Assimilating infrared brightness temperature (BT) from the water vapor sensitive channels of the GOES-16 Advanced Baseline Imager (ABI) has been shown by past studies to improve the analysis and prediction of severe weather events. These studies are limited to using a single microphysics scheme. Microphysics schemes are expected to affect bow echo dynamics and BT. Therefore, this study aims to investigate how assimilating GOES-16 ABI infrared BT with different microphysics schemes affects the analysis and prediction of the 3 May 2020 bow echo case. The Gridpoint Statistical Interpolation based Ensemble Kalman Filter (GSI-EnKF) system and Weather Research and Forecasting (WRF) model are utilized to conduct data assimilation (DA) experiments using Thompson, WDM6, NSSL, and Morrison microphysics schemes. Correlation structures between BT and model state variables indicate that assimilating infrared BT can adjust bowing MCS dynamics via latent cooling and the rear inflow jet. Such corrections during DA cycling enhance the rear inflow jet and bow echo size, primarily for microphysics schemes featuring faster hydrometeor fall velocity and stronger latent cooling. The improved analyses lead to better forecasts of the bow echo’s shape, size, timing of the bowing process, and wind speeds. Substituting a larger microphysics-dependent effective radius for a constant default value increases prior BT, the magnitude of BT innovations, and accumulated impact on the rear inflow jet, especially for the WDM6 and Morrison schemes. In the subsequent forecasts, incorporating microphysics-dependent effective radius further improves the experiment using the Morrison scheme but degrades it when using the WDM6 scheme.