Simultaneous Assimilation of WSR-88D and GOES-16 Observations to Improve Ensemble Forecasts of Convection Initiation

Accurate predictions for the location and timing of convection initiation (CI) remain a challenge in convection allowing models (CAMs). Given the many processes that influence CI, ranging from large-scale forcing for upward motion to planetary boundary layer (PBL) thermals, it is difficult to accurately observe the main ingredients necessary for CI - low-level moisture, instability, and lift. Many of the processes that influence CI occur within the PBL, the structure and evolution of which CAMs often struggle to predict. In order to better observe the ingredients that influence CI, we use data from both the national network of WSR-88Ds as well as the GOES-16. The WSR-88Ds provide observations of PBL depth and clear-air radial wind velocities, while the GOES-16 provides brightness temperature observations. Together, the WSR-88D and GOES-16 observations provide complimentary information to better define the ingredients necessary for CI. For the CAM ensemble forecasts, we employ the Advanced Research Weather Research and Forecasting (WRF-ARW) model using the High-Resolution Rapid Refresh (HRRR) configuration. Observations are assimilated using the Gridpoint Statistical Interpolation (GSI)-based hybrid Ensemble Kalman filter (EnKF) system of the National Centers for Environmental Prediction (NCEP) into a 40-member CAM ensemble. Ensemble experiments with radar, satellite, and conventional surface observations will be assimilated both separately and jointly and results compared.