Simulation of Rainfall in Mumbai using Detailed Urban Morphology and the WRF-UACM Model

Mumbai, one of India's most densely populated cities and its economic hub, is critically vulnerable to the Indian monsoon. Frequent heavy rainfall events not only disrupt daily life but also cause significant economic and infrastructural damage. Given the city's importance, improving the accuracy of rainfall predictions is essential for effective disaster management and urban resilience planning. This study employs the multilayer Weather Research and Forecasting Urban Asymmetric Convective Model (WRF-UACM) (Bhautmage et al., 2022) for Mumbai, incorporating explicit urban physics and advanced land-use data. Land-use and land-cover (LULC) data were updated using the European Space Agency (ESA) WorldCover dataset, derived from Sentinel-1 and Sentinel-2 satellite imagery at a 10-meter resolution, resampled to a 30-arc-second grid. Urban morphological parameters, including average building height, plan area density, frontal area density, and street canyon orientation, were sourced from the WUMPOD dataset (Patel et al., 2025) at a spatial resolution of 1 km² per urban grid cell. Rainfall simulations were validated against observational data from the Mumbai Mesonet rain gauge network. The study investigates the impact of these urban morphology refinements on rainfall predictions by testing multiple microphysics parameterization schemes within the WRF-UACM framework. By integrating high-resolution urban morphology data and optimizing microphysics schemes, this research provides a robust approach to improving the accuracy of rainfall simulations for complex urban environments like Mumbai.

Keywords: WRF-UACM, Urban morphology, WUMPOD, rainfall simulation, Mumbai Mesonet observations.