Urban weather data and building models for the inclusion of the urban heat island effect in building performance simulation

Villas are a very common building typology in Abu Dhabi. Due to its preponderance in residential areas, studying how to effectively reduce energy demand for this type of building is critical for Abu Dhabi, and many similar cities in the region. This study aims to show the impact of proposed energy efficiency measures on a villa using a calibrated model and to demonstrate that to be accurate, the model must be driven using urban weather data instead of rural weather data due to the significance of the urban heat island effect. Available data for this case study includes construction properties, on-site (urban) weather data, occupancy-related loads and schedules and rural weather data. Four main steps were followed, weather data customisation combining urban and rural weather variables, model calibration using a genetic algorithm-based tool and simulating retrofit strategies. We created a calibrated model for electricity demand during 2016–2017 with a 4% normalized mean bias error and an 11% coefficient of variation of the mean square error. Changing from none to all retrofit strategies results in a 34% reduction in annual energy consumption. According to the calibrated model, increased urban temperatures cause a 7.1% increase in total energy consumption.

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

Building Services Engineering Research and Technology ◽

10.1177/0143624416659323 ◽

2016 ◽

Vol 38 (1) ◽

pp. 21-31 ◽

Cited By ~ 2

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.

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

Building Services Engineering Research and Technology ◽

10.1177/0143624411417899 ◽

2012 ◽

Vol 33 (4) ◽

pp. 371-385 ◽

Cited By ~ 14

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.

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

Sustainability ◽

10.3390/su13031099 ◽

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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