Abstract
A statistical analysis for pattern recognition of small cloud particles sampled with a PMS-2DC probe
Highlights
Size spectra obtained from in situ measurements within clouds (Liou, 1992; Kinne and Liou, 1989) show that the number of small particles is very large, and that it is important for the determination of structural, optical and microphysical quantities such as liquid or ice water contents (LWC or IWC)
The representativeness of the sampled images depends on both the true air speed (TAS) clock frequency and the lapse rate of the photodiodes
Dx characterizes the nominal pixel size (25 lm) de®ned by the array of the photodiodes, Dy is the pixel size along theight direction
Summary
Size spectra obtained from in situ measurements within clouds (Liou, 1992; Kinne and Liou, 1989) show that the number of small particles (size ranging from 25 lm to 200 lm) is very large, and that it is important for the determination of structural, optical and microphysical quantities such as liquid or ice water contents (LWC or IWC). The scattering properties of ice crystals (with hexagonal structure or even a more complex shape) dier significantly from that of perfect spheres (as given by the Mie theory), and the spherical assumption induces quite large errors for the calculation of bulk quantities such as the liquid water path or optical thickness of the cloud. The objective was to de®ne a new automatic pattern recognition algorithm in order to dierentiate the images of small hexagonal columns from those of spherical particles. Fouilloux et al.: A statistical analysis for pattern recognition of small cloud particles
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