<p>This study examines the impact of land surface processes on the initiation and development of atmospheric convection during a severe pre-monsoon thunderstorm event that occurred over eastern India on March 17, 2019. Utilising the Weather Research and Forecasting (WRF) model at a high spatial resolution of 1 km × 1 km, we examined the performance of two land surface schemes Noah and Noah-MP in simulating key land–atmosphere interactions, surface energy fluxes, and precipitation. Results indicated that soil moisture plays a pivotal role in modulating surface energy partitioning and near-surface atmospheric conditions. The Noah scheme, with its enhanced representation of soil moisture, produced higher latent heat flux and near-surface humidity, along with lower land surface temperatures. These conditions facilitated more realistic convection and rainfall, closely aligning with observations. On the other hand, the dry bias of Noah-MP led to higher surface temperatures, elevated sensible heat flux, and a deeper planetary boundary layer. An overall increase in instability, accompanied by a drop in evaporative cooling and relative humidity, which suppressed convection, resulted in an underestimated intensity of the storm and precipitation. An analysis of error metrics, such as bias, MAE, and RMSE, reveals that the Noah scheme generally surpassed Noah-MP in performance across the assessed land surface variables. Specifically, for soil temperature, Noah consistently achieved lower MAE and RMSE values at both Alipore (4.29 and 5.53) and Jamshedpur (5.11 and 6.66) compared to Noah-MP. A similar enhancement was observed in sensible heat flux, where Noah significantly reduced the RMSE to 105.42 W m⁻², much lower than the 159.24 W m⁻² recorded with Noah-MP at Alipore. Regarding latent heat flux, Noah-MP showed the greatest underestimation, whereas Noah demonstrated a relatively smaller bias (−132.78 W m⁻²) and RMSE (215.86 W m⁻²), indicating a generally improved depiction of surface energy distribution. It also more accurately captured the diurnal evolution of the boundary layer, particularly its post-convection descent. This study underscores the sensitivity of convective storm simulations to land surface parameterisations, emphasising the importance of accurate soil moisture and energy flux representation in high-resolution weather modelling. Improved storm forecasts can enhance early warning systems, reducing economic losses and safeguarding vulnerable communities.</p>