Utilization of the Beach Climate Index (BCI) based on Meteorological

Review to Support Tourism Development in Bangka Island

Faqih Musyaffa

1,a

, Muhammad Rafli

1,b

, Anwar Budi Nugroho

1,c

, Reynold Mahubessy

1,d

and Yosafat Donni Haryanto

2,e

Undergraduate Program of Meteorology, STMKG, Banten, Indonesia

Lecturer, Department of Meteorology, STMKG, Banten, Indonesia

yosafatdonni@gmail.com

Keywords: BCI, Beach, Development, Tourism.

Abstract: Bangka Island has a beautiful nature, especially in the beach and coastal areas. The tourism sector has been

focused to develop the economy. Climatology factors have a strong impact on natural conditions that can

affect tourism activities, so they need to be considered. This study aims to analyse the beach climate index in

Bangka Island. Application of ECMWF ERA-Interim reanalysis data and observation data from the Pangkal

Pinang Class I Depati Amir Meteorological Station over a 30-years periodic were analysed to determine the

comfort level of the beach climate using the Beach Climate Index (BCI). Meteorological parameters used in

BCI are temperature, precipitation, wind speed, and sunshine duration. Furthermore, this measurement is used

to analyse as temporally and spatial data in monthly periodic. The result shows that the comfort level each

month is classified as “Very Good” in general, with the category of "Excellent" in June, July, August (JJA)

so it is recommended for tourists who want to visit Bangka Island during the dry season. Thus, this study is

important to support information services on the tourism sector development.

1 INTRODUCTION

Tourism is one of the sectors that contribute to

Indonesia's development (Sumargana, 2004). Many

tourist destinations in Indonesia have the potential to

develop. One of them is Bangka Island. Bangka

Island from Bangka Belitung province has many

beach destinations (Habibi et al.,2007). The number

of tourist visits every year has increased rapidly

(Bangka Belitung Culture and Tourism Department,

2010).

Tourism development is a series of efforts to

realize integration in the use of tourism resources and

integrate all forms of aspects outside tourism that are

directly or indirectly related (Swarbrooke, 1996).

Tourism development has proven to have a

positive impact on the existence of major changes in

people's lives. it has an economic impact by on

expanding business and employment opportunities,

increasing per capita income and increasing the

country's foreign exchange (Priambudi, 2013).

In developing the tourism sector, weather and

climate information factors play an important role in

the decision-making process and the travel

experience of consumers or tourists (Scott and

Lemieu, 2010; Eugenio and Campos, 2010; Gossling

et al., 2012). Climate factors need special attention

because they are closely related to natural conditions

that can affect tourism activities. Morgan et al. (2000)

had conducted research in 34 countries including

Indonesia, which was represented by the Bali area

using parameters of precipitation, wind, air

temperature, sun exposure time, thermal sensation,

and bathing water temperature to determine the level

of tourism comfort based on the BCI index (Beach

Climate Index). The results showed that several

tropical destinations such as Gambia, Bali

(Indonesia), Cancun (Mexico), and Jamaica have

hotter thermal sensation values throughout the year.

When entering the transition season of Bali,

Indonesia is very worth a visit for a tour.

Musyaffa, F., Raﬂi, M., Nugroho, A., Mahubessy, R. and Haryanto, Y.

Utilization of the Beach Climate Index (BCI) based on Meteorological Review to Support Tourism Development in Bangka Island.

DOI: 10.5220/0010855500003261

In Proceedings of the 4th International Conference on Marine Technology (senta 2019) - Transforming Maritime Technology for Fair and Sustainable Development in the Era of Industrial

Revolution 4.0, pages 71-76

ISBN: 978-989-758-557-9; ISSN: 2795-4579

The purpose of this study is to analyze the comfort

level in the beach area of Bangka Island using the BCI

Index (Beach Climate Index) with spatial and

temporal data. We hope the result can be a reference

for foreign and local tourists who will take a vacation

to Bangka Island.

2 DATA AND METHODOLOGY

2.1 Data

This study was conducted over Bangka Island, Bangka

Belitung Province, located in latitude (104.9-107.1) and

longitude (1.30S-3.25S). The data used is as follows.

a. ECMWF ERA-Interim reanalysis data synoptic

monthly mean for the parameters of skin

temperature, wind speed 10m, total precipitation,

and sunshine duration with a resolution of 0.125°

x 0.125° and the period 1987-2017.

b. Daily observation data for the years 1987-2017 for

parameters of precipitation, wind speed, sunshine

duration, relative humidity, and average

temperature of Pangkal Pinang Class I Depati Amir

Meteorological Station were obtained from

Database Online BMKG. ECMWF reanalysis data

is processed spatially using ArcGIS 10.3 (trial

version) to display the mapping by inputting the

*.nc to *.xls file extension which is converted using

ODV software. Daily observation data is processed

statistically using Microsoft Office Excel.

2.2 Methods

Daily observation data is processed using Microsoft

Office Excel to obtain normal data for 30 years by

calculating monthly average for parameters of

precipitation, wind speed, sunshine duration, relative

humidity, and average temperature. Auliciems et al.

(2007) developed an effective temperature in terms of

the correlation between air humidity and daily

average temperature to show the perceived

temperature and comfort conditions using the

following equations (Houghten et al, 1923).

𝐸𝑇0.4



𝐷𝐵𝑇101

𝑅𝐻

100





(1)

where ET (°C) is the effective temperature, DBT is

dry ball temperature as the daily average temperature,

and RH is relative humidity.

Based on research conducted by Morgan et al

(2000), a beach climate index has been developed to

determine the comfort level of tourism in coastal

areas with a scale of 0-100 using the following

equation.

𝐵𝐶𝐼0.18𝑇𝑆0.29𝑃0.26𝑊0.27𝑆

(2)

where BCI is beach climate index, TS is thermal

sensation obtained from skin temperature, P is total

precipitation, W is wind speed, and S is sunshine

duration.

Figure 1: Climate and Meteorology information towards tourist decision (Scott and Lemieu, 2010).

senta 2019 - The International Conference on Marine Technology (SENTA)

Each parameter is processed based on a scale

according to criteria determined by Lemesios et al

(2016). The scaling results of each parameter are

entered into equation (2) to obtain the Beach Climate

Index (BCI) with weighting scheme (scale) <40

(Unfavourable), 40-60 (Acceptable), 60-70 (Good),

70-80 (Very Good), and >90 (Excellent).

Based on the results of the calculations are used to

analyse the comfort level of tourism on Bangka Island

spatially and temporally for the rainy season period,

namely DJF (December, January, February), the dry

season, JJA (June, July, August), the transitional

season, MAM (March, April, May), and SON

(September, October, November) to obtain

information on the comfort level of tourism to support

the development of the coastal and marine tourism

sector.

Table 2: BCI Weighting Scheme for Effective Temperature

(Lemesios, 2016).

Ratin

Effective Tem

erature

(

°C

)

100 32.5-34.4

34.5-35.4

29.0-32.4

35.5-36.4

26.0-28.9

21.0-25.9

Table 3: BCI Weighting Scheme for Wind Speed

(Lemesios, 2016).

Ratin

Wind S

eed

(

m/s

)

100

4-6

Table 4: Classification of BCI score (Lemesios, 2016).

Ratin

Comfort Level fo

Beach Activit

>80 Excellent

70-80 Verry Good

60-70 Good

40-60

Acceptable

<40

Unfavorable

3 ANALYSIS AND RESULTS

Comfort is one of the important aspects of tourism.

There are Many aspects that affect the comfort level,

one of them is the meteorological parameter. Based

on Beach Climate Index (BCI), the spatial data shows

that there is a variation of the condition. By using

(

)

Effective tem

erature

(

)

Total

reci

itation

(d) Sunshine

ure 2: Monthl

avera

e observation.

Table 1: BCI Weighting Scheme for Precipitation an

Sunshine (Lemesios, 2016).

Ratin

Preci

itation

(

)

Sunshine

(

hrs

)

100

<15

10 or more

15-30

9h-9h59min

30-45

8h-8h59min

45-60

7h-7h59min

60-75

6h-6h59min

75-90

5h-5h59min

90-105

4h-4h59min

30 105-120 3h-3h59min

20 120-135 2h-2h59min

10 135-150 1h-1h59min

0.0

>150

<1h

Utilization of the Beach Climate Index (BCI) based on Meteorological Review to Support Tourism Development in Bangka Island

spatial data and temporal data as comparison, we can

estimate the beach climate in Bangka Island.

By processing spatial data and temporal data as a

support to analyze the comfort level based on

meteorological parameters in the beach areas. The

mapping results were put together based on the

characteristics of the seasons on Bangka Island

namely the DJF (December, January, February),

MAM (March, April, May), JJA (June, July, August),

and SON (September, October, November) periods.

Processing the observation data as a comparison

parameter to analyze meteorological aspects for the

comfort level. The grouping is then based on the

classification of beach climate index values

categorized as "excellent", "Very good", "Good", and

"Acceptable". With the temporal data as control,

further study regarding the level of comfort is very

easy by using BCI in knowing the exact time and

destination for your trip. Grouping based on seasonal

patterns in Indonesia aims to find monsoon

phenomena related to the comfort level of the beach

Variation of the index during the DJF period shows

an increase in the west coast, and a decrease in the

southeast coast, although the spatial data didn’t show

a significant change. While in the northeast coast

change of the mapping was not significant but tend to

show an increase especially in Belinyu.

From the results of observing data processing, the

period in the DJF month, Bangka Island is in the wet

season. Where in January is at the top of the

precipitation. From the temporal data, this period

generally is a wet season, short sunshine duration,

low effective temperature, and high humidity (See

Figure 3).

Tjasyono (2008) found that the first transition

season happened during the MAM period, where the

transition goes from wet to dry season. Based on

temporal observation as shown in Figure 4, during

this period the average monthly precipitation began to

decrease. However, in March and April, it was still

(a) Decembe

(b) Januar

ure 3: S

atial data of

in Ban

ka Islan

durin

DJF

eriod.

(a) March (b) April (c) Ma

ure 4: S

atial data of BCI in Ban

ka Islan

, MAM.

senta 2019 - The International Conference on Marine Technology (SENTA)

above 150 mm. Most of the Bangka Island are in the

“Acceptable” to “Good” category, while the southeast

coastal areas are in the category “Very Good” to

“Excellent”. For Mentok, Paung, Sungai Selan,

Kelapa, and Jebus areas, the lowest BCI value is 40,

with “Acceptable” as the category, while for the

southeast coast area, Toboali, Lepar Island, the

category is in “Very Good” to “Excellent” with a BCI

value of 75-80. Changes in comfort level are

indicated by index mapping in May where almost all

the Bangka Island, almost all of its coastline was in

the “Very Good” category to “excellent” with a BCI

value 80-90. From the observation data, May is a

transition month with the lowest precipitation, 207

mm the mean sunshine duration is about 4,82 hours

with temperature at 27.4°C. Some research said that

the comfort level based on effective air temperature

also gives a good sensation for the skin (Green, 1967).

Variable of effective air temperature is a decrease

from the interaction of average temperature with the

relative humidity of an environment. In May, it has

the highest effective air temperature among other

months in Indonesia.

JJA period is the dry season with monsoonal

patterns. This indicates by monthly precipitation

below 150 mm. Tabel 5 shows that JJA period has the

same pattern with the previous period. The southeast

and northeast coast especially Toboali, Koba, Pulau

Lepar are in the category of “Acceptable” with BCI

value around 40-60, while the north (Kelapa) to west

coast (Jebus) and most of Bangka land is in the

category of "good" to "very good". Changes in the

BCI index are consistent with time. The index is

rising along the southeast coast and northeast Bangka.

On the west coast and northeast, the coast of

Merawang, Pangkalan Baru and southwest of Patung

experience a decrease in the index over time.

(a) June (b) Jul

Figure 5: Spatial data of BCI in Bangka Island, JJA.

(a) Septembe

(b) Octobe

(c)

ovembe

ure 6: S

atial data of BCI in Ban

ka Islan

, SON.

Utilization of the Beach Climate Index (BCI) based on Meteorological Review to Support Tourism Development in Bangka Island

From the observations of the JJA period, it tends

to provide statistical values which are also not much

different from temporal data with the weather

condition being dry with the precipitation below 150

mm and the sunshine duration about 6-8 hours/day

(see Table 5).

For the SON period, the pattern is almost the same

as in MAM because this pattern classified as the

transition months where October and November have

differences in index with other months. For August, it

still follows the condition of the previous month, JJA

where the west coast is still categorized as "Very

good". Whereas for September and November the

west coast has decreased to “Acceptable” and for the

southeast coast “Excellent”. In November, Lepar

Island are in top condition. transition and October-

November for the dry-wet transition season (see

Table 6).

4 CONCLUSIONS

Based on the data analysis it can concluded that the

BCI index (Beach Climate Index) spatially and

temporally on Bangka Island generally shows the

category of "Excellent" in June, July, August (JJA) so

it is recommended for tourists who want to visit

Bangka Island during the dry season.

ACKNOWLEDGEMENTS

We acknowledge, European Centre for Medium-

Range Weather Forecasts which develop and

compute ECMWF ERA-Interim for reanalysis file

data and also Pangkal Pinang Class I Meteorological

Station for observation data (meteorological

parameters).

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senta 2019 - The International Conference on Marine Technology (SENTA)