An analysis method for data taken by Imaging Air Cherenkov Telescopes at very high energies under the presence of clouds

TL;DR

This paper presents a method to correct for cloud-induced atmospheric effects in Imaging Air Cherenkov Telescopes, enabling more accurate gamma-ray source detection during cloudy conditions without extensive additional simulations.

Contribution

The study introduces correction techniques for data affected by clouds, improving the reliability of gamma-ray measurements under partial cloud cover.

Findings

Correction methods reduce systematic errors to below 20%.

Detection capabilities are maintained with clouds at certain altitudes.

No need for extra Monte Carlo simulations under specific cloudy conditions.

Abstract

The effective observation time of Imaging Air Cherenkov Telescopes (IACTs) plays an important role in the detection of gamma-ray sources, especially when the expected flux is low. This time is strongly limited by the atmospheric conditions. Significant extinction of Cherenkov light caused by the presence of clouds reduces the photon detection rate and also complicates or even makes impossible proper data analysis. However, for clouds with relatively high atmospheric transmission, high energy showers can still produce enough Cherenkov photons to allow their detection by IACTs. In this paper, we study the degradation of the detection capability of an array of small-sized telescopes for different cloud transmissions. We show the expected changes of the energy bias, energy and angular resolution and the effective collection area caused by absorption layers located at 2.5 and 4.5 km above the observation level. We demonstrate simple correction methods for reconstructed energy and effective collection area. As a result, the source flux that is observed during the presence of clouds is determined with a systematic error of < 20%. Finally, we show that the proposed correction method can be used for clouds at altitudes higher than 5 km a.s.l.. As a result, the analysis of data taken under certain cloudy conditions will not require additional time-consuming Monte Carlo simulations.