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| Titel |
A statistical analysis for pattern recognition of small cloud particles sampled with a PMS-2DC probe |
| VerfasserIn |
A. Fouilloux, J. Iaquinta, C. Duroure, F. Albers |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
0992-7689
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| Digitales Dokument |
URL |
| Erschienen |
In: Annales Geophysicae ; 15, no. 6 ; Nr. 15, no. 6, S.840-846 |
| Datensatznummer |
250012846
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| Publikation (Nr.) |
 copernicus.org/angeo-15-840-1997.pdf |
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| Zusammenfassung |
| Although small particles (size between 25 µm
and 200 µm) are frequently observed within ice and water clouds, they
are not generally used properly for the calculation of structural, optical and
microphysical quantities. Actually neither the exact shape nor the phase (ice or
water) of these particles is well defined since the existing pattern recognition
algorithms are only efficient for larger particle sizes. The present study
describes a statistical analysis concerning small hexagonal columns and
spherical particles sampled with a PMS-2DC probe, and the corresponding images
are classified according to the occurrence probability of various pixels
arrangements. This approach was first applied to synthetic data generated with a
numerical model, including the effects of diffraction at a short distance, and
then validated against actual data sets obtained from in-cloud flights during
the pre-ICE'89 campaign. Our method allows us to differentiate small hexagonal
columns from spherical particles, thus making possible the characterization of
the three dimensional shape (and consequently evaluation of the volume) of the
particles, and finally to compute e.g., the liquid or the ice water content. |
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