Strong convective echoes identification based on rough set theory

Abstract

In this paper radar reflectivity image, a range of weather conditions, and image processing technology were applied to extract features of strong convective echoes (hail, torrential rain) from the radar images. Area, vertically integrated liquid water (VIL), vertically integrated liquid water density (VTLD) and other features were obtained to construct the characteristic database. Rough set theory was used to dig out useful rules that can form the knowledge base, thereby the objective model of identifying strong convection weather was established. Finally the objective model was used to identify and forecast hail and torrential rain. Test results indicated that the three features properties of hail and torrential rain had effective recognition results, and prediction accuracy was 76.25% which meets the requirements of preliminary classification.