This work aims to compare the performance of the single-(SLUCM) and multilayer (BEP-Building effect parameterization) urban canopy models (UCMs) coupled with the Weather Research and Forecasting model (WRF), along with the application of two urban heat island (UHI) identification methods. The identification methods are: (1) the "classic method", based on the temperature difference between urban and rural areas; (2) the "local method" based on the temperature difference at each urban location when the model land use is considered urban, and when it is replaced by the dominant rural land use category of the urban surroundings. The study is performed as a case study for the city of Lisbon, Portugal, during the record-breaking August 2003 heatwave event. Two main differences were found in the UHI intensity (UHII) and spatial distribution between the identification methods: a reduction by half in the UHII during nighttime when using the local method; and a dipole signal in the daytime and nighttime UHI spatial pattern when using the classic method, associated with the sheltering effect provided by the high topography in the northern part of the city, that reduces the advective cooling in the lower areas under prevalent northern wind conditions. These results highlight the importance of using the local method in UHI modeling studies to fully isolate urban canopy and regional geographic contributions to the UHII and distribution. Considerable improvements were obtained in the near-surface temperature representation by coupling WRF with the UCMs but better with SLUCM. The nighttime UHII over the most densely urbanized areas is lower in BEP, which can be linked to its larger nocturnal turbulent kinetic energy (TKE) near the surface and negative sensible heat (SH) fluxes. The latter may be associated with the lower surface skin temperature found in BEP, possibly owing to larger turbulent SH fluxes near the surface. Due to its higher urban TKE, BEP significantly overestimates the planetary boundary layer height compared with SLUCM and observations from soundings. The comparison with a previous study for the city of Lisbon shows that BEP model simulation results heavily rely on the number and distribution of vertical levels within the urban canopy.
机构:
CMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences,China Meteorological AdministrationCMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
Yonghong LIU
Yongming XU
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机构:
School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science & TechnologyCMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
Yongming XU
Yeping ZHANG
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机构:
National Satellite Meteorological Centre,China Meteorological AdministrationCMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
Yeping ZHANG
Xiuzhen HAN
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机构:
National Satellite Meteorological Centre,China Meteorological AdministrationCMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
Xiuzhen HAN
Fuzhong WENG
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CMA Earth System Modeling and Prediction Centre,China Meteorological Administration CMACMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
Fuzhong WENG
Chunyi XUAN
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机构:
Beijing Municipal Climate Centre,Beijing Meteorological ServiceCMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
Chunyi XUAN
Wenjun SHU
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机构:
Beijing Municipal Climate Centre,Beijing Meteorological ServiceCMA Earth System Modeling and Prediction Centre,China Meteorological Administration (CMA)
机构:
China Meteorol Adm CMA, CMA Earth Syst Modeling & Predict Ctr, Beijing 100081, Peoples R China
Chinese Acad Meteorol Sci, State Key Lab Severe Weather, China Meteorol Adm, Beijing 100081, Peoples R ChinaChina Meteorol Adm CMA, CMA Earth Syst Modeling & Predict Ctr, Beijing 100081, Peoples R China
机构:
Huazhong Univ Sci & Technol, Sch Architecture & Urban Planning, Wuhan, Peoples R ChinaHuazhong Univ Sci & Technol, Sch Architecture & Urban Planning, Wuhan, Peoples R China
Zhu, Dun
Zhou, Xuefan
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机构:
Huazhong Univ Sci & Technol, Sch Architecture & Urban Planning, Wuhan, Peoples R ChinaHuazhong Univ Sci & Technol, Sch Architecture & Urban Planning, Wuhan, Peoples R China
Zhou, Xuefan
Cheng, Wei
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机构:
Wuhan Land Use & Urban Spatial Planning Res Ctr WL, Wuhan, Peoples R ChinaHuazhong Univ Sci & Technol, Sch Architecture & Urban Planning, Wuhan, Peoples R China
机构:
Harbin Inst Technol, Sch Municipal & Environm Engn, Harbin, Peoples R ChinaHarbin Inst Technol, Sch Municipal & Environm Engn, Harbin, Peoples R China
Liu, Lin
Lin, Yaoyu
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机构:
Harbin Inst Technol, Shenzhen Grad Sch, Shenzhen Key Lab Urban Planning & Decis Making Si, Harbin, Peoples R ChinaHarbin Inst Technol, Sch Municipal & Environm Engn, Harbin, Peoples R China
Lin, Yaoyu
Wang, Dan
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Harbin Inst Technol, Shenzhen Grad Sch, Shenzhen Key Lab Urban Planning & Decis Making Si, Harbin, Peoples R ChinaHarbin Inst Technol, Sch Municipal & Environm Engn, Harbin, Peoples R China
Wang, Dan
Liu, Jing
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机构:
Harbin Inst Technol, Sch Municipal & Environm Engn, Harbin, Peoples R China
Harbin Inst Technol, State Key Lab Urban Water Resource & Environm, Harbin, Peoples R ChinaHarbin Inst Technol, Sch Municipal & Environm Engn, Harbin, Peoples R China