Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/130197
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Type: Journal article
Title: An automated all-sky atmospheric monitoring camera for a next-generation ultrahigh-energy cosmic-ray observatory
Author: Chytka, L.
Mandat, D.
Albury, J.
Bellido, J.A.
Farmerh, J.
Fujii, T.
Hamal, P.
Horvath, P.
Hrabovsky, M.
Kvita, J.
Malacari, M.
Mastrodicasa, M.
Matthews, J.N.
Michal, S.
Ni, X.
Nozka, L.
Palatka, M.
Pech, M.
Privitera, P.
Schovanek, P.
et al.
Citation: Journal of Instrumentation, 2020; 15(10):T10009-1-T10009-16
Publisher: IOP Publishing
Issue Date: 2020
ISSN: 1748-0221
1748-0221
Statement of
Responsibility: 
L. Chytka, D. Mandat, J. Albury, J.A. Bellido, J. Farmerh, T. Fujii ... et al.
Abstract: We have developed a fully-automated instrument (FASCam—Fast All Sky Camera) designed to capture night all-sky images and analyse cloudiness and coarse atmospheric properties for a proposed next-generation ultrahigh energy cosmic ray observatory, called the Fluorescence detector Array of Single-pixel Telescopes (FAST). FASCam has a 360 × 90o (azimuth and elevation) field of view and is equipped with a series of photometric Johnson-Cousins filters (BVR) and an Ultra-violet (UV) filter. The camera is installed on the top of one of the three FAST prototype telescope buildings located in central Utah, U.S.A. . An online analysis of the images provides real time cloud coverage maps and coarse atmospheric extinction measurements and a night sky background estimate in the field of view of the FAST fluorescence telescopes. The result serves as an input parameter for the operation of the telescopes and avoids unnecessary data taking in the case of clouds covering the field of view of the telescopes, high atmospheric extinction, or high night sky background.
Keywords: Image processing; Photometers; Photon detectors forUV, visible and IR photons (solidstate) (PIN diodes, APDs, Si-PMTs, G-APDs, CCDs, EBCCDs, EMCCDs, CMOS imagers, etc)
Rights: © 2020 IOP Publishing Ltd and Sissa Medialab
DOI: 10.1088/1748-0221/15/10/T10009
Grant ID: http://purl.org/au-research/grants/arc/DP150101622
Published version: http://dx.doi.org/10.1088/1748-0221/15/10/t10009
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