Assimilation of satellite and radar observations in a convection-resolving Observing System Simulation Experiment

For this study, data assimilation tests employing different combinations of satellite, radar, and conventional observations were performed for a severe weather event that occurred across the central U.S. during June 2005. Examples of simulated data include hyperspectral sounder temperature and humidity retrievals, GOES-R ABI brightness temperatures, and WSR-88D Doppler radar reflectivity and radial velocity. Assimilating these datasets into convection permitting numerical weather prediction (NWP) models poses many challenges due to observation uncertainties and correlations to model state variables. The study used an Observing System Simulation Experiment (OSSE) framework that provides a useful means to investigate the impact of these observations in a controlled manner. Observations generated using output from an idealized ARPS model simulation were assimilated into a 2-km resolution grid using the Data Assimilation Research Testbed (DART) ensemble Kalman filter (EnKF) system combined with the Weather Research Forecast (WRF) model. Preliminary results documenting the relative benefit of each observation type at convection-resolving scales will be shown.