Spatial and Temporal Structure of the Urban Heat Island in Seoul

Abstract The spatial and temporal structure of the urban heat island in Seoul, Korea, is investigated using near-surface temperature data measured at 31 automatic weather stations (AWSs) in the Seoul metropolitan area for the 1-yr period from March 2001 to February 2002. The urban heat island in Seoul deviates considerably from an idealized, concentric heat island structure, mainly because of the location of the main commercial and industrial sectors and the local topography. Relatively warm regions extend in the east–west direction and relatively cold regions are located near the northern and southern mountains. Several warm cores are observed whose intensity, size, and location are found to vary seasonally and diurnally. Similar to previous studies, the urban heat island in Seoul is stronger in the nighttime than in the daytime and decreases with increasing wind speed and cloud cover, but it is least developed in summer. The average maximum urban heat island intensity is 2.2°C over the 1-yr period and it is 3.4°C at 0300 local standard time (LST) and 0.6°C at 1500 LST. The reversed urban heat island is occasionally observed in the afternoon, but its intensity is very weak. An empirical orthogonal function (EOF) analysis is performed to find the dominant modes of variability in the Seoul urban heat island. In the analysis using temperature data that are averaged for each hour of the 1-yr period, the first EOF explains 80.6% of the total variance and is a major diurnal mode. The second EOF, whose horizontal structure is positive in the eastern part of Seoul and is negative in the western part, explains 16.0% of the total variance. This mode is related to the land use type and the diurnal pattern of anthropogenic heat release. In the analysis using temperature data at 0300 LST, the leading four modes explain 72.4% of the total variance. The first EOF reflects that the weakest urban heat island intensity is in summer. It is found that the urban heat island in Seoul is stronger on weekdays than weekends.

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Radon-based technique for the analysis of atmospheric stability – a case study from Central Poland

Nukleonika ◽

10.2478/nuka-2018-0006 ◽

2018 ◽

Vol 63 (2) ◽

pp. 47-54 ◽

Cited By ~ 6

Author(s):

Agnieszka Podstawczyńska ◽

Scott D. Chambers

Keyword(s):

Wind Speed ◽

Temperature Gradient ◽

Urban Heat Island ◽

Urban Heat Island Intensity ◽

Heat Island ◽

Vertical Temperature Gradient ◽

Mixing State ◽

Vertical Temperature ◽

Near Surface ◽

Urban Heat

Abstract An economical and easy-to-implement technique is outlined by which the mean nocturnal atmospheric mixing state (“stability”) can be assessed over a broad (city-scale) heterogeneous region solely based on near-surface (2 m above ground level [a.g.l.]) observations of the passive tracer radon-222. The results presented here are mainly based on summer data of hourly meteorological and radon observations near Łodź, Central Poland, from 4 years (2008–2011). Behaviour of the near-surface wind speed and vertical temperature gradient (the primary controls of the nocturnal atmospheric mixing state), as well as the urban heat island intensity, are investigated within each of the four radon-based nocturnal stability categories derived for this study (least stable, weakly stable, moderately stable, and stable). On average, the most (least) stable nights were characterized by vertical temperature gradient of 1.1 (0.5)°C·m−1, wind speed of ~0.4 (~1.0) m·s−1, and urban heat island intensity of 4.5 (0.5)°C. For sites more than 20 km inland from the coast, where soils are not completely saturated or frozen, radon-based nocturnal stability classification can significantly enhance and simplify a range of environmental research applications (e.g. urban climate studies, urban pollution studies, regulatory dispersion modelling, and evaluating the performance of regional climate and pollution models).

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

Atmosphere ◽

10.3390/atmos10020067 ◽

2019 ◽

Vol 10 (2) ◽

pp. 67 ◽

Cited By ~ 5

Author(s):

Ping Jiang ◽

Xiaoran Liu ◽

Haonan Zhu ◽

Yonghua Li

Keyword(s):

Urban Heat Island ◽

Urban Areas ◽

Surface Wind ◽

Warm Season ◽

Monitoring Network ◽

Anthropogenic Heat ◽

Heat Island ◽

Near Surface ◽

Urban Heat ◽

Surface Monitoring

The spatial and temporal features of urban heat island (UHI) intensity in complex urban terrain are barely investigated. This study examines the UHI intensity variations in mountainous Chongqing using a dense surface monitoring network. The results show that the UHI intensity is closely related to underlying surfaces, and the strongest UHI intensity is confined around the central urban areas. The UHI intensity is most prominent at night and in warm season, and the magnitude could reach ~4.5 °C on summer night. Our quantitative analysis shows a profound contribution of urbanization level to UHI intensity both at night and in summer, with regression coefficient b = 4.31 and 6.65, respectively. At night, the urban extra heat such as reflections of longwave radiation by buildings and release of daytime-stored heat from artificial materials, is added into the boundary layer, which compensates part of urban heat loss and thus leads to stronger UHI intensity. In summer, the urban areas are frequently controlled by oppressively hot weather. Due to increased usage of air conditioning, more anthropogenic heat is released. As a result, the urban temperatures are higher at night. The near-surface wind speed can serve as an indicator predicting UHI intensity variations only in the diurnal cycle. The rural cooling rate during early evening transition, however, is an appropriate factor to estimate the magnitude of UHI intensity both at night and in summer.

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Modelling spatiotemporal variations of the canopy layer urban heat island in Beijing at the neighbourhood scale

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-13687-2021 ◽

2021 ◽

Vol 21 (17) ◽

pp. 13687-13711

Author(s):

Michael Biggart ◽

Jenny Stocker ◽

Ruth M. Doherty ◽

Oliver Wild ◽

David Carruthers ◽

...

Keyword(s):

Urban Heat Island ◽

Land Surface ◽

Urban Climate ◽

Anthropogenic Heat ◽

Heat Island ◽

Canopy Layer ◽

Near Surface ◽

Air Temperatures ◽

Urban Heat ◽

Neighbourhood Scale

Abstract. Information on the spatiotemporal characteristics of Beijing's urban–rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (∼ 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both local climate zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing's UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at ∼ 4.5 ∘C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher-resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities.

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Modelling spatiotemporal variations of the canopy layer urban heat island in Beijing at the neighbourhood-scale

10.5194/acp-2020-931 ◽

2020 ◽

Author(s):

Michael Biggart ◽

Jenny Stocker ◽

Ruth M. Doherty ◽

Oliver Wild ◽

David Carruthers ◽

...

Keyword(s):

Urban Heat Island ◽

Land Surface ◽

Urban Climate ◽

Anthropogenic Heat ◽

Heat Island ◽

Canopy Layer ◽

Near Surface ◽

Air Temperatures ◽

Urban Heat ◽

Neighbourhood Scale

Abstract. Information on the spatiotemporal characteristics of Beijing's urban-rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (~ 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both Local Climate Zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing's UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at ~ 4.5 °C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities.

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Comparison of Urban Heat Island Intensity Estimation Methods Using Urbanized WRF in Berlin, Germany

Atmosphere ◽

10.3390/atmos11121338 ◽

2020 ◽

Vol 11 (12) ◽

pp. 1338

Author(s):

Julian Vogel ◽

Afshin Afshari

Keyword(s):

Urban Heat Island ◽

Weather Prediction ◽

Urban Canopy ◽

Anthropogenic Heat ◽

Estimation Methods ◽

Mean Bias Error ◽

Surface Model ◽

Heat Island ◽

Near Surface ◽

Urban Heat

In this study, we present a meso-scale simulation of the urban microclimate in Berlin, Germany, using the Weather Research and Forecasting (WRF) numerical weather prediction platform. The objective of the study is to derive an accurate estimate of the near-surface urban heat island (UHI) intensity. The simulation is conducted over a two-week summer period. We compare different physical schemes, different urban canopy schemes and different methods for estimating the UHI intensity. The urban fraction of each urban category is derived using the Copernicus Impervious Density data and the Corine Land Cover data. High-resolution City Geography Markup Language (CityGML) data is used to estimate the building height densities required by the multi-layer urban canopy model (UCM). Within the single-layer UCM, we implement an anthropogenic heat profile based on the large scale urban consumption of energy (LUCY) model. The optimal model configuration combines the WRF Single Moment Five-Class (WSM5) microphysics scheme, the Bougeault–Lacarrère planetary boundary layer scheme, the eta similarity (Mellor–Yamada–Janjic) surface layer scheme, the Noah Multi-Parameterization land surface model, the Dudhia and Rapid Radiative Transfer Model (RRTM) radiation schemes, and the multi-layer UCM (including the building energy model). Our simulated UHI intensity results agree well with measurements with a root mean squared error of 0.86K and a mean bias error of 0.20K. After model validation, we proceed to compare several UHI intensity calculation methods, including the ‘ring rural reference’ (RRR) method and the ‘virtual rural reference’ (VRR) method. The VRR mthod is also known as the ‘urban increment’ method. We suggest and argument that the VRR approach is superior.

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Orographic effects on calculation of the urban heat island intensity

Оптика атмосферы и океана ◽

10.15372/aoo20180208 ◽

2018 ◽

Keyword(s):

Urban Heat Island ◽

Urban Heat Island Intensity ◽

Heat Island ◽

Orographic Effects ◽

Urban Heat

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Quantitative Analysis of Factors Contributing to Urban Heat Island Intensity

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-11-098.1 ◽

2012 ◽

Vol 51 (5) ◽

pp. 842-854 ◽

Cited By ~ 61

Author(s):

Young-Hee Ryu ◽

Jong-Jin Baik

Keyword(s):

Urban Heat Island ◽

Single Layer ◽

Anthropogenic Heat ◽

Heat Island ◽

Impervious Surfaces ◽

Additional Heat ◽

Urban Geometry ◽

Causative Factors ◽

Urban Heat ◽

Vertical Walls

AbstractThis study identifies causative factors of the urban heat island (UHI) and quantifies their relative contributions to the daytime and nighttime UHI intensities using a mesoscale atmospheric model that includes a single-layer urban canopy model. A midlatitude city and summertime conditions are considered. Three main causative factors are identified: anthropogenic heat, impervious surfaces, and three-dimensional (3D) urban geometry. Furthermore, the 3D urban geometry factor is subdivided into three subfactors: additional heat stored in vertical walls, radiation trapping, and wind speed reduction. To separate the contributions of the factors and interactions between the factors, a factor separation analysis is performed. In the daytime, the impervious surfaces contribute most to the UHI intensity. The anthropogenic heat contributes positively to the UHI intensity, whereas the 3D urban geometry contributes negatively. In the nighttime, the anthropogenic heat itself contributes most to the UHI intensity, although it interacts strongly with other factors. The factor that contributes the second most is the impervious-surfaces factor. The 3D urban geometry contributes positively to the nighttime UHI intensity. Among the 3D urban geometry subfactors, the additional heat stored in vertical walls contributes most to both the daytime and nighttime UHI intensities. Extensive sensitivity experiments to anthropogenic heat intensity and urban surface parameters show that the relative importance and ranking order of the contributions are similar to those in the control experiment.

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