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作为云微物理过程测量的重要利器,机载云降水粒子成像仪在云降水物理与人工影响天气研究中具有重要的作用.从采样结果来看,机载云降水粒子成像仪所测粒子图像中含有大量的粒子图像仅是粒子的一部分而已,即部分状粒子.因其数量较多,对该类粒子所选处理方法不同,会引起测量结果的很大差异.本文介绍并分析了现有部分状粒子处理方法的优劣,通过对部分状粒子的再定义与粒子形状分类,提出了一个融合粒子形状识别技术、“粒径重构”和“中心在内”方法的新的部分状粒子处理方法;利用实测数据,对所提方法与现有方法进行了云微物理参量处理结果的对比,发现本文所提方法与“粒径重构”方法处理结果比较一致,能较好地克服“整体在内”与“中心在内”两种方法存在的缺陷;同时,在针柱状粒子占比较多情形下,本文所提方法要比“粒径重构”方法处理后的结果相对合理.因此本文所提方法对仪器所测粒子数据处理具有更好的适应性.
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关键词:
- 机载云降水粒子成像仪 /
- 部分状粒子 /
- 云微物理
As an important instrument for the cloud microphysics measurement, the airborne cloud and precipitation imaging probe plays a significant role in studying the cloud and precipitation physics and artificial weather modification. The particle image data recorded by the probe can be used to process, calculate and produce the cloud microphysical parameters, such as the cloud particle size spectra, cloud particle number concentration, cloud water content, etc. However, there are lots of partial particle images in the sampled data. This is due to the limited sample volume of the probe, the volume that contains only a part of the particles and is imaged by the probe. The number of partial particles in each sample is so large that the technique used to process these particles can have a great influence on the calculation of cloud microphysical parameters. However, there has been no perfect solution for dealing with these partial particles so far.
The three existing processing methods-“All In” method, “Center In” method, and “Diameter Reconstruction” method for the partial particles, are introduced and analysed in this study. After analyzing the advantages and disadvantages of these existing methods, a new definition and a particle shape classification for the partial particle are given, which can discriminate the circularly symmetric particles and the non-circularly symmetric particles from the partials. Then a new partial particle processing method is introduced, which combines the partial particle shape recognition technique and the traditional techniques-“Center In” method and “Diameter Reconstruction” method. The circularly symmetric partial particles are processed with the “Diameter Reconstruction method” and the non-circularly symmetric partial particles are processed with the “Center In” method.
Utilizing the historical airplane observation data from Shanxi Taiyuan, the new method presented in this study and the three traditional methods are used to calculate the cloud particle size spectra, cloud particle number concentration, and the ice water content by using the same data. The calculated results are analyzed and compared. It is found that in most cases the results from the new method are more consistent with those from the “Diameter Reconstruction” technique and can overcome the disadvantages of the existing methods, especially when the cloud has more column-shaped and needle-shaped particles, the result from the new method is more reasonable. Considering the fact that the column shape is one of the main shapes in the cloud, it is strongly recommended to use the new technique in this paper to process the data from the probes.[1] Ramanathan V, Cess R D, Harrison E F, Minnis P, Barkstrom B R, Ahmad E, Hartmann D L 1989 Science 243 57
[2] Zhang D, Liu C M, Liu X M 2012 Water Int. 37 598
[3] Voyant C, Muselli M, Paoli C, Nivet M L 2012 Energy 39 341
[4] Knollenberg R G 1970 J. Appl. Meteor. 9 86
[5] Grosvenor D P, Choularton T W, Lachlan-Cope T, Gallagher M W, Crosier J, Bower K N, Ladkin R S, Dorsey J R 2012 Atmos. Chem. Phys. 12 11275
[6] Zhao Z, Lei H 2014 Adv. Atmos. Sci. 31 604
[7] Min Q, Joseph E, Lin Y, Min L, Yin B, Daum P H, Kleinman L I, Wang J, Lee Y N 2012 Atmos. Chem. Phys. 12 11261
[8] Heymsfield A J, Parrish J L 1978 J. Appl. Meteor. 17 1566
[9] Holroyd E W 1987 J. Atmos. Oceanic Technol. 4 498
[10] Korolev A, Sussman B 2000 J. Atmos. Oceanic Technol. 17 1048
[11] Brown P R A, Francis P N 1995 J. Atmos. Oceanic Technol. 12 410
[12] Bailey M P, Hallett J 2009 J. Atmos. Sci. 66 2888
[13] Korolev A, Isaac G A, Hallett J 2000 Quart. J. Roy. Meteor. Soc. 126 2873
[14] Crosier J, Bower K N, Choularton T W, Westbrook C D, Connolly P J, Cui Z Q, Crawford I P, Capes G L, Coe H, Dorsey J R, Williams P I, Illingworth A J, Gallagher M W, Blyth A M 2011 Atmos. Chem. Phys. 11 257
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[1] Ramanathan V, Cess R D, Harrison E F, Minnis P, Barkstrom B R, Ahmad E, Hartmann D L 1989 Science 243 57
[2] Zhang D, Liu C M, Liu X M 2012 Water Int. 37 598
[3] Voyant C, Muselli M, Paoli C, Nivet M L 2012 Energy 39 341
[4] Knollenberg R G 1970 J. Appl. Meteor. 9 86
[5] Grosvenor D P, Choularton T W, Lachlan-Cope T, Gallagher M W, Crosier J, Bower K N, Ladkin R S, Dorsey J R 2012 Atmos. Chem. Phys. 12 11275
[6] Zhao Z, Lei H 2014 Adv. Atmos. Sci. 31 604
[7] Min Q, Joseph E, Lin Y, Min L, Yin B, Daum P H, Kleinman L I, Wang J, Lee Y N 2012 Atmos. Chem. Phys. 12 11261
[8] Heymsfield A J, Parrish J L 1978 J. Appl. Meteor. 17 1566
[9] Holroyd E W 1987 J. Atmos. Oceanic Technol. 4 498
[10] Korolev A, Sussman B 2000 J. Atmos. Oceanic Technol. 17 1048
[11] Brown P R A, Francis P N 1995 J. Atmos. Oceanic Technol. 12 410
[12] Bailey M P, Hallett J 2009 J. Atmos. Sci. 66 2888
[13] Korolev A, Isaac G A, Hallett J 2000 Quart. J. Roy. Meteor. Soc. 126 2873
[14] Crosier J, Bower K N, Choularton T W, Westbrook C D, Connolly P J, Cui Z Q, Crawford I P, Capes G L, Coe H, Dorsey J R, Williams P I, Illingworth A J, Gallagher M W, Blyth A M 2011 Atmos. Chem. Phys. 11 257
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