GloUCP: A global 1 km spatially continuous urban canopy parameters for the WRF model.

Version 3 Global Urban Canopy Parameters DatasetThis dataset provides Global Urban Canopy Parameters (GloUCP) at a 1-km resolution for approximately the year 2020, which is derived from the global three-dimensional building footprint (3D-GloBFP) dataset generated by Che et al. (2024). The data is divided into 288 tiles, each stored in a compressed file, covering 15°×15° geographic regions. The corresponding geographic area for each compressed file can be identified from its filename (e.g., GloUCP-X105_119.Y15_29.zip contains data for the region spanning 105°E-120°E and 15°N-30°N, while GloUCP-X-180_-166.Y-60_-46.zip corresponds to the region between 180°W-165°W and 60°S-45°S).Each compressed file includes 255 geogrid binary format files, with each file representing a 1°×1° region. The specific geographic coverage of each file can be determined by consulting the index file and the file names, as explained in the WRF (Weather Research and Forecasting) User Guide.(e.g., 35161-35280.14281-14400 contains data for the region spanning 113°E-114°E and 29°N-30°N).Global 1km Resolution Impervious Surface Fraction DataIn addition, this dataset provides two forms of impervious surface data for the year 2020, both derived from the Global Artificial Impervious Area (GAIA) dataset developed by Gong et al. (2020). The first is the impervious surface fraction data, a continuous variable at 1 km spatial resolution, representing the proportion of impervious surfaces within each grid cell, with values ranging from 0 to 1. The second is the impervious surface mask data, a binary classification derived from the fraction data by applying a threshold of 0.01, where a value of 1 denotes impervious surfaces and 0 denotes non-impervious surfaces. These datasets are provided alongside the GloUCP dataset and can support consistent land cover/use classification in WRF simulations.APP: GloUCP ProcessorTo streamline data retrieval and facilitate dataset download, we developed a dedicated GloUCP Data Application. Users may specify the latitude and longitude bounds of their study area (e.g., 110°E–115°E, 25°N–30°N), based on which the application will automatically identify, retrieve, and merge the corresponding tiles along with the index.References:Che, Y., Li, X., Liu, X.*, Wang, Y., Liao, W., Zheng, X., Zhang, X., Xu, X., Shi, Q., Zhu, J., Yuan, H., and Dai, Y. 2024: 3D-GloBFP: the first global three-dimensional building footprint dataset, Earth System Science Data, 16, 5357–5374. doi: 10.5194/essd-16-5357-2024.Gong, P.*, Li, X.C., Wang, J.*, Bai, Y., Chen, B., Hu, T.Y., Liu, X.P., Xu, B., Yang, J., Zhang, W., & Zhou, Y.Y. 2020. Annual maps of global artificial impervious areas (GAIA) between 1985 and 2018. Remote Sensing of Environment, 236, 111510. doi: 10.1016/j.rse.2019.111510.