Keywords

1 Introduction

The effect of climate change is becoming more prevalent as the city grows and make necessary provision for the increasing population. Urban Heat Island (UHI) appears to be an ongoing issue in big cities since the 1818 to 1925 as the result of continuous rapid economic activities in the urban area and is one of the major contributors to climate change [1,2,3,4]. Apart from the environmental degradation caused by UHI, poor thermal comfort, urban health problem, and high cooling loads are among other severe impact of this phenomenon which require closer attention and mitigation efforts from both professional planners and policy makers to achieve a sustainable urban environment [3,4,5,6,7,8,9].

The mitigation effort widely opens the opportunities for scholars to investigate the urban climate to map the alternatives of strategies and actions. This study justifies that microclimate modification is an essential component to form the UHI, besides it is also a uniform measure in assessing the urban energy balance [3, 10]. The micro-urban spaces between buildings generate urban heat generators through short and longwave radiation, surface heat storage, heat canopy, and anthropogenic heat [10]. As the most used variable in urban energy balance study, microclimate significantly affects indoor and outdoor thermal comfort. In general, modification of microclimate mainly focuses on the following variables; solar radiation, air temperature, air velocity, and relative humidity [11]. The main objective of the urban climate study is to minimize the microclimate modification that increases the UHI intensity, which would also reduce the thermal discomfort and demands of cooling loads. Therefore, the methodology of conditioning the microclimate modification is constantly explored. As each city is attached to its context in adapting to the regional climate, the approach frequently varies between one to another. This study however looks closer into the analysis of the most reliable approach to investigate the urban microclimate modeling of a dense tropical city through a comparison study.

2 Urban Microclimate Modeling

As the study on urban climate develops, Oke [12] as one of the pioneers in this area stressed three major methods in the UHI investigation; observation, theoretical, and modeling. As the focus of this study, the modeling method described as a ‘simplified presentation of reality to the current theory [13]. Atkinson [14] grouped UHI modeling into the following approaches; hardware, physical equation, and dynamical numerical. This study reviewed that the category outlined by Oke [15], Svensson et al. [16], and Voogt [7] is the most discussed and relevant in the UHI modeling are as follows; numerical, physical, and empirical.

The empirical modeling method is commonly used in early urban climate study. As the main focus, the UHI investigation was performed through conventional field observation. Empirical modeling was formed by the statistical field data that then formulated into mathematical equations [17, 18]. A significant study using empirical modeling in investigating the relationship between urban canyon geometry and UHI was conducted by Oke in 1981 [19]. From this study, Oke formulated that maximum intensity of UHI in canyon space is resulted by the geometry of high Height to Width (H/W) ratio and low Sky View Factor (SVF) value [11, 20], as shown in Eqs. 1 and 2. The formulas are used as the basic model in this study; particularly in closely investigate the urban temperature behavior in relation with the UHI scenario.

$${\text{dTmax}} = 7. 4 5+ 3. 9 7*\ln \left( {{\text{H}}/{\text{W}}} \right)$$
(1)
$${\text{dTmax}} = 1 5. 2 7{-} 1 3. 8 8*{\text{SVF}}$$
(2)

Physical modeling is an approach by using a scale model to represent the real scenario of urban features. Oke [19] was also among the ones to extends the empirical modeling to physical modeling. Numerical modeling applies the mathematical model into a computer simulation. The rapid development of computer technology provides solutions to the constrain of the both empirical and physical modeling approach. It simulates a more accurate and precise physical and climate features, as well as it eliminates the limitation of time, cost, and research variables Batty [21] strongly described that the computer modeling as comprehensive, detail, and allow planners to perform the more flexible hypothetical urban climate model. Bruse [22] was among the scholars that pioneered the urban climate study by developing the computer model.

The computer simulation as the form of numerical modeling is the recent approach mostly applied to study the complex and dense urban climate. Besides, computer simulation covers most of the urban climate modeling limitations. The computer simulation does not only analyze the existing urban climate scenario but also a hypothetical scenario that eliminates time challenges. Therefore, the computer simulation is a trend approach among planners and scholars to assess the relationship between urban physical features and climate variables to achieve the most effective planning decision [23,24,25,26].

Yet, there is no one particular software covers all of the microclimate or thermal comfort variables [27]. The rapid development and intense use of computer simulation in nowadays urban climate studies do not stop the effort of scholars to include investigation on its’ reliability to perform the current urban scenario with more complexity and meeting the contextual research objectives. The study of reliability or compatibility of the urban simulation tends to always perform to test the accuracy, effectiveness, and prediction of errors of the modeling approach. In short, the reliability of the numerical modeling is often performed by doing validation investigation with other modeling approaches. The example of the reliability study could be seen by comparing it with other simulation and field observations. In the context of this study, the reliability investigation seeks to closely analyze the gap of computer simulation results with the field data.

3 Methods

This study is an extended discussion of the previous study [28,29,30,31] that validates ENVI-met simulation through Oke’s model. The previous study aimed to confirm the reliability of the ENVI-met from the early empirical mathematical model. Thus, this study aims to elaborate on the reliability of the ENVI-met simulation by comparing it with the field observation data. This study investigates two sites of high rise residential urban blocks, situated in a dense city center of Kuala Lumpur, Malaysia. The first site is a 19 storey block (Flat Bandar Tasik Selatan) while the second site is a 15 storey block (Surya Magna). The building configuration in the two sites is a Courtyard Canyon, with the canyon feature in the middle of the courtyard. However, the direction of the canyon in Flat Bandar Tasik Selatan faces East-West while in Surya Magna faces North-South.

The field data observation was conducted on 15 June 2015, set in the middle of the courtyard. The 24-hours data was taken by using the VelociCalc Plus 10 cm from the surface. This study presents data analysis of one of the three microclimate variables; air temperature. With the existing scenario, this study investigated four urban configurations; Courtyard, U configuration, Courtyard Canyon, and Canyon. The Sky View Factor (SVF) varies in each configuration while the Height to Width (H/W) aspect ratio remains constant. The simulation used ENVI-met V.3. The climate data was inserted in the ENVI-met simulation configuration editor are as follow: the initial temperature and inside temperature are 303.15 K and 293 K; relative humidity is 83%; albedo of walls and roofs are 0.3 and 0.5; the wind speed and direction are 1.4 m/s and 225 (South West to North East), and heat transmission wall and roofs are 1.94 W/m2 K and 6 W/m2 K). This study used the 250 × 250 × 30 size of simulation sections as the output data.

4 Results Discussion

This urban configuration and microclimate investigation presented the validation study [31]. It justified the air temperature behavior within the canyon space from the UHI model. It compared Oke’s Model (Eqs. 1 and 2) and ENVI-met simulation. The results (Tables 1 and 2) pointed out that the drop of diurnal to nocturnal air temperature developed as the SVF value increases. This situation was as presented by dTmax in Oke’s model, the UHI intensities were lower when the SVF value increases. Through comparison with the Oke’s model as the empirical modeling, the results validated that Envi-met urban simulation was a suitable approach for this study.

Table 1 Comparison of Oke’s model and Envi-met: East–West
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Table 2 Comparison of Oke’s model and Envi-met: North–South
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The further reliability study on the simulation approach is presented in this paper. The results of this reliability study are also discussed according to the microclimate data from each case site. Overall, regression analysis on the two case sites of Flat Bandar Tasik Selatan (FBTS) and Surya Magna (SM) shows the significant correlations between the two discussed empirical and numerical approaches (Table 3). However, the analysis indicates the small gap between the simulated and observed microclimate data. This situation is due to the unrecorded variables in the existing scenario that was not recorded in the simulation. Among the variables are building material properties, anthropogenic heat from vehicles and air conditioning, green area, and other vertical obstructions in sites.

Table 3 Microclimate regression analysis of observation and simulation
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The significant correlation findings from regression analysis point out that the computer simulation and field observation are both valid approaches to study the microclimate study. Specifically, this study stresses that the computer simulation presents the identical pattern of result with the field observation with the tolerable margin error. In the context of this study, the field observation data validates the ENVI-met simulation as an effective tool of the numerical approach to investigate the microclimate in the dense urban configurations.

5 Conclusions

The development of urban climate study is a part of the positive response to numerous effects of climate change which requires urgent attention from both city planner and policy makers. Thus, understanding valid approach(es) to reliably explore the implications of urban growth and the resulting challenges is an essential stage in urban climate study development. This will provide a range of opportunities to generate comprehensive strategies to address climate change mitigation actions. The regression analysis was adopted in this study to investigate the correlation between the empirical and numerical approach, by comparing the results of the observed and simulated microclimate data of a hypothetical urban configuration in dense tropical residential site contexts. The results showed a significant correlation between the two approaches. The finding shows that ENVI-met simulation provides a strongly reliable results in the assessment of urban microclimate variables. It can also be inferred for the present study that the reliability of these results is due to ENVI-met efficiency, the available features, and the level of accuracy the technology brought to bear in modelling both two and three-dimension urban climate data. Finally, ENVI-met offers the opportunity to model a hypothetical urban configuration which is a limitation of other empirical modelling methods. Therefore, this study provides a scientific justification and the reliability of the results and hence strongly recommend the ENVI-met as an alternative approach in urban climate study.