摘要
本研究利用葵花8/9号静止气象卫星2020~2024年高时空分辨率数据,结合贵阳机场地面观测资料,研究适用于山地机场的夜间雾卫星识别技术。通过量化3.9 μm与11.2 μm通道亮温差(BTD3.9-11.2)与能见度的相关性,确定雾识别最佳阈值为−1.12℃,并融合低云剔除算法构建雾区检测模型,准确率达94.2%。通过典型案例验证表明,该技术可精准捕捉辐射雾生消过程,为贵阳机场低能见度天气实时预警提供可靠技术支撑,同时揭示云贵高原复杂地形下阈值本地化的必要性。
This study utilizes high spatiotemporal resolution data from the Himawari-8/9 geostationary meteorological satellites (2020~2024) combined with ground observation data from Guiyang Airport to develop nighttime fog detection technology suitable for mountainous airports. By quantifying the correlation between brightness temperature difference (BTD3.9-11.2) of 3.9 μm and 11.2 μm channels and visibility, the optimal fog identification threshold was determined as −1.12˚C. The fog detection model, incorporating a low-cloud elimination algorithm, achieved an accuracy rate of 94.2%. Case validation demonstrates that this technology can precisely capture the formation and dissipation processes of radiation fog, providing reliable technical support for real-time low-visibility weather warnings at Guiyang Airport, while revealing the necessity of threshold localization under the complex terrain conditions of the Yunnan-Guizhou Plateau.
出处
《地球科学前沿(汉斯)》
2025年第8期1158-1171,共14页
Advances in Geosciences
基金
中国民用航空西南地区空中交通管理局创新类项目(基于贵阳龙洞堡机场重要天气案例库的辐射雾预报方法研究 SWATMB-202402)资助。
