摘要
中尺度对流系统(MCS)常伴有冰雹、雷暴、龙卷等强烈的对流性灾害天气的产生,对飞行安全及航班准点率有严重影响,当飞机误入其中,对机体结构造成巨大损坏的同时对机组和乘客的人身安全造成威胁。本文研究基于葵花八号气象卫星的MCS识别,对贵阳机场2023年3月16日一次天气过程进行MCS识别,主要根据前人所改进的MCS识别标准,运用python对葵花八号静止气象卫星提供的数据实现计算机自动识别MCS,不仅可以降低由于人工识别带来的主观误差,还为气象工作人员对强对流天气的预报起到辅助作用。
Mesoscale convective systems (MCS) are often accompanied by strong convective disasters such as hail, thunderstorms, and tornadoes, which have a serious impact on flight safety and punctu-ality. When an aircraft enters them by mistake, it causes significant damage to the aircraft structure and poses a threat to the personal safety of the crew and passengers. This article studies the MCS recognition based on the Himawari-8 meteorological satellite, and conducts MCS recognition for a weather process at Guiyang Airport on March 16, 2023. Based on the previously improved MCS recognition standard, Python is used to automatically recognize MCS from the data provided by the Himawari-8 stationary meteorological satellite. This not only reduces subjective errors caused by manual recognition, but also assists meteorological personnel in predicting severe convective weather.
出处
《自然科学》
2024年第1期48-55,共8页
Open Journal of Nature Science
