Executive Summary : | Urbanization in India contributes to economic growth but also creates local weather and climate issues, such as rising air temperatures, sensible heat fluxes, air pollution levels, and altered wind patterns. This leads to more convective potential energy available, contributing to extreme weather events (EWEs). Rapid urbanization in India makes urban areas more vulnerable to more EWEs. To address these challenges, higher-resolution dynamical mesoscale models (DMM) are needed, especially in urban regions due to their complex topography. Land-use and land-cover (LULC) data play a major role in EWE prediction, but current LULC data is outdated and lacks information on building heights, densities, industrial areas, and other local urban infrastructure. The Local Climate Zone (LCZ) tool, developed by stewart and Oke (2012), enables the incorporation of building heights, densities, industrial, and local surface infrastructure data into the WRF model. However, studies have not investigated the role of each urban class, such as compact and open high-, mid-, and open-rise buildings, on HREs and HWs in Indian cities. This study aims to explore the incorporation of the WUDAPT LCZ urban classification into the WRF model for predicting EWEs and examine the role of various types of urban classes on the weather system over Hyderabad, Telangana. |