doi:  10.3878/j.issn.1006-9895.1703.16259
机载云降水粒子成像仪所测数据中伪粒子的识别

Pseudo Particle Identification in the Image Data from the Airborne Cloud and Precipitation Particle Image Probe
摘要点击 214  全文点击 234  投稿时间:2016-11-08  
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基金:  国家重大科研仪器设备研制专项41327803,国家自然科学基金项目41405128
中文关键词:  机载云降水粒子成像仪  伪粒子  破碎粒子
英文关键词:  Airborne cloud and precipitation imaging probe  Pseudo particle  Shattered particle
        
作者中文名作者英文名单位
黄敏松HUANG Minsong中国科学院大气物理研究所云降水物理与强风暴重点实验室, 北京 100029
雷恒池LEI Hengchi中国科学院大气物理研究所云降水物理与强风暴重点实验室, 北京 100029;南京信息工程大学气象灾害预报预警与评估协同创新中心, 南京 210044
金玲JIN Ling中国科学院大气物理研究所云降水物理与强风暴重点实验室, 北京 100029
引用:黄敏松,雷恒池,金玲.2017.机载云降水粒子成像仪所测数据中伪粒子的识别[J].大气科学,41(5):1113-1124,doi:10.3878/j.issn.1006-9895.1703.16259.
Citation:HUANG Minsong,LEI Hengchi,JIN Ling.2017.Pseudo Particle Identification in the Image Data from the Airborne Cloud and Precipitation Particle Image Probe[J].Chinese Journal of Atmospheric Sciences (in Chinese),41(5):1113-1124,doi:10.3878/j.issn.1006-9895.1703.16259.
中文摘要:
      机载云粒子成像仪(Cloud Imaging Probe,简称CIP)和降水粒子成像仪(Precipitation Imaging Probe简称PIP)所测数据中伪粒子的存在会直接导致仪器所测数据质量下降。利用山西Y-12探测飞机在太原地区的三次航测资料对飞机采样期间伪粒子图像的特点及其成因进行了分析和归类,并在此基础上提出了综合利用到达时间间隔阈值和图像处理识别技术的伪粒子识别方法。利用所提的方法对航测的粒子图像资料进行处理、统计和分析,统计结果表明,在一次测量过程中伪粒子的出现概率最高可达45.2%,其平均出现概率分别是36.01%(CIP))和8.64%(PIP);在所有伪粒子成分中,破碎形成的伪粒子的出现概率是最高的,它可以占到伪粒子总数的95%以上;其次是条纹状粒子和并存粒子,相对来说,空白粒子和线状粒子出现的概率是比较低的。研究还发现,机载平台的飞行状态对伪粒子各成分的出现概率也会造成影响。利用所提方法对仪器测量的粒子谱、粒子数浓度和冰水含量值进行订正,订正结果表明伪粒子对仪器量程内的粒子谱、粒子数浓度和冰水含量值均有影响,其中在云粒子谱影响上,伪粒子对粒子谱两端的影响较大,其中对小云粒子谱的影响主要是在400 μm以下,对大云粒子端的影响主要是在1000 μm(CIP)和2000 μm(PIP)以上。所提方法和阈值对于以Y-12飞机为机载探测平台,以CIP和PIP为探测仪器所获取的其它航次云微物理图像资料处理也是有一定的参考使用价值。
Abstract:
      Pseudo particles in the image data from the airborne Cloud Imaging Probe (CIP) and Precipitation Imaging Probe (PIP) measurements can degrade the quality of the measurement data. Utilizing three flights data in Taiyuan area from Shanxi Y-12 research plane, the causes and characteristics of the pseudo particles were analyzed and classified. A pseudo particle identification method was proposed based on the results, which includes the inter-arrival time threshold and the image processing identification technique. Using the algorithm proposed in this study, the image data were processed and analyzed statistically. It was found that the maximum occurrence probability of artifacts in each research flight could reach 45.2% with an average occurrence probability of 36.01% (CIP) and 8.64% (PIP). Among the artifacts, the occurrence probability of the shattered fragments was the highest, which accounted for more than 95% of the total number of pseudo particles; stripe shaped particles and the coexisting particles showed the second highest occurrence probability. Relatively speaking, the occurrence probability of blank particles and line shaped particles appeared to be relatively low. It was also found that the occurrence probability of each individual component of the pseudo particles could be influenced by the flight state of the airborne platform. By using the proposed method, the particle spectrum, particle concentration and ice water content from the probes were corrected, and results show that the artifacts could influence the particle spectrum, particle concentration and ice water content within the measuring range of the probe. Specifically, the effect on the particle spectrum lied on the portion less than 400 μm and greater than 1000 μm (CIP) and 2000 μm (PIP). The method and threshold proposed here provide some references for other flights data from CIP and PIP aboard the Y-12 research plane.
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