By coupling physics-based simulations and statistical modelling techniques, this project introduces a probabilistic, progressive, and accuracy-adaptive modelling approach for faster spatially-resolved OTC estimation that is scalable to large urban neighborhoods. This is achieved through the integration of spatially informed wind distributions. The approach is tested against state-of-the-art computational fluid dynamic simulations for a 3 km2 sample area of San Francisco’s financial district, showing strong agreement between the simulations and the estimation, particularly for diurnal and seasonal results.