Characteristics of the Mediterranean Cyclone IANOS in Convection‐Permitting Simulations: Unraveling Model Sensitivity to Microphysics and Cumulus Parameterization

Abstract This study quantified the relative impact of microphysics parameterization (MP) and cumulus parameterization (CP) schemes on storm prediction using a non‐hydrostatic weather research and forecasting model for an intense Medicane: IANOS. All the simulations agreed with the main observed characteristics of this storm, with some discrepancies in magnitude and location, which vary with CP and MP schemes. These discrepancies were larger during the mature phase of the storm. In the CP‐on simulations, the non‐scale aware Kain–Fritsch (KF) scheme typically resulted in higher precipitation, while the Betts‐Miller‐Janjic (BMJ) scheme led to lower precipitation compared to the CP‐off simulations (C0). The tendency of the KF scheme to consume available convective potential energy at a relatively high rate (i.e., short time scale) resulted in high mass fluxes and latent heat release, leading to strengthened convective activity and, hence, precipitation. The multi‐scale aware (MSKF) substantially reduces the precipitation compared to KF due to the reduced contribution of convective scale precipitation. It also modulates the spatial structure precipitation compared to KF, especially light precipitation over the outer bands, and the contribution of grid‐scale precipitation to total precipitation. KF shows the lowest contribution, around 50%, whereas BMJ exhibits a slightly higher contribution, and MSKF versions nearly reach 100%, making it closer to CP‐off. The improved performance in MSKF compared to KF highlights the importance of MSKF convection parameterization for gray zone (~1–4 km) simulation. The persistent discrepancy in landfall location in CP‐on and CP‐off simulation underscored the need of further investigating other physics parameterizations and dynamical mechanisms.