The sensitivity of the simulated tropical cyclone (TC) intensity and tracks to the different ocean mixed‐layer depth (MLD) initializations is studied using coupled weather research and forecasting (WRF) and ocean mixed‐layer (OML) models. Four sets of numerical experiments are conducted for two TCs formed during the pre‐ and post‐monsoon. In the control run (CONTROL), the WRF model is initialized without coupling. In the second experiment, the WRF‐OML model is initialized by prescribing the MLD as a constant depth of 50 m (MLD‐CONST). In the third experiment, the spatial varying MLD obtained from the formulation of depth of the isothermal layer (MLD‐TEMP) is used. For the fourth experiment (MLD‐DENS), the model is initialized with the density‐based MLD obtained from ARMOR‐3D data. The results indicate that the CONTROL exhibits an early intensification phase with a faster translation movement, leading to early landfall and the production of large track deviations. The coupled OML simulations captured the deepening phase close to the observed estimates, resulting in the reduction of errors in both the vector and along the tracks of the storm. The initialization of the different estimates of the MLD in the WRF‐OML shows that the TC intensity and translation speed are sensitive to the initial representation of the MLD for the post‐monsoon storm. The gradual improvements in the intensity and translation speed of the storm with the realistic representation of the OML are mainly due to the storm‐induced cooling, which in turn alters the simulated enthalpy fluxes supplied to the TC, leading to the better representation of secondary circulation and the rapid intensification of the storm.

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The intensity and frequency variability of cyclones in the North Indian Ocean (NIO) have been amplified over the last few decades. The number of very severe cyclonic storms (VSCSs) over the North Indian Ocean has increased over recent decades. “Phailin”, an extreme severe cyclonic storm (ESCS), occurred during 8–13 October 2013 over the Bay of Bengal and made landfall near the Gopalpur coast of Odisha at 12 UTC on 12 October. It caused severe damage here, as well as in the coastal Odisha, Andhra Pradesh, and adjoining regions due to strong wind gusts (~115 knot/h), heavy precipitation, and devastating storm surges. The fidelity of the WRF model in simulating the track and intensity of tropical cyclones depends on different cloud microphysical parameterization schemes. Thus, four sensitivity simulations were conducted for Phailin using double-moment and single-moment microphysical (MP) parameterization schemes. The experiments were conducted to quantify and characterize the performance of such MP schemes for Phailin. The simulations were performed by the advanced weather research and forecasting (WRF-ARW) model. The model has two interactive domains covering the entire Bay of Bengal and adjoining coastal Odisha on 25 km and 8.333 km resolutions. Milbrandt–Yau (MY) double-moment and WRF single-moment microphysical schemes, with 6, 5, and 3 classes of hydrometeors, i.e., WSM6, WSM5, and WSM3, were used for the simulation. Experiments for Phailin were conducted for 126 h, starting from 00 UTC 08 October to 06 UTC 13 October 2013. It was found that the track, intensity, and structure of Phailin are highly sensitive to the different microphysical parameterization schemes. Further, the precipitation and cloud distribution were studied during the ESCS stage of Phailin. The microphysics schemes (MY, WSM3, WSM5, WSM6), along with Grell–Devenyi ensemble convection scheme predicted landfall of Phailin over the Odisha coast with significant track errors. Supply of moisture remains a more crucial component than SST and wind shear for rapid intensification of the Phailin 12 h before landfall over the Bay of Bengal. Finally, the comparison of cyclone formation between two decades 2001–2010 and 2011–2020 over the Bay of Bengal inferred that the increased numbers of VSCS are attributed to the supply of abundant moisture at low levels in the recent decade 2011–2020.