Urban Climate Modeling

To tackle environmental challenges arising from cities, accurately modeling the physical urban land surface processes and land-atmosphere interactions is of critical importance. Our group has developed urban hydrological models and incorporated them into the urban canopy model coupled with the Weather Research and Forecasting model. We are continuously implementing important features of the complex urban environment into climate models to improve their predictability and reliability.

Heat Island Mitigation

Cities, particularly urban cores, are significantly warmer than their rural surroundings, due to land use land cover changes and human activities. Our group has investigated the effectiveness and efficiency of different strategies for mitigating urban heat islands at a variety of scales, including the use of engineering materials and urban green infrastructure elements. We are investigating how latest technology and innovation contribute to mitigate heat islands and their adverse impacts, and reshape the strategic urban planning towards smart cities.

Energy-water Nexus under Climate Change

Water and energy are precious resources needed for the development of cities. Global climate change poses strict constrains on these resources and make cities unprecedentedly vulnerable. The complex relationship among economic, environmental, and social components in the development of cities requires an intricate balance between energy and water resources, and can exert profound impacts on regional climate beyond the footprint of metropoles. We are studying the interactions between local built environment and global climate change.

Heat and pollution dispersion in Cities

Waste heat and aerosol released by anthropogenic activities in cities have profound impacts on urban air quality and thermal comfort. Turbulent transport of heat and pollutants over heterogeneous built terrains remains a challenging research area. Large-eddy simulation (LES) captures all the scales of motion that are larger than the grid size and parameterizes the effect of the unresolved, sub-grid scales of turbulence. We are adopting LES to explore dynamics of urban flow with high-resolution geographical data (e.g., city geometry, traffic information) in cities.