Abstract
The Weather Research and Forecasting (WRF) model, configured with a single-layer urban canopy model, was employed to investigate the influence of urbanization on boundary layer meteorological parameters during a long-lasting heat wave. This study was conducted over Nanjing city, East China, from 26 July to 4 August 2010. The impacts of urban expansion and anthropogenic heat (AH) release were simulated to quantify their effects on 2-m temperature, 2-m water vapor mixing ratio, and 10-m wind speed and heat stress index. Urban sprawl increased the daily 2-m temperature in urbanized areas by around 1.6 °C and decreased the urban diurnal temperature range (DTR) by 1.24 °C. The contribution of AH release to the atmospheric warming was nearly 22 %, but AH had little influence on the DTR. The urban regional mean surface wind speed decreased by about 0.4 m s−1, and this decrease was successfully simulated from the surface to 300 m. The influence of urbanization on 2-m water vapor mixing ratio was significant over highly urbanized areas with a decrease of 1.1–1.8 g kg−1. With increased urbanization ratio, the duration of the inversion layer was about 4 h shorter, and the lower atmospheric layer was less stable. Urban heat island (UHI) intensity was significantly enhanced when synthesizing both urban sprawl and AH release and the daily mean UHI intensity increased by 0.74 °C. Urbanization increased the time under extreme heat stress (about 40 %) and worsened the living environment in urban areas.
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Acknowledgments
This work is supported by the “Strategic Priority Research Program (B)” of the Chinese Academy of Sciences (XDB05030105, XDB05030102, XDB05030103), the National Basic Research Program of China (2014CB953802), the National Natural Science Foundation of China (40105012) and the Russian Scientific Fund under grant 14-47-00049. The authors thank the reviewer for valuable comments and suggestions.
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Chen, L., Zhang, M. & Wang, Y. Model analysis of urbanization impacts on boundary layer meteorology under hot weather conditions: a case study of Nanjing, China. Theor Appl Climatol 125, 713–728 (2016). https://doi.org/10.1007/s00704-015-1535-6
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DOI: https://doi.org/10.1007/s00704-015-1535-6