Issue |
EPJ Web Conf.
Volume 144, 2017
Atmospheric Monitoring for High Energy Astroparticle Detectors (AtmoHEAD) 2016
|
|
---|---|---|
Article Number | 01003 | |
Number of page(s) | 7 | |
DOI | https://doi.org/10.1051/epjconf/201714401003 | |
Published online | 17 May 2017 |
https://doi.org/10.1051/epjconf/201714401003
CTA Atmospheric Calibration
1 Unitat de Física de les Radiacions, Departament de Física, Universitat Autònoma de Barcelona, Spain
2 CERES-IEEC, Universitat Autònoma de Barcelona, Spain
* e-mail: markus.gaug@uab.cat
Published online: 17 May 2017
The main contribution to the systematic uncertainties of Atmospheric Imaging Cherenkov Telescopes (IACTs) currently stems from the uncertainty in the determination of atmospheric properties for a given moment of observation. This technique uses the atmosphere as a calorimeter of gamma-ray induced atmospheric air showers and measures the amount of Cherenkov light collected by large mirrors and focused towards a pixellized camera. Atmospheric conditions affect the measured Cherenkov light yield in several ways: the air-shower development itself, the variation of the Cherenkov angle with altitude and the loss of photons due to scattering and absorption of Cherenkov light. Although IACTs use to be located at astronomical sites, characterized by extremely clear atmospheric conditions, the local atmosphere should be continuously monitored, in terms of molecular density profiles, aerosol extinction profiles, and clouds. Moreover, a general understanding of the site and particularly aerosol climatology is desirable for a robust interpretation of the sensing instruments’ data. Here, the strategy of the Cherenkov Telescope Array (CTA) on atmospheric monitoring is presented, designed to ensure that the related systematic uncertainties are brought down by at least a factor of two with respect to current installations. Additionally, a more intelligent scheduling scheme is aimed at, where source observations are selected using dedicated auxiliary atmospheric monitoring instruments and taking into account the feasibility of a later analysis according to the underlying scientific case. This plan should reduce data loss during offline data selection and enhance the effective duty cycle of the CTA.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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