The Birmingham Urban Climate Laboratory: An Open Meteorological Test Bed and Challenges of the Smart City

Chapman, Lee; Muller, C.; Young, Duick T.; Warren, Elliott; Grimmond, Sue; Cai, Xiaoming; Ferranti, Emma

doi:10.1175/bams-d-13-00193.1

Cited by 97 publications

(79 citation statements)

References 32 publications

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“…Indeed, even small urban areas (populations 10 3 -10 4 ), can still generate UHI magnitudes in excess of 1 • C (Oke 1973;Ivajňsič et al 2014). However, absolute maximum air-temperature variations are not always captured due to the challenges associated with locating stations within the urban environment (Chapman et al 2015;Stewart 2011). Furthermore, UHI effects are not confined to temperature.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Heat Advection on UK Weather and Climate Observations in the Vicinity of Small Urbanized Areas

Bassett

Cai

Chapman

et al. 2017

Boundary-Layer Meteorol

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Weather and climate networks traditionally follow rigorous siting guidelines, with individual stations located away from frost hollows, trees or urban areas. However, the diverse nature of the UK landscape suggests that the feasibility of siting stations that are truly representative of regional climate and free from distorting local effects is increasingly difficult. Whilst the urban heat island is a well-studied phenomenon and usually accounted for, the effect of warm urban air advected downwind is rarely considered, particularly at rural stations adjacent to urban areas. Until recently, urban heat advection (UHA) was viewed as an urban boundary-layer process through the formation of an urban plume that rises above the surface as it is advected. However, these dynamic UHA effects are shown to also have an impact on surface observations. Results show a significant difference in temperatures anomalies ( p < 0.001) between observations taken downwind of urban and rural areas. For example, urban heat advection from small urbanized areas (∼1 km 2 ) under low cloud cover and wind speeds of 2-3 m s −1 is found to increase mean nocturnal air temperatures by 0.6 • C at a horizontal distance of 0.5 km. Fundamentally, these UHA results highlight the importance of careful interpretation of long-term temperature data taken near small urban areas. Keywords Temperature observations · Urban heat advection · Urban heat island · UrbanizationElectronic supplementary material The online version of this article

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Section: Introductionmentioning

confidence: 99%

The Effects of Heat Advection on UK Weather and Climate Observations in the Vicinity of Small Urbanized Areas

Bassett

Cai

Chapman

et al. 2017

Boundary-Layer Meteorol

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“…The representative of their local environment [23]. Also, Birmingham's schools have a good coverage of the city, and mostly connected to Wi-Fi networks for data transmission.…”

Section: B Datamentioning

confidence: 99%

“…Also, Birmingham's schools have a good coverage of the city, and mostly connected to Wi-Fi networks for data transmission. Furthermore, the points for sensors installed more than 20 m away from heat sources, and the ASM sensors have approximately 3 km average spacing [23]. ASM provide only temperature data, however AWS give other meteorological data such as wind speed and direction which will be considered alongside the analysis of the temperature data [1].…”

Section: B Datamentioning

confidence: 99%

“…HiTemp' readings might be due to the height of the sensors. HiTemp sensors were installed at 3 m (with exceptions no more than 0.5m higher or lower), though, Met Office sensors almost installed 5 m above the ground level [23].…”

Section: Fig 7 Historical Air Temperature Of Birmingham Citymentioning

confidence: 99%

“…To address this deficiency, a novel project called HiTemp has been undertaken by The Birmingham Urban Climate Laboratory (BUCL) funded by The Natural Environment Research Council (NERC) [1]. It has provided near real time data from one of the densest urban meteorological network of automatic weather stations worldwide [23]. This project is ongoing since June 2012, and covers the entire conurbation of Birmingham.…”

Section: -Introductionmentioning

confidence: 99%

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Modelling the spatiotemporal change of canopy urban heat islands

Ali

Marsh

Smith

2016

Building and Environment

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This study models the spatiotemporal change of Birmingham's urban heat island (UHI) using air temperature measurements made during the HiTemp project to study the atmospheric conditions over the city [1]. The study identifies the causative factors and their contributions to the formation of UHI, based on a number of data used to build 2.5 D model; land cover, land use, geometrical factors and shadow layers.The raw air temperature measurements were filtered, georeferenced and interpolated to create maps of temperature variations. The expected influencing parameters on the development of the UHI were derived and prepared for regression modelling. The results showed that the difference in temperature across Birmingham city through two years of ground measurements (June 2012 -June 2014) reached up to 13.53 °C. The UHI's appeared daytime and night-time throughout the different seasons for approximately 56% of the total hours during the study period. However, the high intensity events happened during the calm and clear nights. Moreover, buildings' shadow provided up to 2 °C reduction to the air temperature, while the wind speed and direction are responsible for the size and distribution of hot spots. The built up area contributed to increase the UHI, whereas, the other types of land cover and the geometrical parameters, contributed less.

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Comparing the diurnal and seasonal variabilities of atmospheric and surface urban heat islands based on the Beijing urban meteorological network

et al. 2017

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This study compared the diurnal and seasonal cycles of atmospheric and surface urban heat islands (UHIs) based on hourly air temperatures (Ta) collected at 65 out of 262 stations in Beijing and land surface temperature (Ts) derived from Moderate Resolution Imaging Spectroradiometer in the years 2013–2014. We found that the nighttime atmospheric and surface UHIs referenced to rural cropland stations exhibited significant seasonal cycles, with the highest in winter. However, the seasonal variations in the nighttime UHIs referenced to mountainous forest stations were negligible, because mountainous forests have a higher nighttime Ts in winter and a lower nighttime Ta in summer than rural croplands. Daytime surface UHIs showed strong seasonal cycles, with the highest in summer. The daytime atmospheric UHIs exhibited a similar but less seasonal cycle under clear‐sky conditions, which was not apparent under cloudy‐sky conditions. Atmospheric UHIs in urban parks were higher in daytime. Nighttime atmospheric UHIs are influenced by energy stored in urban materials during daytime and released during nighttime. The stronger anthropogenic heat release in winter causes atmospheric UHIs to increase with time during winter nights, but decrease with time during summer nights. The percentage of impervious surfaces is responsible for 49%–54% of the nighttime atmospheric UHI variability and 31%–38% of the daytime surface UHI variability. However, the nighttime surface UHI was nearly uncorrelated with the percentage of impervious surfaces around the urban stations.

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The Birmingham Urban Climate Laboratory: An Open Meteorological Test Bed and Challenges of the Smart City

Cited by 97 publications

References 32 publications

The Effects of Heat Advection on UK Weather and Climate Observations in the Vicinity of Small Urbanized Areas

The Effects of Heat Advection on UK Weather and Climate Observations in the Vicinity of Small Urbanized Areas

Modelling the spatiotemporal change of canopy urban heat islands

Comparing the diurnal and seasonal variabilities of atmospheric and surface urban heat islands based on the Beijing urban meteorological network

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