典型文献
Improving the WRF/urban modeling system in China by developing a national urban dataset
文献摘要：
Accurate modeling of urban climate is essential to predict potential environmental risks in cities.Urban datasets,such as urban land use and urban canopy parameters(UCPs),are key input data for urban cli-mate models and largely affect their performance.However,access to reliable urban datasets is a chal-lenge,especially in fast urbanizing countries.In this study,we developed a high-resolution national urban dataset in China(NUDC)for the WRF/urban modeling system and evaluated its effect on urban cli-mate modeling.Specifically,an optimization method based on building morphology was proposed to classify urban land use types.The key UCPs,including building height and width,street width,surface imperviousness,and anthropogenic heat flux,were calculated for both single-layer Urban Canopy Model(UCM)and multiple-layer Building Energy Parameterization(BEP).The results show that the derived morphological-based urban land use classification could better reflect the urban characteristics,compared to the socioeconomic-function-based classification.The UCPs varied largely in spatial within and across the cities.The integration of the developed urban land use and UCPs datasets significantly improved the representation of urban canopy characteristics,contributing to a more accurate modeling of near-surface air temperature,humidity,and wind in urban areas.The UCM performed better in the modeling of air temperature and humidity,while the BEP performed better in the modeling of wind speed.The newly developed NUDC can advance the study of urban climate and improve the prediction of potential urban environmental risks in China.
文献关键词：
中图分类号：
作者姓名：
Huidong Li;Fenghui Yuan;Lidu Shen;Yage Liu;Zhonghua Zheng;Xu Zhou
作者机构：
CAS Key Laboratory of Forest Ecology and Management,Institute of Applied Ecology,Chinese Academy of Sciences,Shenyang 110016,China;Lamont-Doherty Earth Observatory of Columbia University,Palisades,NY 10964.United States;National Tibetan Plateau Data Centre,Institute of Tibetan Plateau Research,Chinese Academy of Sciences,Beijing 100101,China
文献出处：
引用格式：
[1]Huidong Li;Fenghui Yuan;Lidu Shen;Yage Liu;Zhonghua Zheng;Xu Zhou-.Improving the WRF/urban modeling system in China by developing a national urban dataset)[J].地学前缘（英文版）,2022(04):75-88
A类：
NUDC,imperviousness
B类：
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AB值：
0.482088
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