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The habits of cloud particles are a significant factor impacting microphysical processes in clouds. The accurate identification of cloud particle shapes within clouds is a fundamental requirement for calculating various cloud microphysical parameters. In this study, we established a cloud particle image dataset encompassing nine distinct habit categories, totaling 8100 images. These images were captured using three probes with varying resolutions: the Cloud Particle Imager (CPI), the Two-Dimensional Stereo Probe (2D-S), and the High-Volume Precipitation Spectrometer (HVPS). Furthermore, this study performs a comparative analysis of ten different transfer learning (TL) models based on this dataset. It was found that the VGG-16 model exhibits the highest classification accuracy, reaching 97.90%. This model also demonstrates the highest recall, precision, and F1 measure. The results indicate that the VGG-16 model can reliably classify the shapes of ice crystal particles measured by both line scan imagers (2D-S, HVPS) and an area scan imager (CPI).
Details
Automatic classification;
Accuracy;
Habits;
Comparative analysis;
Deep learning;
Datasets;
Classification;
Artificial neural networks;
Neural networks;
Cloud particles;
Clouds;
Machine learning;
Crystals;
Radiation;
Transfer learning;
Doppler effect;
Precipitation;
Remote sensing;
Ice crystals;
Atmospheric sciences;
Images;
Methods;
Algorithms
; Jiao, Ruili 2 ; Li, Qiubai 3 ; Huang, Minsong 4 1 China Meteorological Administration Basin Heavy Rainfall Key Laboratory/Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China;
2 School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing 100101, China
3 School of Earth Sciences, Yunnan University, Kunming 650091, China;
4 China Meteorological Administration Basin Heavy Rainfall Key Laboratory/Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan 430205, China;