  Precipitation is dependent on a myriad of atmospheric conditions. In this
paper, we study how certain atmospheric parameters impact the occurrence of
rainfall. We propose a data-driven, machine-learning based methodology to
detect precipitation using various meteorological sensor data. Our approach
achieves a true detection rate of 87.4% and a moderately low false alarm rate
of 32.2%.
