Cloud microphysics (CMP) is crucial for forecasting Tropical Cyclone (TC) with high-resolution atmospheric models. This study explores into the simulation of Cyclone Mandous, which originated over the Bay of Bengal and made landfall near Mahabalipuram in Tamil Nadu between December 6 and 10, 2022. To simulate and predict the behavior of this cyclone, the Advanced Research and Weather Research and Forecasting (WRF-ARW) model version 4.0 was employed with a high resolution of 3 km. Three distinct CMP schemes (Thompson, Goddard, and WDM6) were utilized alongside initial and boundary conditions sourced from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data at a resolution of 0.25°. The simulations extended over a period of 84 h, commencing at 12 UTC on December 6, 2022. A key finding of this study is that while the selection of the CMP schemes did not significantly impact the projected track of the cyclone, it notably influenced intensity predictions. Despite all simulations underestimating the cyclone’s intensity, the experiment employing the Thompson CMP scheme yielded better intensity forecast. This precision was underscored by the close resemblance between the simulated reflectivity pattern from the Thompson scheme and the observed reflectivity data obtained from Doppler Weather Radar (DWR). The study shows that the primary factors influencing intensity forecasts in explicit simulations are the representation of hydrometeor distributions and associated diabetic heating processes within the microphysics schemes. By scrutinizing the performance of various microphysics schemes, the study offers valuable insights into enhancing the accuracy of TC intensity forecasts, essential for effective disaster preparedness and mitigation efforts in vulnerable coastal regions.