Articles | Volume 11, issue 10
https://doi.org/10.5194/amt-11-5549-2018
© Author(s) 2018. 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-11-5549-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Oct 2018
Research article |
| 12 Oct 2018
| 12 Oct 2018
Cloud fraction determined by thermal infrared and visible all-sky cameras
Physikalisch-Meteorologisches Observatorium Davos, World Radiation Center, Davos, Switzerland
Oeschger Center for Climate Change Research and Institute of Applied Physics, University of Bern, Bern, Switzerland
Julian Gröbner
Physikalisch-Meteorologisches Observatorium Davos, World Radiation Center, Davos, Switzerland
Niklaus Kämpfer
Oeschger Center for Climate Change Research and Institute of Applied Physics, University of Bern, Bern, Switzerland
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- Comparison of Cloud Amounts Retrieved with Three Automatic Methods and Visual Observations M. Utrillas et al. 10.3390/atmos13060937
- CloudU-Net: A Deep Convolutional Neural Network Architecture for Daytime and Nighttime Cloud Images’ Segmentation C. Shi et al. 10.1109/LGRS.2020.3009227
- Solar radiation budget in the atmosphere under broken cloudy sky. An analytical model R. Rosa & A. Silva 10.1016/j.jastp.2021.105643
- Observations of Nighttime Clouds Over Chiba, Japan, Using Digital Cameras and Satellite Images N. Lagrosas et al. 10.1029/2021JD034772
- A Novel Ground-Based Cloud Image Segmentation Method Based on a Multibranch Asymmetric Convolution Module and Attention Mechanism L. Zhang et al. 10.3390/rs14163970
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- Solar irradiance components estimation based on a low-cost sky-imager C. Sánchez-Segura et al. 10.1016/j.solener.2021.02.037
- Angular Calibration of Visible and Infrared Binocular All-Sky-View Cameras Using Sun Positions W. Xie et al. 10.3390/rs13132455
- Intrahour solar radiation forecasting based on sun visibility for different cloud types X. Hou et al. 10.1016/j.solener.2025.113477
- Towards an Algorithm for Near Real Time Profiling of Aerosol Species, Trace Gases, and Clouds Based on the Synergy of Remote Sensing Instruments N. Siomos et al. 10.1051/epjconf/202023708023
- Extreme wildfires over northern Greece during summer 2023 – Part A: Effects on aerosol optical properties and solar UV radiation K. Michailidis et al. 10.1016/j.atmosres.2024.107700
- Diurnal (24 h) cycle and seasonal variability of cloud fraction retrieved from a Whole Sky Imager over a complex terrain in the Western Ghats and comparison with MODIS S. Sunil et al. 10.1016/j.atmosres.2020.105180
Latest update: 16 Sep 2025
Short summary
A newly developed hemispherical thermal infrared cloud camera (IRCCAM) is presented. The IRCCAM allows automatic cloud detection during the day and at night-time. The cloud fraction determined from the IRCCAM is compared with the cloud fraction determined from other instruments over a time period of 2 years. The IRCCAM has an agreement of +/- 2 oktas cloud fraction in 90 % of the data compared to other instruments. There are no significant differences between seasons or different times of day.
A newly developed hemispherical thermal infrared cloud camera (IRCCAM) is presented. The IRCCAM...
