Constructing Rapid Refresh System for Rainfall Nowcasting (0-6 h) at the Ho Chi Minh City

Abstract

This study presents an hourly updated assimilation and model forecast system (Rapid Refresh - RAP) designed for rainfall nowcasting at Ho Chi Minh city (named HCM-RAP). The HCM-RAP implemented the Weather Research and Forecasting (WRF) model, driven by Global Forecast System (GFS) data at horizontal resolution of 0.25x0.25 degree, in combination with rapid update of radar data at Nha Be station. The HCM-RAP is evaluated during the heavy rainfall event of 25-26 November 2018 against observation data at 10 stations. Results show the advantage of data assimilation in the improvement of hourly rainfall forecast, in compared with the forecast from the experiment without assimilated data. However, the rainfall forecast amount was still underestimated by the HCM-RAP. This is the first attempt for heavy rainfall forecasting and warning for Ho Chi Minh city. In order to implementing the HCM-RAP for operational forecast, further study is recommended, for instance, more heavy rainfall events and in merger with quantitative precipitation estimation from radar and satellite data.