Features of Urban Heat Island in Mountainous Chongqing from a Dense Surface Monitoring Network

Jiang, Ping; Liu, Xiaoran; Zhu, Haonan; Li, Yonghua

doi:10.3390/atmos10020067

Cited by 14 publications

(6 citation statements)

References 47 publications

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“…Often, the schematic representation of the UTS temporal variation is a depiction of this mirrored silhouette [34,35], a daily profile that is also supported in a more recent worldwide study using harmonic functions to explore the asymmetry of the urban daily air temperature cycle [36]. Moreover, recent case study examples of the temporal variation in the UHI magnitude describe similar harmonic curves; examples include cities across several climatic contexts and geographical settings, such as Vancouver, London, Edmonton, Uppsala and St. Louis [51], Chongqing [52], Oklahoma [53], or Buenos Aires [54].…”

Section: Discussionmentioning

confidence: 73%

Heatwaves and Summer Urban Heat Islands: A Daily Cycle Approach to Unveil the Urban Thermal Signal Changes in Lisbon, Portugal

et al. 2021

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Lisbon is a European Mediterranean city, greatly exposed to heatwaves (HW), according to recent trends and climate change prospects. Considering the Atlantic influence, air temperature observations from Lisbon’s mesoscale network are used to investigate the interactions between background weather and the urban thermal signal (UTS) in summer. Days are classified according to the prevailing regional wind direction, and hourly UTS is compared between HW and non-HW conditions. Northern-wind days predominate, revealing greater maximum air temperatures (up to 40 ˚C) and greater thermal amplitudes (approximately 10 ˚C), and account for 37 out of 49 HW days; southern-wind days have milder temperatures, and no HWs occur. Results show that the wind direction groups are significantly different. While southern-wind days have minor UTS variations, northern-wind days have a consistent UTS daily cycle: a diurnal urban cooling island (UCI) (often lower than –1.0 ˚C), a late afternoon peak urban heat island (UHI) (occasionally surpassing 4.0 ˚C), and a stable nocturnal UHI (1.5 ˚C median intensity). UHI/UCI intensities are not significantly different between HW and non-HW conditions, although the synoptic influence is noted. Results indicate that, in Lisbon, the UHI intensity does not increase during HW events, although it is significantly affected by wind. As such, local climate change adaptation strategies must be based on scenarios that account for the synergies between potential changes in regional air temperature and wind.

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Section: Discussionmentioning

confidence: 73%

Heatwaves and Summer Urban Heat Islands: A Daily Cycle Approach to Unveil the Urban Thermal Signal Changes in Lisbon, Portugal

et al. 2021

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“…As a typical representative mountain city, Chongqing is known as one of the four "ovens" of China due to its geographical location and topography. Chongqing is extremely hot in summer, with a daily maximum temperature of 35 • C [32,33]. atmosphere is not readily exchanged with the surrounding environment.…”

Section: Study Areamentioning

confidence: 99%

Assessment of Urban Heat Risk in Mountain Environments: A Case Study of Chongqing Metropolitan Area, China

De-chao

Sun

et al. 2019

Sustainability

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For urban climatic environments, the urban heat island (UHI) effect resulting from land use and land cover change (LUCC) caused by human activities is rapidly becoming one of the most notable characteristics of urban climate change due to urban expansion. UHI effects have become a significant barrier to the process of urbanization and sustainable development of the urban ecological environment. Predicting the spatial and temporal patterns of the urban heat environment from the spatial relationship between land use and land surface temperature (LST) is key to predicting urban heat environment risk. This study established an Urban Heat Environment Risk Model (UHERM) as follows. First, the urban LST was normalized and classified during three different periods. Second, a Markov model was constructed based on spatio-temporal change in the urban heat environment between the initial year (2005) and middle year (2010), and then a cellular automata (CA) model was used to reveal spatial relationships between the urban heat environments of the two periods and land use in the initial year. The spatio-temporal pattern in a future year (2015) was predicted and the accuracy of the simulation was verified. Finally, the spatio-temporal pattern of urban heat environment risk was quantitatively forecasted based on the decision rule for the urban heat environment risk considering both the present and future status of the spatial characteristics of the urban heat environment. The MODIS LST product and LUCC dataset retrieved from remote sensing images were used to verify the accuracy of UHERM and to forecast the spatio-temporal pattern of urban heat environment risk during the period of 2015–2020. The results showed that the risk of urban heat environment is increasing in the Chongqing metropolitan area. This method for quantitatively evaluating the spatio-temporal pattern of urban heat environment risk could guide sustainable growth and provide effective theoretical and technical support for the regulation of urban spatial structure to minimize urban heat environment risk.

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“…The following are some representative studies conducted in Chongqing: Liu and Li [24] studied the spatial and temporal characteristics of summer UHI intensity and its relationship with land cover in Chongqing from 2007 to 2016 based on Landsat 5 TM and Landsat 8 TIRS. Jiang et al [25] analyzed the daily and seasonal variation characteristics of UHI in Chongqing using the data from 55 automatic meteorological stations in 2017. Liao et al [26] investigated the spatial distribution of UHI in Chongqing using MODIS LST data and meteorological observation data.…”

Section: Introductionmentioning

confidence: 99%

“…Previous studies on UHI in Chongqing have mainly focused on the spatial distribution and short-term temporal variability of UHI, while long-term and comprehensive research on UHI has barely been addressed. In addition, most studies on the factors influencing the urban heat island effect have also focused on the relationship between UHI and land cover or used the nighttime light index to represent the urbanization level and to study its correlation with UHI [25]. Less effort has been put into the quantitative relations between urbanization factors and UHI in Chongqing.…”

Section: Introductionmentioning

confidence: 99%

Temporal Evolution of Urban Heat Island and Quantitative Relationship with Urbanization Development in Chongqing, China

2022

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Urban development always has a strong impact on the urban thermal environment, but it is unclear to what extent urbanization factors influence urban heat island intensity (UHII) in mountainous cities, and fewer studies have been conducted on the trends of long-term UHII in mountainous cities. Chongqing, as the only municipality directly under the central government in Southwest China and a typical mountainous city, is chosen as the case study. This study analyzed the interannual and seasonal variations of UHII based on the data from meteorological stations in Chongqing from 1959 to 2018 using the least-squares method and the Mann–Kendall test, and explored the relationship between urbanization factors (urban resident population, gross domestic product (GDP), fixed investments, and gross industrial output value) and UHII. The results show that the increasing rates of temperature in urban areas of Chongqing are significantly higher than those in rural areas affected by urbanization. Using the Mann–Kendall test, it is found that almost all abrupt temperature changes in Chongqing occurred after the rapid urbanization of Chongqing in the 21st century. The annual mean UHII increased from 0.1 °C to 1.5 °C during the study period, with summer making the largest contribution. It is also found that the UHII in Chongqing has increased year by year, especially after the 1980s. The increasing rates of UHII are larger at night and smaller during the day. The increasing trends of nighttime UHII are statistically significant, while those of daytime UHII are not. In addition, UHII and urbanization factors are found to be correlated using the grey relational analysis (GRA). Eventually, a comprehensive UHII index and a comprehensive urbanization index are constructed using principal component analysis (PCA). A tertiary regression model of UHII and urbanization index is established, which reflects that the UHII in Chongqing will continue to grow rapidly with the development of the city.

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Features of Urban Heat Island in Mountainous Chongqing from a Dense Surface Monitoring Network

Cited by 14 publications

References 47 publications

Heatwaves and Summer Urban Heat Islands: A Daily Cycle Approach to Unveil the Urban Thermal Signal Changes in Lisbon, Portugal

Heatwaves and Summer Urban Heat Islands: A Daily Cycle Approach to Unveil the Urban Thermal Signal Changes in Lisbon, Portugal

Assessment of Urban Heat Risk in Mountain Environments: A Case Study of Chongqing Metropolitan Area, China

Temporal Evolution of Urban Heat Island and Quantitative Relationship with Urbanization Development in Chongqing, China

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