The present study investigates the performance of a regional numerical weather prediction model; namely, the Consortium for Small-scale Modelling (COSMO) in the prediction of the tropical cyclone (TC) trajectories for varying intensities of the storm. A total of 8 TCs formed over the Northern Indian Ocean from 2017 to 2019 are chosen for the evaluation of the COSMO model. The central pressure ( $$P_\mathrm{Central}$$ ), pressure drop ( $$\varDelta P$$ ), and maximum sustained surface wind speed (MSW) simulated by the COSMO model are validated against the concurrent observations from India Meteorological Department. The forecasted mean track errors are 95 km for a lead time of 24 h, whereas it was about 140 km for a lead time of 48 h. The mean initial positional error in identification of the storm was about 50 km. The intensity of a storm is underestimated in terms of $$\varDelta P$$ and MSW, especially for a lead time of 0–24 h, whereas the model shows a consistent overestimation for a lead time of more than 24 h. During the initial stage of a storm, when its intensity is categorized as a Deep Depression, we notice a maximum amount of uncertainty in the prediction of cyclone track. The COSMO model yields improved predictability of the tracks for storms categorized as Very Severe Cyclonic Storms. As the intensity of a storm increases from a Deep Depression to a Very Severe Cyclonic Storm, the track errors associated with model simulations tend to decrease. Results of the present study illustrate the predictability of TCs from COSMO in terms of the trajectory and intensity of the storm.