Impact of cloud microphysical factors on the track prediction of recurved tropical cyclone <i>Vayu</i> (2019) in a convective‐scale model

Abstract Tropical cyclone (TC) Vayu (2019) was unusual because of its sudden recurvature west‐northwestwards skirting the coast of Gujarat state of India, which led to the majority of operational models giving a false warning of landfall. The present work demonstrates how the track forecast was improved by using a double‐moment microphysics scheme, namely Cloud–AeroSol Interacting Microphysics (CASIM) and a Bimodal (BM) cloud fraction scheme. The model with CASIM and BM exhibited improved skill over the previous operational version of the model in predicting the recurved cyclonic track with a mean direct position error (DPE) of about 50–100 km smaller with respect to the latter for up to three days lead time. This is attributed to the ice production processes in CASIM and the vertical distribution of liquid water content which is improved by resolving turbulence in mixed‐phase clouds by BM, and their contribution to the production and fall speeds of ice particles. The potential vorticity tendency associated with the vertical distribution of the resultant latent heating modified the beta drift effect, driving the TC recurvature as observed. Hence, both the specific processes behind the origin of cloud microspecies and the altitudes at which they form play a critical role in driving the dynamics of the deep tropical convective system, and consequently, the motion of TCs.