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一种改进的飞机自然结冰潜势算法研究
李佰平1, 戴建华1, 孙敏1, 史月琴2, 孙俊颖3,3, 杨涛4, 黄可蔚5, 韩昌1
(1.上海中心气象台;2.中国气象科学研究院;3.中国商飞试飞中心;4.中国飞行试验研究院;5.四川航空股份有限公司)
An Improved Aircraft Natural Icing Potential Algorithm
LI Baiping1, DAI Jianhua1, SUN Min1, SHI Yueqin2, SUN Junying3, YANG Tao4, HUANG Kewei5, HAN Chang1
(1.Shanghai Central Meteorological Observatory;2.Weather Modification Center of CMA,Chinese Academy of Meteorological Science;3.Flight Test Center,Commercial Aircraft Corporation of China Ltd;4.Chinese Flight Test Establishment;5.Sichuan Airlines)
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本文已被:浏览 32次   下载 15
投稿时间:2017-09-01    修订日期:2018-01-25
中文摘要: 飞机结冰严重危害飞行安全,随着国产大飞机计划的推进以及自然结冰试飞试验的开展,飞机结冰的研究越来越引起了民航和气象等诸多部门的重视。本文介绍了一个改进的飞机自然结冰潜势算法,该算法直接基于大气温湿层结给出结冰潜势,可以识别多种天气条件下(包括冻雨)的飞机结冰可能,具有命中率高、虚警率低、应用简便、实用性强的特点。用26个飞机结冰试飞(飞行)报告对该算法进行了检验和评估,发现该算法能较好地估测多种天气条件下飞机在飞行中实际遭遇结冰的情况,且能给出结冰的区域和大致高度。同时,在安庆的一次飞机自然结冰外场试验中对该方法进行了应用,发现结合地面观测、探空秒数据和卫星资料等,该结冰潜势诊断方法可以准确诊断结冰层的高度和随时间的变化,与飞机实际空中探测具有较高的符合度。
Abstract:With the progress of China-made large aircraft and natural icing flight test in recent years, Aircraft icing which is dangerous for flight safety, catches more and more attentions from both aviation and meteorology sectors now. . Based on atmospheric temperature and humidity stratification profile, an improved icing potential algorithm with high probability of detection (POD), low false alarms ratio (FAR), easy application and practicability, is introduced in this article. The algorithm is verified and evaluated against 26 flight test/pilot report. It is found that the diagnosed icing potential has high accordance with aircraft observation, can give the approximate icing height and area in multi weather situation. By combing surface observation, radiosonde and satellite data, the algorithm is also verified in an aircraft natural icing observation experiment in Anqing. It is found that the algorithm can diagnose the particular height of icing level and the production and consumption of super cooled water, which has high consistency with aircraft sounding.
文章编号:201709010404     中图分类号:    文献标志码:
基金项目:上海市科委科研计划项目(16dz1206103)、中国气象局预报员专项(CMAYBY2018-025)及“上海市气象局强对流科技创新团队”共同资助
引用文本:
李佰平,戴建华,孙敏,史月琴,孙俊颖,杨涛,黄可蔚,韩昌,0.[en_title][J].Meteor Mon,():-.
LI Baiping,DAI Jianhua,SUN Min,SHI Yueqin,SUN Junying,YANG Tao,HUANG Kewei,HAN Chang,0.An Improved Aircraft Natural Icing Potential Algorithm[J].Meteor Mon,():-.