A Realistic Approach to Urban Climate Mitigation with WRF: Modeling Local and Practical Solutions

Urban climate mitigation strategies, such as increasing vegetation and enhancing surface reflectivity, are widely studied with numerical weather models. However, mesoscale models like the Weather Research and Forecasting (WRF) model typically apply these strategies across all urban areas within the domain, which is neither practical nor reflective of real-world implementations. In reality, mitigation efforts are usually local, incremental, spatially disjointed, or targeted toward the most vulnerable areas. This highlights the need for more flexible modeling approaches that better represent the scale at which urban climate mitigation occurs.

In this study, we introduce a novel method for implementing local urban climate mitigation strategies in WRF. Our approach modifies land use classifications and urban parameterization tables, allowing mitigation strategies to be applied at individual gridcells rather than across the entire domain. This enables more precise testing of interventions and aligns simulations with how cities actually deploy mitigation efforts.

We demonstrate this method in a series of WRF simulations over Baltimore, Maryland, examining the effects of urban greening and surface albedo modifications under different spatial scenarios, including targeted mitigation within select neighborhoods, implementation in low-income communities, and focused interventions in the city's warmest areas. Results highlight how the spatial configuration of mitigation strategies influences urban temperatures and atmospheric conditions. By enabling neighborhood-scale intervention testing, this method bridges the gap between mesoscale climate modeling and real-world urban planning.