Impact of Radar Data Assimilation on the Simulation of a Heavy Rainfall Event Over Manaus in the Central Amazon

Abstract

The aim of this study was to evaluate the impact of radar-detected radial velocity and reflectivity data assimilation (DA) on precipitation forecasts using the Weather Research and Forecasting (WRF) numerical model and its three-dimensional variational DA system (WRFDA-3DVAR). For this purpose, one heavy rain event in the city of Manaus in the Central Amazon on 25 December 2017 was analyzed. Numerical experiments were conducted using different initial conditions and both cyclical and non-cyclical assimilation processes. The evaluation of these experiments, conducted with and without radar DA, was based on comparisons between estimated radar precipitation and simulated precipitation. The results show that radial velocity plays a fundamental role in improving the representation of the convective system. Additionally, the best results were obtained when reflectivity was included alongside radial velocity in non-cyclical assimilation processes. Therefore, it can be concluded that the assimilation of radar data positively impacted the short-term forecast of precipitation associated with the studied convective system.