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

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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Spatial and Temporal Structure of the Urban Heat Island in Seoul

Journal of Applied Meteorology ◽

10.1175/jam2226.1 ◽

2005 ◽

Vol 44 (5) ◽

pp. 591-605 ◽

Cited By ~ 172

Author(s):

Yeon-Hee Kim ◽

Jong-Jin Baik

Keyword(s):

Urban Heat Island ◽

Temporal Structure ◽

Temperature Data ◽

Total Variance ◽

Anthropogenic Heat ◽

Urban Heat Island Intensity ◽

Heat Island ◽

Near Surface ◽

Average Maximum ◽

Urban Heat

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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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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A New Modeling Approach to Forecast Building Energy Demands During Extreme Heat Events in Complex Cities

ASME 2011 5th International Conference on Energy Sustainability, Parts A, B, and C ◽

10.1115/es2011-54844 ◽

2011 ◽

Cited By ~ 1

Author(s):

Estatio Gutie´rrez ◽

Jorge E. Gonza´lez ◽

Robert Bornstein ◽

Mark Arend ◽

Alberto Martilli

Keyword(s):

Urban Heat Island ◽

Heat Wave ◽

Extreme Event ◽

Large City ◽

Urban Canopy ◽

Anthropogenic Heat ◽

Heat Island ◽

Urban Canopy Model ◽

Urban Heat ◽

Canopy Model

The thermal response of a large city including the energy production aspects of it are explored for a large and complex city using urbanized atmospheric mesoscale modeling. The Weather Research and Forecasting (WRF) mesocale model is coupled to a multi-layer urban canopy model that considers thermal and mechanical effects of the urban environment including a building scale energy model to account for anthropogenic heat contributions due to indoor-outdoor temperature differences. This new urban parameterization is used to evaluate the evolution and the resulting urban heat island formation associated to a 3-day heat wave in New York City (NYC) during the summer of 2010. High resolution (250 m.) urban canopy parameters (UCPs) from the National Urban Database were employed to initialize the multi-layer urban parameterization. The precision of the numerical simulations is evaluated using a range of observations. Data from a dense network of surface weather stations, wind profilers and Lidar measurements are compared to model outputs over Manhattan and its surroundings during the 3-days event. The thermal and drag effects of buildings represented in the multilayer urban canopy model improves simulations over urban regions giving better estimates of the surface temperature and wind speed. An accurate representation of the nocturnal urban heat island registered over NYC in the event was obtained from the improved model. The accuracy of the simulation is further assessed against more simplified urban parameterizations models with positive results with new approach. Results are further used to quantify the energy consumption of the buildings during the heat wave, and to explore alternatives to mitigate the intensity of the UHI during the extreme event.

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A New Modeling Approach to Forecast Building Energy Demands During Extreme Heat Events in Complex Cities

Journal of Solar Energy Engineering ◽

10.1115/1.4025510 ◽

2013 ◽

Vol 135 (4) ◽

Cited By ~ 15

Author(s):

Estatio Gutiérrez ◽

Jorge E. González ◽

Robert Bornstein ◽

Mark Arend ◽

Alberto Martilli

Keyword(s):

Urban Heat Island ◽

Heat Wave ◽

Extreme Event ◽

Surface Air Temperature ◽

Urban Canopy ◽

Anthropogenic Heat ◽

Heat Island ◽

Urban Canopy Model ◽

Urban Heat ◽

Canopy Model

The thermal response of a large and complex city including the energy production aspects of it are explored using urbanized atmospheric mesoscale modeling. The Weather Research and Forecasting (WRF) Mesocale model is coupled to a multilayer urban canopy model that considers thermal and mechanical effects of the urban environment including a building scale energy model to account for anthropogenic heat contributions due to indoor–outdoor temperature differences. This new urban parameterization is used to evaluate the evolution and the resulting urban heat island (UHI) formation associated to a 3-day heat wave in New York City (NYC) during the summer of 2010. High-resolution (250 m) urban canopy parameters (UCPs) from the National Urban Database were employed to initialize the multilayer urban parameterization. The precision of the numerical simulations is evaluated using a range of observations. Data from a dense network of surface weather stations, wind profilers, and Lidar measurements are compared to model outputs over Manhattan and its surroundings during the 3-days event. The thermal and drag effects of buildings represented in the multilayer urban canopy model improves simulations over urban regions giving better estimates of the 2 m surface air temperature and 10 m wind speed. An accurate representation of the nocturnal urban heat island registered over NYC in the event was obtained from the improved model. The accuracy of the simulation is further assessed against more simplified urban parameterizations models with positive results with new approach. Results are further used to quantify the energy consumption of the buildings during the heat wave, and to explore alternatives to mitigate the intensity of the UHI during the extreme event.

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

Modern Applied Science ◽

10.5539/mas.v11n4p80 ◽

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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A High-Resolution Monitoring Approach of Canopy Urban Heat Island using Random Forest Model and Multi-platform Observations

10.5194/amt-2021-301 ◽

2021 ◽

Author(s):

Shihan Chen ◽

Yuanjian Yang ◽

Fei Deng ◽

Yanhao Zhang ◽

Duanyang Liu ◽

...

Keyword(s):

High Resolution ◽

Random Forest ◽

Urban Heat Island ◽

Air Temperature ◽

Anthropogenic Heat ◽

Heat Island ◽

Model Framework ◽

Rapid Urbanization ◽

Urban Heat ◽

The City

Abstract. Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high spatial resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a Random Forest (RF) model. Firstly, the observed environmental parameters [e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF)] around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 °C. Then, the spatial distribution of CUHII was evaluated at 30-m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the de-creasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.

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Effects of Dubai coastline extreme urbanization in land and sea on local near-surface climate variables patterns

10.5194/egusphere-egu21-6348 ◽

2021 ◽

Author(s):

Emily Elhacham ◽

Pinhas Alpert

Keyword(s):

Urban Heat Island ◽

Heat Island ◽

Rapid Urbanization ◽

Near Surface ◽

Modis Data ◽

The World ◽

Urban Heat ◽

Surface Urban Heat Island ◽

Coastal Urbanization ◽

The Impact

Over a billion people currently live in coastal areas, and coastal urbanization is rapidly growing worldwide. Here, we explore the impact of an extreme and rapid coastal urbanization on near-surface climatic variables, based on MODIS data, Landsat and some in-situ observations. We study Dubai, one of the fastest growing cities in the world over the last two decades. Dubai's urbanization centers along its coastline &#8211; in land, massive skyscrapers and infrastructure have been built, while in sea, just nearby, unique artificial islands have been constructed.Studying the coastline during the years of intense urbanization (2001-2014), we show that the coastline exhibits surface urban heat island characteristics, where the urban center experiences higher temperatures, by as much as 2.0&#176;C and more, compared to the adjacent less urbanized zones. During development, the coastal surface urban heat island has nearly doubled its size, expanding towards the newly developed areas. This newly developed zone also exhibited the largest temperature trend along the coast, exceeding 0.1&#176;C/year on average.Overall, we found that over land, temperature increases go along with albedo decreases, while in sea, surface temperature decreases and albedo increases were observed particularly over the artificial islands. These trends in land and sea temperatures affect the land-sea temperature gradient which influences the breeze intensity. The above findings, along with the increasing relative humidity shown, directly affect the local population and ecosystem and add additional burden to this area, which is already considered as one of the warmest in the world and a climate change 'hot spot'.&#160;References:E. Elhacham and P. Alpert, "Impact of coastline-intensive anthropogenic activities on the atmosphere from moderate resolution imaging spectroradiometer (MODIS) data in Dubai (2001&#8211;2014)", Earth&#8217;s Future, 4, 2016. https://doi.org/10.1002/2015EF000325E. Elhacham and P. Alpert, "Temperature patterns along an arid coastline experiencing extreme and rapid urbanization, case study: Dubai", submitted.

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