Local Climate Classification and Dublin’s Urban Heat Island

Alexander, Paul J.; Mills, Gerald

doi:10.3390/atmos5040755

Cited by 170 publications

(107 citation statements)

References 35 publications

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“…8). Alexander and Mills (2014) found similar results between LCZ 2-D (4.8 ºC). During the warm season an UHI of 2.64 ºC in average, with a 5 ºC maximum and a 0.82 ºC minimum, was detected.…”

Section: Effect Of the Urban Heat Island (Uhi)supporting

confidence: 74%

“…These differences oscillated from 1.6 ºC between LCZ 3 and LCZ 6, to 4 ºC between LCZ 2 and LCZ B. In agreement with Alexander and Mills (2014), the areas with more urban elements such as high anthropogenic heat flux percentages, impervious surface and building surface fraction, had temperatures over the mean (LCZ 2 and LCZ 3), while the less urbanized areas had temperatures below the mean (LCZ 6 and LCZ B). Among the annual seasons, a 5 ºC difference between cold and warm seasons was detected (P < 0.0001, F = 602.93, 1, 87).…”

Section: The Role Of Vegetation In Urban Temperaturesupporting

confidence: 73%

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The role of urban vegetation in temperature and heat island effects in Querétaro city, Mexico

Colunga

Cambrón-Sandoval

Suzán-Azpiri

et al. 2015

Atm

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RESUMENLa alteración de las condiciones climáticas y el efecto de isla urbana de calor (EIC) son resultado del incremento de la población y de sus actividades en las zonas urbanas. En ciudades medianas como Querétaro es importante determinar la magnitud del EIC y promover la planeación del crecimiento urbano. Conservar y aumentar las áreas con vegetación es una buena opción para mitigar el EIC. En este estudio se analizaron la intensidad del EIC y el efecto de la cobertura vegetal sobre la regularización de la temperatura del aire. Se parcela de medición en la cual se consideraron dos niveles de cobertura vegetal en función del índice de área foliar: bajo y alto (0.5 y 2.0, respectivamente). La temperatura del aire se midió con recolectores de datos a intervalos de 30 min entre junio de 2012 y mayo de 2013. También se analizaron datos climáticos de seis estaciones meteorológicas. La temperatura media diaria aumentó a razón de 0.75 ºC por década (r 2 = 0.38, P < 0.0001); este aumento se relacionó con la dinámica poblacional (r 2 = 0.52, P < 0.0001). Los patrones estacionales de temperatura se describieron como temporada fría de julio a marzo y temporada cálida de abril a junio para la temperatura máxima, y temporada fría de noviembre a marzo y temporada cálida de abril a octubre para la temperatura mínima. La diferencia entre las temporadas cálida y fría fue del orden de 5 ºC ( de la vegetación. Sin embargo, la humedad relativa fue mayor en el nivel alto de la cobertura vegetal. La La intensidad del EIC fue similar para la temporada cálida y fría y varió de 0.1 a 5 ºC. La vegetación con mayor cobertura presentó menor temperatura a las 17:00 horas y mayor de las 9:00 a las 10:00 horas durante la temporada cálida. Al aumentar 50% la cobertura vegetal en la zona urbana se lograría reducir la intensidad del EIC en 2.05 ºC. En conclusión, una mayor cobertura de la vegetación mejora las condiciones ambientales en términos de humedad relativa y regularización de los extremos de temperatura durante la temporada cálida. ABSTRACTAlteration of climatic conditions and the urban heat island effect (UHI) are consequences of increased human population and activities in urban zones. Determining the magnitude of the UHI is important to improve urban planning in medium-size cities like Querétaro. Increase and conservation of vegetated areas is a mitigation option for UHI. Here we characterized both the UHI and the role of vegetation cover over temperature regtemperature and relative humidity were measured with data loggers at a 30 min time step from June 2012 to May 2013. Climatic data from six weather stations was also analyzed. Daily mean temperature increased at a rate of 0.75 ºC per decade (r 2 = 0.38, P < 0.0001), and this was related to population dynamics (r 2 = 0.52, for maximum temperature, and November to March and April to October for minimum temperature. The difference between cold and warm seasons was 5 ºC (P < 0.0001). The minimum temperature was similar doi: 10.20937/ATM.2015.28.03.05 © between canopy cover level...

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Section: Effect Of the Urban Heat Island (Uhi)supporting

confidence: 74%

Section: The Role Of Vegetation In Urban Temperaturesupporting

confidence: 73%

The role of urban vegetation in temperature and heat island effects in Querétaro city, Mexico

Colunga

Cambrón-Sandoval

Suzán-Azpiri

et al. 2015

Atm

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show abstract

“…A near universal finding is that the intensity of a UHI at a given place is greatest at night (and 4 h after sunset) when the synoptic conditions can be characterized by high pressure, clear skies, little wind, and no precipitation, as pointed out by Alexander and Mills [9]. However, if the UHI is consistently under long-term monitoring, results may point to the fact that the temperature difference between the urban and the surrounding areas is more complex.…”

Section: Introductionmentioning

confidence: 92%

Urban Heat Island and Park Cool Island Intensities in the Coastal City of Aracaju, North-Eastern Brazil

Anjos

Lopes

2017

Sustainability

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Abstract:In this study, an evaluation of the Urban Heat Island (UHI) and Park Cool Island (PCI) intensities in Aracaju, North-Eastern Brazil, was performed. The basis of our evaluation is a 2-year dataset from the urban climatological network installed with the principles and concepts defined for urban areas related to climatic scales, sitting and exposure, urban morphology, and metadata. The current findings update UHI intensities in Aracaju refuting the trend registered in previous studies. On average, the UHI was more intense in the cool season (1.3 • C) than in hot season (0.5 • C), which was caused by wind speed decrease. In relation to the PCI, mitigation of high air temperatures of 1.5-2 • C on average was registered in the city. However, the urban park is not always cooler than the surrounding built environment. Consistent long-term monitoring in the cities is very important to provide more accurate climatic information about the UHI and PCI to be applied in urban planning properly, e.g., to provide pleasant thermal comfort in urban spaces.

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“…As an example, Fig. 1 shows the LCZ map of Dublin, which was generated for an urban heat island study using available land-cover data, remote sensing and fieldwork (Alexander and Mills, 2014).…”

Section: Urban Energy Budget (Ueb) Modelsmentioning

confidence: 99%

Using LCZ data to run an urban energy balance model

2015

Self Cite

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a b s t r a c tIn recent years a number of models have been developed that describe the urban surface and simulate its climatic effects. Their great advantage is that they can be applied in environments outside the cities in which they have been developed and evaluated. Thus, they may be applied to cities in the economically developing world, which are growing rapidly, and where the results of such models may have greatest impact with respect to informing planning decisions. However, data requirements, particularly for the more complex urban models, represent a major obstacle to their employment. Here, we examine the potential for running the Surface Urban Energy and Water Balance model (SUEWS) using readily obtained data. SUEWS was designed to simulate energy and water balance terms at a neighbourhood scale (P1 km 2 ) and requires site-specific meteorological data and a detailed description of the surface. Here, its simulations are evaluated by comparison with measurements made over a seven month (approximately 3 seasons) period (April-October) at two flux tower sites (representing urban and suburban landscapes) in Dublin, Ireland. However, the main purpose of this work is to test the performance of the model under 'ideal' and 'imperfect' circumstances in relation to the input data required to run SUEWS. The ideal case uses detailed urban land cover data and meteorological data from the tower sites. The imperfect cases use parameters derived from the Local Climate Zone (LCZ) classification scheme and meteorological data from a standard weather station located beyond the urban area. For the period of record examined, the simulations show good E-mail address: paul.alexander@nuim.ie (P.J. Alexander).Urban Climate 13 (2015) 14-37 Contents lists available at ScienceDirectUrban Climate journ al homepage: www.elsevier.com/locate/uclim agreement with the observations in both ideal and imperfect cases, suggesting that the model can be used with data that is more easily derived. The comparison also shows the importance of including vegetative cover and of the initial moisture state in simulating the urban energy budget.

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Local Climate Classification and Dublin’s Urban Heat Island

Cited by 170 publications

References 35 publications

The role of urban vegetation in temperature and heat island effects in Querétaro city, Mexico

The role of urban vegetation in temperature and heat island effects in Querétaro city, Mexico

Urban Heat Island and Park Cool Island Intensities in the Coastal City of Aracaju, North-Eastern Brazil

Using LCZ data to run an urban energy balance model

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