4.7 Article

A new perspective on evaluating high-resolution urban climate simulation with urban canopy parameters

Journal

URBAN CLIMATE
Volume 38, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.uclim.2021.100919

Keywords

Urban canopy parameter; Model evaluation; Wind speed simulation; Urban canopy model

Funding

  1. Hong Kong Research Grants Council [16204220]

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The study found that urban climate models have stable performances in summer rainfall events, but significant changes in winter wind conditions. Urban canopy parameters have limited impact on air temperature simulations, but significant influence on wind speed simulations.
The 'state-of-the-art' urban climate models have not been evaluated against dense meteorological networks under various weather conditions. In this study, we conducted high-resolution urban climate simulations in Beijing and investigated the relationship between their performances and urban canopy parameters (UCPs). The latest version of single-layer (UCM) and multi-layer (BEP) urban canopy models were tested separately. Results show that model performances are insensitive to rainfall events in summer, but change significantly with wind conditions in winter. Inclusion of UCPs has a limited impact on air temperature simulations. In terms of wind speed simulations, consistent overestimations by UCM and BEP are found in both summer and winter. The overestimation by BEP reduces significantly when UCPs are available, especially on windy days in winter. On the other hand, performance of UCM can degrade over urban areas with canopy parameters. Wind speed biases are found to correlate significantly with UCPs. The accuracy of wind speed simulations by UCM and BEP increases with urban fraction and building surface ratio. This indicates poor model performances over low-density urban areas, which requires enhanced aerodynamic parameterizations to better account for UCPs. This study reveals the limitation of current urban climate simulations and provides guidance for future model developments.

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