Study of thermal environment in Jingjintang urban agglomeration based on WRF model and Landsat data

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Huang, Q.N.^1,2 ; Cao, Z.Q.^1,3,4 ; Guo, H.D.^5 ; Xi, X.H.^5 ; Li, X.W.^5

National Satellite Meteorological Center, No. 46, Zhongguancun South Street Haidian District, Beijing, China^1

Key Lab of Radiometric Calibration and Validation for Environment Satellite, CMA, No. 46, Zhongguancun South Street Haidian District, Beijing, China^2

Institute of Atmospheric Physics, CAS, Chao Yang District, Beijing, China^3

Graduate University of Chinese Academy of Sciences, Yuquan Road, Beijing, China^4

Institute of Remote Sensing and Digital Earth (RADI), Chinese Academy of Sciences (CAS), No.9 Dengzhuang South Road Haidian District, Beijing, China^5

关键词: Environmental issues;    High temperature process;    Land surface temperature;    Remote sensing satellites;    Thermal environment monitoring;    Urban impervious surfaces;    Urban thermal environment;    Weather research and forecasting models;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012158/pdf
DOI  :  10.1088/1755-1315/17/1/012158

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

In recent decades, unprecedented urban expansion has taken place in developing countries resulting in the emergence of megacities or urban agglomeration. It has been highly concerned by many countries about a variety of urban environmental issues such as greenhouse gas emissions and urban heat island phenomenon associated with urbanization. Generally, thermal environment is monitored by remote sensing satellite data. This method is usually limited by weather and repeated cycle. Another approach is relied on numerical simulation based on models. In the study, these two means are combined to study the thermal environment of Jingjintang urban agglomeration. The high temperature processes of the study area in 2009 and 1990s are simulated by using WRF (the Weather Research and Forecasting Model) coupled with UCM (Urban Canopy Model) and the urban impervious surface estimated from Landsat-5 TM data using support vector machine. Results show that the trend of simulated air temperature (2 meter) is in accord with observed air temperature. Moreover, it indicates the differences of air temperature and Land Surface Temperature caused by the urbanization efficiently. The UHI effect at night is stronger than that in the day. The maximum difference of LST reaches to 8-10°C for new build-up area at night. The method provided in this research can be used to analyze impacts on urban thermal environment caused by urbanization and it also provides means on thermal environment monitoring and prediction which will benefit the coping capacity of extreme event.