Simulation of the influence of a fine-scale urban underlying surface on the urban heat island effect in Beijing

Liang, Tian; He, Jianjun; Chen, Liang; Yao, Zhangyu; Zhang, Lei; Che, Huizheng; Gong, Sunling

doi:10.1016/j.atmosres.2021.105786

Cited by 18 publications

(3 citation statements)

References 36 publications

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“…As a result, many studies have been conducted on the formation of the heat island effect: Zou et al (2021) experimentally found that increasing the natural subsurface cover can reduce the intensity and warming potential of the UHI effect; Li, Zhang et al (2020) attributed the formation of the heat island effect to structural changes in the subsurface due to urbanization and found through their study that aerosols affect the UHI; Liang et al (2021) simulated the effect of fine-scale urban subsurface on the urban heat island effect in Beijing and found that near-surface temperature was negatively correlated with emissivity/albedo and that near-surface temperature was positively correlated with urban fraction; The correlation between subsurface transformation and heat island effect was established by analytical and statistical methods by Li, Zhang et al (2020). In terms of general trends, the urban heat island effect is positively correlated with the expansion of hard surfaces and the deterioration of green surfaces and water bodies (Li, Zhang et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Shang,

Xu,

Liu

et al. 2023

SAGE Open

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In recent years, with economic development, urbanization has been accelerating. In the past 100 years, the global average temperature has increased by 0.5°C, and according to the predictions of most global climate models, the temperature will continue to increase by 1.5°C to 3.0°C in the next 100 years. Under the influence of global warming, the urban heat island effect problem is becoming more and more serious, bringing much harm. Studying the thermal effect and its influencing factors is of great significance for sustainable urban development. In this study, the seasonal and interannual surface temperature changes of the study area are inverted based on the SW-TES algorithm, and the LST inversion of the algorithm is simply verified. At the same time, a cell dichotomous model was established to explore the influencing factors of the urban heat island effect and the influence of different land use types and normalized vegetation indices in the Hangzhou metropolitan area was analyzed. The results showed that the overall heating trend of the study area showed a heating trend, the expansion rate of regional construction land was relatively fast, and the scale of urban land was increasing. Based on the results of surface temperature changes of areas with different land types, we obtained the temperature trends of each land type [from 2005 to 2018] and found that there was a negative correlation between surface temperature and normalized vegetation index. This study provides a theoretical basis to evaluate the urban heat island effect and analyze factors that impact it and would promote sustainable urban development.

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Section: Introductionmentioning

confidence: 99%

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Shang,

Xu,

Liu

et al. 2023

SAGE Open

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“…In addition, their research adopted the default canopy parameterization setting; Liang et al ( 2021) added an LCZ to the WRF-SLUCM model to simulate the 2 m temperature in Beijing and improved the urban canopy parameters locally. The results showed that improving the urban canopy parameters can significantly improve the simulation performance of the model [48]. In this study, an LCZ was combined with the WRF-BEM model, and the improved urban canopy parameters were used to simulate the 2 m temperature.…”

Section: Discussionmentioning

confidence: 99%

Study on Urban Thermal Environment in Beijing Based on Local Climate Zone Method

Han

Zheng

et al. 2022

Sustainability

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In recent years, with the introduction of the concept of a local climate zone (LCZ), researchers have proved that adding an LCZ to the Weather Research and Forecasting (WRF) Model can improve the simulation effect. However, many existing studies cannot explain whether the improvement of accuracy in the model results is the effect of the refined zone or the effect of urban area correction, so they cannot explain the advantages of LCZ data. Therefore, this paper uses remote sensing images to generate two kinds of land use data sets and introduces them into the Weather Research and Forecasting Model coupled with the building energy model (WRF-BEM). In this paper, the two factors of urban area expansion and fine classification are considered, and three numerical examples are set up to simulate high-temperature weather in August 2019. The research shows that the simulated 2 m temperature of the scheme of correcting only urban area is the closest to the observed data. Although the RMSE in the 2 m temperature simulated by the LCZ scheme is 0.43 °C higher than that of the scheme of correcting only the urban area, it can well reproduce the spatial variation characteristics of 2 m temperature. In addition, different urban morphologies affect the spatial distribution of the surface urban heat islands in Beijing. High surface urban heat island effect zones mainly appear in the compact low-rise, compact mid-rise, and large low-rise types.

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“…Tran et al [ 11 ] compared and evaluated the surface urban heat island of 18 megacities in temperate and tropical climate zones based on Landsat ETM+ data, studied the urban heat island phenomenon in Asia as a whole, and added practical support for the land surface model of high-resolution satellite thermal sensor data; Liang et al [ 12 ] combined weather research, forecasting models, plate models, and single-layer urban canopy models to simulate the urban heat island effect in Beijing, and found that using accurate emissivity can provide the best simulation result. There is a negative correlation between near-surface temperature and emissivity and albedo, while there is a positive correlation between near-surface temperature and urban proportion.…”

Section: Introductionmentioning

confidence: 99%

How to use BAPV to alleviate the urban heat island effect: An evolutionary game perspective

Fu,

Xie

et al. 2024

PLoS ONE

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In recent years, the phenomenon of the urban heat island caused by the rapid development of cities is very serious. To solve the problem of the urban heat island, this study proposed a PPP project consisting of the government (GOVT), photovoltaic investment company (PVIC), and residential customers (RS). Based on an evolutionary game model and combined with current policies and industry regulations in China, the evolution process and stable evolution strategies were studied. The result shows that more government subsidies, higher carbon trading prices, and feed-in tariffs will promote the development of the PPP project. For relatively suitable reference value ranges, the installation tilt angle of the BAPV system is 30°, the photovoltaic grid electricity price is 0.1096∼0.1296 $/kWh, the carbon trading is 8.92∼9.42 $/t.

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Simulation of the influence of a fine-scale urban underlying surface on the urban heat island effect in Beijing

Cited by 18 publications

References 36 publications

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Study on Urban Thermal Environment in Beijing Based on Local Climate Zone Method

How to use BAPV to alleviate the urban heat island effect: An evolutionary game perspective

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