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

Version 2 2025-01-10, 11:47
Version 1 2024-09-13, 04:12
dataset
posted on 2025-01-10, 11:47 authored by Weilin LiaoWeilin Liao, Yanman LiYanman Li, Xiaoping Liu, Yuhao WangYuhao Wang, Yangzi CheYangzi Che, Ledi ShaoLedi Shao, Guangzhao ChenGuangzhao Chen, Hua Yuan, Ning Zhang, Fei Chen

Version 2

This 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).

Furthermore this dataset incorporates 1 km resolution imprevious surface fraction data for the year 2020, derived from the Global Artificial Imprevious Area (GAIA) dataset created by Gong et al. (2020). It is provided alongside the GloUCP dataset, and allows users to conveniently define land cover/use types in WRF simulations based on the consistent imprevious fraction data. (2024.01.10)



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.


Funding

National Natural Science Foundation of China (grants U2342227 and 42225107)

National Science Fund for Distinguished Young Scholars (grant 42225107)

Fundamental Research Funds for the Central Universities, Sun Yat-sen University (grant 23lgbj014)

Young Talent Support Project of Guangzhou Association for Science and Technology (grant QT-2023-010)

Science and Technology Projects in Guangzhou (grant 2023A04J1515)

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