Further Development of the Regional Boundary Layer Model to Study the Impacts of Greenery on the Urban Thermal Environment

Jianbo Yang * School of Atmospheric Sciences, Nanjing University, Nanjing, China

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Hongnian Liu * School of Atmospheric Sciences, Nanjing University, Nanjing, China
Jiangsu Collaborative Innovation Center for Climate Change, Nanjing, China

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Jianning Sun * School of Atmospheric Sciences, Nanjing University, Nanjing, China

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Yan Zhu Suzhou Meteorological Bureau, Suzhou, China

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Xueyuan Wang * School of Atmospheric Sciences, Nanjing University, Nanjing, China

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Zhe Xiong Key Laboratory of Climate-Environment for East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

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Weimei Jiang * School of Atmospheric Sciences, Nanjing University, Nanjing, China

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Abstract

A forest canopy model is developed and coupled into the Regional Boundary Layer Model (RBLM) to fully consider the vertical structure of tree morphology. Instead of a slab surface model formerly used to represent trees in RBLM, the new version allows refinement of the radiation budgets as well as sensible and latent heat fluxes and, hence, more precise simulation of the thermal impacts of tree plantings on urban meteorological behavior. By applying this new version of RBLM, sensitivity tests are conducted to explore the potential impacts of different greenery scenarios on the thermal environment in an eastern Chinese city, Suzhou, during hot summer days. Greenings, both tree planting and grass surfacing, are beneficial in cooling the ambient air temperature. In general, tree planting is more beneficial than grass surfacing with the same coverage. In terms of surface energy balance, with tree coverage increasing from 0% to 20%, and then to 40%, the average surface net radiation fluxes at noon (1200 LST) are 591, 512, and 421 W m−2, respectively. Correspondingly, the Bowen ratio is reduced from 8.78 to 1.20 and then to 0.43 as result of the redistribution of solar energy absorbed at the ground. The cooling effect of trees is more significant at noontime and can remarkably lower the daily maximum air temperature in urban areas. The cooling effect of urban greenery increases with its coverage. Using the study results, a tree coverage of around 40% may be a feasible and optimized urban greenery scheme.

Corresponding author address: Hongnian Liu, School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China. E-mail: liuhn@nju.edu.cn

Abstract

A forest canopy model is developed and coupled into the Regional Boundary Layer Model (RBLM) to fully consider the vertical structure of tree morphology. Instead of a slab surface model formerly used to represent trees in RBLM, the new version allows refinement of the radiation budgets as well as sensible and latent heat fluxes and, hence, more precise simulation of the thermal impacts of tree plantings on urban meteorological behavior. By applying this new version of RBLM, sensitivity tests are conducted to explore the potential impacts of different greenery scenarios on the thermal environment in an eastern Chinese city, Suzhou, during hot summer days. Greenings, both tree planting and grass surfacing, are beneficial in cooling the ambient air temperature. In general, tree planting is more beneficial than grass surfacing with the same coverage. In terms of surface energy balance, with tree coverage increasing from 0% to 20%, and then to 40%, the average surface net radiation fluxes at noon (1200 LST) are 591, 512, and 421 W m−2, respectively. Correspondingly, the Bowen ratio is reduced from 8.78 to 1.20 and then to 0.43 as result of the redistribution of solar energy absorbed at the ground. The cooling effect of trees is more significant at noontime and can remarkably lower the daily maximum air temperature in urban areas. The cooling effect of urban greenery increases with its coverage. Using the study results, a tree coverage of around 40% may be a feasible and optimized urban greenery scheme.

Corresponding author address: Hongnian Liu, School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China. E-mail: liuhn@nju.edu.cn
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