The present study evaluated the performance of the Weather Research and Forecasting (WRF) model in the forecast of a very severe cyclonic storm (VSCS) Vardah that developed over the Bay of Bengal (BoB) and make landfall over the Tamil Nadu coast on 12 December 2016. The study examined the impact of microwave humidity sounder (MHS) satellite radiance data assimilation to forecast of structure, intensity and rainfall of Vardah cyclone near to the coast using two different land surface model (LSM; Noah and Noah-MP). The mean track error is about 33 and 38 km with data assimilation using Noah and Noah-MP LSM respectively and this error is about 41 km in without data assimilation using Noah and Noah-MP LSM. The predicted intensity of the storm in terms of the maximum surface wind is also slightly better predicted in data assimilation experiment with Noah LSM, this is due to the improved initial condition. Accumulated rainfall and the maximum reflectivity in terms of spatial distribution and magnitude of the VSCS Vardah is well simulated in all the experiments but slightly better in data assimilation experiments. Hovmoller diagram is also presented to see the shifting pattern of accumulated rainfall across the region during simulation period.