Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 10
Articles | Volume 14, issue 10
https://doi.org/10.5194/amt-14-6695-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-6695-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 10
Research article
 | 
18 Oct 2021
Research article |  | 18 Oct 2021

Twenty-four-hour cloud cover calculation using a ground-based imager with machine learning

Bu-Yo Kim, Joo Wan Cha, and Ki-Ho Chang

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Latest update: 20 Nov 2024
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Short summary
This study investigates a method for 24 h cloud cover calculation using a camera-based imager and supervised machine learning methods. The cloud cover is calculated by learning the statistical characteristics of the ratio, difference, and luminance using RGB channels of the image with a machine learning model. The proposed approach is suitable for nowcasting because it has higher learning and prediction speed than the method in which the many pixels of a 2D image are learned.
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