We construct a machine learning model to classify the weather as clear or cloudy during the Telescope Array experiment data acquisition.
The Telescope Array is a high energy physics experiment designed to observe air showers induced by ultra high energy cosmic rays. It does this using a combination of ground array and air-fluorescence techniques. The array of scintillator surface detectors samples the footprint of the air shower when it reaches the Earth's surface, while the fluorescence telescopes measure the scintillation light generated as the shower passes through the gas of the atmosphere. The ultimate goal of the experiment is to determine the sources of ultra high energy cosmic rays to provide a better understanding of the nature of the universe.
The fluorescent telescopes operate on dark moonless nights. However the data they collect is only usable if the night sky was clear (not cloudy). The goal of our machine learning project is to construct a model that can determine whether the sky was clear from the data taken by the telescopes.