Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI 3DVar, EnKF, and Hybrid En3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case

Capabilities to assimilate Geostationary Operational Environmental Satellite “R-series” (GOES-R) Geostationary Lightning Mapper (GLM) flash extent density (FED) data within the operational Gridpoint Statistical Interpolation ensemble Kalman filter (GSI-EnKF) framework were previously developed and tested with a mesoscale convective system (MCS) case. In this study, such capabilities are further developed to assimilate GOES GLM FED data within the GSI ensemble-variational (EnVar) hybrid data assimilation (DA) framework. The results of assimilating the GLM FED data using 3DVar, and pure En3DVar (PEn3DVar, using 100