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

<p>The complexities of urban climate and environmental challenges have garnered significant attention in the 21st century. Numerical simulations, offering high-spatiotemporal-resolution meteorological data, are essential tools in meteorological research and atmospheric science. Accurate repres...

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Main Authors: W. Liao, Y. Li, X. Liu, Y. Wang, Y. Che, L. Shao, G. Chen, H. Yuan, N. Zhang, F. Chen
Format: Article
Language:English
Published: Copernicus Publications 2025-06-01
Series:Earth System Science Data
Online Access:https://essd.copernicus.org/articles/17/2535/2025/essd-17-2535-2025.pdf
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Summary:<p>The complexities of urban climate and environmental challenges have garnered significant attention in the 21st century. Numerical simulations, offering high-spatiotemporal-resolution meteorological data, are essential tools in meteorological research and atmospheric science. Accurate representation of urban morphology parameters is crucial for enhancing the precision of these simulations in urban areas. Despite the availability of urban canopy parameter (UCP) data for 44 major cities in the United States and 60 in China for the Weather Research and Forecasting (WRF) model, a comprehensive global dataset representing urban morphology remains absent. This study addresses this gap by leveraging existing global three-dimensional vector data of buildings, including footprints and heights, to compile a global 1 km spatially continuous UCP (GloUCP) dataset for the WRF model. Our findings indicate that GloUCP not only surpasses existing datasets in accuracy but also provides superior spatial coverage. In key urban agglomerations such as Beijing–Tianjin–Hebei, the Yangtze River Delta, and the Guangdong–Hong Kong–Macau Greater Bay Area, GloUCP offers detailed and reliable urban morphological information that closely aligns with reference datasets, outperforming other available sources. Similarly, in United States cities like Seattle, San Francisco, and Philadelphia, GloUCP consistently achieves lower RMSE values and higher correlation coefficients, demonstrating its robustness in modeling diverse urban environments. Furthermore, GloUCP's capability to effectively capture the vertical distribution of buildings, particularly in high-rise areas, highlights its utility in urban climate modeling and related applications. As UCPs are pivotal in regulating atmospheric responses to urbanization, the availability of this globally consistent urban description is a crucial prerequisite for advancing model development and informing climate-sensitive urban planning policies. The GloUCP dataset, converted to WRF binary file format, is available for download at <a href="https://doi.org/10.6084/m9.figshare.27011491">https://doi.org/10.6084/m9.figshare.27011491</a> (Liao et al., 2025).</p>
ISSN:1866-3508
1866-3516