The Indian subcontinent is very prone to tropical cyclones (TCs) that form in the Indian Ocean during both the pre-monsoon (April-May) and post-monsoon (October-November) seasons. These tropical cyclones bring heavy rainfall and cause widespread destruction of life and property. Consequently, accurate prediction of the cyclone track and its intensity during the landfall is very critical for the prevention of the huge loss. The Weather Research and Forecasting (WRF) model is a numerical weather prediction system, which has been used for the prediction of tropical cyclones for decades. However, there are certain factors that can improve the accuracy of the model prediction, such as accurate initial and boundary conditions and specification of the best physics parameterization schemes. The Global Precipitation Measurement (GPM) satellite carries onboard dual precipitation radar (DPR) that produces reflectivity of the earth's atmosphere. The GPM observations can be used to improve the initial conditions. However, there is a need to identify the best combination of physics parameterization schemes that can accurately reproduce the reflectivities closest to the GPM observations. Thus, the present study focuses on determining the best combination of microphysics (MP) and cumulus parameterization (CP) schemes of the WRF model for the simulation of Tropical Cyclones (TCs) in the Indian subcontinent region. The simulated cyclone track and intensity are validated against the IMD observations, and the reflectivity is validated against the GPM observations. The Kain-Fritsch cumulus scheme in combination with the Thompson microphysics scheme was found to perform better than the remaining schemes.