A machine learning nowcasting method based on real-time reanalysis data

The variational Doppler radar analysis system (VDRAS) is an advanced convective-scale analysis system capable of providing analysis of 3-D wind, temperature, and humidity by assimilating Doppler radar observations.

Although potentially useful, it is still an open question as to how to use these fields to improve nowcasting. In this study, we present results from our first attempt at developing a support vector machine (SVM) box-based nowcasting (SBOW) method under the machine learning framework using VDRAS analysis data. The key design points of SBOW are as follows: (1) The study domain is divided into many position-fixed small boxes, and the nowcasting problem is transformed into one question, i.e., will a radar echo >35dBZ appear in a box in 30min?