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.
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.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Oct 2021
Research article |
| 18 Oct 2021
| 18 Oct 2021
Twenty-four-hour cloud cover calculation using a ground-based imager with machine learning
Convergence Meteorological Research Department, National Institute of
Meteorological Sciences, Seogwipo, Jeju 63568, Republic of Korea
Joo Wan Cha
Convergence Meteorological Research Department, National Institute of
Meteorological Sciences, Seogwipo, Jeju 63568, Republic of Korea
Ki-Ho Chang
Convergence Meteorological Research Department, National Institute of
Meteorological Sciences, Seogwipo, Jeju 63568, Republic of Korea
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M. L. Krüger, S. Mertes, T. Klimach, Y. F. Cheng, H. Su, J. Schneider, M. O. Andreae, U. Pöschl, and D. Rose
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M. I. A. Berghof, G. P. Frank, S. Sjogren, and B. G. Martinsson
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A. Schwarzenboeck, G. Mioche, A. Armetta, A. Herber, and J.-F. Gayet
Atmos. Meas. Tech., 2, 779–788, https://doi.org/10.5194/amt-2-779-2009, https://doi.org/10.5194/amt-2-779-2009, 2009
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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.
This study investigates a method for 24 h cloud cover calculation using a camera-based imager...
