The all-sky Infrared (IR) radiance assimilation from geostationary satellites has been a prime research area in the numerical weather prediction (NWP) modeling. In this study, the variational data assimilation system of the weather research and forecasting (WRF) model has been customized to assimilate all-sky assimilation of water vapour (WV) radiance from Imager onboard two geostationary Indian National Satellites (INSAT-3D and INSAT-3DR). This study also integrated different hydrometeors (like cloud, rain, ice, snow and graupel) as control variables in the WRF variation assimilation system. To do this, parallel experiments were performed by carrying out model simulations with and without INSAT WV radiance assimilation during July 2018. Results of these simulations suggested that the WRF model analyses for all-sky assimilation are closer to the brightness temperature (T­_B) of channel-1 (183.31 ± 0.2 GHz) of SAPHIR (Sondeur Atmosphérique du Profil d’Humidité Intertropicale par Radiométrie) sensor onboard Megha-Tropiques satellite and channel-3 (183.31 ± 1.0 GHz) of MHS (Microwave Humidity Sounder) sensor onboard National Oceanic and Atmospheric Administration (NOAA-18/19) and Meteorological Operational Satellite (MetOp-A/B/C) satellites. Furthermore, noteworthy changes are noticed in hydrometeors analyses with all-sky assimilation and the number of assimilated observations are increased significantly (around 2.5 times). The short-range predictions from all-sky assimilation runs revealed notable positive impact as compared to clear-sky assimilation runs when verified with SAPHIR and MHS T­_B, and NCEP (National Centers for Environmental Prediction) final analysis.