日本大学文理学部自然科学研究所研究紀要
No.57（2022）pp.1−10

資料

Seasonal and Diurnal Variations of Meteorological Elements
in a Tropical Deforested Area in Cambodia
Tetsuya WARAGAI ＊（Accepted November 11, 2021）

Recently, deforestation in Cambodia has been progressing rapidly, resulting in significant environmental changes.
Although meteorological observations under tropical forests have been conducted in the past, it is necessary to continue
collecting scientific knowledge and assessing the impact of deforestation on the natural environment. Therefore, thisstudy analyzed the seasonal and diurnal variations of meteorological elements based on observation data obtained fromthe forest area and deforestation site located at an altitude of about 274 to 280 m in Kulen Mountain from 2017 to 2020. As
a result, the temperature showed a seasonal variation with a maximum value of 31℃ to 34℃ around April and a decrease
to around 25℃ from December to January due to solar radiation and rainfall. A large diurnal range in temperature wasobserved during the dry season (November-April) due to defoliation in the forest area. However, the annual precipitation(1077.8 mm) in Kulen Mountain was approximately 27％ less than that in the plains, and approximately 89％ of the annual
precipitation was concentrated in the rainy season (May to October). The humidity deﬁcit of the logging area is greaterthan that of the forest area, and it is always drier than the forest area throughout the year.
Keywords : Tropical forest, Deforestation, Meteorological elements, Humidity deﬁcit, Seasonal variation,
Diurnal variation, Phnom Kulen

1. Introduction

between 1990 and 2015 (Yasmi et al., 2017). Deforestation

Deforestation and forest degradation are increasing inin Cambodia is progressing in every province in the coun-

many parts of the world (FAO, 2015), and unplanned andtry (Nakazono, 2012). In Siem Reap Province, which is

rapid deforestation is particularly considered to degrade

home to the UNESCO World Heritage Site of Angkor, de-and destroy the geosphere and ecosphere. Globally, for-forestation is most pronounced in Phnom Kulen (Kulen

ests contribute to the carbon cycle and biodiversity

Mountain), located in the northern part of the province.

(Harris et al., 2012). Locally, deforestation reduces forest

Kulen Mountain was designated as a national park inresources and negatively impacts the natural and social

1993, covering approximately 37,000 ha. However, after

environment, such as reduced water source recharge

the civil war, the area was cleared of landmines andcapacity, topsoil runof f, and disaster occurrence. The

turned into a tourist destination. Additionally, deforesta-

background to deforestation, both legal and illegal, is thetion is being promoted as villages are rebuilt and formed

conversion of agricultural land to cultivate cash and sub-(Waragai and Kajiyama, 2016). Recently, roads have beensistence crops, in addition to meeting the commercial

developed across mountains to improve accessibility fromdemand for wood. Some developing countries are unableurban areas; the logging area in Kulen Mountain has

to cope with inadequate forest protection and conservation

grown to about 5,092 ha (Shida et al., 2019).
However, there is little knowledge about the impact oflaws, poverty, and rapid population growth and are unable

such deforestation on the natural environment, especiallyto stop the rapid deforestation.
Recently, Cambodia has experienced rapid deforesta-

on the meteorological environment, which is expected totion, legally and illegally (e.g., Shima, 2006; Davis et al.,change significantly. Recently, examples of the forest

2015; Kurashima, 2020), with forest area reportedly de-environment and meteorological observation under tropicalcreasing from 12.94 (about 75％) to 9.46 (54％) million haforests in Cambodia have been accumulated (e.g., Araki＊

Department of Geography, College of Humanities and Sciences, Nihon
University: 3-25-40 Sakurajyosui, Setagaya-ku, Tokyo, 156-8550 Japan

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Tetsuya WARAGAIand Ito, 2009; Nobuhiro et al., 2010, 2011); however, theyvegetation is covered by evergreen forest with shallow

are not continuous. Therefore, it is necessary to continu-

root systems (Fig. 1).

ously collect scientiﬁc knowledge from various regions in

An ancient capital of the Khmer dynasty built in the ear-Cambodia to evaluate the impact of deforestation. In thisly 9th century was located in the Kulen Mountain (Pennystudy, we present a preliminar y report on the seasonal

et al., 2014). Thus, many temples are scattered through-and diurnal variations of meteorological elements inout the mountain as ruins. Kulen Mountain is also a tour-

Kulen Mountain based on the observation data of meteo-

ism site because of its abundant natural resources, suchrological instruments installed in the forest and deforestation

as waterfalls and springs, as well as religious facilities,

sites (logging sites) in the Mountain from 2017 to 2020.

such as pagodas and reclining Buddha built recently. To

2. Natural environment of the study area andobservation methods

protect and preserve these sites and natural resources,
37,373 ha of Kulen Mountain was designated as Kulen
National Park in 1993 (Global Forestry Services, 2014).

2.1. Natural environment and land use

However, at the end of the civil war, this mountainous area

Kulen Mountain is a table-shaped low mountain with an

was cleared of landmines. As a result, villages have been

elevation of about 300 to 500 m, located about 240 km

rebuilt and established1), and deforestation and conver-

nor thwest of Phnom Penh (Fig. 1). The mountainsion of agricultural land to other uses have progressed.

extends in the northwest and southeast directions, with a

The logging area converted to agricultural land is oval-

length and maximum width of about 47 and 1 km, respec-

shaped (Waragai, 2017), and cashew, rice, corn, banana,tively. Tonle Sap Lake, the largest lake in Southeast Asia,and other crops are widely cultivated. Most of the areas

stretches about 40 km south of Kulen Mountain. The

have a size of 1.6 to 2.4 ha, and there are more than 3,000

mountain constitutes the uppermost basin of the Siem

logging areas in the eastern par t of Kulen Mountain

Reap River and other rivers ﬂowing into the lake. The cli-

(Shida et al., 2019; Waragai, 2019).

matic environment of Kulen Mountain is unknown due tolack of observational data. However, it is estimated that

2.2. Locations and method of observation

the rainy season from May to October alternates with the

The meteorological observation at Kulen Mountain was

dry season from November to April, and the annual pre-conducted in a logging and forest area (under the canopy)

cipitation is less than 1200 mm (Waragai 2019). The

located in the eastern village of Virak Kat (Fig. 1). The

mountains consist of Cretaceous sandstone. Thus, thelogging area is slightly oval with long and short axes ofregolith is thin, except in the valley ﬂoor, and the natural

about 200 and 97 m, respectively. The major axis is in theFig. 1 Study area located in Cambodia. A: A schematic map of Southeast Asia showing a location of B. B: The land cover map
surrounding Kulen Mountain modified from the map of land cover 2013 of Open Development Cambodia (https://data.
opendevelopmentcambodia.net/dataset/land-cover-in-cambodia-2012--2016). AMOS: The automatic weather station of
Angkor Wat temple, K: a location of C. C: Locations of the meteorological station (KL1, KL 2, and KF1) in Virak Kat village.
The map was made based on an image of Google Earth.

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Seasonal and diurnal variations of meteorological elements in a tropical deforested area in Cambodia

AMOS. These data were aggregated for each month andnortheast–southwest direction.
In the logging area, a station (KL1: 13°35′22″N, 104°
3′39″E, 274 m asl.) for temperature and relative humidity (RH)
measurements and a simple micro-station (KL2: 13 °35 ′22″N, 104°03′40″E, 274 m asl.) for temperature, RH, andtime.

3. Results and discussion
3.1. An overview of the air temperature

precipitation measurements were installed at the height of

A timeseries over view of the characteristic obser va-

about 1.5 m. KL 2 is located at about 27 m to the south-

tions obtained from each station shows that the common

west of KL1. Data loggers were ﬁxed under a tree left infeature is that the dr y season from December 2017 to

the logging area for KL1 and ﬁxed to a wooden fence sur-

February 2018 was a low-temperature period, and fromrounding the logging area for KL 2. However, a logger

March to May 2019 was a high-temperature period.

was set up in the forest area approximately 490 m south of

In KL1, the dry season from early December 2017 toKL1 at the height of 1.5 m under the canopy (KF1: 13 °mid-Februar y 2018 was the low-temperature period 2)

35′
6.63″N, 104°
3′39.02″, 280m asl.). The tree density inwith frequent periods of minimum temperature below

the forest area is high, and the forest ﬂoor is covered with

20℃. Additionally, KL1 experienced a high-temperature

herbaceous vegetation.

period2) from early March to late May 2019 with a series

The data loggers installed in KL1 and KF1 are all-of days with maximum temperatures of 35℃ or higher. In

weather temperature/RH loggers (Onset Computer Cor-KL 2, the high-temperature period from early February to

poration, H08-032-IS, 102 × 81 × 51 mm), with an

early June 2019 was marked by consecutive days of 35℃

accuracy of ± 0.2℃ for temperature (at 20℃ ) and ±3％

or higher; a low-temperature period from early December

for RH (at 0 ℃ to 50 ℃ ). In KL2, temperature, RH, and2019 to early February 2020 was marked by intermittent

precipitation were measured using sensors (Onset, tem-days with minimum temperatures of 20℃ or lower3). In

perature/RH sensor: S-THB-M002, rain gauge sensor: S-

KF1, the low-temperature period with days below 20℃ was

RGB-M002) connected with a logger (Onset, HOBO

observed intermittently from late December 2017 to mid-Micro Station). A temperature/RH sensor has an accura-February 20184). Periods of 35℃ or above appeared con-cy of ± 0.21 ℃ for temperature (at 0 ℃ to 50 ℃ ) and ±tinuously from mid-February to late April 2018, and high-

2.5％ for RH (at 10％ to 90％), and ±1％ at up to 20 mm/

temperature periods of 35℃ or above occurred every day

hour for a rain gauge sensor. Observations at these three

from early February to early May 20195).

stations were made at 30-minute intervals from 9:00 on

However, in AMOS, the low-temperature period6) with

August 30, 2017, to 9:30 on February 16, 2020, for KL1,

intermittent days below 20 ℃ appeared from late Decem-

from 15:00 on August 2, 2018, to 10:30 on February 16,

ber 2017 to mid-Februar y 2018. Additionally, AMOS

2020, for KL2, and from 9:00 on August 30, 2017, to 11:30

experienced a high-temperature period7) with consecutive

on August 27, 2019, for KF1.

days above 35℃, especially from early March to early

Waragai et al. (2013) and Waragai (2018) have conduct-

May 2019. Thus, in Kulen Mountain, the low-temperature

ed meteorological observations by an automatic weather

period appeared from December 2017 to February 2018,

station (called AMOS) since 2010 in the precincts ofand the high-temperature period appeared from March to

Angkor Wat temple (13°24′48.1″N, 103°51′44.7″E, 29m

May 2019. The high-temperature period in 2019 corre-asl.), located 28.6 km southwest of KL1. In this study, wesponds to extremely high temperatures in Januar y,employ the observation data of AMOS (measurement in-March, May, and September–October in and aroundterval: 10 minutes) for comparison with the meteorologi-

northeastern East Asia8).

cal data of Kulen Mountain. We used hourly data in the
period from 9:00 on August 30, 2017, to 9:00 on February

3.2. Seasonal and diur nal variations in air
temperature

16, 2020, for KL1, from 15:00 on August 2, 2018, to 10:00
on February 16, 2020, for KL 2, from 9:00 on August 30,

The results of aggregating the obser vations for each2017, to 11:00 on August 27, 2019, for KF1, and from 9:00

station by month and time are shown in Figure 2. Figure

on August 30, 2017, to 23:00 on Februar y 16, 2020, for

3 shows the results for KL1, as an example of seasonal

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Tetsuya WARAGAI

Fig. 2 Box-plot diagrams showing seasonal variations of the air temperature. The solid line indicates the monthly mean air
temperature of the station. The box shows the interquartile range from 25th to 75th percentiles with an average (×) andmedian (―). The circle ( 〇 ) shows data without any outliers. Notches on the box show the minimum and maximum data
without any outliers.

and diurnal variations in temperature. Other stations

temperature difference appeared during the daytime, it isshowed the same pattern of variability as KL1.

likely that the natural ventilation of the temperature sen-

The annual mean temperature was 26.2℃, 26.8℃,

sor of KL 2 stored in the radiation-shielding tube was

26.0℃ , and 27.6℃ at KL1, KL2, KF1, and AMOS, respec-

obstructed. Therefore, we will use the observation data

tively. Although there was a small difference between KL1of KL1 as a representative for the subsequent observations

and KL 2 in the same logging area and within a short dis-in the logging area. The fact that the data loggers of KF1tance, the temperature was lowest in KF1 under the cano-under the canopy and KL1 at the logging site are the samepy, followed by the logging area (KL1, KL 2) and AMOS.

type is also convenient for comparing the observed data.

This may reﬂect the cooling effect of tropical forests (SuAs shown in Figures 2 and 3, the seasonal temperature

et al., 2019) and a temperature lapse rate. Considering thevariation showed a similar trend at all stations. The

temperature lapse rate of 5℃/km, the temperature atmonthly mean temperature reached a maximum of 31℃

Kulen Mountain is about 1.2℃ lower than that of AMOS.

to 34 ℃ around April but decreased to around 25 ℃ from

Therefore, the temperature at Kulen Mountain (26.0℃ to

December to January. However, a slight decrease in the

26.8℃) reﬂects the lapse rate.

monthly temperature was observed around September at

Besides, the temperature difference between KL1 andall stations (Figs. 2 and 3). This seasonal temperature

KL 2 is presumed to be caused by the obstruction of thevariation can be attributed to the effects of solar radiation

natural ventilation of the temperature sensor at KL 2. To

and rainfall. Figure 4 shows changes in the monthly mean

analyze the cause of the temperature difference between

solar radiation (MJ/m2 ) at AMOS. The maximum andKL1 and KL 2, we examined a correlation between theminimum solar radiations of 585 and 476 MJ/m2 weretemperatures during the rainfall-free period from 0:00 on

observed in April and November, respectively. However, aAugust 4 to 0:00 on August 6, 2018 (rainy season), andsmall decrease was observed in September (499 MJ/m2 ).

from 0:00 on February 4 to 0:00 on February 6, 2019 (dryFurthermore, a comparison between the solar radiation atseason), respectively. Consequently, the correlation coef-

AMOS and the seasonal temperature variation at KL1

ﬁcient of temperature at both stations was 0.999, which isshows that the two are synchronized. The correlation

extremely high. However, the temperature at KL 2 was

coefﬁcient between the stations is as high as 0.75, conﬁrm-

approximately 1％ higher than that of KL1. Since thising a strong correlation between temperature and solar

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Seasonal and diurnal variations of meteorological elements in a tropical deforested area in Cambodia

Fig. 3 Seasonal and diurnal variations of the air temperature at KL1.

radiation. However, in addition to the variation in solar

perature appeared at 15:00 in the dry (31.7℃ ) and rainyradiation, the temperature is also affected by precipitation.

(30.2℃ ) seasons. Additionally, the diurnal minimum tem-

The rainy season occurs from May to October in theperature appeared at 6:00 in the dry (21.8℃) and rainy

study area, and the decrease in sunshine hours during(23.8℃) seasons. In KF1 under the canopy, the diurnal

this period means that an increase in solar radiation

maximum temperature appeared at 15:00 (32.7℃ ) in thecannot be expected. Therefore, the seasonal temperature

dry season and at 14:00 (29.1℃ ) in the wet season. The

variation also reﬂects the precipitation.

diurnal minimum temperature in KF1 was obser ved at

For a diurnal temperature variation, KL1 and KF1
showed the same trend. The diurnal temperature varia-

6:00 (22.2℃ in the dry season and 23.8℃ in the wet season).

tion in KL1 (Fig. 3) shows that the diurnal maximum tem-

The diurnal range in temperature was larger in the dry

Fig. 4 Seasonal variations of the solar radiation in AMOS and the air temperature in KL1. Notches show the standard deviation of
the monthly solar radiation.

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Tetsuya WARAGAI

season and smaller in the wet season at both stations;mum precipitation of 33 mm (2:00 on September 14,

however, the temperature difference between the dry and2019), until November 3, 2019.

wet seasons was larger at KF1. In other words, the diur-

In AMOS, located in the plains, there was a continuous

nal range of KL1 is about 10℃ in the dr y season andperiod of 10 mm hourly precipitation until November 22,

about 6℃ in the rainy season, with a large difference in2017, with a maximum of 105 mm hourly precipitation

the dry season. In KF1, the diurnal range was about 11℃

recorded at 20:00 on October 1 during this period. In

in the dry season and about 5℃ in the rainy season, which

2018, there was a period of 10 mm hourly precipitation

was larger in the dr y season. However, the difference

from March 9 to December 10, during which 322 mm of

between the dry and rainy seasons was about 4℃ in KL1

hourly maximum precipitation was recorded at 16:00 on

and about 6 ℃ in KF1, indicating that the difference was

September 4 and 52 mm at 0:00 on September 5. Cambodia,

larger in KF1. This is because of the defoliation of trees

including Siem Reap Province, experienced heavy ﬂoodingin the forest area. In other words, defoliation of trees inin 2018 due to heavy rains. However, the AMOS data of

the forest area allows solar radiation to reach the forest

September 4 may contain errors. AMOS experienced aﬂoor in the dry season. Additionally, because of the highsustained period of 10 mm hourly precipitation fromdensity of trees in the forest area, wind speed is low, andMarch 24 to October 28, 2019.

the heat exchange rate is low. The temperature differ-According to the monthly and time-specific precipita-

ence in the forest area is larger than that in the logging

tion data, the annual precipitation at KL 2 and AMOS wasarea because of these factors. This is supported by the1077.8 mm and 1483.8 mm, respectively. Although thefact that the diurnal maximum and minimum tempera-

precipitation is low in Kulen Mountain and high in thetures during the dry season were higher in KF1.

plain, it is difficult to make a simple comparison as therain gauges at the two points are not the same. The pre-3.3. Seasonal and diurnal variations

cipitation in KL 2 during the rainy season (May to Octo-in precipitationber) was 961 mm, which accounted for about 89％ of the

Although there is only one observation point for precip-

annual precipitation. The precipitation at AMOS during

itation at Kulen Mountain (KL2) and the observation peri-

the rainy season was 1346 mm, which accounted for aboutod (15:00 on August 2, 2018, to 10:30 on Februar y 16,

91％ of the annual precipitation.

2020) is limited, the rainy season of 2018 was very wet. A

Figure 5A shows the variation of the monthly precipita-

timeseries over view of precipitation shows that hourly

tion in KL 2 and AMOS. During the rainy season (May tomaximum rainfall of 63 mm was recorded at 21:00 on

October), more than 81 mm/month of rainfall was

August 8, 2018. However, no rainfall was observed after

observed every month. During the dry season from Novem-

the hourly precipitation of 17 mm at 18:00 on October 11.

ber to April, rainfall was less than 45 mm/month but

The ﬁrst hourly precipitation of 23 mm was observed atslightly increased in March and April before the rainy sea-

0:00 on March 24, 2019, followed by periods of more thanson and in November after the rainy season. In KL2, the

10 mm of hourly precipitation, including the hourly maxi-

monthly maximum precipitation was 335 and 286 mm inFig. 5 Seasonal (A) and hourly (B) variations of the precipitation in KL 2 and AMOS. Notches show standard deviations of monthly
precipitation (A) and standard errors of hourly precipitation (B).

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Seasonal and diurnal variations of meteorological elements in a tropical deforested area in Cambodia

Fig. 6 Box-plot diagrams showing seasonal variations of the humidity deﬁcit. The solid line indicates the monthly mean humidity
deﬁcit. The box shows the interquartile range from 25th to 75th percentiles with an average (×) and median (―). The circle( 〇 ) shows the data without any outliers. Notches show the minimum and maximum data without any outliers.

September and August, respectively. In AMOS, a large・・・(3)

peak (528 mm) was observed in September, reﬂecting thewhere HD is the humidity deficit (g/m3 ), a(T ) is thehourly maximum precipitation in September 2018, as

saturated water vapor (g/m3 ), RH is the relative humidity

mentioned earlier.
There is no signiﬁcant difference in the diurnal variation of precipitation between KL2 and AMOS. Figure 5B(％), e(T ) is the saturated water vapor pressure (hPa),
and T is the temperature (℃ ).

shows that precipitation was higher in the evening and

The calculation results showed a slight dif ferencenighttime. However, there was a one-hour difference inbetween KL1 and KF1 with an annual mean HD of 5.85 g/m3

hourly maximum precipitation. It means that the peakand 4.51 g/m3, respectively. Canopy decreases the diurnal

hourly precipitation at Kulen Mountain was observed at

maximum temperature and increases RH (Ar x et al.,

17:00 and 21:00, one hour after those of AMOS (16:00 and2012). Therefore, a t -test was conducted to determine

20:00). The reason is that the temperature rises in thewhether the difference in the annual mean HD was statis-

ground layer because solar radiation is delayed in KL 2,

tically significant at the 5％ level of significance. The

which is located on the Kulen Mountain, compared to theresult was t (11) = 1.069, p = 0.296, indicating no signiﬁcant

plains.

difference. However, the seasonal variation of HD (Fig. 6)
shows that HD is high in February and March, the middle

3.4. Seasonal variations in humidity deficitof the dry season, and low in August and September, theLand cover between KL1 and KF1 is different. As the

middle of the rainy season, at all stations. The maximum

observed data includes RH, the difference in meteorologi-

and minimum values of the monthly mean HD at KL1

cal conditions between KL1 and KF1 can be described

were 9.7 g/cm3 in March and 2.1 g/cm3 in September,using the humidity deﬁcit (HD, g/m3 ) as an indicator ofrespectively. The values in KF1 were about 9.8 g/cm3 inplant growth. HD is calculated from the saturated water

Febr uar y and 0.5 g/cm 3 in September, respectively.

vapor pressure in the air, e(T ), based on the obser ved

These seasonal variations indicate that HD is negatively

temperature and RH using Tetens equation (1).

correlated with precipitation. Therefore, we examine the6.107810.

.

relationship between the monthly precipitation at KL 2・・・(1)and HD at KL1 and KF1 (Fig. 7). Consequently, we obtain

Then, the amount of saturated water vapor, a(T ), is
obtained from equation (2) by considering water vapor asa negative correlation between precipitation and HD atboth stations.
There is no clear difference in the monthly mean HD

an ideal gas.
.

between KL1 and KF1 in the dry season; however, there・・・(2)

is a clear difference in the wet season. Figure 8 shows

Therefore, HD is calculated from the following equation(3);

the difference between KL1 and KF1 (dHD = KL1(HD)KF1(HD)) during the dry and wet seasons. As shown in

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Tetsuya WARAGAI

Fig. 7 Relationship between the monthly precipitation in KL 2 and humidity deﬁcit in KL1 and KF1.

26.0℃ to 26.2℃ , which is about 1.2℃ lower than that in
the plains (AMOS), reﬂecting the temperature lapse rate.
The monthly mean temperature reaches a maximum of
31 ℃ to 34 ℃ around April and decreases to about 25 ℃
from December to January due to solar radiation and rainfall. Diurnal temperature variations show a minimum at
6:00 (22℃ to 24℃ ) and a maximum at 14:00–15:00 (29℃
to 33℃ ), with a large diurnal range in the dry season anda small diurnal range in the wet season. The magnitudeFig. 8 Seasonal variation of the dif ference in monthly
humidity deficit between KL1 and KF1 (dHD =KL1(HD)-KF1(HD)). A broken line of “Ave” indicatesmean dHD. The monthly precipitation of KL 2 is also
shown in the ﬁgure.

of the diurnal range between the dry and wet seasons islarger (6℃ ) in the forest area affected by defoliation andsmaller (4℃ ) in the logging area.
The annual precipitation at Kulen Mountain is 1077.8
mm, which is about 27％ less than the precipitation in theplains (AMOS). In the rainy season (May to October),Figure 8, the difference in dHD was lower than the annual
3

precipitation at Kulen Mountain accounts for about 89％

mean value of dHD (1.4 g/cm ) in July. However, it wasof the annual precipitation. Precipitation is heavy in thelarger during the rainy season from May to November.

evening and at night, with peaks at 17:00 and 21:00, one

Especially in June and August, the maximum dHD value

hour later than in the plains.

of 2.5 g/cm 3 was obser ved, and the dif ference was

The humidity deﬁcit is negatively correlated with pre-remarkable. This may indicate that the logging area iscipitation, being higher in the middle of the dry season

drier than the forest area, where sensible heat transport(February to March) and lower in the middle of the rainy

is constant throughout the year, and that desiccation isseason (August to September). The humidity deﬁcit in therelatively easier in the rainy season due to the lack oflogging area is higher than that in the forest area, and thevegetation cover.

area is always drier than the forest area throughout theyear.

4. Conclusions
The seasonal and diurnal variations of meteorologicalAcknowledgments
We would like to express our gratitude for the under-

elements in the logging and forest areas in Kulen Moun-standing and cooperation of the mayor and residents oftain can be summarized as follows.
The annual mean temperature in Kulen Mountain is（ 8 ）Virak Kat village in setting up the observation equipment

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Seasonal and diurnal variations of meteorological elements in a tropical deforested area in Cambodia

at Kulen Mountain. Additionally, we would like to express

This paper was supported by a joint research grant

our gratitude to Professors T. Otsuka, K. Ishikawa, Y.

from the Institute of Natural Science, College of Humani-

Ochiai, and T. Takemura of the Nihon University, and Ms.

ties and Sciences of Nihon University (Research Repre-

S. Shida of the Master’s Course of Nihon University (atsentative: T. Waragai) in 2021.

that time) for accompanying us to the village.

Notes1）According to the 2008 census (Economic_Census_of_
Cambodia_2011_SiemReap_01.03.2012.pdf), Kulen Mountain has six villages with a population of 1811, however at
the time of our survey, more villages can be seen in theﬁeld.
2）In KL1, the lowest maximum temperature of 12.8℃ was
shown at 6:00 on December 20, 2017 and the lowest temperature on Februar y 6, 2018 was 13.8℃. In 2019, thehighest temperatures of 38.7℃ and 38.5℃ were shown at
15:00 on March 11 and 16:00 on April 24, respectively.
3）The highest temperature of 41.5℃ was observed at 14:00
on May 2, 2019. On the other hand, the minimum temperature was 14.8℃ at 6:00 on December 9, 2019.
4）The minimum temperature was particularly low from December 19 to 21, 2017, with the minimum value of 13.0℃

recorded at 6:00 on December 20, 2017. The temperatureof 14.0℃ was recorded at 6:00 on February 6, 2018.
5）The maximum temperature of 45.9℃ was obser ved in
KF1 at 15:00 on March 11, 2019. During this dry season of
2019, many days above 40 ℃ appeared from February 19
to March 30.
6）The lowest maximum temperature was 14.2℃ (6:00 on
December 20, 2017) and 15.9℃ (7:00 on Februar y 6,2018).
7）The highest maximum temperature was 39.3℃ (15:00 on
May 1, 2019).
8）According to the Japan Meteorological Agency, Yearly
World Extreme Weather Events (https://www.data.jma.
go.jp/gmd/cpd/monitor/annual/annual_2019.html).

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