scholarly journals Multi-annual variability of summertime atmospheric and surface urban heat island in Kraków, Poland

2021 ◽  
Author(s):  
Monika J. Hajto ◽  
Anita Bokwa
Keyword(s):  
Spatial Distribution ◽  
Urban Heat Island ◽  
Spatial Resolution ◽  
Heat Load ◽  
Detailed Knowledge ◽  
Heat Island ◽  
Diurnal Variability ◽  
Urban Heat ◽  
The Relationship ◽  
The City

<p>The urban heat island (UHI) effect is primarily related to the atmosphere, but may also refer to the surfaces. The atmospheric UHI (AUHI), determined using air temperature (Tair), and the surface UHI (SUHI), assessed using land surface temperature (LST), are distinguished. There is undoubtedly a relationship between SUHI and AUHI due to the modulation of Tair by LST. On hot days in the summer months, the SUHI/AUHI effect may increase the heat load, which is dangerous to the health and comfort of people staying in the city. Detailed characteristics of the spatial distribution of Tair and LST in urban areas are required to identify the parts of the city with the highest heat load. Spatially continuous Tair data, enabling better characterizing AUHI, can be obtained by modelling. Satellite thermal data (LST) can be used as input to the Tair spatial distribution model. Satellite data with 1 km spatial resolution, due to availability several times a day, are most useful in characterizing SUHI diurnal variability and the relationship of LST with Tair. The detailed knowledge of LST and Tair correlation should be helpful in the development of the Tair estimation algorithm based on the LST values. Better recognition of the relationship between LST and Tair, and thus improving the quality of modelling the spatial distribution of Tair in urban area, can possibly be achieved through downscaling of LST data to higher spatial resolution. In the study the method of LST downscaling from 1 km to 100 m was developed, using LST derived from AVHRR, Landsat, ASTER and ECOSTRESS data. The LST-Tair correlation in the diurnal course was examined and the influence of LST downscaling on the correlation was assessed. A Tair regression model was developed based on LST, depending on local climate zone (LCZ). LST and Tair maps for Kraków and its vicinities were prepared, and on the basis of them the intensities of AUHI and SUHI in the multi-year period (2010-2019) in the summer months (June, July, August) were determined, separately for day and night.</p>

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 SPATIAL AND TEMPORAL CHANGE ANALYSIS OF URBAN HEAT ISLAND EFFECT IN WUHAN CITY

2020 ◽  
Vol XLII-3/W10 ◽  
pp. 705-712
Author(s):  
M. H. Huang ◽  
J. J. Chen
Keyword(s):  
Spatial Distribution ◽  
Urban Heat Island ◽  
Vegetation Cover ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
City Center ◽  
Wuhan City ◽  
Island Effect ◽  
Urban Heat ◽  
The City

Abstract. China has experienced rapid urbanization and rapid development of economy in the past decades, resulting in severe damage to the urban ecological environment, causing changes in the urban thermal environment and triggering the urban heat island effect. Moreover, the heat island effect has become a hot topic for scholars. The urban heat island effect refers to the phenomenon that the urban surface temperature is significantly higher than that of surrounding suburbs due to the interaction of man-made and natural. The city is considered to be the largest man-made ecosystem. Its heat island effect will not only change the growth habit of urban vegetation， but also affect the outer environment of urban buildings, it further influences human life and has a great negative impact on human health. Therefore, the study of the spatial-temporal variation characteristics of urban heat island effect and its influencing factors can provide data support for the environmental quality control and urban planning of local government departments. Based on the surface temperature remote sensing product data, we studied the spatial distribution characteristics of urban heat island effect in Wuhan from 2001 to 2013, by calculating the temperature difference between the highest and lowest temperatures and the average interval method for heat island classification. We conducted a trend analysis of vegetation cover from 2001 to 2013 initially explore the effects of vegetation cover n heat island effect. The results showed that: (1) From 2001 to 2013, the intensity of heat island in Wuhan was strong in the city center, weaker surrounding city center and the weakest in the suburbs; From 2001 to 2011, the intensity of heat island in Wuhan city was significantly weaken, among which Huangpi, Xinzhou, Jiangxia, Hannan and Caidian district were weaken, and the urban heat island effect of the city center was enhanced; From 2011 to 2013, the intensity of heat island in Wuhan city presented an increasing trend, among which Huangpi district, Xinzhou district and Caidian district were the most obvious, and the urban heat island effect was slightly weaken. (2) Between 2001 and 2013, the vegetation cover in Huangpi district and Xinzhou district increased significantly, and the vegetation cover in the downtown, Jiangxia district and Dongxihu district decreased significantly, corresponding to the urban heat island effect of Wuhan increased volatility. Our results showed that the spatial distribution of urban heat island effect in Wuhan city fluctuated with time during the study period, and the vegetation cover had a significant influence on it.

Evaluating the spatial distribution and the intensity of urban heat island using remote sensing, case study of Isfahan city in Iran

2019 ◽  
Vol 45 ◽  
pp. 686-692 ◽  
Author(s):  
Niloufar Shirani-bidabadi ◽  
Touraj Nasrabadi ◽  
Shahrzad Faryadi ◽  
Adnan Larijani ◽  
Majid Shadman Roodposhti
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Urban Heat Island ◽  
Heat Island ◽  
Urban Heat

scholarly journals Urban "Heat-Island Effect" and its Connection with Architectural and Climatic Features on the Example of Poltava

2018 ◽  
Vol 7 (3.2) ◽  
pp. 597
Author(s):  
Yuri Golik ◽  
Oksana Illiash ◽  
Nataliia Maksiuta
Keyword(s):  
Urban Heat Island ◽  
Traditional Method ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Island Effect ◽  
Temperature Regimes ◽  
Architectural Features ◽  
Urban Heat ◽  
The Given ◽  
The City

The concept of "heat-island effect", its structure and features of formation over the city are given. The climatic and other features of the city that influence the formation of this phenomenon are mentioned.  The data on functioning in the city of the municipal production enterprise of the heat economy is indicated. The traditional method for determining the formation of the urban "heat-island effect" is described. The data and comparative graphs on the temperature regimes of the city and region are presented. The possibility of influencing architectural features of the city on the formation of the "heat-island-effect" is determined. According to the obtained results, further integrated researches are proposed for obtaining reliable results of the given question. 

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 Solar Irradiance Reduction Using Optimized Green Infrastructure in Arid Hot Regions: A Case Study in El-Nozha District, Cairo, Egypt

2021 ◽  
Vol 13 (17) ◽  
pp. 9617 ◽  
Author(s):  
Wesam M. Elbardisy ◽  
Mohamed A. Salheen ◽  
Mohammed Fahmy
Keyword(s):  
Climate Change ◽  
Urban Heat Island ◽  
Green Infrastructure ◽  
Solar Irradiance ◽  
Urban Trees ◽  
Heat Island ◽  
Physiological Equivalent Temperature ◽  
Urban Climatology ◽  
Urban Heat ◽  
The City

In the Middle East and North Africa (MENA) region, studies focused on the relationship between urban planning practice and climatology are still lacking, despite the fact that the latter has nearly three decades of literature in the region and the former has much more. However, such an unfounded relationship that would consider urban sustainability measures is a serious challenge, especially considering the effects of climate change. The Greater Cairo Region (GCR) has recently witnessed numerous serious urban vehicular network re-development, leaving the city less green and in need of strategically re-thinking the plan regarding, and the role of, green infrastructure. Therefore, this study focuses on approaches to the optimization of the urban green infrastructure, in order to reduce solar irradiance in the city and, thus, its effects on the urban climatology. This is carried out by studying one of the East Cairo neighborhoods, named El-Nozha district, as a representative case of the most impacted neighborhoods. In an attempt to quantify these effects, using parametric simulation, the Air Temperature (Ta), Mean Radiant Temperature (Tmrt), Relative Humidity (RH), and Physiological Equivalent Temperature (PET) parameters were calculated before and after introducing urban trees, acting as green infrastructure types that mitigate climate change and the Urban Heat Island (UHI) effect. Our results indicate that an optimized percentage, spacing, location, and arrangement of urban tree canopies can reduce the irradiance flux at the ground surface, having positive implications in terms of mitigating the urban heat island effect.

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