scholarly journals A Study of Local Climate Zones in Abu Dhabi with Urban Weather Stations and Numerical Simulations

2019 ◽  
Vol 12 (1) ◽  
pp. 156 ◽  
Author(s):  
Prajowal Manandhar ◽  
Lindita Bande ◽  
Alexandros Tsoupos ◽  
Prashanth Reddy Marpu ◽  
Peter Armstrong

In many cities that have experienced rapid growth like Abu Dhabi, urban microclimate scenarios evolve rapidly as well and it is important to study the urban thermal dynamics continuously. The Local Climate Zone (LCZ) classification considers factors related to the physical properties like surface cover and surface structure of the city which allow to analyze urban heat flows. Abu Dhabi city is rapidly expanding and is characterized by highly heterogeneous types of built forms that comprise mainly of old mid-rise and modern high-rise buildings with varied degrees of vegetation cover in different parts of the city. The fact that it is a coastal city in a desert environment makes it quite unique. This paper presents an approach of studying urban heat flows in such heterogeneous setup. First, the city is classified into local climate zones using images acquired by Landsat Satellite. Numerical simulations are performed in the designated LCZs using a computational fluid dynamics software, Envi-met. The results of Envi-met are calibrated and validated using in-situ measurements across all four seasons. The calibrated models are then applied to study entire Abu Dhabi island across different seasons. The results indicate a clear presence of urban heat island (UHI) effect when averaged over the full day which is varying in different zones. The zones with high vegetation do not show large average UHI effect whereas the effect is significant in densely built zones. The study also validates previous observations on the inversion of UHI effect during the day and in terms of diurnal response.

2020 ◽  
Author(s):  
Ines Langer ◽  
Alexander Pasternack ◽  
Uwe Ulbrich

<p>Urban areas show higher nocturnal temperature comparing to rural areas, which is denoted by urban heat island. This effect can intensify the impact of global warming in urban areas especially during heat waves, that leads to higher energy demand for cooling the building and higher thermal stress for residents.  </p><p>The aim of this study is to identify the Urban Heat Island (UHI) effect during the heat spell 2018 and 2019 in order to calculated human thermal comfort for Berlin. Berlin, the capital city of Germany covers an area of 892km<sup>2</sup> and its population is growing, therefore more residential areas will be planned in future through higher building. The methodology of this research is to divide Berlin into Local Climate Zones (LCZ's) regarding the concept of Stewart & Oke (2012). Then to evaluate the accuracy of this concept using 30 microclimate stations. Estimating the magnitude of urban heat island and its seasonal changes in combination with human thermal perception in different LCZ during summer time is another objective of this research. </p><p>Ten LCZ's for Berlin were selected, as class 1 (compact high rise), class 3 (compact low rise), class 7 (lightweight low-rise), class C (bush, scrub), class E (bare rock or paved) and class F (bare soil or sand) don't exist in Berlin. Class A (dense trees) is with a fraction of 18.6% in a good agreement with the percentage of dense trees reported from the city administration of Berlin (18.4%), class G (water) has a coverage of 5.1% through our classification instead of 6.7% reported by the city administration. In summary, the LCZ 1-10 cover 59.3% (more than half) of the city area.</p><p>Regarding temperature measurements, which represent a hot summer day with calm wind and clear sky the difference of Local Climate Zones will be calculated and the temperature variability in every LCZ's regarding sky view factor values show the hot spot of the city.</p><p>The vulnerability of LCZ's to heat stress will be ranked and discussed regarding ventilation and other factors.</p><p> </p><p>Literature</p><p>Matzarakis, A. Mayer, H., Iziomon, M. (1999) Applications of a universal thermal index: Physiological equivalent temperature: Intern. J. of Biomet 43 (2), 76-84.</p><p>Stewart, I.D., Oke, T.R. (2012) Local climate zones for urban temperature studies. Bull. Amer. Meteor. Soc. 93 1879-1900. DOI: 10.1175/BAMS-D-11-00019.1.</p><p> </p>


2021 ◽  
Vol 13 (11) ◽  
pp. 6374
Author(s):  
Yang Lu ◽  
Jiansi Yang ◽  
Song Ma

Local climate zones (LCZs) emphasize the influence of representative geometric properties and surface cover characteristics on the local climate. In this paper, we propose a multi-temporal LCZ mapping method, which was used to obtain LCZ maps for 2005 and 2015 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), and we analyze the effects of LCZ changes in the GBA on land surface temperature (LST) changes. The results reveal that: (1) The accuracy of the LCZ mapping of the GBA for 2005 and 2015 is 85.03% and 85.28%, respectively. (2) The built type category showing the largest increase in area from 2005 to 2015 is LCZ8 (large low-rise), with a 1.01% increase. The changes of the LCZs also vary among the cities due to the different factors, such as the economic development level and local policies. (3) The area showing a warming trend is larger than the area showing a cooling trend in all the cities in the GBA study area. The main reasons for the warming are the increase of built types, the enhancement of human activities, and the heat radiation from surrounding high-temperature areas. (4) The spatial morphology changes of the built type categories are positively correlated with the LST changes, and the morphological changes of the LCZ4 (open high-rise) and LCZ5 (open midrise) built types exert the most significant influence. These findings will provide important insights for urban heat mitigation via rational landscape design in urban planning management.


Author(s):  
Chunhong Zhao

The Local Climate Zones (LCZs) concept was initiated in 2012 to improve the documentation of Urban Heat Island (UHI) observations. Despite the indispensable role and initial aim of LCZs concept in metadata reporting for atmospheric UHI research, its role in surface UHI investigation also needs to be emphasized. This study incorporated LCZs concept to study surface UHI effect for San Antonio, Texas. LCZ map was developed by a GIS-based LCZs classification scheme with the aid of airborne Lidar dataset and other freely available GIS data. Then, the summer LST was calculated based Landsat imagery, which was used to analyse the relations between LST and LCZs and the statistical significance of the differences of LST among the typical LCZs, in order to test if LCZs are able to efficiently facilitate SUHI investigation. The linkage of LCZs and land surface temperature (LST) indicated that the LCZs mapping can be used to compare and investigate the SUHI. Most of the pairs of LCZs illustrated significant differences in average LSTs with considerable significance. The intra-urban temperature comparison among different urban classes contributes to investigate the influence of heterogeneous urban morphology on local climate formation.


2020 ◽  
Vol 260 ◽  
pp. 114279 ◽  
Author(s):  
Xiaoshan Yang ◽  
Lilliana L.H. Peng ◽  
Zhidian Jiang ◽  
Yuan Chen ◽  
Lingye Yao ◽  
...  

Author(s):  
Lindita Bande ◽  
Prajowal Manandhar ◽  
Prashanth Marpu ◽  
Mohammad Al Battah

2020 ◽  
Vol 185 ◽  
pp. 107268 ◽  
Author(s):  
Max Anjos ◽  
Admir Créso Targino ◽  
Patricia Krecl ◽  
Gabriel Yoshikazu Oukawa ◽  
Rodrigo Favaro Braga

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jun Han ◽  
Jiatong Liu ◽  
Liang Liu ◽  
Yuanzhi Ye

Intensified due to rapid urbanization and global warming-induced high temperature extremes, the urban heat island effect has become a major environmental concern for urban residents. Scientific methods used to calculate the urban heat island intensity (UHII) and its alleviation have become urgent requirements for urban development. This study is carried out in Zhongshan District, Dalian City, which has a total area of 43.85 km2 and a 27.5 km-long coastline. The mono-window algorithm was used to retrieve the land surface temperatures (LSTs), employing Landsat remote sensing images, meteorological data, and building data from 2003, 2008, 2013, and 2019. In addition, the district was divided into local climate zones (LCZs) based on the estimated intensities and spatiotemporal variations of the heat island effect. The results show that, from 2003 to 2019, LCZs A and D shrank by 3.225 km2 and 0.395 km2, respectively, whereas LCZs B, C, and 1–6 expanded by 0.932 km2, 0.632 km2, and 2.056 km2, respectively. During this period, the maximum and minimum LSTs in Zhongshan increased by 1.365°C and 1.104°C, respectively. The LST and UHII levels of all LCZs peaked in 2019. The average LSTs of LCZs A–C increased by 1.610°C, 0.880°C, and 3.830°C, respectively, and those of LCZs 1–6 increased by 2°C–4°C. The UHIIs of LCZs A, C, and D increased by 0.730, 2.950, and 0.344, respectively, and those of LCZs 1–6 increased from 1.370–2.977 to 3.744–5.379. Overall, the regions with high LSTs are spatiotemporally correlated with high building densities. In this study, the land cover was then classified into four types (LCZs A–D) using visual interpretation and object-oriented classification, including forested land, low vegetation, bare ground, and water. Besides, the buildings were categorized as LCZs 1–6, which, respectively, represented low-density low-rises buildings, low-density high-rises buildings, low-density super high-rises buildings, high-density low-rises buildings, high-density high-rises buildings, and high-density super high-rises buildings.


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