Oxford’s urban growth and its potential impact on the local climate

2019 ◽  
pp. 28-37
Author(s):  
Stephen Burt ◽  
Tim Burt
Keyword(s):  
Urban Heat Island ◽  
Urban Growth ◽  
Rural Site ◽  
Temperature Record ◽  
Heat Island ◽  
Local Climate ◽  
Island Effect ◽  
Central England Temperature ◽  
Urban Heat ◽  
Period Data

This chapter deals with the growth of Oxford since 1767 and assessment of the potential influence of the expanding urban area on the temperature record from the Radcliffe Observatory, using long-period data from a semi-rural site at Rothamsted (Hertfordshire) and a more recent 3-year comparison with records from nearby Wallingford to assess the extent of, and changes in, Oxford’s urban heat island. The urban heat island effect remains small but is shown to have increased in magnitude in recent decades, and is likely to affect the homogeneity of the Oxford temperature record. In addition, the chapter provides a comparison of the data from the Radcliffe Observatory with that from the Central England Temperature series.

scholarly journals Spatiotemporal Changes in the Urban Heat Island Intensity of Distinct Local Climate Zones: Case Study of Zhongshan District, Dalian, China

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jun Han ◽  
Jiatong Liu ◽  
Liang Liu ◽  
Yuanzhi Ye
Keyword(s):  
Urban Heat Island ◽  
High Density ◽  
Urban Heat Island Intensity ◽  
Low Density ◽  
Heat Island ◽  
Climate Zones ◽  
Local Climate ◽  
Island Effect ◽  
Local Climate Zones ◽  
Urban Heat

Intensified due to rapid urbanization and global warming-induced high temperature extremes, the urban heat island effect has become a major environmental concern for urban residents. Scientific methods used to calculate the urban heat island intensity (UHII) and its alleviation have become urgent requirements for urban development. This study is carried out in Zhongshan District, Dalian City, which has a total area of 43.85 km2 and a 27.5 km-long coastline. The mono-window algorithm was used to retrieve the land surface temperatures (LSTs), employing Landsat remote sensing images, meteorological data, and building data from 2003, 2008, 2013, and 2019. In addition, the district was divided into local climate zones (LCZs) based on the estimated intensities and spatiotemporal variations of the heat island effect. The results show that, from 2003 to 2019, LCZs A and D shrank by 3.225 km2 and 0.395 km2, respectively, whereas LCZs B, C, and 1–6 expanded by 0.932 km2, 0.632 km2, and 2.056 km2, respectively. During this period, the maximum and minimum LSTs in Zhongshan increased by 1.365°C and 1.104°C, respectively. The LST and UHII levels of all LCZs peaked in 2019. The average LSTs of LCZs A–C increased by 1.610°C, 0.880°C, and 3.830°C, respectively, and those of LCZs 1–6 increased by 2°C–4°C. The UHIIs of LCZs A, C, and D increased by 0.730, 2.950, and 0.344, respectively, and those of LCZs 1–6 increased from 1.370–2.977 to 3.744–5.379. Overall, the regions with high LSTs are spatiotemporally correlated with high building densities. In this study, the land cover was then classified into four types (LCZs A–D) using visual interpretation and object-oriented classification, including forested land, low vegetation, bare ground, and water. Besides, the buildings were categorized as LCZs 1–6, which, respectively, represented low-density low-rises buildings, low-density high-rises buildings, low-density super high-rises buildings, high-density low-rises buildings, high-density high-rises buildings, and high-density super high-rises buildings.

An empirical model for the urban heat island intensity for a site in Manchester

2016 ◽  
Vol 38 (1) ◽  
pp. 21-31 ◽  
Author(s):  
Geoffrey J Levermore ◽  
John B Parkinson
Keyword(s):  
Urban Heat Island ◽  
Cloud Cover ◽  
Urban Heat Island Effect ◽  
Urban Heat Island Intensity ◽  
Weather Data ◽  
Rural Site ◽  
Heat Island ◽  
Island Effect ◽  
Urban Heat ◽  
A Site

The urban heat island intensity is the difference in temperature between a site close to the centre of a city and a site close to but outside the city (the rural site). The urban heat island intensity varies continuously throughout the day and is strongly dependent on the weather conditions at the time. The most important weather parameters are the wind speed, the cloud cover and the solar radiation. We have developed an empirical model for the urban heat island intensity and applied it to a site near the centre of Manchester and a rural site at Rostherne, approximately 17 km away. Weather data from the Met Office station at Rostherne are available from the British Atmospheric Data Centre. Our model uses the measured wind speed, the measured cloud cover and the measured solar radiation from Rostherne. The parameters of the model are adjusted to give a best fit to the measured urban heat island intensity for the year 2014. The model is then used to predict the hourly urban heat island intensity for the first six months of 2015, obtaining good results especially as the values of the parameters are not changed throughout the year and the model does not make use of the temperatures at either site. The accuracy of the model is such that if used for a basic heating and cooling load calculations the accuracy of the annual demand is high. Practical applications: Many buildings that building services engineers and other building designers design are in urban or city centres. However, the weather data for their designs are based on near-rural weather data which do not include the urban heat island effect. This paper describes a method to ascertain the urban heat island effect in the centre of Manchester. A designer could apply this for Manchester and as an initial indication to other similar urban areas. This will allow the rural weather data to be adjusted on an hourly basis for the urban heat island effect throughout the year.

A low-order canyon model to estimate the influence of canyon shape on the maximum urban heat island effect

2012 ◽  
Vol 33 (4) ◽  
pp. 371-385 ◽  
Author(s):  
GJ Levermore ◽  
HKW Cheung
Keyword(s):  
Urban Heat Island ◽  
Weather Data ◽  
Rural Site ◽  
City Centre ◽  
Wave Radiation ◽  
Heat Island ◽  
Practical Applications ◽  
Island Effect ◽  
Urban Heat ◽  
Ventilation Rates

A simple mathematical model of an urban canyon is developed. The canyon model consists of horizontal and vertical slabs providing thermal storage for heat and absorption of and shielding from solar radiation and long wave radiation to the sky. The model is compared to a horizontal slab in a rural location to examine the effect of the canyon shape. The results show the same trend as measurements by others, with increasing urban heat island (UHI) effect with increasing canyon aspect ratio. The model is then used to determine the maximum UHI effect by producing a simple algebraic equation. This compares well with measurements in Greater Manchester of canyon and rural temperatures although some empirical adjustments are required. The strong influence of cloud cover is shown by the model and measurements as are the canyon shape and the ground temperature. Practical applications: The model is simple and developed in terms applicable to building services engineers, using ventilation rates through the canyon. It also does not require more than the standard weather data available in a CIBSE Test Reference Year or a Design Summer Year. From this model, the UHI effect can be developed to adjust the data from a rural site to that of an urban and city centre site. This is useful for building designers to take account of the UHI effect which they cannot do at present. This would also be useful for UKCP09 data which have been released.

Optimizing local climate zones to mitigate urban heat island effect in human settlements

2020 ◽  
Vol 275 ◽  
pp. 123767 ◽  
Author(s):  
Jun Yang ◽  
Yichen Wang ◽  
Chunliang Xiu ◽  
Xiangming Xiao ◽  
Jianhong Xia ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Human Settlements ◽  
Climate Zones ◽  
Local Climate ◽  
Island Effect ◽  
Local Climate Zones ◽  
Urban Heat

scholarly journals Cooling Effect of Different Land Cover Types: A Case Study in Xi’an and Xianyang, China

2021 ◽  
Vol 13 (3) ◽  
pp. 1099
Author(s):  
Yuhe Ma ◽  
Mudan Zhao ◽  
Jianbo Li ◽  
Jian Wang ◽  
Lifa Hu
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Cooling Effect ◽  
Heat Island ◽  
Land Cover Types ◽  
Island Effect ◽  
Urban Heat

One of the climate problems caused by rapid urbanization is the urban heat island effect, which directly threatens the human survival environment. In general, some land cover types, such as vegetation and water, are generally considered to alleviate the urban heat island effect, because these landscapes can significantly reduce the temperature of the surrounding environment, known as the cold island effect. However, this phenomenon varies over different geographical locations, climates, and other environmental factors. Therefore, how to reasonably configure these land cover types with the cooling effect from the perspective of urban planning is a great challenge, and it is necessary to find the regularity of this effect by designing experiments in more cities. In this study, land cover (LC) classification and land surface temperature (LST) of Xi’an, Xianyang and its surrounding areas were obtained by Landsat-8 images. The land types with cooling effect were identified and their ideal configuration was discussed through grid analysis, distance analysis, landscape index analysis and correlation analysis. The results showed that an obvious cooling effect occurred in both woodland and water at different spatial scales. The cooling distance of woodland is 330 m, much more than that of water (180 m), but the land surface temperature around water decreased more than that around the woodland within the cooling distance. In the specific urban planning cases, woodland can be designed with a complex shape, high tree planting density and large planting areas while water bodies with large patch areas to cool the densely built-up areas. The results of this study have utility for researchers, urban planners and urban designers seeking how to efficiently and reasonably rearrange landscapes with cooling effect and in urban land design, which is of great significance to improve urban heat island problem.

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