The auroral event is defined as a period of various special aurora appearance. It is a good way to understand the interaction among the solar wind plasma, the terrestrial magnetic field, and the Earth’s atmosphere, since the motion of auroral event supplies a powerful tool to discover the underlying coherence among those natural phenomena. Therefore, studies on different types of auroral events have attracted growing attentions. In this study, an auroral event representation approach is proposed for automatic aurora classification. Specifically, 3D steerable filters are used to generate space-time oriented energies, which can simultaneously capture texture and motion of the auroral event. Then, n-ary fusion operator is used to combine oriented energies together to generate a unified representation, which also makes the representation has the property of gray-scale invariance. In order to capture roughly global shape information, a block partition scheme is used to further represent the auroral event. Finally, the performance of the representation is evaluated by the auroral event classification. The superior experimental results demonstrate the effective of our proposed auroral event representation method.