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Modeling the radiation balance of different urban underlying surfaces
Cui Y. P.; Liu J. Y.; Hu Y. F.; Wang J. B.; Kuang W. H.
Source PublicationChinese Science Bulletin
2012
Volume57
Issue9
Pages1046-1054
KeywordNet All-wave Radiation Parameterization Net Radiation Urban Heat Island Energy Balance Climate Change Beijing Parameterization Scheme Lumps Longwave Radiation Solar Irradiance Weather Data Energy Wave Fluxes Island Areas Clear
AbstractAn urban net all-wave radiation parameterization scheme is evaluated using annual datasets for 2010 recorded at a Beijing urban observation site. The statistical relationship between observed data and simulation data of net radiation has a correlation coefficient of 0.98 and model efficiency of 0.93. Therefore, it can be used to simulate the radiation balance of Beijing. This study analyzes the variation in the radiation balance for different underlying surfaces. To simulate radiation balance differences, we set four pure land-cover types (forest, grass, roads, and buildings). Keeping all other conditions inputted unchanged, we model the radiation balance by changing the land-cover type. The results show that the effects of different underlying surfaces on radiation differ, and that there is much upward long-wave radiation, accounting for 84.3% of the total radiation energy falling incident on the land surface. The annual averages of net radiation for the four land-cover types are in the range of 38.2-53.4 W/m(2). The net radiation of the grass surface is minimal while that of the roads surface is maximal. Additionally, with urbanization the net radiation values of common types of land-cover change, such as conversion from forest to roads, grass to roads, and grass to buildings, all have increasing trends, indicating that net radiation usually increases with urban sprawl.
Indexed BySCI
ISSN1001-6538
Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/26653
Collection历年回溯文献
Recommended Citation
GB/T 7714
Cui Y. P.,Liu J. Y.,Hu Y. F.,et al. Modeling the radiation balance of different urban underlying surfaces. 2012.
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