WRF-Urban Model Driven By Fine-Scale Urban Canopy Parameters in Mega-City China

The fast urbanization in Guangzhou Metro area (with population more than 10 million) has significantly modified local and regional meteorological conditions. As one of the largest industrialized regions in China, Guangzhou has also experienced increased levels of air pollutants. However the current trend of population increase and urban expansion is expected to continue in the future. It is therefore imperative to understand and project effects of urbanization on weather, regional climate and air quality using regional models such as the Weather Research and Forecasting (WRF) model coupled to urban canopy models. However, fine-scale gridded urban canopy parameters (UCPs) are needed to drive the model but yet difficult to obtain in cities where the detailed urban morphological data do not exist. In this study, we developed a new approach to derive UCP database of Guangzhou from Google-earth imagery, which are freely available at high resolution (0.61 meter) and frequently updated. Two images at the same place with different view angles of buildings were used to identify the building span and height and to calculate urban morphology parameters (e.g., mean building height, building plan area fraction, building plan area density). Frontal area index was calculated under 8 wind directions with 45-degree intervals. The sky view factor was calculated with 32 slices number of 1-m resolution and no limit rang of extended distance. Special efforts were undertaken to ensure consistency between various datasets of UCPs, land-use and land-cover (LULC), urban fraction, and plan area fraction in WRF. Numerous high-resolution WRF numerical experiments were conducted using various sources of LULC and UCP data to reveal the impacts of new UCPs on regional weather and air quality.