Articles | Volume 18, issue 11
https://doi.org/10.5194/amt-18-2311-2025
https://doi.org/10.5194/amt-18-2311-2025
Research article
 | 
03 Jun 2025
Research article |  | 03 Jun 2025

Convolutional neural networks for specific and merged data sets of optical array probe images: compatibility of retrieved morphology-dependent size distributions

Louis Jaffeux, Jan Breiner, Pierre Coutris, and Alfons Schwarzenböck

Related authors

Distinct secondary ice production processes observed in radar Doppler spectra: insights from a case study
Anne-Claire Billault-Roux, Paraskevi Georgakaki, Josué Gehring, Louis Jaffeux, Alfons Schwarzenboeck, Pierre Coutris, Athanasios Nenes, and Alexis Berne
Atmos. Chem. Phys., 23, 10207–10234, https://doi.org/10.5194/acp-23-10207-2023,https://doi.org/10.5194/acp-23-10207-2023, 2023
Short summary
Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach
Anne-Claire Billault-Roux, Gionata Ghiggi, Louis Jaffeux, Audrey Martini, Nicolas Viltard, and Alexis Berne
Atmos. Meas. Tech., 16, 911–940, https://doi.org/10.5194/amt-16-911-2023,https://doi.org/10.5194/amt-16-911-2023, 2023
Short summary
Ice crystal images from optical array probes: classification with convolutional neural networks
Louis Jaffeux, Alfons Schwarzenböck, Pierre Coutris, and Christophe Duroure
Atmos. Meas. Tech., 15, 5141–5157, https://doi.org/10.5194/amt-15-5141-2022,https://doi.org/10.5194/amt-15-5141-2022, 2022
Short summary

Related subject area

Subject: Clouds | Technique: In Situ Measurement | Topic: Data Processing and Information Retrieval
An analysis of cloud microphysical features over United Arab Emirates using multiple data sources
Zhenhai Zhang, Vesta Afzali Gorooh, Duncan Axisa, Chandrasekar Radhakrishnan, Eun Yeol Kim, Venkatachalam Chandrasekar, and Luca Delle Monache
Atmos. Meas. Tech., 18, 1981–2003, https://doi.org/10.5194/amt-18-1981-2025,https://doi.org/10.5194/amt-18-1981-2025, 2025
Short summary
IceDetectNet: a rotated object detection algorithm for classifying components of aggregated ice crystals with a multi-label classification scheme
Huiying Zhang, Xia Li, Fabiola Ramelli, Robert O. David, Julie Pasquier, and Jan Henneberger
Atmos. Meas. Tech., 17, 7109–7128, https://doi.org/10.5194/amt-17-7109-2024,https://doi.org/10.5194/amt-17-7109-2024, 2024
Short summary
Distribution characteristics of the summer precipitation raindrop spectrum on the Qinghai–Tibet Plateau
Fuzeng Wang, Yuanyu Duan, Yao Huo, Yaxi Cao, Qiusong Wang, Tong Zhang, Junqing Liu, and Guangmin Cao
Atmos. Meas. Tech., 17, 6933–6944, https://doi.org/10.5194/amt-17-6933-2024,https://doi.org/10.5194/amt-17-6933-2024, 2024
Short summary
Exploring the effect of training set size and number of categories on ice crystal classification through a contrastive semi-supervised learning algorithm
Yunpei Chu, Huiying Zhang, Xia Li, and Jan Henneberger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3160,https://doi.org/10.5194/egusphere-2024-3160, 2024
Short summary
In situ observations of supercooled liquid water clouds over Dome C, Antarctica, by balloon-borne sondes
Philippe Ricaud, Pierre Durand, Paolo Grigioni, Massimo Del Guasta, Giuseppe Camporeale, Axel Roy, Jean-Luc Attié, and John Bognar
Atmos. Meas. Tech., 17, 5071–5089, https://doi.org/10.5194/amt-17-5071-2024,https://doi.org/10.5194/amt-17-5071-2024, 2024
Short summary

Cited articles

Baker, B. and Lawson, R. P.: Improvement in Determination of Ice Water Content from Two-Dimensional Particle Imagery. Part I: Image-to-Mass Relationships, J. Appl. Meteorol. Clim., 45, 1282–1290, https://doi.org/10.1175/JAM2398.1, 2006. a
Duroure, C.: Une nouvelle méthode de traitement des images d'hydrométéores données par les sondes bidimensionnelles, Journal de recherches atmosphériques, https://hal.uca.fr/hal-01950254 (last access: 24 May 2025), 1982.​​​​​​​ a
Emersic, C. and Saunders, C.: Further laboratory investigations into the relative diffusional growth rate theory of thunderstorm electrification, Atmos. Res., 98, 327–340, 2010. a
Field, P., Heymsfield, A., and Bansemer, A.: Shattering and particle interarrival times measured by optical array probes in ice clouds, J. Atmos. Ocean. Tech., 23, 1357–1371, 2006. a
Download
Short summary
Airborne cloud observation relies on high-frequency black-and-white-image information. The study presents automatic shape recognition tools developed with machine learning techniques and adapted for this type of image. Applied on a recent field campaign, these tools produce morphology-specific size distributions that can be compared across four instruments covering different size ranges. The analysis show that the tools are performing well and are consistent across the different instruments.
Share