The study presents the "first application of Deep Learning techniques as an alternative methodology for climate extreme events detection." The developed deep Convolutional Neural Network (CNN) classification system is able to learn high-level representations of a broad class of patterns from labeled data and achieves 89%-99% of accuracy in detecting extreme events.