Impact of Doppler Weather Radar Data Assimilation on the Predictions of Mesoscale Convective Systems

The quantitative data such as Doppler Weather Radar (DWR) radial winds and reflectivity are useful for improvement of the numerical prediction of weather events like squalls. Mesoscale convective systems (MCS) are responsible for majority of the squall and hail events and related natural hazards that occur over Bangladesh and surrounding region in pre-monsoon season. In this study, DWR observations (radial winds and reflectivity) of Bangladesh Meteorological Departments (BMD) are used during 19 May 2011 squall events in order to update the initial and boundary conditions through three-dimensional variational assimilation (3DVAR) technique within the Weather Research Forecasting (WRF) modeling system. The simulated mean sea level pressure and 850 hPa wind fields from the experiments are presented in this study in order to analyze the observed and simulated features of the squall events. The model results are also compared with the Kalpana-1 images and the India Meteorological Department (IMD) predicted results. Further, the intensity of the events, generated from the simulations is also compared with the BMD predictions in order to evaluate the model performance.

Keywords: Squall; MCS; WRF modeling system; 3DVAR assimilation; DWR radial winds; reflectivity.