A Novel Neural Based Rainfall Nowcasting System in Hong Kong

This paper describes the development of a new approach of rainfall nowcasting (very short term forecasting) by using a neural network. This approach consisted of extracting the information from radar images and evaluating past rain gauge records to provide short term rainfall forecasting. All meteorology data were provided by the Royal Observatory of Hong Kong (ROHK). Pre-processing procedures were essential for this neural network rainfall nowcasting. The forecast of rainfall every half an hour is such that a storm warning signal can be delivered to the public in advance. The network architecture was based on a recurrent Sigma-Pi network. The results are very promising and this neural based rainfall nowcasting system was capable of providing a reliable rain storm warning signal to the Hong Kong public in advance.