流雾起雾与消散时刻预报误差较大的主要原因。基于上述分析，提出依托自动站实况监测、建立上下游联动预警、优化数值预报订正等改进措施，为深圳机场低能见度精准预报及航空安全保障提供支撑。

Abstract: Based on the airport weather report data from 2020 to 2025, this paper systematically investigates low-visibility weather processes with visibility below 1000 meters using statistical analysis and synoptic diagnostic methods. The results show that a total of 13 low-visibility weather events occurred at the airport during the six years, presenting an uneven interannual distribution with a significantly higher frequency in even years than in odd years. These events mainly concentrated from late winter to early spring (January to March), with the high-incidence period at 18~00 UTC and the peak occurrence at 20:00 UTC. Low-visibility weather is predominantly advection fog (84.6%) and secondarily frontal fog (15.4%), with the minimum visibility dropping to 200 meters, which imposes prominent impacts on flight takeoff and landing safety. Advection fog formation is conditioned by low-level warm-wet airflow transport, near-surface saturated humidity (temperature-dew point difference ≤ 1˚C), weak southerly wind (1~3 m/s) and a stable inversion layer. Accompanying cold front passages, frontal fog is characterized by abrupt onset, short duration, rapid dissipation and small spatial coverage. Deviations of numerical weather prediction in surface wind field and humidity are the primary contributors to large forecasting errors in the onset and dissipation time of advection fog. On this basis, improvement measures are proposed, including utilizing real-time monitoring of automatic weather stations, establishing upstream-downstream collaborative early warning, and optimizing numerical forecast correction, so as to provide technical support for accurate low-visibility forecasting and aviation safety assurance at Shenzhen Airport.