Abstract
Atmospheric monitoring is a field of special importance for astroparticle physics, especially for Imaging Atmospheric Cherenkov Telescopes (IACTs) as clouds will absorb and scatter the Cherenkov photons of air showers. Conventional tools used for atmospheric monitoring (e.g. LIDAR) are very expensive and monitor only a small part of the sky at once. Therefore, they are not suitable to perform a wide scan of the sky which is necessary to detect clouds in advance.This article gives a short overview about a method that uses an all sky camera with a 180 ° field of view to identify the cloud distribution by measuring the absorption of star light. It can be used to assign a sky quality rating to single spots, arbitrary regions or the whole sky at once within a 1 min exposure time. A cloud map can be created from the available data that can be used to determine shape and dimension of clouds and to predict their movement. The resulting data can be used by a scheduling algorithm or the operating crew to point the telescope to a different source before the current source gets covered by clouds. The all sky cameras used so far are located on La Palma at the observatory Roque de los Muchachos close to the telescopes FACT and MAGIC and the planned northern CTA site.
Highlights
A precise cloud forecast would be very valuable for the operation of Imaging Atmospheric Cherenkov Telescopes (IACTs)
A precise cloud forecast would be very valuable for the operation of IACTs
Projecting the cloud map onto the model of the spherical atmosphere will increase the accuracy of the prediction because clouds move faster in the image center due to the fish eye lens
Summary
A precise cloud forecast would be very valuable for the operation of IACTs. If the time was known when a source will cover up, the telescope could switch to another source in advance and continue taking data. The detection of clouds at night using a camera is difficult as they do not emit light on their own and are as dark as the night sky unless they refract moon light and appear as white objects in the camera image. The number of visible stars in the image is a good approximation of the cloud coverage as their appearance does not depend on ambient light or wind conditions. A partial absorption of light will not be recognized if stars have only two states: ‘visible’ or ‘not visible’. This effect makes it very difficult to reconstruct the smooth shape of a cloud or detect thin clouds in the first place
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