A High-Resolution Urban Land Surface Dataset for the Hong Kong-Shenzhen Area

Abstract

In recent years, with fast-developing computational capabilities, high-resolution techniques have been widely employed in atmospheric models. Thus, researchers can apply these high-resolution models to produce detailed meteorological scenarios, which empowers studies of urban-scale climatology relying on finer grid spacing. The WRF ARW/Noah LSM/UCM model is often used in urban climate research. However, the default input land surface data in urban areas is not precise enough, especially for the data describing in China. This study was pertinent to the increasing presence of ambiguous modeling practices in urban-scale climatology because of the out-of-date land surface data with insufficient fixes. Given the lack of quality-assured high-spatial-resolution land surface datasets, we produced a high-resolution urban land surface dataset including the land cover, vegetation coverage, urban morphology, artificial impervious area, and anthropogenic heat data for the Hong Kong-Shenzhen area - one of the world’s largest metropolitan areas and a unique pair of twin cities. In short, the high-resolution urban land surface dataset provided a complete set of land surface information required for high-resolution urban climate modeling in the Hong Kong-Shenzhen area, which is exceedingly rare, especially in which the data on detailed urban morphology and anthropogenic heat fluxes.