New atmospheric profiles for H.E.S.S. data analysis

Mónica Seglar-Arroyo,Fabian Schüssler

doi:10.1051/epjconf/201714401013

Abstract

Particles arriving to Earth allow us to scan and improve our understanding of the Universe, both in its composition and its dynamics. For ground-based experiments in astroparticle physics, the atmosphere plays a key role and its understanding, monitoring and modelling is essential for a realistic description in data analysis and simulations. In this work we present the development of a novel experimental atmospheric model, the GNNA120 model, describing the atmosphere above the H.E.S.S. gamma-ray observatory in Namibia. This new description is the most realistic to date and introduces the possibility to study variations at different time scales. This enables us to provide the first ever study of seasonal effects based on actual measured atmospheric profiles for the H.E.S.S. observatory and opens up the window to further improvements of the H.E.S.S. Monte Carlo simulations.

Highlights

Much of the radiation propagating in the Cosmos and incident on the Earth is thermal radiation generated in hot objects such as stars
Even though the existance of cosmic rays has been known since the first decades of the 20th century, their acceleration locations have not been found yet
The impact of the parametrisation of different atmospheric variables relevant for the atmospheric Cherenkov technique in the atmosphere above the H.E.S.S. site has been presented by means of data coming from Global Data Assimilation System [5] (GDAS) and NRLMSISE, the new GNNA120 model has been built

Summary

Introduction

Much of the radiation propagating in the Cosmos and incident on the Earth is thermal radiation generated in hot objects such as stars. The parameters that are used as an input for its calculation are the energy threshold of the telescope, which shows a direct proportion to the transparency of the atmosphere, and other inversely proportional quantities related to the telescope data taking efficiency like the telescopes-wise muon efficiency, average pixel gains and number of active telescopes. This approach has been proven to be an effective and a pratical method of distinguinshing good quality datasets without the need to measure the aerosols distributions [3] , that is a rather difficult task

Experimental GNNA120 atmospheric model

GNNA120 atmospheric profiles

Comparison KASKADE-to-GNNA120 atmospheric profiles

Slant depth

Summary