A study on the spatial patterns of the Moscow megacity urban heat island based on the dense official and crowdsourcing observations

2020 ◽  
Author(s):  
Mikhail Varentsov ◽  
Timofey Samsonov ◽  
Pavel Konstantinov ◽  
Pavel Kargashin ◽  
Daniel Fenner ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Spatial Patterns ◽  
Air Temperature ◽  
Urban Climate ◽  
Basic Research ◽  
Area Fraction ◽  
Heat Island ◽  
Urban Heat ◽  
Non Local ◽  
The City

<p>The presented study is devoted to the investigation of the spatial patterns of the urban-induced air temperature anomaly, known as the urban heat island (UHI) effect, based on the example of Moscow megacity. The numerous previous studies have already shown that Moscow exhibits urban-induced climatic effects (Varentsov e al., 2018) and could serve as a good test-bed for urban climate studies. In the presented study, we have further analyzed the UHI using high-quality observations from the official meteorological networks in Moscow region as well as the uncertified crowdsourcing observations from Netatmo network. The official meteorological networks include more than 70 observational sites in the city and surroundings, while the Netatmo network additionally provides the data from more than 1500 citizen weather stations (CWSs) in Moscow region. Previous studies have shown that CWS observations could be used for urban climate studies after application of the special quality control and filtering routines (Meier et al., 2017).</p><p>The analysis performed for a number of summer and winter seasons has revealed the seasonal variations of the UHI spatial patterns. In order to investigate the driving factors of the observed spatial heterogeneity of the air temperature within the city, we have analyzed its linkages with different qualitative and quantitative parameters of the urban environment, including the Local Climate Zone (LCZ) type, the impervious area fraction, building density, vegetation area fraction, etc. These parameters were obtained using the Landsat and Sentinel satellite images, Copernicus Global Land Cover data and OpenStreetMap data. We have shown that the UHI spatial patterns are shaped both by local and non-local driving factors. The factors such as LCZ type represent the local features of the urban environment, while the non-local drivers represent the influence of remote parts of the megacity, transformed by the atmospheric diffusion and advection. The non-local effects are reflected e.g. in the dependence between the UHI intensity and the distance from the city center; in the differences between similar LCZs, located in the different parts of the city; in the heat advection to the leeward side of the city. The findings of the study clearly illustrate the importance of taking the non-local effects into consideration in urban planning applications, biometeorological assessments and when applying the LCZ approach for big cities.</p><p><strong>Acknowledges:</strong> The processing and analysis of the official and crowdsourcing observations were supported by Russian Foundation for Basic Research (project no. 19-35-70009). The analysis of the impervious surface area fraction data was supported by Russian Foundation for Basic Research (project no. 18-35-20052). The analysis of the impacts of urban vegetation on the urban heat island was supported by Russian Science Foundation (project no. 19-77-30012).</p><p><strong>References: </strong></p><p>Meier F., Fenner D., Grassmann T., Otto M., & Scherer D. (2017). Crowdsourcing air temperature from citizen weather stations for urban climate research. Urban Climate, 19, 170–191.</p><p>Varentsov M., Wouters H., Platonov V., & Konstantinov P. (2018). Megacity-Induced Mesoclimatic Effects in the Lower Atmosphere: A Modeling Study for Multiple Summers over Moscow, Russia. Atmosphere, 9(2), 50.</p>

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

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.

scholarly journals Changes in the Water Temperature of Rivers Impacted by the Urban Heat Island: Case Study of Suceava City

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1343 ◽  
Author(s):  
Andrei-Emil Briciu ◽  
Dumitru Mihăilă ◽  
Adrian Graur ◽  
Dinu Iulian Oprea ◽  
Alin Prisăcariu ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Water Temperature ◽  
Urban Heat Island ◽  
River Water ◽  
Air Temperature ◽  
Stream Water ◽  
Heat Island ◽  
Urban Heat ◽  
The City ◽  
River Water Temperature

Cities alter the thermal regime of urban rivers in very variable ways which are not yet deciphered for the territory of Romania. The urban heat island of Suceava city was measured in 2019 and its impact on Suceava River was assessed using hourly and daily values from a network of 12 water and air monitoring stations. In 2019, Suceava River water temperature was 11.54 °C upstream of Suceava city (Mihoveni) and 11.97 °C downstream (Tişăuţi)—a 3.7% increase in the water temperature downstream. After the stream water passes through the city, the diurnal thermal profile of Suceava River water temperature shows steeper slopes and earlier moments of the maximum and minimum temperatures than upstream because of the urban heat island. In an average day, an increase of water temperature with a maximum of 0.99 °C occurred downstream, partly explained by the 2.46 °C corresponding difference between the urban floodplain and the surrounding area. The stream water diurnal cycle has been shifted towards a variation specific to that of the local air temperature. The heat exchange between Suceava River and Suceava city is bidirectional. The stream water diurnal thermal cycle is statistically more significant downstream due to the heat transfer from the city into the river. This transfer occurs partly through urban tributaries which are 1.94 °C warmer than Suceava River upstream of Suceava city. The wavelet coherence analyses and ANCOVA (analysis of covariance) prove that there are significant (0.95 confidence level) causal relationships between the changes in Suceava River water temperature downstream and the fluctuations of the urban air temperature. The complex bidirectional heat transfer and the changes in the diurnal thermal profiles are important to be analysed in other urban systems in order to decipher in more detail the observed causal relationships.

Climate Bubbles: Games to Monitor Urban Climate

Leonardo ◽  
2011 ◽  
Vol 44 (1) ◽  
pp. 64-65
Author(s):  
Drew Hemment ◽  
Carlo Buontempo ◽  
Alfie Dennen
Keyword(s):  
Urban Heat Island ◽  
Air Flow ◽  
Urban Climate ◽  
Heat Island ◽  
Local Climate ◽  
Flow Circulation ◽  
Urban Heat ◽  
The City

Climate Bubbles was a playful, participatory mass observation project on local climate. Bubble blowing games were devised to enable people across the city of Manchester to test air flow circulation and, by sharing the results online, enabled the Met Office to create a snapshot of the effect the Urban Heat Island has on wind.

scholarly journals Lisbon Urban Heat Island Updated: New Highlights about the Relationships between Thermal Patterns and Wind Regimes

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
António Lopes ◽  
Elis Alves ◽  
Maria João Alcoforado ◽  
Raquel Machete
Keyword(s):  
Urban Heat Island ◽  
Urban Climate ◽  
City Centre ◽  
Heat Island ◽  
Local Wind ◽  
Urban Heat ◽  
Thermal Patterns ◽  
Wind Regimes ◽  
The Relationship ◽  
The City

Urban growth implies significant modifications in the urban climate. To understand the influence of the city of Lisbon on the urban boundary layer, a mesoscale meteorological network was installed in 2004. The main goals of the present study are to update the results of the research published in 2007 and to bring more precise information about the relationship between the Urban Heat Island (UHI) and the regional and local wind systems. The highest frequencies of the UHI were found in the city centre (Restauradores). In the green park of Monsanto, the highest frequency occurred between −2 and 0°C. During the summer, the effect of the breezes was observed in Belém, lowering the temperature. The “strong” UHI (intensity >4°C) occurred more often during the summer, with median values of 2°C by night and 1.8°C by day. The highest frequencies of UHI occurred for winds between 2 and 6 m/s and were not associated with atmospheric calm, as pointed out in the literature. Winds above 8 m/s inhibit the occurrence of strong UHI in Lisbon. Summer nighttime strong UHI should be further investigated, due to the heat stress consequences on the population and probable increase of energy consumption.

scholarly journals Using the dendro-climatological signal of urban trees as a measure of urbanization and urban heat island

2021 ◽  
Author(s):  
Christoph Schneider ◽  
Burkhard Neuwirth ◽  
Sebastian Schneider ◽  
Daniel Balanzategui ◽  
Stefanie Elsholz ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Tree Ring ◽  
Air Temperature ◽  
Tree Species ◽  
Urban Climate ◽  
Ring Width ◽  
Urban Trees ◽  
Pedunculate Oak ◽  
Heat Island ◽  
Urban Heat

AbstractUsing dendroclimatological techniques this study investigates whether inner city tree-ring width (TRW) chronologies from eight tree species (ash, beech, fir, larch, lime, sessile and pedunculate oak, and pine) are suitable to examine the urban heat island of Berlin, Germany. Climate-growth relationships were analyzed for 18 sites along a gradient of increasing urbanization covering Berlin and surrounding rural areas. As a proxy for defining urban heat island intensities at each site, we applied urbanization parameters such as building fraction, impervious surfaces, and green areas. The response of TRW to monthly and seasonal air temperature, precipitation, aridity, and daily air-temperature ranges were used to identify climate-growth relationships. Trees from urban sites were found to be more sensitive to climate compared to trees in the surrounding hinterland. Ring width of the deciduous species, especially ash, beech, and oak, showed a high sensitivity to summer heat and drought at urban locations (summer signal), whereas conifer species were found suitable for the analysis of the urban heat island in late winter and early spring (winter signal).The summer and winter signals were strongest in tree-ring chronologies when the urban heat island intensities were based on an area of about 200 m to 3000 m centered over the tree locations, and thus reflect the urban climate at the scale of city quarters. For the summer signal, the sensitivity of deciduous tree species to climate increased with urbanity.These results indicate that urban trees can be used for climate response analyses and open new pathways to trace the evolution of urban climate change and more specifically the urban heat island, both in time and space.

scholarly journals Quantifying Local and Mesoscale Drivers of the Urban Heat Island of Moscow with Reference and Crowdsourced Observations

2021 ◽  
Vol 9 ◽  
Author(s):  
Mikhail Varentsov ◽  
Daniel Fenner ◽  
Fred Meier ◽  
Timofey Samsonov ◽  
Matthias Demuzere
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Urban Climate ◽  
Winter Season ◽  
Local Scale ◽  
Driving Factors ◽  
Heat Island ◽  
Local Climate Zones ◽  
Urban Heat ◽  
Climate Studies

Urban climate features, such as the urban heat island (UHI), are determined by various factors characterizing the modifications of the surface by the built environment and human activity. These factors are often attributed to the local spatial scale (hundreds of meters up to several kilometers). Nowadays, more and more urban climate studies utilize the concept of the local climate zones (LCZs) as a proxy for urban climate heterogeneity. However, for modern megacities that extend to dozens of kilometers, it is reasonable to suggest a significant contribution of the larger-scale factors to the temperature and UHI climatology. In this study, we investigate the contribution of local-scale and mesoscale driving factors of the nocturnal canopy layer UHI of the Moscow megacity in Russia. The study is based on air temperature observations from a dense network consisting of around 80 reference and more than 1,500 crowdsourced citizen weather stations for a summer and a winter season. For the crowdsourcing data, an advanced quality control algorithm is proposed. Based on both types of data, we show that the spatial patterns of the UHI are shaped both by local-scale and mesoscale driving factors. The local drivers represent the surface features in the vicinity of a few hundred meters and can be described by the LCZ concept. The mesoscale drivers represent the influence of the surrounding urban areas in the vicinity of 2–20 km around a station, transformed by diffusion, and advection in the atmospheric boundary layer. The contribution of the mesoscale drivers is reflected in air temperature differences between similar LCZs in different parts of the megacity and in a dependence between the UHI intensity and the distance from the city center. Using high-resolution city-descriptive parameters and different statistical analysis, we quantified the contributions of the local- and mesoscale driving factors. For selected cases with a pronounced nocturnal UHI, their respective contributions are of similar magnitude. Our findings highlight the importance of taking both local- and mesoscale effects in urban climate studies for megacities into account. Furthermore, they underscore a need for an extension of the LCZ concept to take mesoscale settings of the urban environment into account.

scholarly journals How the urban environment affects the microclimate and the building energy demand for the City of Rome

2019 ◽  
Vol 23 (Suppl. 4) ◽  
pp. 1035-1042 ◽  
Author(s):  
Andrea Vallati ◽  
Luca Mauri ◽  
Chiara Colucci
Keyword(s):  
Urban Heat Island ◽  
Urban Environment ◽  
Urban Area ◽  
Air Temperature ◽  
Energy Demand ◽  
The Other ◽  
Weather Data ◽  
Heat Island ◽  
Urban Heat ◽  
The City

Urban heat island has significant impacts on buildings? energy consumption. The phenomenon is associated with increased urban air temperatures compared to the air temperature of the surrounding rural or suburban areas. The ambient air temperature growth due to climate changes and the urban heat island phenomenon are dramatically increasing the cooling demand in buildings. This is worsened by irradiation conditions, construction technologies, and subjective comfort expectations. This paper examines the impact of the urban environment on the energy demand of buildings, considering the case of two districts of the city of Rome, Italy: one is representative of a central zone, the other of a rural zone. Weather data were then used to calculate the thermal demand of a typical Italian building, ideally located in the monitored areas of the city. Standalone building with modified weather file was modeled in TRNSYS. Results show that urban heat island intensity causes an increase in cooling demand up to +33% for the urban area (+20% for the rural area) compared to the demand calculated using weather data from airportual areas. On the other hand, urban heat island intensity has a positive effect on heating demand which turns out to decrease up to -32% for the urban area (-14% for the rural area).

scholarly journals Estimating the Urban Heat Island Contribution to Urban and Rural Air Temperature Differences over Complex Terrain: Application to an Arid City

2010 ◽  
Vol 49 (10) ◽  
pp. 2159-2166 ◽  
Author(s):  
Hadas Saaroni ◽  
Baruch Ziv
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Complex Terrain ◽  
Order Approximation ◽  
Temperature Record ◽  
Heat Island ◽  
Regional Warming ◽  
Study Region ◽  
Urban Heat ◽  
The City

Abstract This study proposes a method for estimating the canopy-layer net urban heat island (UHI) in regions with complex terrain that lack preurban observations. The approach is based on a linear relationship between the urban–rural temperature difference (ΔTu−r), measured via screen-level air temperature, and the population of the city, which was found to have the highest correlation with observations. The linear relation is extrapolated to zero population to yield the desired preurban value. The difference between the zero population ΔTu−r and the current one is proposed to represent the net UHI. Given the uncertainties of the population method, the relatively short time period of the temperature record, and possible inhomogeneity in the data, the results should be regarded as a first-order approximation of the net UHI contribution. The UHI was evaluated for an arid city, Beer Sheba, Israel, for the minimum and maximum air temperatures for the summer and the winter. The study region resembles the combined effect of complex terrain (i.e., the concave topography of the city in contrast with the plateau landscape surrounding it), the UHI, and the regional warming trend. The study assumes that the regional warming does not affect the ΔTu−r. The concave topography of the city dominates over the UHI contribution during nighttime, resulting in an average lower minimum temperature in the city relative to the rural area. This difference has decreased considerably during the study period and has even reversed for the summer nights toward the end of the period. The estimated net UHI contribution in Beer Sheba varies between +0.8° and +3.1°C, with the highest values during the night hours. The high positive UHI during the night is in line with previous studies. The positive UHI in the summer implies further aggravation of heat stress beyond that occurring, and that predicted to increase, over the region.

scholarly journals Analysis of the urban heat island in representative points of the city of Bayeux / PB

2018 ◽  
Vol 7 (6) ◽  
pp. 345
Author(s):  
Amanda Mayara Paulino Da Silva
Keyword(s):  
Land Use ◽  
Urban Heat Island ◽  
Thermal Field ◽  
Urban Climate ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Thermal Discomfort ◽  
Heat Islands ◽  
Urban Heat ◽  
The City

Abstrat Urban growth has generated several socio-environmental problems and has altered the quality of life of people living in these environments. Due to the disorderly growth of cities and the various forms of urban land use and occupation, changes in the thermal field of these areas have occurred and caused the formation of urban heat islands and thermal discomfort in urban environments. Thus, the need to understand the formation of heat islands in these areas and the study of their causes and consequences grows. Given this context, the present work intends to study the urban climate of the city of Bayeux / PB, specifically the urban thermal field, and the formation of heat islands. For the accomplishment of the research, initially a bibliographical survey of the subject in question was made. Subsequently experimental points of meteorological data collection (temperature and relative air humidity) were defined in the metropolitan area of the city of João Pessoa, specifically in the municipality of Bayeux / PB. These points were defined based on the different types of land use and cover in the study area. The following experimental points were defined: a point in the center of the city of Bayeux / PB, another point on the banks of the BR230 direction Bayeux, and a reference point in a remnant of Atlantic forest. To obtain the urban heat island the reference point was used as a parameter of the climatic conditions of a natural environment. The data of temperature and relative humidity were collected through thermometers (HOBO U-10), which were placed on steel tripods (1.5 meters high) and monitored at uninterrupted intervals of 1 and 1 hour during the dry period and rainy region. The analysis of the data points to the formation of urban heat islands in the two periods evaluated in the city of Bayeux / PB, being the center of the city, the most critical area with the most intense heat islands. The vegetative cover played a predominant role in the climatic mitigation of the experimental samples as well as the presence of precipitation. The areas with impermeable soil cover presented the largest heat islands and contributed to the thermal discomfort of the study area. Keywords: Urban Climate, Thermodynamic Field, Urban Heat Island.

scholarly journals Ilhas de calor urbano em cidade do semiárido nordestino

GeoTextos ◽  
2020 ◽  
Vol 16 (2) ◽  
Author(s):  
Juliana Maria Oliveira Silva ◽  
Marcelo De Oliveira Moura ◽  
Vinicius Ferreira Luna
Keyword(s):  
Data Collection ◽  
Air Temperature ◽  
Urban Climate ◽  
Temperature Data ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Heat Islands ◽  
Intensity Category ◽  
Urban Heat ◽  
The City

<p>A pesquisa pautou-se nas concepções do Sistema Clima Urbano de Monteiro (1976) e procurou identificar e mapear as ilhas de calor urbano na cidade do Crato-CE, em dois períodos sazonais do ano. Para isso, foram selecionados 10 pontos experimentais distribuídos em bairros na zona urbana da cidade, e aferiram-se dados de temperatura do ar com termohigrômetros instalados em abrigos meteorológicos durante os meses de abril (mês chuvoso) e outubro (mês seco). A partir da coleta de dados, a categoria predominante de intensidade das Ilhas de Calor intra e interurbana para a cidade do Crato foi o de ‘Média magnitude’. O horário que ocorre a maior intensidade da ilha de calor é pela tarde, 14h, com valores superiores a 5ºC de diferença de um local para o outro. Os bairros mais densamente ocupados e com baixa cobertura vegetal apresentaram os maiores valores de temperatura, enquanto que, nos que se localizam mais próximos da encosta da chapada e com vegetação mais densa, ocorreram as temperaturas mais amenas.</p><p>Abstract</p><p>URBAN HEAT ISLANDS IN CITY OF THE NORTHEAST SEMIARID</p><p>The research was based on the conceptions of the Monteiro Urban Climate System (1976) and sought to identify and map the urban heat islands in the city of Crato/ Ce in two seasonal periods of the year. For this, 10 experimental points were selected and distributed in neighborhoods in the urban area of the city and air temperature data was measured with thermohygrometers installed in meteorological shelters during the months of April (rainy month) and October (dry month). From the data collection, the predominant intensity category of the intra and interurban Heat Islands for the city of Crato was that of ‘Medium magnitude’. The time that occurs the greatest intensity of the heat island is in the afternoon, 14h, with values above 5ºC of difference from one place to another. The most densely occupied neighborhoods and with low vegetation cover had the highest temperature values, while those located closer to the slope of the plateau and with more dense vegetation, the milder temperatures occurred.</p>

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