| DMT机载云粒子图像形状识别及其应用 |
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| 引用本文： | 张荣,李宏宇,周旭,李昊,胡向峰,夏强.DMT机载云粒子图像形状识别及其应用[J].应用气象学报,2021,32(6):735-747. |
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| 作者姓名： | 张荣 李宏宇 周旭 李昊 胡向峰 夏强 |
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| 作者单位： | 1.中国气象局云雾物理环境重点开放实验室, 北京 100081 |
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| 摘 要： | 利用机载云粒子探测设备入云进行观测是目前获取云粒子微物理特征最直接有效的手段。国内已有多家单位引进美国DMT（Droplet Measurement Technologies）公司的云粒子图像探头CIP（cloud imaging probe）。由于其配套软件不能输出逐个粒子的详细信息,在很大程度上限制了对云粒子图像探测数据的深入挖掘和分析。基于解析粒子图像原始数据,对粒子图像数据进行质量控制,并根据粒子形状几何特征将粒子形状分为8类（微小、线状、聚合状、霰状、球状、板状、枝状和不规则状）。利用2018年12月—2019年3月河南省3次冬季航测获取的灰度CIP探测数据,分析云粒子形状及各形状粒子面积的统计特征,并对比基于不同形状粒子的质量-尺度关系与将所有粒子视作球形液滴计算所得的粒子水凝物含量,发现后者超过前者约1个量级。
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| 关 键 词： | 云粒子 粒子图像 粒子形状 水凝物含量 |
| 收稿时间： | 2021-07-15 |
Shape Recognition of DMT Airborne Cloud Particle Images and Its Application |
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| Institution: | 1.Key Laboratory for Cloud Physics of China Meteorological Administration, Beijing 1000812.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 1000813.Weather Modification Center of Henan Province, Zhengzhou 4500034.Hebei Provincial Weather Modification Center, Shijiazhuang 0500215.China Huayun Meteorological Technology Group Corporation, Beijing 100081 |
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| Abstract: | Currently, the most direct and effective way to obtain cloud precipitation microphysical characteristics is from in-situ measurements acquired by airborne imaging probes. There are many studies based on CIP (cloud imaging probe) and PIP (precipitation imaging probe) detection data, which are mostly based on the limited output from the software PADS (Particle Analysis and Display System) provided by DMT (Droplet Measurement Technologies). Since PADS only outputs the second-by-second statistical results rather than the detailed particle-by-particle information, it greatly limits the deep mining and analyzing of cloud particle image data. Besides, particle shapes in previous studies are mainly classified through naked-eye observations, which is time consuming, subjective, and unreliable to conduct statistical analysis on thousands of cloud particle images. Therefore, it is impossible to calculate the hydrometeor content based on mass-dimension relationships for particles of different shapes in ice or mixed cloud observations.The operation principle of airborne two-dimensional optical array probes is introduced. Then techniques of recognition and elimination of shattering particles and fake particles are illustrated in detail. Particle shapes are divided into 8 types (tiny, linear, aggregated, graupel, spherical, plate, dendritic and irregular) based on geometric characteristics of particle shapes. Statistical characteristics of different cloud particle shapes and their areas are analyzed by using gray CIP data detected in three wintertime stratiform clouds in Henan Province. The recognition of particle shapes are basically consistent with results through naked-eye observations, and also consistent with dominant particle shapes in each temperature range obtained by previous studies. The hydrometeor content obtained using the mass-dimension relationship for particles of different shapes is compared with that from treating all particles as spherical liquid particles (i.e., the algorithm used by PADS). It is found that when all particles are treated as spherical liquid particles, the hydrometeor content is roughly one magnitude higher than that from considering different particle shapes, indicating the technique of particle shape classification can improve the accuracy of hydrometeor content in ice or mixed clouds. In addition, some matters needing attention in the use of two-dimensional particle image data are pointed out to ensure proper use of two-dimensional particle image data. |
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