Nowcasting of rain with Doppler weather radar – A comparative strategy for complex orography

Abstract

Abstract: Nowcasting of North Eastern Himalayan orographic rainfall has been attempted using ground-based Doppler weather radar reflectivity echo information for more than 532 samples covering various rain events of the year 2023 over two densely populated hilly Indian locations, Agartala and Mohanbari. Various optical motion fields of rain are used as input to the nowcasting algorithm. Both ensemble and non-ensemble-based nowcasting algorithms have been used, and performances have been considered. Lead time of nowcast has been increased from half an hour to two hours. The performance analysis shows that there are significant seasonal and locational variations with respect to the statistical error parameter and contingency error parameter. With an increase in lead time, performance skill decreases. Use of a short-term ensemble prediction system in nowcasting with ensemble size varying from 24 to 72 does not indicate any significant improvement in performance. Detailed performance analysis of the algorithms will help in the efficient, targeted use of a suitable rain nowcasting algorithm for operational purposes. Research highlights: Nowcasting of orographic rain with Doppler Weather Radar reflectivity echo. Prediction using optical motion field of rain. Both ensemble and non-ensemble-based algorithm have been used for nowcasting. Prediction performance and skill score have been compared for orographic rain. © 2025 Elsevier B.V., All rights reserved.