CLOWN: The PASO Cloud Detection for Optimization of Automatic Optical Surveys

Abstract Orbiting space objects have become in the last decade a major nuisance impacting ground astronomy and orbiting space assets, from observatories to satellites and space stations. In particular with the rise of the satellite population in Low Earth Orbits, space objects are becoming an even bigger threat and a strong problem to astronomical observations. To tackle these threats, several coordinated surveillance networks composed of dedicated sensors (telescopes, radars, and laser ranging facilities) track and survey space objects, from debris to active satellites. As part of the European Space Surveillance & Tracking network, Portugal is developing the Pampilhosa da Serra Space Observatory, with both radio and optical telescopes dedicated to the Space Situational Awareness domain, deployed at a Dark Sky destination. To optimize telescope survey time, we developed CLOud Watcher at Night (CLOWN), an application interface that automatically monitors clouds in real time. This software can correctly trace cloud positions in the sky and provide accurate pointing information to the observation planning of the optical telescope to avoid cloudy areas. CLOWN only requires the use of an all-sky camera, which is already a norm in observatories with optical telescopes and can be used with any camera, including those for which no information about its model specification do exist. CLOWN does not require great computing power, and it does not require the installation of additional equipment. CLOWN results are very promising and confirm that the app can correctly identify clouds in a variety of different conditions and cloud types.

Authors

Publication Details

Journal
The Astronomical Journal
Published
2024-10-22
DOI
https://doi.org/10.3847/1538-3881/ad779a
Primary Topic
Astro and Planetary Science
Type
article
Field-Weighted Citation Impact
0.00

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article

CLOWN: The PASO Cloud Detection for Optimization of Automatic Optical Surveys

Miguel Bergano, Vítor Bonifácio, Bruno Coelho, Domingos Barbosa et al.
The Astronomical Journal
Astro and Planetary Science
article

CLOWN: The PASO Cloud Detection for Optimization of Automatic Optical Surveys

Miguel Bergano, Vítor Bonifácio, Bruno Coelho, Domingos Barbosa, D. Maia, Luís Gonçalves
article en

Abstract

Abstract Orbiting space objects have become in the last decade a major nuisance impacting ground astronomy and orbiting space assets, from observatories to satellites and space stations. In particular with the rise of the satellite population in Low Earth Orbits, space objects are becoming an even bigger threat and a strong problem to astronomical observations. To tackle these threats, several coordinated surveillance networks composed of dedicated sensors (telescopes, radars, and laser ranging facilities) track and survey space objects, from debris to active satellites. As part of the European Space Surveillance & Tracking network, Portugal is developing the Pampilhosa da Serra Space Observatory, with both radio and optical telescopes dedicated to the Space Situational Awareness domain, deployed at a Dark Sky destination. To optimize telescope survey time, we developed CLOud Watcher at Night (CLOWN), an application interface that automatically monitors clouds in real time. This software can correctly trace cloud positions in the sky and provide accurate pointing information to the observation planning of the optical telescope to avoid cloudy areas. CLOWN only requires the use of an all-sky camera, which is already a norm in observatories with optical telescopes and can be used with any camera, including those for which no information about its model specification do exist. CLOWN does not require great computing power, and it does not require the installation of additional equipment. CLOWN results are very promising and confirm that the app can correctly identify clouds in a variety of different conditions and cloud types.

The Astronomical JournalVol. 168(5)
Fundação para a Ciência e a Tecnologia, H2020 Industrial Leadership
Openalex Percentile: Top 86%
Astro and Planetary Science
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