Assessing Seasonality in the Surface Urban Heat Island of London

2016 ◽  
Vol 55 (3) ◽  
pp. 493-505 ◽  
Author(s):  
Bin Zhou ◽  
Dirk Lauwaet ◽  
Hans Hooyberghs ◽  
Koen De Ridder ◽  
Jürgen P. Kropp ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Urban Heat Island ◽  
Land Surface ◽  
Climate Modeling ◽  
Heat Island ◽  
Incoming Solar Radiation ◽  
Air Temperatures ◽  
Urban Rural ◽  
Background Temperature ◽  
Urban Heat

AbstractThis paper assesses the seasonality of the urban heat island (UHI) effect in the Greater London area (United Kingdom). Combining satellite-based observations and urban boundary layer climate modeling with the UrbClim model, the authors are able to address the seasonality of UHI intensity, on the basis of both land surface temperature (LST) and 2-m air temperature, for four individual times of the day (0130, 1030, 1330, and 2230 local time) and the daily means derived from them. An objective of this paper is to investigate whether the UHI intensities that are based on both quantities exhibit a similar hysteresis-like trajectory that is observed for LST when plotting the UHI intensity against the background temperature. The results show that the UrbClim model can satisfactorily reproduce both the observed urban–rural LSTs and 2-m air temperatures as well as their differences and the hysteresis in the surface UHI. The hysteresis-like seasonality is largely absent in both the observed and modeled 2-m air temperatures, however. A sensitivity simulation of the UHI intensity to incoming solar radiation suggests that the hysteresis of the LST can mainly be attributed to the seasonal variation in incoming solar radiation.

scholarly journals Analysis of Urban Heat Island and Heat Waves Using Sentinel-3 Images: a Study of Andalusian Cities in Spain

2021 ◽  
Author(s):  
David Hidalgo García
Keyword(s):  
Solar Radiation ◽  
Urban Heat Island ◽  
Heat Wave ◽  
Land Surface ◽  
Heat Waves ◽  
Economic Cost ◽  
Heat Island ◽  
Multivariate Relationships ◽  
Urban Heat ◽  
Wave Conditions

Abstract At present, understanding the synergies between the Surface Urban Heat Island (SUHI) phenomenon and extreme climatic events entailing high mortality, i.e., heat waves, is a great challenge that must be faced to improve the quality of life in urban zones. The implementation of new mitigation and resilience measures in cities would serve to lessen the effects of heat waves and the economic cost they entail. In this research, the Land Surface Temperature (LST) and the SUHI were determined through Sentinel-3A and 3B images of the eight capitals of Andalusia (southern Spain) during the months of July and August of years 2019 and 2020. The objective was to determine possible synergies or interaction between the LST and SUHI, as well as between SUHI and heat waves, in a region classified as highly vulnerable to the effects of climate change. For each Andalusian city, the atmospheric variables of ambient temperature, solar radiation, wind speed and direction were obtained from stations of the Spanish State Meteorological Agency (AEMET); the data were quantified and classified both in periods of normal environmental conditions and during heat waves. By means of Data Panel statistical analysis, the multivariate relationships were derived, determining which ones statistically influence the SUHI during heat wave periods. The results indicate that the LST and the mean SUHI obtained are statistically interacted and intensify under heat wave conditions. The greatest increases in daytime temperatures were seen for Sentinel-3A in cities by the coast (LST = 3.90 °C, SUHI = 1.44 °C) and for Sentinel-3B in cities located inland (LST = 2.85 °C, SUHI = 0.52 °C). The existence of statistically significant positive relationships above 99% (p < 0.000) between the SUHI and solar radiation, and between the SUHI and the direction of the wind, intensified in periods of heat wave, could be verified. An increase in the urban area affected by the SUHI under heat wave conditions is reported. Graphical Abstract

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

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.

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

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.

scholarly journals Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban–Rural Gradient

2021 ◽  
Vol 13 (7) ◽  
pp. 1396
Author(s):  
Darshana Athukorala ◽  
Yuji Murayama
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Gradient Analysis ◽  
Temporal Analysis ◽  
Heat Island ◽  
Island Effect ◽  
Greater Cairo ◽  
Urban Rural ◽  
Urban Heat ◽  
Spatio Temporal

An urban heat island (UHI) is a significant anthropogenic modification of urban land surfaces, and its geospatial pattern can increase the intensity of the heatwave effects. The complex mechanisms and interactivity of the land surface temperature in urban areas are still being examined. The urban–rural gradient analysis serves as a unique natural opportunity to identify and mitigate ecological worsening. Using Landsat Thematic Mapper (TM), Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), Land Surface Temperature (LST) data in 2000, 2010, and 2019, we examined the spatial difference in daytime and nighttime LST trends along the urban–rural gradient in Greater Cairo, Egypt. Google Earth Engine (GEE) and machine learning techniques were employed to conduct the spatio-temporal analysis. The analysis results revealed that impervious surfaces (ISs) increased significantly from 564.14 km2 in 2000 to 869.35 km2 in 2019 in Greater Cairo. The size, aggregation, and complexity of patches of ISs, green space (GS), and bare land (BL) showed a strong correlation with the mean LST. The average urban–rural difference in mean LST was −3.59 °C in the daytime and 2.33 °C in the nighttime. In the daytime, Greater Cairo displayed the cool island effect, but in the nighttime, it showed the urban heat island effect. We estimated that dynamic human activities based on the urban structure are causing the spatial difference in the LST distribution between the day and night. The urban–rural gradient analysis indicated that this phenomenon became stronger from 2000 to 2019. Considering the drastic changes in the spatial patterns and the density of IS, GS, and BL, urban planners are urged to take immediate steps to mitigate increasing surface UHI; otherwise, urban dwellers might suffer from the severe effects of heatwaves.

scholarly journals Urban Heat Island Effects in Tropical Climate

2020 ◽  
Author(s):  
Luz E. Torres Molina ◽  
Sara Morales ◽  
Luis F. Carrión
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Tropical Climate ◽  
Heat Island ◽  
Prevention Measures ◽  
Flood Warning ◽  
Air Temperatures ◽  
Urban Heat ◽  
Flood Warning System

This paper reviews some of the characteristics of urban climates and the causes and effects of urban heat island (UHI) issues in the tropical climate. UHI effect is a kind of heat accumulation phenomenon within the urban areas due to urban construction and human activities. It is recognized as the most evident characteristic of urban climate. The increase of land surface temperature in San Juan, Puerto Rico, caused by the UHI effect was influenced by the change of land use and material types in construction. The impacts of daily temperature, surface albedo, evapotranspiration (ET), and anthropogenic heating on the near-surface climate are discussed. Analyzed data and field measurements indicate that increasing albedo and vegetation cover can be effective in reducing the surface and air temperatures near the ground. Some mitigation and prevention measures are proposed for the effects of UHI, such as a flash flood warning system.

scholarly journals ANALYSIS OF THE IMPACT OF VEGETATION DISTRIBUTION, URBANIZATION, AND SOLAR RADIATION ON THE SEASONAL VARIATION OF THE URBAN HEAT ISLAND EFFECT IN CEBU CITY USING LANDSAT AND GLOBAL HORIZONTAL IRRADIANCE DATA

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 93-100
Author(s):  
S. F. Cañete ◽  
L. L. Schaap ◽  
R. Andales ◽  
R. E. S. Otadoy ◽  
A. C. Blanco ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Solar Radiation ◽  
Urban Heat Island ◽  
Land Surface ◽  
Dry Season ◽  
Heat Island ◽  
Hot Dry Season ◽  
Urban Heat ◽  
The Impact ◽  
Cool Dry Season

Abstract. The Urban Heat Island (UHI) phenomenon is a manifestation of the abnormal amount of heat generated in urban areas and anthropogenic land surface modifications. While urbanization can improve material comfort and be a boon to the economy, the accompanying problems associated with urbanization like the UHI effect has implications on health, demand for water and energy, and impacts the microclimate. Land surface temperature (LST), the Normalized Difference Vegetation Index (NDVI), and the Normalized Difference Built-up Index (NDBI) were calculated from historical remotely-sensed Landsat data from 2013 to present. The global horizontal irradiance (GHI) was computed from the lidar-derived elevation model of Cebu City using the Geographical Resources Analysis Support System (GRASS). It is shown that annual variation in average temperatures in Cebu is generally less than 5 °C. Mean UHI temperatures in Cebu City do not show a clear trend over time, but categorizing data by season, namely the rainy season (June–November), the cool dry season (December–February), and the hot dry season (March–May), permits the emergence of a pattern. Surface temperatures for the cool dry season and hot dry season show a linearly increasing trend with R2 values of 0.916 and 0.514, respectively. This study further investigates the temporal change in the degree and extent of the UHI in Cebu City by analyzing LST maps. Regression analysis is done to determine how LST is affected by the distribution of vegetation (NDVI) and built-up (NDBI), and the seasonal variation in solar radiation through the GHI.

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.

scholarly journals Patterns of Urban Heat Island Effect in Adelaide: A Mobile Traverse Experiment

2017 ◽  
Vol 11 (4) ◽  
pp. 80
Author(s):  
Ehsan Sharifi ◽  
Ali Soltani
Keyword(s):  
Heat Stress ◽  
Urban Heat Island ◽  
Urban Policy ◽  
Urban Heat Island Effect ◽  
Urban Structure ◽  
Heat Island ◽  
Near Surface ◽  
Island Effect ◽  
Urban Rural ◽  
Urban Heat

Urban structure, hard surfaces and shortage of vegetation cause an artificial temperature increase in cities, known as the urban heat island effect. This paper determines the daily patterns of urban heat in Adelaide, Australia. The near-surface temperature profile of Adelaide was mapped in 60 journeys alongside a straight cross route connecting Adelaide Hills to the West Beach between 26 July and 15 August 2013. Results indicate that the most intense urban-rural temperature differences occurred during midnight in Adelaide. However, the afternoon urban heat had more temperature variation in the urban area. In the late afternoon, the near-surface urban heat fluctuates by 2°C within three kilometres and by 1.2°C in just one kilometer. Afternoon heat stress can vary based on space configurations and urban surface covers. Afternoon heat stress causes the highest heat load on urban dwellers. A better understanding of daily urban heat variations in cities assists urban policy making and public life management in the context of climate change.

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