MATEC Web of Conferences 4 7, 0 4 0 05 (2016 )
DOI: 10.1051/ m atecconf/ 2016 47 0 4 0 05
C Owned by the authors, published by EDP Sciences, 2016
Assessment of Outdoor Thermal Comfort and Wind
Characteristics at Three Different Locations in Peninsular
Malaysia
1,a
1
2
1
Mohd Hafizal Hanipah , Abd Halid Abdullah , Nor Azwadi Che Sidik , Riduan Yunus , Mohd Nor
1
2
Azam Yasin and Muhammad Noor Afiq Witri Muhammad Yazid
1
Faculty of Civil and Environmental Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Batu Pahat, Johor
Malaysia
2
Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
Abstract. Urbanization and rapid growth in construction have led to the problems of global
warming and urban heat island throughout the world. In order to reduce these problems
particularly in hot and humid climatic region, a research on current level of outdoor thermal
comfort and wind characteristics based on the local weather conditions around Malaysia should
be conducted. This paper reports on the analysis of outdoor thermal comfort level at hottest
temperatures and wind characteristics at three locations in Peninsular Malaysia by using hourly
climatic data recorded by Malaysian Meteorological Department (MetMalaysia). The level of
outdoor thermal comfort was assessed based on the Universal Thermal Climate Index (UTCI).
The results showed extreme heat stress conditions have occurred at Alor Setar, Kuantan, and
Subang with UTCI values of 51.2°C, 49.7°C, and 49.0°C respectively taking into account only
temperature data from the year 2012 to 2014. However, for 20 years data from 1994 to 2014,
the calculated UTCI also showed extreme heat stress conditions with their respective values of
49.6°C, 43.8°C, and 49.7°C for Alor Setar, Kuantan, and Subang respectively. Meanwhile, the
hourly mean wind speed for three years data at Alor Setar, Kuantan, and Subang, were 1.70m/s,
1.69m/s, and 1.63m/s respectively. The highest mean wind speed of 11.6m/s was observed at
Subang, while no wind movement (i.e. 0m/s) was considered to be the lowest hourly wind
speed for all three locations. The observed prevailing wind direction for all the three locations
was from the north (0°). It can be concluded that Peninsular Malaysia is generally facing
extreme heat stress problem due to unfavourable climatic conditions.
1 Introduction
Global warming and urban heat island have become major concerns in developed and developing
countries throughout the world [1-3]. Inevitably, Malaysia has also been facing this heat stress and
thermal comfort problems [4-6]. The yearly mean temperature for Central Peninsular Malaysia for the
period of 1969-2014 shows an increment of 0.35°C per decade [7]. The warmer urban climate may
have some negative impacts towards people outdoor thermal comfort in Malaysia. Major problem
such as urban heat island can directly affect the outdoor human thermal comfort level. Currently in
a
Corresponding author : hafizal@uthm.edu.my
4
MATEC Web of Conferences
Malaysia, there is very limited research being conducted on these issues with regard to building
construction and urban development. It is even more critical as the building arrangement parameters
such as packing density (λp), frontal area density (λf), height-to-width ratio (λs) etc [2,8-10] have not
been considered during earlier stage of urban design. Therefore, the primary aim of this research study
is to determine current extreme outdoor thermal comfort index and wind characteristics. For future
studies, factors affecting outdoor thermal comfort in urban areas, and dominant building arrangement
parameters in hot humid climate will be examined.
2 Study Area
In general, Malaysia is a South East Asian country which is located in the equatorial zone. The
geographic coordinate is 2°30’ in the north latitude and 112°30’ in the east longitude. Throughout the
year, Malaysia experiences a wet and humid condition with daily temperature ranging from about
24°C to 38°C [7]. Wind speed and wind direction across the Peninsular Malaysia are influenced by the
monsoon seasons, namely southwest monsoon, northeast monsoon and two short inter-monsoons.
Figure 1. Map of Peninsular Malaysia showing the case study stations.
The wind speed range is below 8m/s during southwest monsoon season, and 5m/s to 10m/s for
northeast monsoon season. While during inter-monsoons, the wind is generally light and variable.
Malaysia has high humidity where the monthly mean relative humidity is ranging from 70% to 90%
throughout the year varying from different places and times. In addition, Malaysia receives about 6
hours of sunshine per day on average [7]. For this study, three different locations or cities around
Peninsular Malaysia were chosen; which include Alor Setar (i.e. Northern region), Kuantan (i.e. East
Coast region facing the South China Sea), and Subang (i.e. Central region) as shown in Figure 1 and
stated in Table 1. The weather data representing the hot and humid tropical climate of Malaysia from
three principal weather stations namely Alor Star, Kuantan, and Subang were utilized to investigate
outdoor thermal comfort conditions and wind characteristics of the three respective locations
mentioned earlier.
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Table 1. Location of wind speed stations used in the study.
Station
Latitude
Longitude
Alor Setar
Kuantan
Subang
6° 12' N
3° 46' N
3° 08' N
100° 24' E
103° 13' E
101° 33' E
Height above
sea level (m)
3.90
15.20
16.60
3 Methods
The hourly data for wind speed and direction within the three years period of 2012-2014 were
obtained from the MetMalaysia. The hottest temperature of the day for the past 20 years from 19942014 were also obtained and analyzed. At all the selected weather stations, wind speed and direction
were measured using the anemometer and wind vane which were installed at the height of 10 m. The
instrument used for measuring the surface wind speed is rotating cup type anemometer where the cups
are mounted symmetrically at right angle to a vertical shaft. Installing the anemometer at 10m height
is in accordance to ref. [11], which is basically for climatological and practical reason. It has been
agreed that this elevation should be the standard meteorological reference level. The data on wind
speed and direction were taken at 1 hour interval and stored in a data logger. The hourly wind speed
and direction data for three years were analyzed in order to investigate the wind characteristics. The
hottest ambient temperatures were analyzed and calculated to get UTCI values. In this study, UTCI
was calculated by a program based on regression equation which is devised by International Society
of Biometeorology Commission 6 by COST (European Cooperation in Science and Technology)
Action 730 under the umbrella of the WMO Commission on Climatology [12]. The weather
parameters, which include value of ambient temperature (°C), solar radiation (W/m2), relative
humidity (%), and wind speed (m/s) are required for the calculation of UTCI (°C) [13].
4 Universal Thermal Climate Index (UTCI)
The UTCI is divided into 10 different stress levels which comprise no thermal stress, 4 heat stress
levels, and 5 cold stress levels [14]. UTCI is stated as the equivalent ambient temperature of a
reference environment that causes the same physiological response of a reference person as would the
actual environment [15]. It is based on Fiala multi-node model [16] of human thermal regulation in
combination with an adaptive clothing model. UTCI is appropriate for thermal assessments in all
climates and seasons, and on any scale [12].
5 Results and Discussion
The determination of outdoor thermal comfort and wind characteristics were made by conducting
detailed analysis on weather data such as ambient temperature, relative humidity, sun radiation, minmax wind speed, mean wind speed, wind direction and its frequency. Heat stress is one of the major
concerns of this study. Figure 2 shows the monthly mean wind speed in three years. From the
observation, the windiest months were in January and February which recorded approximately
1.84m/s and 1.87m/s respectively. The minimum mean wind speed indicated in the month of
November was just below 1.40m/s. On the following month, the mean wind speed tremendously
increased up until the month of January before it gradually decreased until the month of April which
might be due to northeast monsoon season. Between the months of April to November, the trend of
mean wind speed showed gradual increase and reach a peak at about 1.73m/s before decreasing quite
steeply due to southwest monsoon season.
Furthermore, the yearly mean wind speed for three years data analysis at Alor Setar, Kuantan, and
Subang were at 1.70m/s, 1.69m/s, and 1.6m/s respectively. The yearly mean wind speeds trend at all
locations show only slight differences. The mode of wind speed at Kuantan expressed no wind
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MATEC Web of Conferences
movement at all (i.e. 0m/s) as the dominant readings at 13.94% of frequency. Meanwhile, the
remaining locations demonstrated calmness and no wind with the range of frequency from 10% to
13%. On average, the maximum wind speed at all locations was about 10m/s except for Subang with
the maximum wind speed of 11.6m/s. The variations of yearly mean wind speed are also constant as
the display values of standard deviation are in the range of 1.19 to 1.39.
Figure 2. Monthly mean wind speeds at 10m height for the selected sites.
Besides the value and trend of wind speed, the direction of the wind is the most significant in
evaluating the possibilities of outdoor thermal comfort. The urban planner, architect and engineer can
strategize the orientation of the building in order to increase building permeability and indirectly, will
increase the induced wind as a matter of reducing urban heat island. In general, the annual trend of
prevailing wind as shown in Table 2 in all locations sticks at the same North direction (0°) with
average frequency of about 12.21%. It indicates that Kuantan has the highest frequency which is at
13.94%. In contrast, Alor Setar illustrates the less dominant wind direction with frequency at about
10.21%.
Three years weather data were analyzed in order to obtain UTCI values at the worst heat stress
cases. In general, it can be seen from Table 3 that during hottest temperatures, all the 3 locations
experience extreme heat stress conditions, except for Kuantan which is slightly better with sometimes
experiencing only very strong heat stress conditions. In the year 2012, Subang has the highest UTCI
value of 47.6°C. For the following year, the calculated UTCI value of 51.2°C for Alor Setar is the
highest highlighting the most extreme heat stress condition as compared to the other locations.
Meanwhile, in the next two years, Subang station once again experienced extreme heat stress
condition with the highest calculated UTCI value of 49.7°C. Based on Table 3, the range of maximum
heat stress in three years data are in between 42°C to 52°C at all locations which indicate occurrence
of very strong heat stress and extreme heat stress conditions. Hence, it is worth to mention that heat
stress would be a common problem in Peninsular Malaysia which would enhance people’s level of
discomfort especially to whom living in urban areas. The problem of urban heat island is crucial
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nowadays which might be due to the variation of solar radiation and inadequate wind speed to wipe
out the heat entrapped around the building.
Table 2. Annual wind rose distribution and frequency in the study.
7.12%
7.18%
8.06%
8.90%
14.83%
2.65%
2.65%
5.30%
7.95%
10.59%
13.24%
15.89%
18.54%
W
21.19%
E 23.73%
20.76%
17.80%
14.83%
11.87%
8.90%
5.93%
2.97%
2.97%
5.93%
8.90%
11.87%
14.83%
17.80%
20.76%
W
23.73%
E 24.62%
21.55%
18.47%
15.39%
12.31%
9.23%
6.16%
3.08%
3.08%
6.16%
9.23%
12.31%
15.39%
18.47%
21.55%
W
24.62%
5.30%
E 15.73%
5.93%
13.77%
6.16%
11.80%
3.93%
9.83%
7.95%
7.87%
8.90%
5.90%
9.23%
3.93%
10.59%
5.90%
2.65%
1.97%
3.08%
2.97%
2.65%
3.93%
6.16%
5.93%
5.30%
5.90%
9.23%
8.90%
7.87%
12.31%
11.87%
9.83%
15.39%
14.83%
18.47%
SW
SE
13.77%
21.55%
20.76%
15.73%
24.62%
23.73%
S
0
1.45
2.90
4.35
5.80
7.25
8.70
10.15
11.60
NE
S
0
1.08
2.15
3.23
4.30
5.38
6.45
7.53
8.60
N
17.11%
14.97%
NW
NE
12.83%
10.69%
7.95%
10.59%
13.24%
17.80%
SW
SE
15.89%
SW
0
1.45
2.90
4.35
5.80
7.25
8.70
10.15
11.60
12.87%
NE
11.03%
9.20%
21.19%
N
15.39%
13.47%
NW
9.62%
1.92%
1.92%
3.85%
5.77%
7.70%
9.62%
11.54%
13.47%
W
15.39%
E 14.71%
12.87%
11.03%
9.20%
7.36%
5.52%
1.84%
3.68%
1.84%
1.84%
3.68%
5.52%
7.36%
9.20%
11.03%
12.87%
W
14.71%
E 17.11%
14.97%
12.83%
10.69%
8.55%
6.42%
2.14%
2.14%
4.28%
6.42%
8.55%
10.69%
12.83%
3.85%
14.97%
3.68%
W
17.11%
4.28%
E 14.35%
3.59%
12.56%
5.77%
10.76%
5.52%
8.97%
6.42%
7.18%
7.70%
5.38%
5.38%
7.36%
3.59%
8.55%
2.14%
1.92%
1.79%
2.14%
1.84%
1.92%
3.59%
4.28%
3.68%
3.85%
5.38%
6.42%
5.52%
7.18%
8.55%
7.36%
8.97%
10.69%
9.20%
10.76%
SE
12.83%
SW
SE
11.03%
SW
14.97%
12.56%
14.35%
S
5.77%
7.70%
9.62%
SE
11.54%
SW
12.87%
17.11%
S
NE
11.54%
7.18%
1.79%
SE
18.54%
S
N
14.71%
NW
11.26%
13.24%
11.87%
2.97%
NE
15.89%
12.31%
SE
9.65%
18.54%
7.87%
3.08%
E 12.86%
N
21.19%
NW
E 21.19%
NE
17.80%
E 15.39%
20.76%
18.54%
15.39%
0
1.33
2.65
3.98
5.30
6.63
7.95
9.28
10.60
N
23.73%
NW
13.47%
NE
18.47%
15.89%
21.55%
12.86%
11.54%
0
1.33
2.65
3.98
5.30
6.63
7.95
9.28
10.60
N
24.62%
NW
SE
11.26%
13.24%
0
1.20
2.40
3.60
4.80
6.00
7.20
8.40
9.60
9.65%
S
9.62%
14.24%
10.59%
12.90%
SW
7.70%
11.49%
SE
7.95%
12.46%
NE
8.04%
8.04%
11.29%
S
6.43%
6.43%
10.05%
S
4.82%
4.82%
10.68%
SW
SE
5.77%
9.68%
SW
SE
3.22%
1.61%
1.61%
3.22%
4.82%
6.43%
8.04%
9.65%
11.26%
W
12.86%
12.46%
10.68%
E 14.24%
8.90%
7.12%
5.34%
3.56%
1.78%
1.78%
3.56%
5.34%
7.12%
8.90%
10.68%
12.46%
W
14.24%
11.29%
9.68%
8.06%
E 12.90%
6.45%
4.84%
3.23%
1.61%
1.61%
3.23%
3.22%
5.34%
6.45%
1.79%
1.79%
3.59%
5.38%
4.84%
3.56%
4.84%
5.74%
8.97%
7.18%
6.45%
3.23%
4.31%
10.76%
8.97%
8.06%
1.61%
2.87%
1.97%
1.97%
3.93%
5.90%
7.87%
9.83%
11.80%
9.68%
1.78%
12.56%
10.76%
1.61%
1.61%
11.80%
S
1.78%
1.44%
N
14.35%
12.56%
11.29%
W
12.90%
10.05%
8.62%
7.18%
E 11.49%
3.22%
5.74%
3.56%
4.31%
3.23%
2.87%
2.87%
1.44%
1.44%
2.87%
4.31%
5.74%
7.18%
8.62%
4.82%
1.97%
SW
8.04%
6.43%
1.61%
NE
9.65%
5.34%
11.80%
NW
11.26%
4.84%
9.83%
0
1.10
2.20
3.30
4.40
5.50
6.60
7.70
8.80
8.90%
N
12.86%
NW
4.31%
13.77%
S
NE
10.68%
7.12%
N
15.73%
SW
W
14.35%
8.06%
12.46%
NW
6.45%
8.62%
NW
13.77%
W
15.73%
0
1.08
2.15
3.23
4.30
5.38
6.45
7.53
8.60
NE
9.68%
(2012-2014)
0
1.34
2.67
4.01
5.35
6.69
8.02
9.36
10.70
N
14.24%
5.74%
1.44%
S
Subang
11.29%
NW
7.18%
SW
Kuantan
NE
8.62%
2014
0
1.34
2.67
4.01
5.35
6.69
8.02
9.36
10.70
N
12.90%
5.30%
10.05%
NW
10.05%
W
11.49%
Alor
Setar
2013
0
1.04
2.08
3.11
4.15
5.19
6.23
7.26
8.30
N
11.49%
3.85%
2012
0
1.16
2.33
3.49
4.65
5.81
6.98
8.14
9.30
4.28%
Location/
Year
SE
13.47%
14.71%
S
15.39%
Table 3. Annual UTCI in the study at hottest temperature in 2012-2014 (3 years).
Location
Alor Setar
Kuantan
Subang
Date
Time
Temperature
(°C)
Relative
Humidity
(%)
Wind
Speed
(m/s)
Solar
Radiation
(W/m2)
UTCI
(°C)
7.2.2012
1600
35.4
41
1.90
855.56
46.7
1.4.2013
1500
37.2
42
1.70
1025.00
51.2
28.3.2014
1700
37.5
37
2.10
644.44
46.2
3.10.2012
1600
34.5
52
4.00
702.78
43.2
19.6.2013
1600
36.0
48
4.80
758.33
45.1
24.4.2014
1400
35.3
55
1.60
922.22
49.0
5.6.2012
1500
36.4
49
6.7
938.89
47.6
18.6.2013
1400
36.0
39
6.0
933.33
46.2
5.3.2014
1500
37.8
17
3.4
1097.22
49.7
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Stress
Category
extreme
heat stress
extreme
heat stress
extreme
heat stress
very strong
heat stress
very strong
heat stress
extreme
heat stress
extreme
heat stress
extreme
heat stress
extreme
heat stress
MATEC Web of Conferences
By analyzing the 20 years weather data (1994-2014), the hottest days during that period for all the
three locations were determined and together with other weather parameters their UTCI values were
calculated as detailed in Table 4. Based on UTCI calculation, it was shown that the extreme heat
stress conditions would occur at Alor Setar and Subang. Table 4 also shows that Subang has not only
the highest UTCI value of 49.7°C but also the highest solar radiation intensity of 1097.22 W/m2.
Although Subang’s solar radiation is 30% higher than that of Alor Setar, their UTCI values differ only
slightly at 0.01°C. This might be due to the value of wind speed at Subang which is 47% higher at
about 3.4m/s as compared to that of Alor Setar. Again, it is crucial to mention that wind speed
variation plays an important factor affecting heat stress performance.
Table 4. UTCI index at the hottest temperature in 1994 to 2014 (20 years).
Relative
Humidity
(%)
Wind
Speed
(m/s)
Solar
Radiation
(W/m2)
UTCI
(°C)
Stress
Category
Location
Date
Time
Temperature
(°C)
Alor setar
27.3.1998
1600
39.0
36
1.8
769.44
49.6
extreme heat
stress
Kuantan
26.5.1998
1500
36.6
50
4.0
536.11
43.8
very strong
heat stress
Subang
5.3.2014
1500
37.8
17
3.4
1097.22
49.7
extreme heat
stress
6 Conclusion
To recapitulate, there are several major findings from this study. The findings are the mean wind
speed for three years data at Alor Setar, Kuantan, and Subang, were found to be 1.70m/s, 1.69m/s, and
1.63m/s respectively. The highest hourly wind speed was observed to be 11.6m/s at Subang on 13rd
July 2013 at 4.00p.m. It was also observed that no wind movement (i.e. 0 m/s) could be considered as
the lowest hourly wind speed for all 3 locations, and Kuantan showed the highest frequency of
calmness at13.94%. Alor Setar, Kuantan, and Subang demonstrated the prevailing wind from North
direction (0°) with about 10% of frequencies. The extreme heat stress conditions were calculated to be
at Alor Setar and Subang as the latest trend of UTCI in year 2012 to 2014. Meanwhile, Kuantan
demonstrated very strong heat stress conditions. The 20 years weather data from 1994 to 2014 were
analyzed where the values of UTCI at Alor Setar, Kuantan, and Subang were 49.6°C, 43.8°C, and
49.7°C respectively. Here, it should be noted that the current work is just a preliminary study in
estimating the prevailing wind and wind speed in order to have a comprehensive wind data base for
obtaining a good prediction of outdoor thermal comfort. Apart from that, this study can also contribute
towards the awareness on the current level of heat stress problem in Peninsular Malaysia. Ultimately,
it is hope that the overall findings from this study can be beneficial to researchers, state's authorities
and country's policy makers for achieving a sustainable environment.
Acknowledgements
The author would like to express gratitude to Ministry of Education Malaysia and Universiti Tun
Hussein Onn Malaysia for funding this study, Malaysian Meteorological Department for providing
weather data, and all individuals for their help throughout the course of this research study.
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