Radar data assimilation for the prediction of Front Range convection

Techniques have been tested for assimilating Doppler radar radial winds and reflectivity into the Real-Time Four-Dimensional Data Assimilation and forecasting system (RTFDDA) developed jointly by NCAR and ATEC (Army Test and Evaluation Command). The RTFDDA is a WRF-based numerical modeling system, typically run on multiple domains with a high-resolution inner domain at 1–3 km grid spacing and with 3-hourly or 6-hourly cycling schemes. The capability for assimilation of radar data has been designed to improve RTFDDA in creating dynamically and cloud/precipitation “spun-up” initial conditions such that very short-term convection forecasts can be improved. A hybrid method for radar data assimilation has been adopted, in which hourly radar data analysis is first obtained using the WRFDA 3DVAR, and hydrometeor and latent heat adjustment techniques. The radar analysis is then blended into the model using the grid-nudging method.

In this study, extensive numerical experiments are performed to evaluate the impact of radar data assimilation on 0–12 h RTFDDA forecasts. The tests are conducted for the Rocky Mountains Front Range area. The capability of WRFDA 3DVAR and latent heat adjustment to retrieve convective features from radial velocity and reflectivity data in the initial conditions and to improve the forecast is examined through case studies. Several alternative configurations of 3DVAR and latent heating adjustment are tested. Impact of the radar data on the forecasts of precipitation and surface meteorological fields will be presented.