Articles | Volume 12, issue 10
https://doi.org/10.5194/amt-12-5519-2019
© Author(s) 2019. 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-12-5519-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Oct 2019
Research article |
| 21 Oct 2019
| 21 Oct 2019
ELIFAN, an algorithm for the estimation of cloud cover from sky imagers
Marie Lothon
CORRESPONDING AUTHOR
Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
Paul Barnéoud
Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
Omar Gabella
Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
Fabienne Lohou
Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
Solène Derrien
Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
Sylvain Rondi
Direction Académique Hautes-Pyrénées, Tarbes, France
formerly at: Laboratoire d'Astrophysique, University of Toulouse, Tarbes, France
Marjolaine Chiriaco
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, Guyancourt, France
Sophie Bastin
LATMOS/IPSL, UVSQ Université Paris-Saclay, Sorbonne Université, CNRS, Guyancourt, France
Jean-Charles Dupont
Institut Pierre-Simon Laplace, École Polytechnique, UVSQ, Université Paris-Saclay, 91128 Palaiseau, France
Martial Haeffelin
Institut Pierre-Simon Laplace, École Polytechnique, CNRS, Université Paris-Saclay, 91128 Palaiseau, France
Jordi Badosa
LMD, IPSL, École Polytechnique, IP Paris, ENS PSL, Sorbonne Université, CNRS, 91128 Palaiseau France
Nicolas Pascal
AERIS/ICARE Data and Services Center, 59658 Villeneuve d'Ascq, France
Nadège Montoux
Université Clermont Auvergne, CNRS, LaMP, 63000 Clermont-Ferrand, France
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- Feasibility of Ground-Based Sky-Camera HDR Imagery to Determine Solar Irradiance and Sky Radiance over Different Geometries and Sky Conditions P. Valdelomar et al. 10.3390/rs13245157
- Twenty-four-hour cloud cover calculation using a ground-based imager with machine learning B. Kim et al. 10.5194/amt-14-6695-2021
- Estimation of 24 h continuous cloud cover using a ground-based imager with a convolutional neural network B. Kim et al. 10.5194/amt-16-5403-2023
- An experiment of double dynamic lighting in an office responding to sky and daylight: Perceived effects on comfort, atmosphere and work engagement E. Hansen et al. 10.1177/1420326X21991198
- Machine Learning Models for Approximating Downward Short-Wave Radiation Flux over the Ocean from All-Sky Optical Imagery Based on DASIO Dataset M. Krinitskiy et al. 10.3390/rs15071720
- Cézeaux-Aulnat-Opme-Puy De Dôme: a multi-site for the long-term survey of the tropospheric composition and climate change J. Baray et al. 10.5194/amt-13-3413-2020
- MAP-IO: an atmospheric and marine observatory program on board Marion Dufresne over the Southern Ocean P. Tulet et al. 10.5194/essd-16-3821-2024
- The Pyrenean Platform for Observation of the Atmosphere: site, long-term dataset, and science M. Lothon et al. 10.5194/amt-17-6265-2024
Latest update: 20 Nov 2024
Short summary
In the context of an atmospheric network of instrumented sites equipped with sky cameras for cloud monitoring, we present an algorithm named ELIFAN, which aims to estimate the cloud cover amount from full-sky visible daytime images. ELIFAN is based on red-to-blue ratio thresholding applied on the image pixels and on the use of a blue-sky library. We present its principle and its performance and highlight the interest of combining several complementary instruments.
In the context of an atmospheric network of instrumented sites equipped with sky cameras for...
