Sprite Distribution of Different Polarities From ISUAL Observations With Machine Learning Method

Abstract

AbstractThe morphological features of sprites are closely related to the polarity of their causative lightning strokes. Using the machine learning method, we develop a model with an accuracy of 93.8% to identify the polarity of sprite‐producing cloud‐to‐ground (CG) lightning strokes for events recorded during the Imager of Sprites and Upper Atmospheric Lightning (ISUAL) mission. Approximately 17% of the sprites are identified to be produced by negative CG lightning strokes. The global distribution of the polarity of sprite‐producing CG lightning strokes suggests that the ratio of sprites produced by negative CG lightning strokes relative to sprites produced by positive ones varies with latitude and sea‐land distribution. Sprites produced by negative CG lightning strokes appear to be generated in the tropical regions below 20° latitude and the oceanic area. Moreover, the proportion of sprites produced by negative CG lightning strokes over Africa and North America are much smaller than that over the rest of the continents and the sea.