The catastrophic flood that hit the Marche region (central Italy) on 15 September 2022 has been analyzed using high-resolution Weather Research and Forecasting (WRF) model simulations. The convective rainfall event responsible for the flood was favored by the passage of warm, moist air masses that interacted with the Central Apennines. The convective cells, triggered by the rough orography of the area, formed quasi-stationary bands that caused high rainfall accumulation in limited areas. The formation of these rainbands was sustained by the interaction between the low-level flow and the local topography, which generated a persistent low-level convergence line extending downwind from Mount Amiata northeastward towards the Apennines. The observed vertical profile upstream of the orography reveals that the instability was initially suppressed by an inversion layer and was released only when the humid air arrived at low levels and eroded the inhibition. Although the model somewhat underestimates a peak of rainfall (simulating 160–180 mm versus over 400 mm observed), it correctly reproduces the position of the storm and its evolution, confirming the key role of the orography in anchoring the system and making it quasi-stationary. Furthermore, the simulations suggest that gravity waves generated by the mountains helped to sustain the vertical motion of the impinging air, and highlight the role of upper-level dynamics (passage of a jet streak). Sensitivity experiments reveal a strong dependence on initial and boundary conditions. A comparison of the control run (forced with Global Data Assimilation System (GDAS) analysis/forecasts) with a European Centre for Medium-Range Weather Forecasts (ECMWF)-driven simulation shows a strong sensitivity in the low-level dynamics. Although the large-scale upper-level forcing is almost identical, the ECMWF-driven forecast fails to reproduce the correct amount and distribution of rainfall due to a weaker surface pressure gradient, reduced moisture advection, and lower instability at the time of the event. Specifically, the simulation forced with the ECMWF data anticipates the arrival of the moist air mass, determining a timing mismatch between the low-level supply of moist air (and the consequent release of instability) and the upper-level forcing. This lack of synchronization shifts the rainfall away from the observed area.