Articles | Volume 15, issue 17
https://doi.org/10.5194/amt-15-5141-2022
https://doi.org/10.5194/amt-15-5141-2022
Research article
 | 
13 Sep 2022
Research article |  | 13 Sep 2022

Ice crystal images from optical array probes: classification with convolutional neural networks

Louis Jaffeux, Alfons Schwarzenböck, Pierre Coutris, and Christophe Duroure

Data sets

Louis Jaffeux: LJaffeux/AMT-2022-72: Ice crystals images from Optical Array Probes: classification with Convolutional Neural Networks Louis Jaffeux https://doi.org/10.5281/zenodo.6912294

Model code and software

Louis Jaffeux: LJaffeux/AMT-2022-72: Ice crystals images from Optical Array Probes: classification with Convolutional Neural Networks Louis Jaffeux https://doi.org/10.5281/zenodo.6912294

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Short summary
Optical array probes are instruments used aboard research aircraft to capture 2D images of ice or water particles in clouds. This study presents a new tool using innovative machine learning, called convolutional neural networks, designed to identify the shape of imaged ice particles for two of these imagers, namely 2DS and PIP. Such a tool will be a very strong asset for understanding cloud microphysics. Beyond traditional evaluation metrics, human inspections were performed of unknown data.