Development of Radar and GOES-R Lightning Data Assimilation Capabilities in JEDI LETKF and En3DVar and Realtime Testing and Evaluation during Hydrometeorology Testbed Summer Rainfall Experiment

The Joint Effort for Data assimilation Integration (JEDI) is a new data assimilation (DA) system being developed for use by operational forecasting systems of the U.S. National Weather Service from global to regional scales. Towards this goal, the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma implemented capabilities to directly assimilate high-resolution Doppler radar data and flash extent density (FED) data of the GOES-R Geostationary Lightning Mapper (GLM) within the local ensemble transform Kalman filter (LETKF) and the ensemble-variational (EnVar) DA components of the JEDI. Such capabilities are first evaluated with simple experiments including single-observation experiments, and the effects of covariance localization within the observation-space v.s. model-space localization algorithms with observation operators involving spatial averaging are investigated. The LETKF DA capabilities are then tested in realtime during the Hydrometeorology Testbed (HMT) Flash Flood and Intense Rainfall (FFaIR) Forecast Experiment in summer 2024 for ~30 cases, with JEDI coupled with FV3-based prototype Rapid Refresh Forecasting System version 1 (RRFSv1) that has a 3-km domain covering the continental U.S. (CONUS). The impact of assimilating WSR-88D radar reflectivity data and/or GLM FED lightning data in addition to conventional data on precipitation forecasts are evaluated systematically. Some technical aspects of the DA implementation and the testing results will be presented at the conference.