Urban Climate Simulation in the Metropolitan Area of Buenos Aires (SUrAMBA): Study on the vertical influence of urban areas in km resolution urban simulations.

Urbanization and growing city populations amplify the risks of extreme weather events, a vulnerability worsened by climate change. Although climate models have advanced to better represent urban areas, many of their parameters, processes, and results remain insufficiently understood. As these models become more complex, it is crucial to focus on addressing key processes and enhancing climate monitoring before prioritizing further complexity, to effectively contribute to local decision-making. A previous study conducted in the Metropolitan Area of Buenos Aires (AMBA) analyzed the sensitivity of the WRF model to changes in urban canopy parameters (UCP). Results from a heat wave event showed that, while the model exhibited sensitivity in surface variables to morphological and anthropogenic parameters, the biggest changes come from the selection of the scheme itself rather than its configuration. However, further evaluation of the urban canopy schemes and UCP changes is needed to better understand the vertical influence of urban areas in urban climate simulations. Additionally, the definition of planetary boundary layer height (PBLh) requires deeper analysis, as it is highly dependent on the surface layer representation within the models. This study explores these issues using the WRF model integrated with a refined Local Climate Zone (LCZ) and three urban canopy schemes to simulate extreme weather events in the AMBA region. 

This study also incorporates some results from multiple years of high-resolution (1 km) urban climate simulations over AMBA with the WRF model to provide broader insights into urban climate behavior and modeling approaches. Initial results show how the presence of urbanization has a strong impact on the circulation at local scale. These additional findings offer context for understanding the dynamics of urban environments and enhancing future modeling efforts, and help to explore alternatives for a collaborative effort with local agencies to develop adaptation strategies.