scholarly journals Climate change over UK cities: the urban influence on extreme temperatures in the UK climate projections

2021 ◽  
Author(s):  
William J. Keat ◽  
Elizabeth J. Kendon ◽  
Sylvia I. Bohnenstengel
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Climate Model ◽  
Climate Projections ◽  
Heat Island ◽  
Night Time ◽  
Urban Heat ◽  
The Uk

AbstractIncreasing summer temperatures in a warming climate will increase the exposure of the UK population to heat-stress and associated heat-related mortality. Urban inhabitants are particularly at risk, as urban areas are often significantly warmer than rural areas as a result of the urban heat island phenomenon. The latest UK Climate Projections include an ensemble of convection-permitting model (CPM) simulations which provide credible climate information at the city-scale, the first of their kind for national climate scenarios. Using a newly developed urban signal extraction technique, we quantify the urban influence on present-day (1981–2000) and future (2061–2080) temperature extremes in the CPM compared to the coarser resolution regional climate model (RCM) simulations over UK cities. We find that the urban influence in these models is markedly different, with the magnitude of night-time urban heat islands overestimated in the RCM, significantly for the warmest nights (up to $$4~^{\circ }$$ 4 ∘ C), while the CPM agrees much better with observations. This improvement is driven by the improved land-surface representation and more sophisticated urban scheme MORUSES employed by the CPM, which distinguishes street canyons and roofs. In future, there is a strong amplification of the urban influence in the RCM, whilst there is little change in the CPM. We find that future changes in soil moisture play an important role in the magnitude of the urban influence, highlighting the importance of the accurate representation of land-surface and hydrological processes for urban heat island studies. The results indicate that the CPM provides more reliable urban temperature projections, due at least in part to the improved urban scheme.

scholarly journals Urban Thermal Environment and Heat Island in Ho Chi Minh City, Vietnam from Remote Sensing Data

2017 ◽  
Author(s):  
Van Tran Thi ◽  
Bao Ha Duong Xuan ◽  
Mai Nguyen Thi Tuyet
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Ho Chi Minh City ◽  
Heat Island ◽  
Urban Heat ◽  
Surface Urban Heat Island ◽  
The Impact

In urban area, one of the great problem is the rise of temperature, which leads to form the urban heat island effect. This paper refers to the trend of the urban surface temperature extracted from the Landsat images from which to consider changes in the formation of surface urban heat island for the north of Ho Chi Minh city in period 1995-2015. Research has identified land surface temperature from thermal infrared band, according to the ability of the surface emission based on characteristics of normalized difference vegetation index NDVI. The results showed that temperature fluctuated over the city with a growing trend and the gradual expansion of the area of the high-temperature zone towards the suburbs. Within 20 years, the trend of the formation of surface urban heat island with two typical locations showed a clear difference between the surface temperature of urban areas and rural areas with space expansion of heat island in 4 times in 2015 compared to 1995. An extreme heat island located in the inner city has an area of approximately 18% compared to the total area of the region. Since then, the solution to reduce the impact of urban heat island has been proposed, in order to protect the urban environment and the lives of residents in Ho Chi Minh City becoming better

scholarly journals SPATIAL VARIATION OF URBAN HEAT ISLAND INTENSITY IN URBAN CITIES USING MODIS SATELLITE DATA

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 147-151 ◽  
Author(s):  
R. Bala ◽  
R. Prasad ◽  
V. P. Yadav ◽  
J. Sharma
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Linear Relation ◽  
Urban Areas ◽  
Heat Island ◽  
Night Time ◽  
Natural Land ◽  
Urban Cool Island ◽  
Urban Heat ◽  
Positive Linear Relation

Abstract. Urban Heat Island (UHI) refers to the occurrence of higher temperatures in urban areas than the neighbouring rural areas. The neighbouring land cover also has some influence on the urban temperatures. The present study focuses on the UHI effect observed in four different cities i.e. Bikaner, Hyderabad, Vadodara and Varanasi which were surrounded by different natural land covers using MODIS satellite images. Bikaner shows Urban Cool Island (UCI) and Varanasi show UHI during day time. Vadodara and Hyderabad do not show much variation in urban and rural LST during day time. However, UHI effect was found clearly significant during night time in the four cities. UHI intensity was calculated using night LST and found highest in Hyderabad and lowest in Bikaner. The relation of LST with % Impervious was studied which shows good positive linear relation when significant UHI effect was observed and negative linear relation when UCI effect was observed. The slope obtained from linear regression of night LST with % Impervious was compared with the UHI intensity in the four cities and found to show good positive linear relation. Therefore, % Impervious can be used to quantify UHI intensity in urban areas.

scholarly journals Surface Urban Heat Islands Dynamics in Response to LULC and Vegetation across South Asia (2000–2019)

2021 ◽  
Vol 13 (16) ◽  
pp. 3177
Author(s):  
Talha Hassan ◽  
Jiahua Zhang ◽  
Foyez Ahmed Prodhan ◽  
Til Prasad Pangali Sharma ◽  
Barjeece Bashir
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Thermal Environment ◽  
Urban Heat Islands ◽  
Heat Island ◽  
Heat Islands ◽  
Urban Heat

Urbanization is an increasing phenomenon around the world, causing many adverse effects in urban areas. Urban heat island is are of the most well-known phenomena. In the present study, surface urban heat islands (SUHI) were studied for seven megacities of the South Asian countries from 2000–2019. The urban thermal environment and relationship between land surface temperature (LST), land use landcover (LULC) and vegetation were examined. The connection was explored with remote-sensing indices such as urban thermal field variance (UTFVI), surface urban heat island intensity (SUHII) and normal difference vegetation index (NDVI). LULC maps are classified using a CART machine learning classifier, and an accuracy table was generated. The LULC change matrix shows that the vegetated areas of all the cities decreased with an increase in the urban areas during the 20 years. The average LST in the rural areas is increasing compared to the urban core, and the difference is in the range of 1–2 (°C). The SUHII linear trend is increasing in Delhi, Karachi, Kathmandu, and Thimphu, while decreasing in Colombo, Dhaka, and Kabul from 2000–2019. UTFVI has shown the poor ecological conditions in all urban buffers due to high LST and urban infrastructures. In addition, a strong negative correlation between LST and NDVI can be seen in a range of −0.1 to −0.6.

scholarly journals Comparasion of NDBI and NDVI as Indicators of Surface Urban Heat Island Effect in Landsat 8 Imagery: A Case Study of Iasi

2017 ◽  
Vol 11 (2) ◽  
pp. 141-150 ◽  
Author(s):  
Paul Macarof ◽  
Florian Statescu
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Heat Island ◽  
Sensing Technology ◽  
Urban Heat ◽  
Surface Urban Heat Island

Abstract This study compares the normalized difference built-up index (NDBI) and normalized difference vegetation index (NDVI) as indicators of surface urban heat island effects in Landsat-8 OLI imagery by investigating the relationships between the land surface temperature (LST), NDBI and NDVI. The urban heat island (UHI) represents the phenomenon of higher atmospheric and surface temperatures occurring in urban area or metropolitan area than in the surrounding rural areas due to urbanization. With the development of remote sensing technology, it has become an important approach to urban heat island research. Landsat data were used to estimate the LST, NDBI and NDVI from four seasons for Iasi municipality area. This paper indicates than there is a strong linear relationship between LST and NDBI, whereas the relationship between LST and NDVI varies by season. This paper suggests, NDBI is an accurate indicator of surface UHI effects and can be used as a complementary metric to the traditionally applied NDVI.

Emergence of opposite trends in daytime and night-time urban heat island intensities in England

2020 ◽  
Author(s):  
Eunice Lo ◽  
Dann Mitchell ◽  
Sylvia Bohnenstengel ◽  
Mat Collins ◽  
Ed Hawkins ◽  
...  
Keyword(s):  
Urban Heat Island ◽  
Urban Areas ◽  
Urban Land Use ◽  
Urban Heat Islands ◽  
Urban Heat Island Effect ◽  
Heat Island ◽  
Night Time ◽  
Heat Islands ◽  
Island Effect ◽  
Urban Heat

<p>Urban environments are known to be warmer than their sub-urban or rural surroundings, particularly at night. In summer, urban heat islands exacerbate the occurrence of extreme heat events, posing health risks to urban residents. In the UK where 90% of the population is projected to live in urban areas by 2050, projecting changes in urban heat islands in a warming climate is essential to adaptation and urban planning.</p><p>With the use of the new UK Climate Projections (UKCP18) in which urban land use is constant, I will show that both summer urban and sub-urban temperatures are projected to increase in the 10 most populous built-up areas in England between 1980 and 2080. However, differential warming rates in urban and sub-urban areas, and during day and at night suggest a trend towards a reduced daytime urban heat island effect but an enhanced night-time urban heat island effect. These changes in urban heat islands have implications on thermal comfort and local atmospheric circulations that impact the dispersion of air pollutants. I will further demonstrate that the opposite trends in daytime and night-time urban heat island effects are projected to emerge from current variability in more than half of the studied cities below a global mean warming of 3°C above pre-industrial levels.</p>

scholarly journals Weather Pattern Classification to Represent the Urban Heat Island in Present and Future Climate

2013 ◽  
Vol 52 (12) ◽  
pp. 2699-2714 ◽  
Author(s):  
Peter Hoffmann ◽  
K. Heinke Schlünzen
Keyword(s):  
Urban Heat Island ◽  
Climate Model ◽  
Global Climate Model ◽  
Limited Area ◽  
Climate Projections ◽  
Heat Island ◽  
Cluster Number ◽  
Statistical Measures ◽  
Urban Heat ◽  
Optimal Cluster

AbstractA classification of weather patterns (WP) is derived that is tailored to best represent situations relevant for the urban heat island (UHI). Three different types of k-means-based cluster methods are conducted. The explained cluster variance is used as a measure for the quality. Several variables of the 700-hPa fields from the 40-yr ECMWF Re-Analysis (ERA-40) were tested for the classification. The variables as well as the domain for the clustering are chosen in a way to explain the variability of the UHI as best as possible. It turned out that the combination of geopotential height, relative humidity, vorticity, and the 1000–700-hPa thickness is best suited. To determine the optimal cluster number k several statistical measures are applied. Except for autumn (k = 12) an optimal cluster number of k = 7 is found. The WP frequency changes are analyzed using climate projections of two regional climate models (RCM). Both RCMs, the Regional Model (REMO) and Climate Limited-Area Model (CLM), are driven with the A1B simulations from the global climate model ECHAM5. Focusing on the periods 2036–65 and 2071–2100, no change can be found of the frequency for the anticyclonic WP when compared with 1971–2000. Since these WPs are favorable for the development of a strong UHI, the frequency of strong UHI days stays the same for the city of Hamburg,Germany. For other WPs changes can be found for both future periods. At the end of the century, a large increase (17%–40%) in the frequency of the zonal WP and a large decrease (20%–26%) in the southwesterly WP are projected.

scholarly journals Quantification of Urban Heat Island-Induced Contribution to Advance in Spring Phenology: A Case Study in Hangzhou, China

2021 ◽  
Vol 13 (18) ◽  
pp. 3684
Author(s):  
Yingying Ji ◽  
Jiaxin Jin ◽  
Wenfeng Zhan ◽  
Fengsheng Guo ◽  
Tao Yan
Keyword(s):  
Surface Temperature ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Heat Island ◽  
Spring Phenology ◽  
Urban Heat ◽  
The Difference

Plant phenology is one of the key regulators of ecosystem processes, which are sensitive to environmental change. The acceleration of urbanization in recent years has produced substantial impacts on vegetation phenology over urban areas, such as the local warming induced by the urban heat island effect. However, quantitative contributions of the difference of land surface temperature (LST) between urban and rural (ΔLST) and other factors to the difference of spring phenology (i.e., the start of growing season, SOS) between urban and rural (ΔSOS) were rarely reported. Therefore, the objective of this study is to explore impacts of urbanization on SOS and distinguish corresponding contributions. Using Hangzhou, a typical subtropical metropolis, as the study area, vegetation index-based phenology data (MCD12Q2 and MYD13Q1 EVI) and land surface temperature data (MYD11A2 LST) from 2006–2018 were adopted to analyze the urban–rural gradient in phenology characteristics through buffers. Furthermore, we exploratively quantified the contributions of the ΔLST to the ΔSOS based on a temperature contribution separation model. We found that there was a negative coupling between SOS and LST in over 90% of the vegetated areas in Hangzhou. At the sample-point scale, SOS was weakly, but significantly, negatively correlated with LST at the daytime (R2 = 0.2 and p < 0.01 in rural; R2 = 0.14 and p < 0.05 in urban) rather than that at nighttime. Besides, the ΔSOS dominated by the ΔLST contributed more than 70% of the total ΔSOS. We hope this study could help to deepen the understanding of responses of urban ecosystem to intensive human activities.

scholarly journals Evaluating the roles of green and built-up areas in reducing a surface urban heat island using remote sensing data

Urbani izziv ◽  
2019 ◽  
Vol 2 (30) ◽  
pp. 105-112
Author(s):  
Gordana Kaplan
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Heat Island ◽  
Negative Effects ◽  
Rapid Urbanization ◽  
Green Areas ◽  
Urban Heat ◽  
Surface Urban Heat Island

Rapid urbanization has several negative effects on both the environment and human health. Urbanization has also become an important contributor to global warming. One of these effects is the urban heat island (UHI), which is caused by human activities and defined as the temperature difference between urban and surrounding rural areas. With rapid urbanization in the past few decades, Skopje has experienced remarkable UHI effects. To investigate the roles of built-up and green areas in a surface UHI, this article uses satellite data from Landsat ETM+ to analyse the land surface temperature and high-resolution Planet Scope DOVE data to analyse built-up and green areas. For geostatistical analyses, seventeen randomly selected subareas in Skopje were used. The results show a significant correlation between the UHI and built-up areas, and strong correlation between green areas and areas not affected by the UHI, indicating that the UHI effect can be significantly weakened with additional green areas. One of the significant findings in the study is the ideal proportion of built-up (40%) and green areas (60%), where the UHI effect is weak, or in some cases prevented. For future studies, investigating other factors that may contribute to the UHI phenomenon is suggested.

scholarly journals Changes in Urbanization and Urban Heat Island Effect in Dhaka City

2021 ◽  
Author(s):  
A S M Shanawaz Uddin ◽  
Najeebullah Khan ◽  
Abu Reza Md. Towfiqul I ◽  
Mohammad Kamruzzaman ◽  
Shamsuddin Shahid
Keyword(s):  
Urban Heat Island ◽  
Land Surface ◽  
Urban Areas ◽  
Clustering Algorithm ◽  
Planning Process ◽  
Urban Expansion ◽  
Heat Island ◽  
Dhaka City ◽  
Urban Heat ◽  
The City

Abstract Urbanization changes the local environment, resulting in urban heat island (UHI) effect and deteriorating human life quality. Knowledge of urban environments and temperature changes is important to outline the urban planning process for mitigation of UHI effect. The study aimed to assess the changes in urban areas and UHI effects in Dhaka city, Bangladesh from 2001to 2017, using Moderate Resolution Imaging Spectroradiometer (MODIS) daily day- and nighttime land surface temperature (LST) data from 2001to 2017. The expansion of the city was calculated using the city clustering algorithm (CCA). The temperature of the identified urbanized area was analyzed and compared with the adjacent regions. The changes in urban temperature were estimated using non-parametric statistical methods. The results showed that the Dhaka city area has grown by 19.12% and its inhabitants by 76.65% during 2001–2017. Urban expansion and dense settlements caused an increase in average temperature in some areas of Dhaka city nearly 3°C compared to that at its boundary. The day and night temperatures at Dhaka city's warmest location were nearly 7 and 5ºC, respectively, more than the coolest point outside the city. The city's annual average day- and nighttime temperature was increasing at a rate of 0.03° and 0.023°C/year over the period 2001–2017. The rising temperature would increase the UHI effect in the future, which combined with high humidity, may cause a significant increase in public health risk in the city if mitigation practices are not followed.

scholarly journals The urban heat island effect is closely related to cicada density in metropolitan Seoul

2017 ◽  
Author(s):  
Hoa Q. Nguyen ◽  
Yuseob Kim ◽  
Yikweon Jang
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Urban Areas ◽  
Underlying Mechanism ◽  
Heat Island ◽  
Population Densities ◽  
Island Effect ◽  
Significant Difference ◽  
Order Of Magnitude ◽  
Urban Heat

Background. Cryptotympana atrata and Hyalessa fuscata are the most abundant cicada species in the Korean Peninsula, where their population densities are higher in urban areas than in rural ones. The urban heat island (UHI) effect, wherein human activities cause urban areas to be significantly warmer than surrounding rural areas, may underlie this difference. We predicted a positive relationship between the degrees of UHI in urban areas and population densities of C. atrata and H. fuscata. Methods. To test this prediction, we examined cicada population densities in three groups: those of high and low UHI areas within metropolitan Seoul, and suburban areas. Enumeration surveys of cicada exuviae were conducted from July to August, 2015. Results. C. atrata and H. fuscata constituted almost 30% and 70% of the cicada populations, respectively, collected across all sampling localities. No significant difference in species composition was observed, regardless of groups, but the densities of the two species were significantly higher in urban areas with high UHI than in other groups. Specifically, densities of C. atrata in high UHI areas were approximately seven and four times higher compared to those in low UHI and in suburban groups, respectively. The order of magnitude was greater in H. fuscata, where densities in high UHI group were respectively 22 and six times higher than those in low UHI and in suburban groups. Discussion. These results suggest that the UHI effect may be closely linked to high cicada densities in metropolitan Seoul, although the underlying mechanism for this remains unclear.

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