随着民航运输业的持续快速发展，航班量日益增多，而秋冬季的大雾天气日渐成为影响飞机航班正常的主要因素，因此对机场大雾天气的监测预报具有非常大的应用价值。航空气象部门一般靠人工资料分析、人工监测，持续跟踪来预报大雾以及其发展趋势，预报员需要分析多种观测资料来判断是否会起雾，这对预报员形成较大的预报压力。关于机场低能见度监测及预警系统的开发很有必要。系统利用数值预报资料建立低能见度预警模型，首先对出雾形势进行分析，在判断为易出雾的形势后，再结合气象要素特征(湿度、风向、风速、温度变化和前期降水等)来综合判断出雾概率。同时，基于葵花8号新一代静止气象卫星的高时空分辨率多通道数据，使用3.9 μm伪比辐射率法和3.9 μm与11.2 μm通道亮温差法进行雾区的监测和不同级别能见度的识别。
With the continuous and rapid development of the civil aviation transportation industry, the number of flights has increased day by day, and the foggy weather in autumn and winter has gradually become the main factor affecting the normal flight of aircraft. Therefore, the monitoring and forecasting of foggy weather in airports has great application value. Aeronautical meteorological departments generally rely on manual data analysis, manual monitoring, and continuous tracking to forecast heavy fog and its development trend. Forecasters need to analyze a variety of observation data to determine whether it will fog, which puts a greater forecast pressure on forecasters. It is necessary to develop the monitoring and warning system of low visibility in airport. The system uses the numerical forecast data to establish the low visibility warning model. The fog situation is analyzed at first, and then the fog probability is comprehensively judged by combining the meteorological elements, such as humidity, wind direction, wind speed, temperature change and precipitation in the early stage. At the same time, based on the high-temporal-spatial resolution multi-channel data of the Himawari-8 geostationary meteorological satellite, the 3.9 μm pseudo-emissivity method and the 3.9 μm and 11.2 μm channel brightness temperature difference method are used to monitor the fog area and identify different levels of visibility.
