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TABLE OF CONTENTS
Pages
EXECUTIVE SUMMARY
i
LIST OF FIGURES
iii
LIST OF TABLES
iv
CHAPTER 1
INTRODUCTION
1
CHAPTER 2
LITERATURE REVIEW
7
CHAPTER 3
METHODOLOGY
24
CHAPTER 4
RESULT AND DISCUSSION
37
CHAPTER 5
CONCLUSION AND RECOMMENDATION
68
REFERENCES
APPENDICES
APPENDICES A:
PAPER PRESENTED
A.1 Relationships Of Sea Level Variation During El Nino And La Nina With Certain
Meteorological Paramaters
A.2 Preliminary Study Of The Response Of The Malaysian Sea Level During The
ENSO Events
A.3 Variations Of Malaysian Sea Level Due To Northeast Monsoons And
Southwest Monsoons Seasons During The El Nino And La Nina Events
APPENDICES B :
B1
Annual Sea Level
B2
Annual Sea Level During Normal, El Nino and La Nina Years
B3
Highest Mean Sea Level During Normal, El Nino and La Nina Years
B4
Lowest Mean Sea Level During Normal, La Nina and El Nino Years
B5
Minimum and Maximum Sea Level During NE Monsoon
B6
Minimum and Maximum Sea Level During NE Monsoon
B7
Comparison of MSL between NE monsoon and SW monsoon
B8-A Annual Sea Level During La Nina Years and Southwest Monsoon Season
B8-B Annual Sea Level During La Nina Years and Northeast Monsoon Season
B8-C Annual Sea Level During El Nino Years and Northeast Monsoon Season
B8-D Annual Sea Level During El Nino Years and Southwest Monsoon Season
B9
SW Monsoon During El Nino Years vs SW Monsoon During Normal Years
B10
NE Monsoon During La Nina Years vs NE Monsoon During Normal Years
B11
(El Nino vs Normal) During SW Monsoon
B12
(El Nino vs Normal) During NE Monsoon
APPENDICES C:
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8,9
Figure 10,11,12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Sea level observation tool in Johor Bahru tide gauge station
Sea level observation tools in Johor Bahru tide station
Location of tide gauge station in Johor Bahru
Location of tide gauge station in Johor Bahru
Tide gauge station in Tg Sedili, Johor
Tide gauge station in Tg Sedili, Johor
Tide gauge station in Kukup, Pontian Johor
Sea level observation tool and general information in
Kota Kinabalu, Sabah.
Tide gauge station at Sabah
Tg Mengayau, Sabah
Kudat, Sabah
Kota Kinabalu, Sabah
Manukan Island, Sabah
Gaya Island, Sabah
LIST OF FIGURES
Pages
Fig. 1.1
Fig. 2.1
Fig. 2.2
Fig. 2.3
Fig. 2.4
Fig. 2.5
Fig. 2.6
Fig. 2.7
Fig. 3.1
Fig. 3.2
Fig. 3.3
Fig. 3.4
Fig. 3.5
Fig. 3.6
Fig. 3.7
Fig. 3.8
Fig. 3.9
Fig. 3.10
Fig. 4.2-1a
Fig.4.2-1b
Fig. 4.2 -1c
Fig. 4.2-2a
Fig. 4.2-2b
Fig. 4.2-2c
Fig. 4.2-3a
Fig. 4.2-3b
Fig. 4.2-3c
Fig. 4.2-4a
Fig. 4.2-4b
Fig. 4.2-4c
Fig. 4.3-1a
Fig. 4.3-1b
Fig. 4.3-1c
Malaysian Map by Malaysian Meteorological Services, 2007
Wind-driven surface currents.
Coastal upwelling and downwelling
Equatorial upwelling
Downwelling caused by convergence of surface currents
Atmospheric circulation and wind belts of the world
El Nino conditions
La Nina conditions
Flowchart of the procedures in this study
Getting Annual Sea Level
Trend Analysis for Getting
Trend Analysis for Tg Gelang
Trend Analysis for Tg Sedili
Trend Analysis for Kukup
Trend Analysis for P Klang
Trend Analysis for P Pinang
Trend Analysis for K Kinabalu
Trend Analysis for Tawau
Sea Level During Northeast Monsoon versus Sea Level During
Northeast Monsoon in Getting
Minimum and Maximum Sea Level During Northeast Monsoon
in Getting
Sea Level During La Nina And Northeast Monsoon in Getting
Sea Level During Northeast Monsoon versus Sea Level During
Northeast Monsoon in Tg Gelang
Minimum and Maximum Sea Level During Northeast Monsoon
in Tg Gelang
Sea Level During La NinaAnd Northeast Monsoon in Tg Gelang
Sea Level During Northeast Monsoon versus Sea Level During
Northeast Monsoon in Tg Sedili
Minimum and Maximum Sea Level During Northeast Monsoon
in Tg Sedili
Sea Level During La Nina And Northeast Monsoon in Tg Sedili
Sea Level During Northeast Monsoon versus Sea Level During
Northeast Monsoon in Tawau
Minimum and Maximum Sea Level During Northeast Monsoon
in Tawau
Sea Level During La Nina And Northeast Monsoon in Tawau
K Kinabalu Sea Level (La Nina Year vs Normal Year) During
Southwest Monsoon
Kota Kinabalu Maximum and Minimum Sea Level During
Southwest Monsoon Season
Sea Level During Southwest Monsoon and La Nina Years in
Kota Kinabalu
4
8
11
12
13
19
22
23
25
28
31
32
32
33
33
34
34
35
39
39
39
40
40
40
41
41
41
42
43
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46
46
46
ii
Fig. 4.3-1d
Fig. 4.3-1e
Fig. 4.3-1f
Fig. 4.4-1a
Fig. 4.4-1b
Fig. 4.4-1c
Fig. 4.4-2a
Fig. 4.4-2b
Fig. 4.4-2c
Fig. 4.4-3a
Fig. 4.4-3b
Fig. 4.4-3c
Fig. 4.4-4a
Fig. 4.3-4b
Fig. 4.3-4c
Fig. 4.5-1a
Fig. 4.5-1b
Fig. 4.5-1c
Fig. 4.5-1d
Fig. 4.5-1e
Fig. 4.5-1f
Fig. 4.6-1a
Fig. 4.6-1b
Fig. 4.6-1c
Fig. 4.6-2a
Fig. 4.6-2b
Fig. 4.6-2c
Fig. 4.6-3a
Fig. 4.6-3b
Kota Kinabalu rainfall
Kota Kinabalu temperature
Kota Kinabalu mean sea level pressure
Kukup Sea Level (La Nina vs Normal) During Southwest
Monsoon
Kukup Maximum and Minimum Sea Level During
Southwest Monsoon
Comparison of Sea Level During La Nina and Sea Level
P Klang Sea Level (La Nina vs Normal) During Southwest
Monsoon During Southwest Monsoon Season
P Klang Maximum and Minimum Sea Level During Southwest
Monsoon
Comparison of Sea Level During La Nina and Sea Level
During Southwest Monsoon Season
P Pinang Sea Level (La Nina vs Normal) During Southwest
Monsoon
P Pinang Maximum and Minimum Sea Level During
Southwest Monsoon
Comparison of Sea Level During La Nina and Sea Level
During Southwest Monsoon Season
Kota Kinabalu Sea Level (La Nina vs Normal) During
Southwest Monsoon
Kota Kinabalu Maximum and Minimum Sea Level During
Southwest Monsoon
Comparison of Sea Level During La Nina and Sea Level
During Southwest Monsoon Season
Kota Kinabalu Sea Level During El Nino and Normal Years
Kota Kinabalu Maximum and Minimum Sea Level
during Northeast Monsoon
Sea Level During El Nino and Northeast Monsoon Season
Kota Kinabalu Temperature
Kota Kinabalu Mean Sea Level Pressure
Kota Kinabalu Rainfall
Geting El Nino Year vs Geting Normal Year During Southwest
Monsoon
Getting Maximum and Minimum Sea Level During Southwest
Monsoon
Sea Level During El Nino and Southwest Monsoon Season in
Getting
Tg Gelang El Nino Year vs Tg Gelang Normal Year During
Southwest Monsoon
Tg Gelang Maximum and Minimum Sea Level During
Southwest Monsoon
Sea Level During El Nino and Southwest Monsoon Season in
Tg Gelang
Tg Sedili El Nino Year vs Tg Sedili Normal Year During
Southwest Monsoon
Tg Sedili Maximum and Minimum Sea Level During
47
48
48
49
49
50
50
51
51
52
52
52
53
54
54
57
57
57
58
58
58
60
60
60
61
61
61
62
62
iii
Fig. 4.6-3c
Fig. 4.6-4a
Fig. 4.6-4b
Fig. 4.6-4c
Fig. 4.7-1a
Fig. 4.7-1b
Fig. 4.7-1c
Fig. 4.7-2a
Fig. 4.7-2b
Fig. 4.7-2c
Fig. 4.7-3a
Fig. 4.7-3b
Fig. 4.7-3c
Southwest Monsoon
Sea Level During El Nino and Southwest Monsoon Season in
Tg Sedili
Tawau El Nino Year vs Tawau Normal Year During Southwest
Monsoon
Tawau Maximum and Minimum Sea Level During Southwest
Monsoon
Sea Level During El Nino and Southwest Monsoon Season in
Tawau
Kukup Sea Level During El Nino and Normal Years
Kukup Maximum and Minimum Sea Level during Northeast
Monsoon
Sea Level During El Nino and Northeast Monsoon Season in
Kukup
P Klang Sea Level During El Nino and Normal Years
P Klang Maximum and Minimum Sea Level during Northeast
Monsoon
Sea Level During El Nino and Northeast Monsoon Season in
P Klang
P Pinang Sea Level During El Nino and Normal Years
P Pinang Maximum and Minimum Sea Level during Northeast
Monsoon
Sea Level During El Nino and Northeast Monsoon Season in
P Klang
62
63
63
64
66
66
66
67
67
67
68
68
68
iv
LIST OF TABLES
Pages
Table 3.1
Table 3.2
Tidal stations geographic coordinates
Statistic z-test result for selected tidal stations
26
30
v
CHAPTER 1
INTRODUCTION
Coastal and marine environment are linked to climate in many ways. Ocean role
as a distributor of the planet’s heat could strongly influence the changes in global climate
over the 21st century. Sea level rise, increasing nitrogen on coastal waters and increasing
carbon dioxide on coral reef are examples of the impact of climate change.
El Nino have been linked with coastal erosion or cliff erosion along the Pacific
Coast. The 1998 EL Nino in particular was associated with record sea-surface
temperatures and associated coral bleaching, coral diseases with major die-offs reported
in Florida and Caribbean region (Boesch et al, 2000).
Phenomena on sea-level rise is received a great concern by the Malaysia
government. Peninsular Malaysia, Sabah and Sarawak is surrounding by the South China
Sea, Celebes Sea, Malacca Straits, Johor Straits and Karimata Straits. Eventhough the sea
is shallower (located on Sunda Shelf) compared to other open sea such as Pacific Ocean
or Indian Ocean, the South China Sea surface temperature is closely related to ENSO
(Klein et al, 1999). Because of tidal inundation, about 1200km2 in Peninsular Malaysia,
will be submerged subsequent to bund failure (MINC,2000).
However, coastal resources gave many benefits to society. Fisheries for
commercial or recreational are a tremendously important economy activity in coastal
areas. Travel and tourism in the coastal areas also generates enormous revenues to coastal
communities and in the United States it is a multi-billion industry. This sector represents
the second largest employer in the nation (Boesch et al, 2000).
1.1 Climate Change
The analysis prepared by the Malaysia Initial National Communication ( MINC)
on July 2000 shows a warming trend of the temperature records in Malaysia. In that
report the temperature changes ranging from +0.3˚C to +0.4˚C and the rainfall changes
ranging from –30% to +30% were used for the assessment. Fredolin T. Tangang et al
(2007) observed the warming rates of Malaysia is between 2.7 to 4.0 C/100 years and the
interannual variability of Malaysian temperature is largely dominated by the EL NinoSouthern Oscillation (ENSO).
Using Global Climate Models (GCM), IPCC projects an increase in temperature
between 1˚C and 4.5˚C. But when the effect of aerosols is included, the lower value is
observed, between 1˚C and 3.5˚C. However in The Third Report Of The IPCC in 2001,
the Figure has been revised by the experts; the global surface temperature is projected to
increase by 1.4 to 5.8˚C over the period 1990 to 2100.
When the temperature increases, it will cause the ocean to expand and the sea
level will rise between 13 and 94 cm or 0.9cm/year (based on the High Rate of Sea Level
Rise) in the next 100 years (MINC,2000). The General Circulation Model, Canadian and
Hadley models suggest a mean expected sea-level rise of approximately 45-51 cm above
current levels by the end of the century (Boesch et al, 2000). These scenario are
consistent with the Intergovernmental Panel on Climate Change’s 1995 estimates that
sea-levels would most likely increase by approximately 37 cm by 2100 (Houghton et al
1995).
It has been observed since 1977, more frequent El Nino Southern Oscillation
(ENSO) occurred. This warm event, for example the persistent warm phase from 19911995 is significantly influenced rainfall. This long, warm period of El Nino-Southern
Oscillation was unusual compared with previous 120 years (Houghton et al 1995).
Leroux, 2005 suggested that precipitation has increased by between 0.2% and 0.3% per
decade in the tropics between 10˚N and 10˚S.
2
El Nino is brought by the temperature changes in the Pacific. These changes cause
the weather conditions vary around the world. The increasing temperature felt by the
Southeast Asian region.
Study by Rong et al (2006) has found that the sea level anomalies during the
period 1993-2004 may not be dominated by a straightforward trend but rather than interannual fluctuations. He also found that the mean sea level curve anomalies appears
dominated by inter-annual fluctuations in 1987-1998 when Southern Oscillation Index
(SOI) is minimum during El Nino event and when SOI has maximum during La Nina
event occur. Therefore, it is evident that the mean sea level anomalies over South China
Sea are strongly corresponding to ENSO. Sea level related to ENSO falls synchronously
during El Nino years and the reverse situation takes place during El Nina years.
1.2 Impact of the Sea Level Rise
A thousand of kilometers could be lost especially in low-lying areas such as the
Mississippi delta in United States if sea-level rise occurs. An increase of storm surge
flooding as a result of the higher mean water level and extensive flooding would be
experienced in some areas. Another example caused by the sea-level rise or storm surges
is an erosion of shores and associated habitat, increased salinity of estuaries, changed in
sediment and nutrient transport and coastal flooding.
As for Malaysia, as much as 6% of land planted with oil palm and 4% of land
under rubber may be flooded and abandoned as a result of sea level rise. Upland forest
which is expected to expand by 5% to 8%, but this could be nullified by a loss of between
15% to 20% of mangrove forests located along the coast as a result of sea level rise
(MINC, 2000).
3
1.3 Problem Statement
An attempt is made to study the variations of Malaysian sea level during El Nino
and La Nina event. Three meteorological parameters were used in this study to identify
the correlation between three meteorological parameters; air temperature, air pressure and
rainfall and the variations of the sea level in the Malacca Straits and the South China Sea.
Therefore, it is hope that this study will be useful to a wide range of professionals having
responsibilities in policy making, agriculture, environmental planning, decision making,
economies, etc.
1.4 Description of Study Area
Malaysia lies between 1˚N and 7˚N latitude and 99˚E and 120˚E longitude(Figure
1.1). Malaysia has a climate, which is generally regarded as equatorial. The mean
temperature of the lowland station is between 26˚C to 28˚C with little variation in the
different month or across different latitude (MINC, 2000). The rainfall is high, regular
and fairly uniform. Most parts of Malaysia receive rainfall peaks during the northeast
monsoon. During this period, the east coast of Peninsular Malaysia and northeast coast of
Borneo island receive up to 40% of their annual rainfall at this time (Andrews et al,
1973).
4
Figure 1.1: Malaysian Map by Malaysian Meteorological Services, 2007
Malaysia is divided into separate sections by the South China Sea; West Malaysia
or Peninsular Malaysia and East Malaysia also known as Borneo Island. The South China
Sea is the largest marginal sea (semi-isolated bodies of water) situated at the Southeast
Asia. The sea is surrounded by South China, the Philippines, Borneo Islands; Sabah and
Sarawak, and the Indo China Peninsula. This sea are shallower and have different e.g
salinity and temperature from those of typical open ocean seawater. Because of it
geographical location, the South China Sea surface temperature is closely related to
ENSO (Klein et al, 1999). The Mediterranean Sea and the Caribbean Sea are another
examples of marginal sea which are located in the Atlantic Ocean.
Peninsular Malaysia is hilly and mountainous with few large areas of plains
(Andrews et al, 1973). Human settlements are concentrated along the alluvial plains
towards the coast. Specific locations in the country such as the coastal areas, is home to
more than 60% of the total population of the country (MINC, 2000) and major cities like
Kuala Lumpur, Penang, Johor Bahru, Kota Bharu, Kuching is located less than 50 to 60
kilometers from the coastal region.
5
Most of the coastal regions are low-lying areas that are less than 0.5m above the
astronomical tide, or are within 100m inland of the high-water mark and it is vulnerable
to sea-level rises.
Southeast Asia is dominated by the monsoon wind system, which produces two
major types of climate in Malaysia, Singapore and Indonesia. First, the monsoonal
climate which occurs in northern Malaysia, northern Sumatra and eastern Indonesia;
second, the equatorial rainforest climate which occurs over the southern section of
Peninsular Malaysia, Singapore, southern Indonesia, western Java, Kalimantan and
Sulawesi (Andrews et al, 1973).
1.5 Objective of the Study
1. To investigate the response of the sea level to El Niño and La Niña events.
2. To identify the correlation between three meteorological parameters – air
temperature, air pressure and rainfall – and the variations of the sea level in the
Malacca Straits and the South China Sea.
1.6 Scope of the Study
This study was limited to the following scope of work to meet the specified objectives:
i.
The relevant data and information consist of mean sea level, temperature,
mean sea level pressure and rainfall data.
ii.
The analyzed period will be subdivided into three categories: (i) El Niño
years, (ii) La Niña years and (iii) normal years.
6
CHAPTER 2
LITERATURE REVIEW
2.1 Ocean Circulation
Major ocean current systems (Figure 2.1) can be affected in critical ways by changes
in global and local temperatures, precipitation and runoff, and wind fields. Similarly, oceanic
features such as fronts and upwelling and downwelling zones will be strongly influenced by
variations in temperature, salinity and winds.
Ocean circulation is driven by the energy of the sun and the rotation of the Earth.
Energy from the sun is transferred from winds to the upper layers of the ocean through
frictional coupling between the ocean and the atmosphere at the sea-surface. Ocean
circulation caused by the sun affected the variations in the temperature and salinity of
seawater. However the frictional coupling between moving water and air masses with the
Earth is weak (Brown et al , 1989).
Figure 2.1 Wind-driven surface currents.
Adapted from Thurman and Trujillo, 2000
2.1.1 Sea Level Change
Generally, sea level refers to the average water level over the course of a 20-year
period, which is enough time for astronomic and most climatic fluctuations to run through
their complete cycles. Over geological time scales however, sea-level has fluctuated greatly.
On average, global sea-level have been gradually rising since the last ice age. During the last
100 years, sea-level rise has occurred at a rate of approximately 1 to 2 millimeter per year, or
10 to 20 centimeters per century (Gornitz 1995, IPCC 1996). How ever, other factors such as
storm surges, winds, currents and rainfall could also affect water level on short time scales.
A change in sea level that is experienced worldwide due to changes in seawater
volume or ocean basin capacity is called eustatic. Changes in sea floor spreading rates can
change the capacity of the ocean basin, resulting in eustatic sea level changes. Significant
changes in sea level due to changes in spreading rate typically take hundreds of thousands to
millions of years and may have changed sea level by 1000 meters or more. For every 1ْC
(1.8˚F) change in the average temperature of ocean surface waters, sea level changes about 2
meters or 6.6 feet (Thurman and Trujillo, 2004). Two basic types of sea level change is, first
the eustatic or world-wide change in sea level due primarily to increasing or decreasing ocean
8
volumes and second the local apparent change in sea level due to the vertical movement of
land (Boon, 2004).
Two major variables have been used to observe sea level change over the last several
hundred thousand years; the thermal expansion or contraction of the sea and the amount of
water that is locked up in glaciers and ice sheets. Current major glaciers and ice sheets is
enough to raise sea-level by approximately 80 meters if all were to melt and flow to sea
(Boesch et al, 2000 and Emery et al, 1991). Groundwater mining, deforestation and water
released from the combustion of fossil fuels would have the effect of slightly increasing
global sea level.
2.1.2 Sea Level Rise, Climate Variability and Marine Ecosystems
Sea-level rise is a significant consequence of climate change on marine ecosystems.
The effect of climate variability and change on coastal areas and marine resources is made
more difficult by the confounding effects on human activities. For example, naturally the
estuarine and coastal wetland environments will migrate inland in response to relative sealevel rise, but this migration is blocked by coastal development, diking, filling or hardening
of upland areas. While the biological communities which might be able to adapt to
temperature, salinity or productivity associated with variable climate regimes might be able
less to do the adaptation process.
The general status and trends in coastal and marines resources have been done by
Boesch et al (2000). Also the current and future impacts associated with population
concentration and growth in the coastal zone has been evaluated. The review on climate
forcing such as sea-level rise rates, changes in storm tracks and frequencies, changes in ocean
current patterns and etc. However further and details description on this topics is referred to
IPCC report, ; Houghton et al (1996), Biggs (1996) and Mann and Lazier (1996). The climate
forcing is also intended to provide a brief foundation for assessing the real and potential
impacts of climate and various types of coastal and marine ecosystems (coastal wetlands,
estuaries, shorelines, coral reef and ocean margins). Case studies on this topic have been
inserted by the National Oceanic and Atmospheric Administration (NOAA) to provide
specific examples of the complex set of interaction between the effects of climate and human
activities.
9
2.1.3 Implications of Sea Level Rise
An important impact of future storms, whether tropical or extratropical, may be their
superposition on arising sea-level. The higher reach of waves on the beaches and barrier
islands of the nation’s coast, flooding and erosion damage will be expected to increase
(Ruggiero et al, 1996 and Heinz Center 2000). For example, during both the 1982-83 and the
1997-98 El Nino events, elevated sea levels of a few tens of centimeters in the Pacific
Northwest were sufficient to force wave runup to impact and erode coastal cliffs, causing
widespread property losses and damages (Komar 1986, Komar 1998).
The worst-case determine by the IPCC is, if a one meter rise in sea level during the
next century, thousands of square of kilometers could be lost, particularly in low-lying areas
such as the Mississippi delta
The effects of sea-level rise are unlikely to have a catastrophic impact of coastal
wetlands in themselves before the middle of the 21 century, but when combined with
subsidence and other environmental changes, the consequences may be severe. Groundwater
withdrawals may exacerbate the effects of sea-level rise and these various responses are
difficult to predict.
In Malaysia, the impact of climate change and sea level rise on coastal resources can
be classified into four broad categories. The tidal inundation, shorelines erosion, the
increasing of wave action, which can affect the structural integrity of coastal facilities and
installation such as power plant. Lastly is, saline intrusion, which can pose a potential threat
of water contamination at water abstract points (MINC,2000).
2.1.4 The Importance of Coastal Resources
Fisheries for both commercial and recreational are important activity in coastal areas.
About 4.5 million tons of marine stocks landed in the Unites States coast over the past ten
years and become world’s fifth larger fishing nation. While coastal tourism generates
enormous revenues, which bring a multi-billion dollar industry in the United States. As A
10
consequences, clean water, healthy ecosystems and access to coastal areas are critical to
maintain the tourism industries.
Also as coastal populations increase, the vulnerability of developed coastal areas to
natural hazards is also expanding. In the Unites States, thousand and other million peoples
especially the coastal communities will be facing greatest impacts of storm surge, flood and
hurricanes. For example Hurricane Katrina, Hurricane Andrew and Georges caused billion
dollar, in damages to coastal communities.
2.2 Coastal Upwelling and Downwelling
Oceanic features such fronts and upwelling and downwelling zones strongly
influenced by variations in temperature, salinity and winds. Upwelling has a biological
implication of considerable ecological and economic importance. Surface waters replaces by
deeper nutrient rich waters, resulting in high levels of primary productivity of fisheries on
global basis in upwelling zones (Boesch et al, 2000).
Figure 2.2 Coastal upwelling and downwelling.
Adapted from Thurman and Trujillo, 2004
Generally, upwelling is a wind-driven phenomena, upwelling zones support the
highest volume fisheries on a global basis. Coastal upwelling is the result of a divergence of
surface water away from the coastal boundary. The average movement of the wind-driven
11
layer to the right of the wind which is known as the Ekman transport causing the divergence
of surface water and upwelling. In other word, the cause of coastal upwelling is the offshore
movement of the water in response to wind stress.
The rate of upwelling may be calculated by
τ
ū = ________
Dρf
ū = magnitude of the depth mean current
D = depth
f =Coriolis parameter
ρ = density of seawater
Convergence of the surface water leads to sinking. In the regions of convergence, are
characterized by sinking depleted in nutrients and the productivity is low. The thermocline is
depressed and led to phytoplankton being carried down.
Figure 2.3 Equatorial upwelling
Adapted from Thurman and
Trujillo, 2004
12
Figure 2.4 Downwelling caused by
convergence of surface currents
Adapted from Thurman and
Trujillo, 2004
Upwelling along the western coasts of continents thus varies seasonally according to
the Trade Winds and the position of the Intertropical Convergence Zone. However, it is
difficult to investigate the process of upwelling directly because it occurs episodically.
Most upwelling regions have similar characteristic fish populations and corresponding
large-scale fisheries for fishes such as sardine and anchovy. The fisheries industries is badly
affected by the strong ENSO event in 1972. The California Current is a classical upwelling
system with cold, nutrient-rich waters from depth replacing the surface waters which are
displaced offshore. By contrast, downwelling is seasonally prevalent in the Alaska Current
system (Boesch et al, 2000).
The region of upwelling have been classified into three types:
a) the stationary type
The upwelling occurs during whole year, for example the region off the coast of
Peru
b) the periodic type
The upwelling occurs only during one season, for example in the region of
northwest of Australia
c) the alternating type
13
The upwelling and sinking occur alternately, for example in the region of the
Banda and Arafura Seas.
2.3 Climate Variability and Change
Levitus et al. (2000) gave a strong evidence for ocean warming over the last halfcentury. Their result indicated that the mean temperature of the oceans between 0 and 300
meters has increased by 0.31˚ C over the period. Boesch et al (2000) concluded that
according to climate variability, Levitus result is in strong agreement with those projected by
many circulation models. Sea surface temperature is now measured throughout the earth
using remote sensing platforms such as the Advanced Very High Resolution Radiomater
(AVHRR), ships, drifting buoy, moored and sampling stations at the coastal sites. However,
the Canadian Global Coupled Model (CGCM1) and Hadley Center Coupled Model
(HadCM2) were used because it is better equipped to handle hydrology, radiation and cloud
cover than their earlier version.
As a consequence of global climate change, the hydrologic cycle will be intensified
with increased precipitation and evaporation, and varying impacts to coastal runoff. The
development of retentive zones defined by stratified waters and associated fronts can be
important in maintaining planktonic organisms within regions where the probability of
survival is enhanced. However, strong stratification can impede mixing and nutrient
regeneration, resulting in a decrease in primary production some areas. While in an increased
in temperatures and enhanced stratification have been implicated in a decline in production in
the California Current system during the last two decades (McGowan et al, 1998). Mann and
Lazier (1996) also stated that an increased in temperatures and river runoff could lead to an
earlier onset of stratification and the timing of phytoplankton blooms, which also could lead
to a shift in phytoplankton species composition.
Increases in temperature will also result in further melting of sea ice in polar and
subpolar regions, with direct effects on the input of fresh water into these systems with
attendant effects on buoyancy-driven flow and stratification. The reduction and potential loss
of sea ice has enormous feedback implications for the climate systems; ice and snow are
highly reflective surface, returning 60 to 90 % of the sun’s incoming radiative heat back to
outer space, while open oceans reflect only 10 to 20 % of the sun’s energy.
14
2.3.1 Rainfall
The rainfall regime is reflected by the wind seasons over Malaysia (Dale,1959). He
also stated that heavy rainfall occurs anywhere at anytime of the year and whilst short dry
spells occur, they are not sufficiently long and regular in their occurrence. The general pattern
of the wind reflected in the rainfall regime. Rainfall maximum coincides with time premonsoonal period and minimum occurs sometimes dry each of the two monsoons.
During southwest monsoon, the relatively high percentage of rainfall received during
the southwest monsoon may be due to the diminished sheltering effects of the mountains of
the northern Sumatra compared with those to the south. While during northeast monsoon, a
maximum rainfall appears in the night or early morning due to landward drift of showers
from the South China Sea. During the northeast monsoon season, the exposed areas like the
east coast of Peninsular Malaysia, Western Sarawak and the northeast coast of Sabah
experiences heavy rain spells (Malaysian Meteorological Services, 2007).
2.3.2 Temperature
Dale (1963) showed an evidence that the annual means for temperature on the western
side of the country are slightly higher than those on the east even though the observed station
is in the same latitude. But the difference between the two sides of the country decreases
northwards. The annual variation is less than 2°C except for the east coast areas of Peninsular
Malaysia which are often affected by cold surges originating from Siberia during the
northeast monsoon. Even there, the annual variation is below 3°C (Malaysian Meteorological
Services, 2007).
2.3.3 Sea Level Pressure
Mean sea level pressure (MSLP) is the pressure at sea level or (when measured at a
given elevation on land) the station pressure reduced to sea level assuming an isothermal
layer at the station temperature. Average sea-level pressure is 101.325 kPa (1013.25 mbar) or
29.921 inches of mercury (inHg) or 760 millimeters (mmHg). The highest sea-level pressure
15
on Earth occurs in Siberia, where the Siberia High often attains a sea-level pressure above
1032.0 mbar. The lowest measurable sea-level pressure is found at the centers of hurricanes
(typhoons, baguios).
2.4 Monsoon Characteristics
According to Cheang (1986), winter monsoon or northeast monsoon and summer
monsoon or southwest monsoon names are derived from the low-level prevailing winds of
the two seasons. However in our neighbourhood country, Indonesia, they experience west
and east monsoons seasons, respectively. In south (north) of about 10 degrees north (south),
the northeast (southwest) monsoon season brings about 50 percent of the annual rainfall of
Southeast Asian countries. However, in the western part of Peninsular Malaysia and
southwest of Thailand, normally more rains is received during two transitional period than
during the monsoon periods.
The oceanic regions most affected by these seasonal changes are in the Indian Ocean
and western Pacific, where the seasonally reversing winds are known as the monsoons. The
word monsoon meaning ‘ winds that change seasonally’ and it is derived from Arabic word,
‘mausim’. However, the westernmost part of the Pacific Ocean; Malaysia and Indonesian
archipelagos is the most obvious region affected by the seasonally reversing winds (Brown et
al, 1989).
Changes in the direction and speed of the air-streams that cross the Peninsula
Malaysia are responsible for the division of the year, in most areas, into four seasons. The
time of commencement and duration of these vary slightly with latitude and from year to year
(Dale, 1959).
2.4.1 The northeast monsoon
This monsoon occurred between early November or December to March when the
equatorial low pressure lies to the south of the equator. During this monsoon the sun is
overhead over the Tropic of Capricorn. The wind prevail during these months and the speeds
is between 15km/hr to 50km/hr (Andrews et al, 1972).The pressure is high over the mainland
16
Asia and winds blow from Asia toward low pressure area in the equator. This wind brings
heavy rain to the northeast coast of Kudat and Sandakan.
According to Camerlengo et al, NE monsoon is represented by two air masses from
different sources; first air mass is derived from a high pressure system situated over the
northern half of the Asian continent. In southward motion, this air mass upon reaching South
China Sea, is shallow as it rarely exceeds 2000m off the east coast of Peninsular Malaysia.
The air masses become warmer and losses much of dryness. The second air mass is derived
from the Pacific Ocean. Northeast trade winds will transport the air mass towards the SCS.
The air mass is warmer and more humid than the first air mass.
2.4.2 First inter-monsoon period
First inter-monsoon period occurs from April (in the south) to May (in the north).
Rain may occur at almost any hour of the day in contrast to the more regular afternoons rains
common during the monsoon periods and rainfall is very variable from one place to another.
The winds are either weak and variable, or reduced to calm.
2.4.3 The southwest monsoon
Wind blows between the month of June and September or early October. Country will
experiences light southerly winds from the southern hemisphere and south-westerly winds
from the Indian Ocean advance across northern Malaysia. These winds are weaker than
north-easterlies The temperature is high over the mainland Asia and this results in area of low
pressure well to the north of Sabah into which winds blow in a curved path. The wind speeds
seldom exceeding 25km/hr.
Camerlengo et al (2002) said that Southern Sabah is largely affected by the poleward
migration of the area of convergence associated with the SW monsoon. Larger values of
rainfall due to onset of SW monsoon, are observed at the western coast in May while lesser
rainfall is observed in the eastern coast of Sabah.
17
2.4.4 Second inter-monsoon period
This monsoon occurred in October and early November, and will be followed by the
northeast monsoon season. The southwest winds wane and northeast winds gradually become
dominant. Both coast of Sabah will experience heavy rains during this period.
2.5 Inter-tropical Convergence Zone
ITCZ or Inter-tropical Convergence Zone, the zone which the wind systems of the
two hemispheres converge is generally associated with the zone of highest surface
temperature. The ITCZ the zone along which the Trade Winds is distorted towards land in the
hemisphere experiencing summer. Great proportion of land in the Northern Hemisphere than
in the Southern made the mean position of the ITCZ shifted to north of the Equator.
ITCZ is located 5 degrees north of the Equator, therefore it is bound to pass over
Peninsular Malaysia twice a year which bring high precipitation. ITCZ is recorded passing
Peninsular Malaysia between April and May and between October and December
(Camerlengo et al, 1996). ITCZ is characterized by light winds and there is no significant
Ekman transport in the region between the two Trade Wind zones.
18
Figure 2.5 Atmospheric circulation and wind belts of the world
Adapted from Thurman and Trujillo, 2004
2.5.1 Divergence and Convergence
Wind stress at the surface caused horizontal movement and vertical motion of the
water. When divergence occurs, deeper water rises up to take its place; conversely, sinking
occurs when there is a convergence of the surface water. Upwelling of subsurface water and
sinking of surface water occur throughout the oceans. The Ekman transport, causing
divergence of surface water and upwelling.
During these event, the sea surface is lowered and the thermocline is raised and
upward movement of water in response to wind stress is called Ekman pumping. The
convergence of water as a result of anticyclonic winds thus causes the sea-surface to slope
upwards towards the middle of the gyre and the circulating water will be acted upon by a
horizontal pressure gradient force.
19
2.6 Southern Oscillation
The situation in which a high sea surface pressure occurs in the southeastern and the
central Pacific Ocean and a low sea surface pressure occurs in the western Pacific is referred
as the Southern Oscillation (Philander, 1989). This cycle is discontinued whenever a warming
of the sea surface temperature (SST) at the eastern Pacific takes place. The occurrence of this
high SST occurs within the interval ranging from 2 to 5 years. (Rasmusson, 1984).
Considerable disruptions of regional coastal ecosystems and socioeconomic activities
are originated by the appearance of these warm waters (Glantz, 1996). This event is usually
referred as El Niño (“the child”, in Spanish), in reference to “Christ Church”, so named due
to its emergence during Christmas time (Cushman Roisin, 1994). El Niño represents the
warm phase of the Southern Oscillation.
The warmest waters known in Earth are located in the western Pacific. Whenever the
strength of the trade winds (blowing from east to west in tropical areas) is greater than usual
there is an enhancement of this warm pool of water, with the consequent increase of
convective activity. This case is known as “La Niña” (“the girl”, in Spanish). It is also
referred as “anti-El Niño” or “El Viejo” (“the old man”, in Spanish). This case represents the
cold phase of the Southern Oscillation (Toole, 1984).
A particular study shows that the rainfall pattern of the 1968-69 El Niño event is
negatively correlated with the 1975 La Niña event in a similar fashion as insolation (h of
sunshine) and air temperature (Camerlengo, 1999). The low pressure located at the western
Pacific represents an area of convergence at the lower layers of the atmosphere. By
continuity, this convergent area rises into the stratosphere (approximately 20 kms high). It
represents an active area of precipitation. It is referred in the scientific literature as the
“Indonesian Low”.
The parcel of water traveling from east to west, driven by the trade winds, at tropical
latitudes warms considerably. Given the fact that the tropical Pacific Ocean is wider than the
tropical Atlantic, the waters at the western boundary of the tropical Pacific are considerable
warmer than at similar boundary in the tropical Atlantic Ocean. Philander (1990) refers to the
former region as the “heat engine of the atmosphere”. The vertical structure of the ocean
20
consists of an upper layer (usually referred as the ocean mixed layer) and the deep ocean
layer. The area between these two layers is very narrow and a sharp discontinuity in the
different properties of the ocean (temperature, salinity, density and current velocity) takes
place. It is usually referred as the thermocline.
During “normal conditions” the thermocline is deeper at the western boundary of the
tropical Pacific and surfaces at the opposite boundary. (This situation is driven by the trade
winds.) Thus, the ocean current at the western boundary off South America, flowing towards
the Equator, is much colder than the one at the opposite boundary. It is also wider (in the order
of 100 km) and much slower (in the order of 0.1 m/sec). On the other hand, The order of
magnitude of the horizontal length and the velocity of the western boundary current in the
tropical Pacific is 1 km and 1m/sec, respectively.
Every three to five years an abatement of the trade winds usually takes place.
Moreover, a reversal of the winds occurs from three to five weeks. This situation is known as
the “westerly wind bursts”. The Indonesian Low and its associated area of convective rainfall
migrates eastwards. The warm pool of water also moves towards the eastern boundary. This
situation represents the early stages of the El Niño event.
During an El Niño event the thermocline levels all across the Pacific Ocean. In other
words, the thermocline deepens at the eastern boundary and surges at the western boundary.
Therefore, the waters off Peru and Ecuador become warmer. Therefore, the warming of the
SST off Peru and Ecuador, during an El Niño event may be due to three different effects: (a)
the eastward displacement of the warm pool of water from the western boundary of the
Pacific ocean, (b) the deepening of the thermocline and (c) the combination of the two
previous phenomena.
2.7 El Nino
An El Nino events is a climatic fluctuation, centered in the Pacific, that occurs every
2-10 years. This event occurs within a few months of Christmas. El Nino means ‘the Christ
child’, the originally simply the local name for the seasonal increase in the temperature of
coastal waters that occurs around Christmas. El Nino represents the warm phase of the El
21
Nino/Southern Oscillation (ENSO) cycle, and is sometimes referred to as Pacific warm
episode.
El Nino events are perturbations of the ocean-atmosphere system. Southeast trade
winds over the equatorial Pacific depends on the difference in surface atmospheric pressure
in the eastern South Pacific and Indonesia region. During El Nino, Indonesian Low has
anomalously high pressure which is weaker low than usual. This event moves eastwards into
the central Pacific while the South Pacific high becomes anomalously low. The southeast
trade weaker and often becoming westerly in the western Pacific.
Figure 2.6 El Nino conditions.
Adapted from Thurman and Trujillo, 2004
In the Atlantic Basin, hurricane are less prevalent during El Nino year compared to
non-El Nino years. The supposition of storm surges on a sea-level (3.9mm/year at Atlantic
City) has resulted in an increase of storm impact over the length record, from 200 event of
hurricane to 1200 event in past decade (Boesch et al, 2000).
NOAA’s Climate Prediction Center, declares the onset of an El Nino episode when
the 3-month average sea-surface temperature departure exceeds 0.5 C in the east-central
equatorial Pacific ( between 5˚ N-5˚ S and 170˚ W–120˚ W). El Nino events may occur more
22
frequently as a result of global warming (Thurman and Trujillo, 2004). Presumably, increased
ocean temperatures could trigger more frequent and more severe El Ninos.
Rong et al (2006), the South China Sea lies near the anomalous descent region where
surface wind, air temperature, humidity and cloud cover were altered there which in turn
influence the ocean circulation and surface heat fluxes and eventually sea surface temperature
(SST). Also from his study, every ENSO event is associated with a change of the SCS SST
anomalies.
2.8 La Nina
La Nina refers to the periodic cooling of ocean surface temperature in the central and
east-central equatorial Pacific that occurs every 3 to 5 years. La Nina represents the cool
phase of the El Nino/Southern Oscillation (ENSO) cycle, and is sometimes referred to as
Pacific cold episode. La Nina originally referred to an annual cooling of ocean waters off the
west coast of Peru and Ecuador. Larger pressure difference across Pacific ocean creates
stronger Walker Circulation and stronger trade winds, which in turn causes more upwelling ,
a shallower thermocline in the eastern Pacific and a band of cool than normal water that
stretches across the equatorial South Pacific.
Figure 2.7 La Nina conditions.
Adapted from Thurman and Trujillo, 2004
23
CHAPTER 3
METHODOLOGY
3.1 Introduction
In this study, the sea level variation due to El Nino and La Nina event of the
temperature, mean sea level pressure and rainfall in Malaysian waters are analyzed. Least
square regression with null hypothesis tests and time series analysis were carried out to view
any sea level variation due to above mention parameters.
The general procedures of this study are illustrated in the following flowchart (Figure 3.1).
3.2 Data
Data from 20 tidal stations and 18 meteorological stations were used in this study.
However only data from 8 tidal stations and 8 meteorological stations; namely, Kota
Kinabalu, Tawau, Geting, Tg Gelang, Tg Sedili, Kukup, P Klang and P Pinang, will be
discussed in this study. These stations have had satisfy two requirements:
a) Geographical locations
All selected stations representing all the geographical locations in Malaysia (Table 3.1). Kota
Kinabalu and Tawau were selected for west and east coast of West Malaysia, while Getting
Tg Gelang and Tg Sedili for east coast of Peninsular Malaysia. 3 stations were chose to
represent west coast of Peninsular Malaysia; Kukup, P Klang and P Pinang.
Mean Sea Level and
Meteorological Parameters
Regression Analysis
1. The regression lines of the mean annual values for longest
available year.
2. The regression lines of the mean monthly values during the
northeast monsoon and southwest monsoon seasons.
3. The regression lines of mean annual values during normal
years, El Nino and La Nina years.
4. Comparison of regression lines of the northeast, southwest, El
Nino and La Nina events.
5. Correlation of the meteorological parameters and the mean sea
level of Malaysian waters.
Null Hypothesis
Time Series Analysis
Result and Discussion
Conclusion
Figure 3.1 Flowchart of the procedures in this study
25
Table 3.1 Tidal stations geographic coordinates
No.
Station
Latitude (ºN)
Longitude (N)
1
Getting
06º 13’ 35” N
102º 06’ 24” E
2
Tg Gelang
03º 58’ 30” N
103º 25’ 48” E
3
Tg Sedili
01º 55’ 54” N
104º 06’ 54” E
4
Kukup
01º 19’ 30” N
103º 26’ 34” E
5
P Klang
03º 03’ 00” N
101º 2’1 30” E
6
P Pinang
05º 25’ 18” N
100º 20’ 48” E
7
K Kinabalu
05º 59’ 00” N
116º 04’ 00” E
8
Tawau
04º 14’ 00” N
117º 53’ 00” E
Years Of
Record
1987-2004
(18 years)
1984-2004
(21 years)
1987-2004
(18 years)
1986-2004
(19 years)
1984-2004
(21 years)
1986-2004
(19 years)
1988-2004
(17 years)
1988-2004
(17 years)
b) Historical records
For this research, the longest possible time span of records for each station is needed in
this study, thus the longest records will be used in this study (Table 3.1).
26
3.2.1 Sources of Data
In this study, the sources of data are obtained and purchased from the Department of
Survey and Mapping Malaysia and the Malaysian Meteorological Service.
3.2.1.1 Department of Survey and Mapping Malaysia
Observational tidal data from eight (8) Malaysian tide gauge stations has been
obtained from the Department of Survey and Mapping Malaysia.
3.2.1.2 Malaysian Meteorological Service
Temperature, mean sea level pressure and rainfall record data from stations in
Malaysia has been obtained from the “Monthly Summary of Meteorological Observations”
published by the Malaysian Meteorological Service.
3.3 Regression Analysis
The analysis of:
i)
the regression lines of the mean annual value for the longest available year span,
ii)
Determination of the magnitude of the sea level rise during La Niña events and El
Niño events
iii)
the importance of the sea level rise during La Niña events as compared to the sea
level rise during the northeast monsoon- off the east coast of Peninsular Malaysia
and East Sabah
iv)
the sea level rise due to downwelling, as compared to sea level rise during La
Niña years during the southwest monsoon season in West Sabah
v)
the sea level rise during La Niña events as compared to the sea level rise during
the southwest monsoon for the west coast of Peninsular Malaysia and West
Borneo
vi)
a decrease of the sea level, due to upwelling, in the boreal winter compared to the
amplitude of the lowering of the sea level during El Niño years in West Sabah
vii)
a lowering of the sea level in the boreal summer compared with the lowering of
the sea level due to El Niño events at the east coast of Peninsular Malaysia and
East Borneo
27
viii)
a decrease of the sea level in the boreal winter versus the decrease observed
during El Niño events at the west coast of Peninsular Malaysia
The regression lines of the mean annual value is plotted to identify whether there is
any increasing or decreasing trend of the mean annual sea level. The slope of the linear
regression equation will show any significant increasing or decreasing trend. Due to the fact
that the regression lines is plotted by using the mean annual value, the seasonal effect is
absent. Figure 3.2 shows the regression line of the mean sea level of the Geting for the period
1987-2004. The increasing rate for sea level for Tg Sedili is 19 cm in 100 years with Pearson
correlation coefficient of 0.47. This increasing rate is still within the value released by the
MINC (2000), between 13 and 94 cm in 100 years or 0.9 mm per year. After that the
correlation coefficient required to be tested for their statistical significance using hypothesis
testing.
Annual Mean Sea
Level (cm )
Geting
y = 0.1984x - 166.54
R = 0.47
234
232
230
228
226
224
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
Year
Figure 3.2 Geting Annual Sea Level
Hypothesis testing were divided into two types, the null hypothesis and the alternative
hypothesis. Null hypothesis ( Ho: ρ = 0 ) is defined as that there are no difference between
two parameters. Alternative hypothesis ( Ho: ρ ≠ 0) is defined that there is a difference
between two parameters. ρ represents the population correlation coefficient, r is the sample
correlation coefficient and n is the number of the sample.
From Sufi (1988), for reasonably large sample, the distribution of a sample correlation
coefficient, r, is normal with a mean ρ and a standard error (S.E) of
28
1 − r2
n−2
A t-test is used to test the hypothesis with respect to significance of such statistics
(difference between samples and when the samples are taken from normal distributed
populations) and the sample sizes is less than 30. This condition suit the small sample size of
tidal records, which is less than 30 years of record.
t=
r2
1 − r2
n−2
which in turn may be compared against standard t-distribution table values. Value of r and t
will be used to determine whether the correlation coefficient is significantly different from
zero or are the relationship between two variables are truly related (Sufi, 1988).
By using a 5% level of significance (95% confidence level),
r = 0.47
S .E , r , =
1 − (0.47)2 0.2207
= 0.048694
18 − 2
t − distribution =
0.47
= 2.1296
0.2207
The table values of t-distribution at 5% level of significance and degrees of freedom is
16 (obtained from n-2) is 2.120.
The computed value is larger than the value of t-
distribution. Therefore the null hypothesis is rejected and alternative hypothesis is accepted,
and the relationship between x and y is significant. This result proved that the sea-level rise
for past 100 years is significant, as suggested by MINC, 2000.
The same procedure is repeated for other stations. Table 3.2 shows the result for the statistical
test.
29
Table 3.2 Statistic t-test result for selected tidal stations.
Degree of
No.
Station
Freedom
(n-2)
Correlation
Standard
Coefficient, r
Error of r
t-distribution
1
Tg Gelang
19
0.59
0.1852
3.1852
2
Tg Sedili
16
0.60
0.2000
3.0000
3
Kukup
17
0.29
0.2321
1.2494
4
P Klang
19
0.21
0.2243
0.9362
5
P Pinang
17
0.39
0.2233
1.7465
6
K Kinabalu
15
0.53
0.2190
2.4206
7
Tawau
15
0.19
0.2535
0.7495
From table 3.2, only Tg Gelang, Tg Sedili and Kota Kinabalu accept the alternative
hypothesis, including Getting, while other stations rejected the alternative hypothesis. This is
due to smaller sample size; record of the tidal stations is not long enough. However, this
result will be used in this study and hopefully new and longer record will be used in the
future.
3.5 Time Series Analysis
Chatfield (1975) define a time series is a collection of observations made sequentially
in time. Time series arise in many different areas such as in economic, marketing and
oceanography and many types of time series occur in the physical sciences; meteorology,
marine science and geophysics.
Time series is often used to forecast future, to predict changes. So when unexpected
conditions occur, the corrective or immediate action should be taken to control the process or
stabilized the condition. If the time series can be predicted it is called deterministic else it is
30
stochastic. Knowledge of past values with probability distribution is use to predict the future
value for stochastic time series.
Andrew (1993), stated that there are two aspects to study time series; analysis and
modeling. The aim of analysis is to summarise the properties of a series and to characterize
its salient features. Andrew (1993) also support Chatfield (1975) that the main reason for
model a time series is to enable forecasts of future values to be made.
For this study, forecasting on tidal data for selected tidal stations have been made to
predict any changes to Malaysian sea level in the future. MINITAB 13 software will be used
to do the time series analysis. Figure 3.3 to Figure 3.10 show a trend analysis which give a
observed values, best fit values and forecast values for next 50 years (from 2004 to 2054).
Figure 3.3 Trend Analysis for Getting
31
Figure 3.4 Trend Analysis for Tg Gelang
Figure 3.5 Trend Analysis for Tg Sedili
32
Figure 3.6 Trend Analysis for Kukup
Figure 3.7 Trend Analysis for P Klang
33
Figure 3.8 Trend Analysis for P Pinang
Figure 3.9 Trend Analysis for K Kinabalu
34
Figure 3.10 Trend Analysis for Tawau
The x-axis will be the years of tidal record and y-axis is the annual sea level of the
tidal stations. From Figure 3.3 to Figure 3.10, the different trend of forecast value from linear
trend of fits values for Kukup, Kota Kinabalu and Tawau is obtained. The linear trend of
forecast values is above the linear trend of fits values. While linear trend of forecast values
for P Pinang and Getting is slightly above the linear trend line of fits values. Linear trend line
of forecast values for other stations does not showed any differences between the fits values
and forecast values.
The differences between the fits values and forecast values trend lines may be due to
years of tidal record which have less than 30 years of records. Another factor will be taken
into consideration is error of the observed values perhaps the error occurred during data
recording at the tidal stations.
From Figure 3.9 and Figure 3.10, the forecast values of annual sea level of Kota
Kinabalu and Tawau is high from the fits value, and this trend line gave a sign of next 50
years that this two places and its community may vulnerable to the effect of sea level rise.
35
Kota Kinabalu and Tawau is located at the open sea of this region, the South China Sea and
the Celebes Sea. Tawau is facing the Pacific Ocean and the strong effect of El Nino and La
Nina will be affect Tawau compared to other places. Chapter 4 will be discussed about this
matter latter.
36
CHAPTER 4
RESULT AND ANALYSIS
4.1 Introduction
In this chapter, six different analyses will be conducted relevant to the overall
objective. The six analyses are as follows:
1. The sea level rise during La Niña events as compared to the sea level rise during the
northeast monsoon off the east coast of Peninsular Malaysia and East Sabah
2. The sea level rise due to downwelling as compared to sea level rise during La Niña
years during the southwest monsoon season in West Sabah
3. The sea level rise during La Niña events as compared to the sea level rise during the
southwest monsoon for the west coast of Peninsular Malaysia and West Borneo
4. A decrease of the sea level due to upwelling, in the boreal winter compared to the
amplitude of the lowering of the sea level during El Niño years in West Sabah
5. A lowering of the sea level in the boreal summer compared with the lowering of the
sea level due to El Niño events at the east coast of Peninsular Malaysia and East
Borneo
6. A decrease of the sea level in the boreal winter versus the decrease observed during El
Niño events at the west coast of Peninsular Malaysia
4.2 THE SEA LEVEL RISE DURING LA NIÑA EVENTS AS COMPARED TO THE
SEA LEVEL RISE DURING THE NORTHEAST MONSOON OFF THE EAST
COAST OF PENINSULAR MALAYSIA AND EAST SABAH
A piling up of water followed quite naturally at the eastern boundary of Peninsular
Malaysia during boreal winter due to monsoons wind with magnitude 10m-1s-1. The water
flows in equatorward motion at the eastern coast of Peninsular Malaysia during this season.
In the east coast of Peninsular Malaysia, the regression lines of normal year and of La
Niña year during the northeast monsoon season were parallel weakly increase. As a
consequence, the slope (m) and the correlation coefficient, r, of the graph that had been
observed in Geting (Figure 4.2-1a) is small compared to the other two stations in East Coast
of Peninsular Malaysia. The correlation coefficient in Geting is the weakest among the three
stations located in East Coast of Peninsular Malaysia that were used in this study with the
increasing rate, m, is about 0.015cm per year and the correlation coefficient is , r =0.09
during La Niña year. While during normal year, the correlation coefficient and slope of the
regression line (m) is also the smallest and weakly increase with m = 0.014 cm per year and r
= 0.10. However , Figure 4.2-1c, showed that the regression line of northeast monsoon is
grew stronger than regression line of La Nina years regression line.
Tg Gelang (Figure 4.2-2a) regression line stronger increase during La Niña year with
m=0.034 cm per year and r = 0.41 which is considered almost moderate strong correlation
coefficient. The normal year regression line showed that Tg Gelang still have the stronger
correlation coefficient and higher slope value compared to other stations in East Coast of
Peninsular Malaysia. Tg Sedili (Figure 4.2-3a) regression line represented the moderate
strong increase compared to other stations. Figure 4.2-2c and 4.2-3c showed the same
condition occurred in both places as in Geting, where the sea level in increased stronger in
northeast monsoon than sea level during La Nina years.
38
NE Monsoon During La Nina Years vs NE Monsoon During
Normal Years - Geting
Monthly Mean Sea
Level (cm)
300
280
y = 0.0158x + 246.96
R = 0.09
260
240
y = 0.0143x + 244.13
R = 0.10
220
200
084
06
2486 48 88 72 90 96 92120 94
144 96
168
98
192
00
216
02
240
04
264
Year
La Nina
Normal
Linear (Normal)
Linear (La Nina)
Figure 4.2-1a. Sea Level During Northeast Monsoon versus Sea Level
During Northeast Monsoon in Getting
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During NE Monsoon Geting
290
y = -0.5007x + 1260.5
R = 0.34
270
250
230
y = 0.3724x - 511.69
R = 0.42
210
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.2-1b. Minimum and Maximum Sea Level During Northeast
Monsoon in Getting
Annual Sea Level (cm )
Geting
255
250
245
y = 0.1318x - 16.921
y = 0.0375x + 156.19
r = 0.24
r = 0.15
240
235
230
225
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.2-1.c. Sea Level During La Nina And Northeast Monsoon in Getting
39
NE Monsoon During La Nina Years vs NE Monsoon During
Normal Years - Tg Gelang
Monthly Mean Sea Level
(cm)
330
y = 0.0348x + 291.96
R = 0.41
310
290
y = 0.0188x + 290.96
R = 0.21
270
250
084
06
2486 48 88 72 90 96 92 120 94144 96168 98192 00216
02
240
04
264
Year
La Nina
Year
Linear (Normal)
Normal
Linear (La Nina)
Figure 4.2-2.a. Sea Level During Northeast Monsoon versus Sea Level During
Northeast Monsoon in Tg Gelang
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During NE Monsoon Tg Gelang
320
y = 0.1686x - 34.301
R = 0.20
310
300
290
280
y = 0.2163x - 147.49
R = 0.36
270
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.2-2.b. Minimum and Maximum Sea Level During Northeast Monsoon
in Tg Gelang
Annual Sea Level (cm )
Tg Gelang
300
295
290
y = 0.2184x - 142.19 y = 0.2759x - 268.23
r = 0.79
r = 0.49
285
280
275
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.2-2.c. Sea Level During La NinaAnd Northeast Monsoon in Tg Gelang
40
NE Monsoon During La Nina Years vs NE Monsoon During
Normal Years - Tg Sedili
Monthly Mean Sea
Level (cm)
280
y = 0.0223x + 253.34
R = 0.24
260
y = 0.0176x + 251.62
R = 0.17
240
220
0
84
06
2486 48 88 72 90 96 92 120 94144 96168 98
192 00
216
240
02
264
04
Year
La Nina
Normal
Linear (Normal)
Linear (La Nina)
Figure 4.2-3.a. Sea Level During Northeast Monsoon versus Sea Level
During Northeast Monsoon in Tg Sedili
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During NE Monsoon Tg Sedili
280
y = -0.0264x + 315.47
R = 0.03
260
240
y = 0.3609x - 477.21
R = 0.54
220
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.2-3.b. Minimum and Maximum Sea Level During Northeast
Monsoon in Tg Sedili
Tg Sedili
Annual Sea Level (cm )
260
255
250
y = 0.2427x - 230.9
r = 0.47
245
y = 0.272x - 300.09
r = 0.98
240
235
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.2-3.c. Sea Level During La Nina And Northeast Monsoon in Tg Sedili
41
From Figure 4.2-1b, 4.2-2b and 4.2-3b, east coast of Peninsular Malaysia observed a
highest maximum sea level during northeast monsoon in strong cool event in 1999 except
Getting. La Niña event in 1988 had not showed any significant increment of sea level during
northeast monsoon season except Tg Gelang.
Findings in the East Coast of Peninsular Malaysia in this study are consistent with
Camerlengo and Demmler (1997) findings. In their study, they said that due to persistence of
the northeasterly winds during the northeast monsoon, the water mass piled up against the
western boundary of South China Sea, in this case it is the East Coast of Peninsular Malaysia,
which caused sea surface elevation to increase towards the coastlines. Eventhough the slope
of the regression is small, it still shows that the water piled up during the boreal winter and
when the La Niña occured, the slope of the graphs increase stronger than the regression line
in normal year.
While in Tawau (Figure 4.2-4a), which is located in the east coast of Sabah, the
regression line of the La Niña year grows stronger compared to the other three stations in
East Coast of Peninsular Malaysia. The slope, m of the graph increases 0.05 cm per year and
the correlation coefficient is almost stronger with r=0.79, again the strongest compared to
other stations. However, the regression line during the normal year is decreased weakly.
From Figure 4.2-4c, opposite condition occurred in Tawau compared to east coast of
Peninsular Malaysia. The sea level in La Niña increased stronger than sea level in northeast
monsoon.
NE Monsoon During La Nina Years vs NE Monsoon During
Normal Years - Tawau
Monthly Mean Sea
Level (cm)
300
290
y = 0.0506x + 269.35
R = 0.79
280
270
y = -0.0026x + 270.04
R = 0.05
260
250
240
84
0
2486
4888 72 90 96 92 120 94 144 96 168 98192 00216 02240 04
264
Year
La Nina
Normal
Linear (Normal)
Linear (La Nina)
Figure 4.2-4.a. Sea Level During Northeast Monsoon versus Sea Level During
Northeast Monsoon inTawau
42
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During NE Monsoon Tawau
290
280
y = 0.1295x + 14.746
R = 0.14
270
260
y = 0.3562x - 445.57
R = 0.30
250
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.2-4b. Minimum and Maximum Sea Level During Northeast
Monsoon in Tawau
Tawau
Annual Sea Level (cm )
285
280
y = 0.4672x - 655.51
r = 0.99
275
270
y = 0.2249x - 179.83
r = 0.23
265
260
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.2-4c. Sea Level During La Nina And Northeast Monsoon in Tawau
Figure 4.2-4b had shows that the principal maximum of sea level is observed during
the strongest La Nina event in 1999. This maximum of sea level was continued until 2001
and the secondary maximum occurred in 1988 La Niña year.
From Figure 4.2-1a to Figure 4.2-1b, Figure 4.2-2a to Figure 4.2-2b, Figure 4.2-3a to
Figure 4.2-3b and Figure 4.2-4a to Figure 4.2-4b, the value of the sea level is higher during
La Niña year in all stations and in Tawau, the sea level is the highest during La Niña year
compare to other stations that have been discussed in this study. In the end of the year,
November 1999 to March 2000 were recorded to have the highest value of sea level in five
consecutive months. When the La Niña event occurs Tawau was among the early places in
ECS received the effects of this cool event because Tawau is facing the Pacific Ocean.
However, if these Figures compared to Figures 4.2-1c to Figure 4.2-4c, the sea level in
43
Tawau showed a consistent increasing in sea level in both events, while other stations showed
that strong effect of northeast monsoon to the sea level in ECPM.
44
4.3 THE SEA LEVEL RISE DUE TO DOWNWELLING AS COMPARED TO SEA
LEVEL RISE DURING LA NIÑA YEARS DURING THE SOUTHWEST MONSOON
SEASON IN WEST SABAH
During the northeast monsoon season, the water mass piled up, but during southwest
monsoon (SW) season the opposite conditions occurred. Lowering of the water mass
occurred and might cause the sea surface elevation to decreased against the coastlines.
SW monsoon during normal years was observed to have a positive regression line in
Kota Kinabalu. From Figure 4.3-1a, it had been observed that Kota Kinabalu had a moderate
strong correlation coefficient during La Nina year with r = 0.63 compared to normal year
which is, the correlation coefficient, r=0.33, which is almost half of correlation coefficient
value in La Nina year.
From Figure 4.3-1a, the value of sea level during normal year is relatively higher than
sea level during La Nina year as stated by Camerlengo et al (1999). The slope of the
regression line (m) of the normal year is increased 0.018 cm per year, however the slope of
southwest monsoon season in the La Nina year have the higher value, m = 0.032.
In the beginning of the record, the regression line of normal year during southwest
monsoon was above the La Nina year regression line. However, the occurrence of the strong
cool events in 1988 and 1999 gave an effect to sea level and the La Nina regression line grew
stronger than normal year.
45
Monthly Mean Sea Level
(cm )
(La Nina vs Normal) During SW Monsoon - K Kinabalu
270
y = 0.0323x + 248.55
R = 0.63
260
250
y = 0.0187x + 249.72
R = 0.33
240
84
86
88
90
La Nina
92
94
Year
Normal
96
98
00
Linear (La Nina)
02
04
Linear (Normal)
Figure 4.3-1a. K Kinabalu Sea Level (La Nina Year vs Normal Year)
During Southwest Monsoon
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During SW Monsoon Kota Kinabalu
270
260
y = 0.2522x - 247.66
R = 0.43
250
y = 0.3853x - 520.77
R = 0.63
240
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (SW)
Linear (Minimum (SW))
Minimum (SW)
Linear (Maximum (SW))
Figure 4.3-1b. Kota Kinabalu Maximum and Minimum Sea Level During
Southwest Monsoon Season
Annual Sea Level (cm )
K Kinabalu
265
260
y = 0.6195x - 980.52
r=1
255
250
245
1984
y = 0.323x - 392.94
r = 0.63
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.3-1c. Sea Level During Southwest Monsoon and La Nina Years in
Kota Kinabalu
46
This means that when La Nina existed during SW monsoon season, the sea level is
higher than sea level in normal year. However, from Figure 4.3-1b, the piling up of water
occurred highly during 2001, which is not a La Nina year. The maximum value of sea level
during this year is the highest compared to the other year including the La Nina year.
The high precipitation occurred with maximum rainfall (Figure 4.3-1d) is increased
during the cool event in Kota Kinabalu. The La Nina years were grouped in the right-hand
side as compared to the warm event, which is in left-hand side. The temperature and mean
sea level pressure (Figure 4.3-1e and 4.3-1f) also showed the same condition as rainfall.
However, the regression line of temperature and mean sea level pressure is in inverse
direction as compared to regression line of rainfall.
Figure 4.3-1d, 4.3-1e and 4.3-1f gave an evident that when maximum rainfall, low
temperature and low mean sea level pressure occurred, the sea level is higher during La Nina.
While when minimum rainfall, high temperature and high mean sea level pressure is existed,
the sea level is at the minimum level.
Kota Kinabalu
y = 5.6243x - 1204.4
R = 0.56
Annual Rainfall (cm)
300
01
88 95
250
93
92
200
94
91
150
90
96
98
89
99
00
03
04
02
250
252
97
100
246
248
254
256
258
260
Annual Sea Level (cm )
Figure 4.3-1d. Kota Kinabalu rainfall profile
47
y = -0.0119x + 30.327
R=0.20
Kota Kinabalu
28.5
Temperature (C)
98
28.0
97
27.5
91
92
27.0
02
90
95
93 94
04
88
99
03
96
00
01
89
26.5
245
247
249
251
253
255
257
259
Annual Sea Level (cm )
Figure 4.3-1e. Kota Kinabalu temperature profile
Kota Kinabalu
y = -0.0705x + 1027.3
R=0.54
Mean Sea Level Pressure
(hPa)
1011.0
97
1010.5
93
1010.0
98
04
03 02
92 94
1009.5
91
1009.0
95
90
89
99
01
96
88
1008.5
246
248
250
00
252
254
256
258
260
Annual Sea Level (cm )
Figure 4.3-1f. Kota Kinabalu mean sea level pressure profile
48
4.4 THE SEA LEVEL RISE DURING LA NIÑA EVENTS AS COMPARED TO THE
SEA LEVEL RISE DURING THE SOUTHWEST MONSOON FOR THE WEST
COAST OF PENINSULAR MALAYSIA AND WEST BORNEO
An early observation in Kukup (Figure 4.4-1a) showed that the La Nina year
regression line is at the bottom of the normal year regression line and Figure 4.4-1c has
proved that sea level during La Nina events is increased stronger compared to sea level
during southwest monsoon season in Kukup. However regression line of normal years
(Figure 4.4-1a) is increased weakly with slope, m = 0.003cm per year and correlation
coefficient, r = 0.09. In the middle of observational record, in 1995, the La Nina year
regression line is intersected with normal year regression line. La Nina years regression line
is strongly increased with m = 0.015cm per year and r = 0.43.
(La Nina vs Normal) During SW Monsoon- Kukup
Monthly Mean Sea Level
(cm )
406
404
y = 0.0036x + 398.44
R = 0.09
402
400
398
y = 0.0156x + 396.66
R = 0.43
396
394
392
84
86
88
La Nina
90
92
94
Year
Normal
96
98
Linear (La Nina)
00
02
04
Linear (Normal)
Figure 4.4-1a. Kukup Sea Level (La Nina vs Normal) During Southwest
Monsoon
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During SW Monsoon Kukup
410
405 y = 0.1577x + 86.11
R = 0.23
400
395
390
y = 0.0777x + 240.59
R = 0.13
385
380
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (SW)
Linear (Maximum (SW))
Minimum (SW)
Linear (Minimum (SW))
Figure 4.4-1b. Kukup Maximum and Minimum Sea Level During
Southwest Monsoon
49
Annual Sea Level (cm )
Kukup
410
y = 0.291x - 177.03
r=1
405
400
395
390
1984
y = 0.1445x + 109.8
r = 0.26
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.4-1c. Comparison of Sea Level During La Nina and Sea Level
During Southwest Monsoon Season
Different situation is occurred in the other station in the west coast of Peninsular
Malaysia. Pelabuhan Klang (Figure 4.4-2a) regression lines is decreased slowly. Data
observation in 1985 southwest monsoon during La Nina years had showed that the value of
mean sea level is the highest value compared to the southwest monsoon in normal years.
Eventhough in Figure 4.4-2a, showed a decreased in sea level, Figure 4.4-2c, showed small
increases in sea level during La Nina years compared to sea level during southwest monsoon
season.
(La Nina vs Normal) During SW Monsoon - P Klang
Monthly Mean Sea Level
(cm )
390
380
y = -0.0046x + 368.32
R = 0.07
370
360
y = -0.014x + 368.53
R = 0.22
350
84
86
88
La Nina
90
92
Normal
94
Year
96
98
Linear (La Nina)
00
02
04
Linear (Normal)
Figure 4.4-2a. P Klang Sea Level (La Nina vs Normal) During Southwest Monsoon
50
390
Minimum and Maximum Sea Level During SW Monsoon P Klang
y = -0.0592x + 489.12
R = 0.07
Annual Mean Sea
Level (cm )
380
370
360
350
340
1982
y = -0.0209x + 403.34
R = 0.03
1984 1986
1988
1990 1992
1994
1996 1998
2000
2002 2004
2006
Year
Maximum (SW)
Minimum (SW)
Linear (Maximum (SW))
Linear (Minimum (SW))
Figure 4.4-2b. P Klang Maximum and Minimum Sea Level During Southwest
Monsoon
Annual Sea Level (cm )
P Klang
375
370
y = 0.2748x - 179.5
r = 0.84
365
360
355
1984
y = 0.0033x + 359.61
r = 0.02
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.4-2.c. Comparison of Sea Level During La Nina and Sea Level
During Southwest Monsoon Season
During La Nina years, the regression line is increased in Pulau Pinang. However,
normal year regression line is decreased for the same station. From Figure 4.4-3a, the effect
of La Nina event have been caused the sea level to increased higher during southwest
monsoon season compared to the same monsoon season in normal years. Eventhough the
slope for both regression lines, m, is small (0.006 ≤ m ≤ 0.01), the range of the minimum and
maximum value of monthly mean sea level is big during southwest monsoon in normal years,
for example in 2004. While in Figure 4.4-3c, the sea level during southwest monsoon is
generally higher than sea level during La Nina years, but the regression line of La Nina years
is increased stronger compared to regression line during southwest monsoon season.
51
(La Nina vs Normal) During SW Monsoon - P Pinang
Monthly Mean Sea Level
(cm )
290
285
y = -0.0064x + 275.58
R = 0.10
280
275
270
y = 0.0176x + 269.98
R = 0.26
265
260
84
86
88
90
La Nina
92
94
Year
Normal
96
98
00
Linear (La Nina)
02
04
Linear (Normal)
Figure 4.4-3a. P Pinang Sea Level (La Nina vs Normal) During Southwest
Monsoon
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During SW Monsoon P Pinang
300
y = 0.1182x + 42.193
R = 0.15
290
280
270
260
y = 0.1095x + 49.32
R = 0.47
250
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (SW)
Minimum (SW)
Linear (Maximum (SW))
Linear (Minimum (SW))
Figure 4.4-3b. P Pinang Maximum and Minimum Sea Level During
Southwest Monsoon
Annual Sea Level (cm )
P Pinang
280
275
y = 0.2945x - 315.15
r = 0.98
270
y = 0.1284x + 16.799
r = 0.19
265
260
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.4-3c. Comparison of Sea Level During La Nina and Sea Level
During Southwest Monsoon Season
52
Figure 4.4-1b showed that the sea level of non-La Nina years have the maximum
value compared to the other years. From Figure 4.4-2b, there are no significant effects of La
Nina to sea level during southwest monsoon season. The same condition occurred for P
Pinang (Figure 4.4-3b).
Generally, when using annual sea level data, the result shows that sea level in
southwest monsoon season during La Nina years is higher compared to sea level in the same
monsoon during normal years. However maximum sea level is observed in non-La Nina
years in west coast of Peninsular Malaysia.
Meanwhile in west coast of Borneo island, the regression line of Kota Kinabalu
(Figure 4.4-4a), is increased with slope of the regression line, m, is between 0.01 and 0.03.
The correlation coefficient, r, is more than 0.30 for both regression lines. Maximum value
occurred in 2001 southwest monsoon season compared to other years including the La Nina
years (Figure 4.4-4b) and in Figure 4.4-4c shows an increment of higher sea level and it is
occurred during cool event compared to sea level during southwest monsoon season.
Monthly Mean Sea Level
(cm )
(La Nina vs Normal) During SW Monsoon - K Kinabalu
270
y = 0.0323x + 248.55
R = 0.63
260
250
y = 0.0187x + 249.72
R = 0.33
240
84
86
88
La Nina
90
92
Normal
94
Year
96
98
Linear (La Nina)
00
02
04
Linear (Normal)
Figure 4.4-4a. Kota Kinabalu Sea Level (La Nina vs Normal) During
Southwest Monsoon
53
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During SW Monsoon Kota Kinabalu
270
260
y = 0.2522x - 247.66
R = 0.43
250
y = 0.3853x - 520.77
R = 0.63
240
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (SW)
Linear (Minimum (SW))
Minimum (SW)
Linear (Maximum (SW))
Figure 4.4-4b. Kota Kinabalu Maximum and Minimum Sea Level During
Southwest Monsoon
K Kinabalu
Annual Sea Level (cm )
265
260
y = 0.6195x - 980.52
r =1
255
250
245
1984
y = 0.323x - 392.94
r = 0.63
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
La Nina
Linear (La Nina)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.4-4c. Comparison of Sea Level During La Nina and Sea Level
During Southwest Monsoon Season
The occurrence of cool event gave an effect to sea level rise and from Figure 4.4-4b,
maximum value of sea level during southwest monsoon season is occurred in non-La Nina
years.
54
4.5 A DECREASE OF THE SEA LEVEL DUE TO UPWELLING, IN THE BOREAL
WINTER COMPARED TO THE AMPLITUDE OF THE LOWERING OF THE SEA
LEVEL DURING EL NIÑO YEARS IN WEST SABAH
Sabah is the passage of the area of convergence associated with the northeast
monsoon. This monsoon lags one month compared to the corresponding one in Peninsular
Malaysia (Camerlengo, 2002). In December, the northeast monsoon is fully developed over
the South China Sea (SCS) and the currents are strong and off the shore of Vietnam often
exceed 1ms-1. The westward intensification is stronger than during the southwest monsoon,
when a deflection of the current occurs to the east caused by the wind (Wyrtki, 1961).
During neutral period or normal years, the normal years northeast monsoon sea level
regression line is increased 0.03 cm per year compared to El Nino year northeast monsoon
sea level regression line, which recorded an increasing trend 0.06 cm per year. From the
Figure 4.5-1a, it has been found that, in the end of 1998, the sea level observed the highest
value compared to the other warm event. This may be due to the end of the warm event and
to onset of the La Nina or cool event. This cool event occurred in the following year (1999).
As compared to Figure 4.5-1b, the range of maximum and minimum sea level is clearly
noticed, where lowering of the principal maximum of sea level is occurred in 1994 and 1997
warm event, which is the effect of the strong El Nino occurred in west Sabah. While in
Figure 4.5-1c, the regression line of northeast monsoon is increased higher than regression
line of El Nino years, which mean the sea level is higher in northeast monsoon than the sea
level in warm events.
According to Wyrtki (1961), the water from Sulu Sea flows into the SCS and mixed
into the main current with a very weak flow occurs along the coast of Borneo
southwestwards. The wind is cyclonic during the northeast monsoon.
An increase in the mean of the temperature and sea level pressure (Figure 4.5-1d and
Figure 4.5-1e) also recorded during El Nino event, as contrast to the rainfall (Figure 4.5-1f),
which observed the minimum values. From the same Figures, the warm years was grouped in
the left-hand side while the cool event on the right-hand side.
56
Kota Kinabalu
280
y = 0.0306x + 248.32
r = 0.257
Mean Monthly Sea
Level (cm )
270
260
250
240
y = 0.0698x + 241.55
r = 0.248
230
220
88
90
92
94
96
98
00
02
04
06
Year
Normal Year
Linear (El Nino Year)
El Nino Year
Linear (Normal Year)
Figure 4.5-1a. Kota Kinabalu Sea Level During El Nino and Normal Years
Minimum and Maximum Sea Level During NE Monsoon Kota Kinabalu
Annual Mean Sea
Level (cm )
280
270
y = 0.2187x - 173.22
R = 0.17
260
250
y = 0.3842x - 525.42
R = 0.38
240
230
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.5-1b. Kota Kinabalu Maximum and Minimum Sea Level during
Northeast Monsoon
Annual Sea Level (cm )
K Kinabalu
265
y = 0.4893x - 725.7
r = 0.48
260
255
250
y = 0.4451x - 638.93
r = 0.78
245
240
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.5-1c. Sea Level During El Nino and Northeast Monsoon Season
57
y = -0.0119x + 30.327
R=0.20
Kota Kinabalu
Tem perature (C)
28.5
98
28.0
97
27.5
91
92
27.0
02
90
95
93 94
04
88
99
03
00
01
96
89
26.5
245
247
249
251
253
255
257
259
Annual Sea Level (cm )
Figure 4.5-1d. Kota Kinabalu Temperature Profile
Mean Sea Level Pressure
(hPa)
Kota Kinabalu
y = -0.0705x + 1027.3
R=0.54
1011.0
97
1010.5
93
1010.0
9
04
03 02
92 94
1009.5
91
1009.0
95
90
99
89
01
96
88
1008.5
246
248
250
00
252
254
256
258
260
Annual Sea Level (cm )
Figure 4.5-1e. Kota Kinabalu Mean Sea Level Pressure Profile
Kota Kinabalu
y = 5.6243x - 1204.4
R = 0.56
Annual Rainfall (cm )
300
88 95
250
93
92
200
94
91
150
100
246
90
01
96
98
89
99
00
03
04
02
250
252
97
248
254
256
258
260
Annual Sea Level (cm )
Figure 4.5-1f. Kota Kinabalu Rainfall Profile
58
4.6 A LOWERING OF THE SEA LEVEL IN THE BOREAL SUMMER COMPARED
WITH THE LOWERING OF THE SEA LEVEL DUE TO EL NIÑO EVENTS
AT THE EAST COAST OF PENINSULAR MALAYSIA AND EAST BORNEO
The regression line of Figure 4.6-1a, 4.6-2a and 4.6-3a, during El Nino years and
normal years is increased in Geting, Tg Gelang and Tg Sedili. However, regression line of
normal year is decreased in Tawau (Figure 4.6-4a).
Geting regression line of normal year during boreal summer intersects with El Nino
years regression line during boreal summer, in the middle of the record with slope of the
graph lesser than 0.045 cm per year and the correlation coefficient, r, is lesser than 0.50,
which is considered as moderate strong correlation coefficient. If compared to Figure 4.6-1b,
the sea level observed in Geting in boreal summer during El Nino years, the lowering of the
mean sea level is at the principal minimum, during strong El Nino event 1991-1995 and
secondary minimum during El Nino event in 2002.
While regression lines of Tg Gelang (Figure 4.6-2a) and Tg Sedili (Figure 4.6-3a)
during normal year intersect with regression line during El Nino year in the end of the record.
The value of the increasing slope during normal year is between 0.01 cm and 0.02 cm per
year and the correlation coefficient, r, is between 0.25 and 0.33. However, the regression line
during El Nino years increase stronger compared to normal years. The slope of the graph is
between 0.025 cm and 0.040 cm per year and the correlation coefficient is , 0.30 ≤ r ≤ 0.45. If
Figure 4.6-1b compared to Figure 4.6-2b and Figure 4.6-3b, the different condition occurred
in Tg Gelang and Tg Sedili, where the effect of the El Nino event is not so strong compared
to Geting.
59
Monthly Mean Sea Level (cm )
(El Nino vs Normal) During SW Monsoon - Geting
230
225
y = 0.0422x + 205.77
R = 0.43
220
215
210
y = 0.031x + 207.06
R = 0.41
205
200
84
0
86
24
88
48
7290
9692
94
120
14496 168 98 19200 216 02 240 04264
Year
El Nino
Normal
Linear (El Nino)
Linear (Normal)
Figure 4.6-1a. Geting El Nino Year vs Geting Normal Year During
Southwest Monsoon
Minimum and Maximum Sea Level During SW Monsoon Geting
Annual Mean Sea Level
(cm )
230
225
220
215
210
205
y = 0.4763x - 732.5
R = 0.53
y = 0.4035x - 597.58
R = 0.72
200
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
Year
Maximum (SW)
Linear (Maximum (SW))
Minimum (SW)
Linear (Minimum (SW))
Figure 4.6-1b. Getting Maximum and Minimum Sea Level During
Southwest Monsoon
Geting
Annual Se a Le vel (cm )
235
230
225
y = 0.227x - 224.26
r = 0.47
220
215
210
y = 0.3388x - 464.01
r = 0.60
205
200
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.6-1c. Sea Level During El Nino and Southwest Monsoon
Season in Geting
60
(El Nino vs Normal) During SW Monsoon - Tg Gelang
Monthly Mean Sea Level (cm)
280
y = 0.0218x + 262.02
R = 0.33
275
270
265
260
y = 0.0263x + 260.79
R = 0.34
255
250
084
24
86
48
88
7290
9692
12094 14496 168 98 192 00 216 02 240 04264
Year
El Nino
Normal
Linear (El Nino)
Linear (Normal)
Figure 4.6-2a. Tg Gelang El Nino Year vs Tg Gelang Normal Year
During Southwest Monsoon
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During SW Monsoon Tg Gelang
290
280
y = 0.2656x - 258.09
R = 0.55
270
260
y = 0.2498x - 237.1
R = 0.62
250
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (SW)
Linear (Maximum (SW))
Minimum (SW)
Linear (Minimum (SW))
Figure 4.6-2.b. Tg Gelang Maximum and Minimum Sea Level
During Southwest Monsoon
Tg Gelang
Annual Sea Level (cm )
285
280
275
y = 0.224x - 167.97
r = 0.68
270
265
y = 0.2348x - 203.3
r = 0.62
260
255
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.6-2c. Sea Level During El Nino and Southwest Monsoon
Season in Tg Gelang
61
Monthly Mean Sea Level (cm)
(El Nino vs Normal) During SW Monsoon - Tg Sedili
240
y = 0.0153x + 225.62
R = 0.25
230
220
y = 0.0395x + 221
R = 0.45
210
084
86
24
88
48
7290
9692 12094 14496 168 98 192 00 216 02240 04264
Year
Linear (El Nino)
Normal
El Nino
Linear (Normal)
Figure 4.6-3a. Tg Sedili El Nino Year vs Tg Sedili Normal Year During
Southwest Monsoon
Minimum and Maximum Sea Level During SW Monsoon Tg Sedili
Annual Mean Sea Level
(cm)
250
y = 0.4272x - 618.77
R = 0.57
240
230
220
y = 0.3289x - 432.93
R = 0.67
210
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (SW)
Linear (Maximum (SW))
Minimum (SW)
Linear (Minimum (SW))
Figure 4.6-3b. Tg Sedili Maximum and Minimum Sea Level During
Southwest Monsoon
Tg Sedili
Annual Sea Level (cm )
245
240
y = 0.2316x - 222.6
r = 0.75
235
230
225
y = 0.3229x - 417.04
r = 0.67
220
215
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.6-3c. Sea Level During El Nino and Southwest Monsoon
Season in Tg Sedili
62
While in Tawau, the regression line of El Nino years is stronger increase, the
correlation coefficient, r, is between weak to moderate strong during El Nino, with r = 0.48
and the correlation coefficient of regression line of normal years is a negative correlation, r =
0.33. The effect strong El Nino is noticed in 1991-1995 and 1997 where two principal
minimum of sea level lowering occurred during these warm event.
Monthly Mean Sea Level (cm)
(El Nino vs Normal) During SW Monsoon - Tawau
290
y = -0.0197x + 274.43
R = 0.33
280
270
260
y = 0.0452x + 260.52
R = 0.48
250
084
24
86
48
88
7290
9692
12094 14496 168 98 192 00 216 02 240 04264
Year
El Nino
Normal
Linear (El Nino)
Linear (Normal)
Figure 4.6-4a. Tawau El Nino Year vs Tawau Normal Year During Southwest
Monsoon
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During SW Monsoon Tawau
285
275
265
y = 0.0277x + 216.97
R = 0.03
y = 0.1784x - 87.955
R = 0.18
255
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (SW)
Linear (Maximum (SW))
Minimum (SW)
Linear (Minimum (SW))
Figure 4.6-4b. Tawau Maximum and Minimum Sea Level During
Southwest Monsoon
63
Tawau
Annual Sea Level (cm )
280
275
270
y = 0.1195x + 31.532
r = 0.12
y = 0.4426x - 616.28
r = 0.63
265
260
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Southw est Monsoon
Linear (Southw est Monsoon)
Figure 4.6-4c. Sea Level During El Nino and Southwest Monsoon Season
in Tawau
As a conclusion, the lowering of sea level occurred during southwest monsoon season
compared to the sea level during El Nino event in East Coast of Peninsular Malaysia and East
Coast of Sabah except in Tawau.
64
4.7 A DECREASE OF THE SEA LEVEL IN THE BOREAL WINTER VERSUS
THE DECREASE OBSERVED DURING EL NIÑO EVENTS AT THE WEST
COAST OF PENINSULAR MALAYSIA
Sea level in west coast of Peninsular Malaysia is increased weakly during normal year
as the sea level in El Nino years during northeast monsoon season. However, during warm
event, the sea level is lower than sea level in normal year. In other word, the lowering of sea
level is clearly noticed during El Nino years compare to normal years.
Minimal effect of northeast monsoon is received in west coast of Peninsular Malaysia
due to mountain range that covers west coast from northeast monsoon rains. Regression line
of normal year in all places showed small increasing in sea level. However, during the El
Nino year, the regression line is at the bottom of regression line of normal year. In normal
year, the slope of regression line during northeast monsoon season is between 0.01 and 0.04.
Located at the southern west coast of Peninsular Malaysia, Kukup (Figure 4.7-1a)
observed the smallest correlation coefficient, r, and slope of the graph is also small compare
to other stations with r = 0.13 and m = 0.01, which mean it is increased weakly in normal
year during boreal winter. P Pinang (Figure 4.7-3a) regression line is increased strongly (m =
0.04) and located at the northern west coast of Peninsular Malaysia. The correlation
coefficient in P Pinang also recorded the strongest compared to the other two stations,
eventhough the correlation coefficient of P Pinang is considered weak (r = 0.29).
From the Figure 4.7-1c, warm event that was recorded in 1991-1995 gave a strong
effect to Kukup sea level during northeast monsoon season compare to P Klang and P Pinang
(Figure 4.7-2c and 4.7-3c). However one of the strong El Nino that has been ever recorded in
1997 gave a strong effect to P Pinang sea level during northeast monsoon. The lowering sea
level occurred during this monsoon season.
65
Monthly Mean Sea Le vel (cm )
(El Nino vs Normal) During NE Monsoon- Kukup
430
y = 0.0144x + 399.26
R = 0.13
420
410
400
390
y = 0.0039x + 398.72
R = 0.03
380
370
0
24
48
72
96
120
144
168
192
216
240
264
Year
El Nino
Normal
Linear (El Nino)
Linear (Normal)
Figure 4.7-1a. Kukup Sea Level During El Nino and Normal Years
Minimum and Maximum Sea Level During NE Monsoon Kukup
Annual Mean Sea
Level (cm )
430
420
y = -0.2279x + 865.92
R = 0.24
410
400
y = 0.3125x - 230.68
R = 0.36
390
380
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.7-1b. Kukup Maximum and Minimum Sea Level during Northeast
Monsoon
Annual Sea Level (cm )
Kukup
415
410
y = 0.151x + 99.993
R2 = 0.045
405
400
y = 0.042x + 314.62
R2 = 0.0055
395
390
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.7-1c. Sea LevelDuring El Nino and Northeast Monsoon Season in
Kukup
66
Monthly Mean Sea Level (cm )
(El Nino vs Normal) During NE Monsoon- P Klang
400
390
y = 0.0327x + 354.79
R = 0.23
380
370
360
350
340
y = 0.0145x + 354.2
R = 0.07
330
084
2486
48 88 72 90 96 92 120 94 144 96168 98 192
00216
02
240
04
264
Year
El Nino
Normal
Linear (El Nino)
Linear (Normal)
Figure 4.7-2a. P Klang Sea Level During El Nino and Normal Years
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During NE Monsoon P Klang
420
y = 0.0103x + 352.61
R = 0.0002
400
380
360
340
y = 0.2012x - 51.074
R = 0.18
320
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.7-2b. P Klang Maximum and Minimum Sea Level during
Northeast Monsoon
Annual Sea Level (cm )
P Klang
375
y = 0.1437x + 73.934
R2 = 0.0348
370
365
360
355
y = 0.2205x - 80.305
R2 = 0.0582
350
345
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.7-2c. Sea Level During El Nino and Northeast Monsoon Season
in P Klang
67
(El Nino vs Normal) During NE Monsoon- P Pinang
Monthly Mean Sea Leve l
(cm )
300
y = 0.0427x + 256.46
R = 0.29
290
280
270
260
250
y = 0.0139x + 257.11
R = 0.06
240
230
0 84
86
24
88
48
90
72
92
96
94
120
96
144
98
168
00
192
02
216
24004 264
Year
El Nino
Normal
Linear (El Nino)
Linear (Normal)
Figure 4.7-3a. P Pinang Sea Level During El Nino and Normal Years
Annual Mean Sea Level
(cm )
Minimum and Maximum Sea Level During NE Monsoon P Pinang
300
290
y = -0.1953x + 665.69
R = 0.13
280
270
260
y = 0.409x - 563.73
R = 0.31
250
240
230
1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Maximum (NE)
Linear (Maximum (NE))
Minimum (NE)
Linear (Minimum (NE))
Figure 4.7-3b. P Pinang Maximum and Minimum Sea Level during
Northeast Monsoon
Annual Sea Level (cm )
P Pinang
275
y = 0.1022x + 62.363
R2 = 0.0154
270
265
260
y = 0.3384x - 413.2
R2 = 0.1124
255
250
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
Year
El Nino
Linear (El Nino)
Northeast Monsoon
Linear (Northeast Monsoon)
Figure 4.7-3c. Sea Level During El Nino and Northeast Monsoon Season
in P Klang
68
CHAPTER 5
CONCLUSION AND RECOMMENDATION
Sea level rise or change will give challenges to the government especially the coastal
communities. Two things will appear in their thought, whether a given community will
attempt to hold back the sea or allow the shore to retreat and whether to prepare now or waits
for the effects of sea level rise to emerge.
Two fundamental ways for holding back the sea was given by Boesch et al (2000).
First is to build structures such as dikes, seawalls, bulkheads and revetments which form a
barrier between water and land, but will sacrifice the beach, wetlands and other intertidal
zones and leave the dry land relatively unaffected. Second, an elevation of all land surfaces,
which can allow wetlands and beach to survive. Built a shoreline armoring such as bulkhead,
revetment etc, are the most common way to hold back the sea. For examples, in Maryland,
USA.
Boesch et al (2000) also given two fundamental ways to ensure that human activities
do not impede the natural inland migration of shorelines as the sea level rise. First to prevent
development in the coastal areas, otherwise decrease the property owner’s economic
motivation to hold back the sea. Another option is the use of rolling easements, which allow
development but explicitly prevent property owners from holding back the sea with structures
that eliminate wetlands and beaches. Policies that prevent development can conserve natural
shorelines
Policy makers or the government as the law maker may take this recommendation for
making policies or as an alternative to existing policies to make sure the coastal areas and
coastal communities are not vulnerable to sea-level rise. Malaysia has endeavoured to
introduce a variety of measures to achieve sustainable development in relevant policies for
short, medium or long-term development plans. The strategies include promulgation of
environmental and related regulations and their enforcement, land use planning and
increasing public awareness. The government has had introduced an integrated approach
towards attaining both environmental and development activities including impose
Environmental Impact Assessment (EIA) and a National Policy on Biological Diversity. The
national and marine parks, wild reserve and sanctuaries enacted various legislation to protect
land, coastal and marine resources from erosion, air and water pollution (MINC,2000).
Campaigns to the public by the government to increase the awareness of the sea-level
rise, cause of the development to coastal areas, coastal erosion, effect of sea-level rise to coral
reef will help the policy makers to control the effect of the sea-level rise to coastal
community and also save the environments for future generation.
70
Figure 1:
Figure 2
Figure 1 and 2 show sea level observation tools in Johor Bahru tide station
Figure 3
Figure 4
Figure 3 and 4 shows the location of the tide gauge station in Johor Bahru
Figure 5
Figure 6
Figure 5 and 6 shows a tide gauge station in Tg Sedili, Johor; which is located
at the Lembaga Kemajuan Ikan Malaysia jetty.
Figure 7
Tide gauge station in Kukup, Pontian Johor.
Figure 8
Figure 9
Figure 8 and 9 shows the sea level observation tool and general information in
Kota Kinabalu, Sabah.
Figure 10
Figure 11
Figure 10 and 11 shows tide gauge location in Kota Kinabalu and tide gauge station in
station in Kudat, Sabah
Figure 12: Kota
Kinabalu tide gauge
station
Figure 13 :
Tg Mengayau, sabah
Figure 14 :
Kudat, Sabah
Figure 15 :
Kota Kinabalu, Sabah
EXECUTIVE SUMMARY
Issue on sea-level rise has been a main concern for many countries especially the coastal
region since the last decade and has gotten the attention of coastal scientists and
engineers for some time now. More than 60% of Malaysia population lives near the
coastal zone. Most of the coastal regions are low-lying areas that are less than 0.5m
above the astronomical tide, or are within 100m inland of the high-water mark and it is
vulnerable to sea-level rises.
Global warming and climate change is connected to sea-level rise in many ways.
Sea level is projected to accelerate during this century with dramatic impact in low-lying
areas. Infrastructure such as Paka Power Station located in Terengganu is an example of
facility, which is experiencing the effects of severe coastal erosion and has to be
defended by structural works (MINC, 2000).
Another factors have been taken into our interest is the El Nino and La Nina
events. During El Nino years, the lowering of the sea level occured especially in the East
Malaysia, which received the great impact of the warm event compared to the West
Malaysia. The lowering of sea level is recorded level in 1991-1995 which is a warm
event for five consecutive years and during strong warm event in 1997-1998. Also during
these years, Malaysia faced the water shortage; effected from the El Nino event. While
La Nina event in 1999 caused the sea level rose higher than other normal years.
Generally, all station recorded a higher sea level compared to other years.
Effect of the monsoon to the Malaysian sea level rise is also investigated in this
study. Malaysia received two types of monsoons, namely, northeast monsoon and
southwest monsoon. The northeast monsoon prevails from early November or December
to March. Borneo Island and the east coast of Peninsular Malaysia received this type of
wind while in the west coast of Peninsular Malaysia, the southwest monsoon occurred. It
has been a question whether the monsoons have the effect on the sea level rise. However
from this study, it is clearly noticed that the occurrence of the El Nino event, La Nina
event and monsoon together, have affected the sea level rise.
Three meteorological parameters have been included into this study to find the
connection between these parameters and sea level. The result shows during unusual
warm temperature (during the El Nino years), the sea level was really affected by the
temperature and the lowering of sea level occurred. The similar result for mean sea level
pressure is observed. While, the higher rainfall cause the piling up of sea level.
RINGKASAN EKSEKUTIF
Isu berkenaan dengan peningkatan paras laut telah menjadi perhatian banyak negara terutamanya
di kawasan pesisiran laut sejak sedekad yang lalu dan telah mendapat perhatian saintis dan
jurutera pantai. Lebih daripada 60% kependudukan Malaysia tinggal berhampiran pesisiran
pantai. Kebanyakan kawasan pesisiran pantai terletak di kawasan yang rendah dimana ia terletak
kurang daripada 0.5m dari aras astronomi air pasang surut, atau dalam lingkungan 100m di
daratan dari aras tertinggi air laut dan terdedah kepada kejadian peningkatan paras laut.
Pemanasan global dan perubahan cuaca dikaitkan dengan kejadian peningkatan paras
laut. Dijangkakan paras laut akan meningkat pada abad ini dengan kesan serius di kawasan
rendah. Infrastruktur seperti stesen janakuasa Paka yang terletak di Terengganu adalah satu
contoh kemudahan yang mengalami kesan buruk daripada penghakisan pantai dan perlu
dikukuhkan dengan kerja-kerja struktur (MINC,2000).
Faktor lain yang menjadi perhatian adalah fenomena El Nino dan La Nina. Semasa tahun
El Nino, aras laut adalah lebih rendah, terutama di Malaysia Timur yang mana menerima kesan
yang kuat daripada fenomena pemanasan tersebut jika dibandingkan dengan Malaysia Barat.
Paras laut yang rendah semasa fenomena pemanasan ini direkodkan telah berlaku selama lima
tahun berturut-turut iaitu daripada tahun 1991 hingga 1995 dan daripada tahun 1997 hingga
1998. Pada tahun-tahun ini juga Malaysia telah mengalami kekurangan bekalan air, kesan
daripada kejadian El Nino ini. Bagaimana pun, kejadian La Nina pada 1999 telah menyebabkan
paras laut lebih tinggi daripada tahun-tahun biasa. Secara umumnya, semua stesen merekodkan
paras laut yang lebih tinggi semasa La Nina dibandingkan dengan tahun-tahun lain.
Kesan monsun kepada paras laut Malaysia juga dikaji dalam penyelidikan ini. Malaysia
menerima 2 jenis monsun; monsun timur laut dan monsun barat daya. Monsun timur laut bertiup
dari awal November atau Disember hingga Mac. Kepulauan Borneo dan kawasan pantai timur
Semenanjung Malaysia menerima jenis monsun ini sementara pantai barat Semenanjung
Malaysia menerima monsun barat daya. Menjadi persoalan sama ada monsun-monsun ini
memberi kesan kepada peningkatan paras laut. Bagaimana pun, daripada kajian ini didapati,
kemunculan El Nino atau La Nina bersama kemunculan monsun memberi kesan kepada paras
laut.
Tiga parameter meteorologi telah disertakan dalam kajian ini untuk melihat hubungan
parameter-parameter ini dengan paras laut. Hasilnya telah menunjukkan semasa kejadian
pemanasan luar biasa ( kejadian El Nino), suhu dan tekanan paras laut telah mempengaruhi
paras laut dan menyebabkan paras laut lebih rendah. Sementara itu, kekerapan hujan telah
menyebabkan peningkatan paras laut.
VARIATIONS OF MALAYSIAN SEA LEVEL DUE TO NORTHEAST
MONSOONS AND SOUTHWEST MONSOONS SEASONS DURING
THE EL NINO AND LA NINA EVENTS
Anie Raflikha Abd Malek 1, Noor Baharim Hashim,PhD 1
1 Faculty of Civil Engineering, University Technology Malaysia, 81300 Skudai, Johor, Malaysia
Email: anieraflikha@yahoo.com, drbaharim@yahoo.com
Abstract. The northeast monsoon from South China Sea is the major rainy season in the country. Heavy rain that
occurs in the end of the year often cause severe flood along the east states of Kelantan, Terengganu, Pahang and East
Johor in Peninsular Malaysia and in Sarawak in East Malaysia. Purpose of this study is to determine the variation of
Malaysian sea level during El Nino and La Nina event, specifically during the northeast and southwest monsoon that
occur from late November to Mac and from June to September every year respectively. The southwest monsoons is
drier compared to northeast monsoons with minimum rainfall. From this study, the sea level increases during the
northeast monsoon compared to the southwest monsoon. ENSO event also affected the sea level during these
monsoons season.
Keywords: northeast monsoon, southwest monsoons, La Nina, El Nino, sea level
INTRODUCTION
The Intertropical Convergence Zone (ITCZ) represents a highly convective area; the boundary between
the dry, hot air to the north and the warm, humid air to the south. The ITCZ is located (averagely) globally at 5
degrees north of the equator and the ITCZ is bound to pass over the Peninsular Malaysia twice a year.
Camerlengo (2004) showed that the double passage of the ITCZ causes a double maximum of rainfall
in Peninsular Malaysia. These two maximum are recorded between April and May, and between September and
October, respectively; along the western side of the mountain range. On the other hand, the east coast of
Peninsular Malaysia has a single maximum rainfall around November or December ( Wai, 2004).
In the East Malaysia, the southward migration of the area of convergence formed by the advancing NE
monsoon and retreating SW monsoon favors uplifting and this phenomenon in turn enhances convection. Larger
value of rainfall is observed in the west coast of East Malaysia compared to the east coast of East Malaysia. The
disruption of rainfall pattern of the East Malaysia is clearly noticed during El Nino and La Nina years.
DATA COLLECTION
An extensive data set by the Department of Survey and Mapping Malaysia (DSMM) and the InterGovernmental Panel of Climatic Change and the National Oceanic and Atmospheric Administration (IPCC) has
been obtained for this study. A complete datasets of more than 17 years from six tidal station were used to
investigate the effect of the monsoons seasons, La Nina and El Nino events to the sea level, in the east coast
and west coast of Sabah (in East Malaysia) and the east coast and west coast of Peninsular Malaysia.
RESULT AND DISCUSSION
A piling up of water (POW) follows quite naturally at the eastern boundary of Peninsular Malaysia
during the boreal winter ( due to the monsoon winds) and the magnitude is 10 –1 m sec -1 (Azmy et al, 1991 and
Gouy,1989) . As a sequence of this, the water flows equatorward motion along the coast of Peninsular
Malaysia. This precisely happens during the northeast (NE) monsoons seasons (Camerlengo, 2004). From the
figure 1a,1b and figure 2a,2b during the NE monsoons, the water level is high at the east coast Peninsular
Malaysia (Chendering and Tg. Sedili) and the sea level rises and becomes higher during strong La Nina years in
1988, 1999-2001 as compared to the normal years. On the other hand, the water flows in a poleward direction
during
the
boreal
winter
at
the
western
boundary
of
Peninsular
Malaysia.
Chendering (1985-1990)
240
(cm)
1985
220
1986
200
1987
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
180
Feb
1988
Jan
Monthly Mean Sea Level
260
Month
1989
1990
Figure 1a
Chendering (1996-2000)
240
1996
(cm)
1997
220
1998
200
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
2000
Feb
180
1999
Jan
Monthly Mean Sea Level
260
Month
Figure 1b
300
280
(cm)
260
1987
240
1988
1989
220
1990
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
200
Jan
Monthly Mean Sea Level
Tg Sedili (1987-1990)
M onth
Figure 2a
300
280
1996
260
1997
240
1998
220
1999
2000
Month
Figure 2b
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
200
Jan
(cm)
Monthly Mean Sea Level
Tg Sedili (1996-2000)
When the SW monsoon occurs beginning in June till the end of September or early October, the
Malaysian water in the west coast of Peninsular Malaysia increases. This condition is reversed in the east coast
of Peninsular Malaysia. Furthermore, the condition of the water level in the west coast of Peninsular Malaysia
(P Langkawi and P Klang) is slightly different, where the effect of La Nina to the water is not strong as
compared to the east coast. Figure 3a,3b and 4a,4b show the condition during the strong La Nina years in 1988
and 1999-2001.
Pulau Langkawi (1986-1990)
240
(cm)
1986
220
1987
200
1988
1989
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
180
Jan
Monthly Mean Sea Level
260
1990
Month
Figure 3a
P Langkawi (1996-2000)
240
(cm)
1996
1997
220
1998
1999
200
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
2000
180
Jan
Monthly Mean Sea Level
260
Month
Figure 3b
380
360
1986
340
1987
1988
320
M onth
Figure 4a
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
300
1989
Jan
(cm)
Monthly Mean Sea Level
P Klang (1986-1990)
400
1990
400
380
(cm)
1996
360
1997
1998
340
1999
320
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
2000
300
Jan
Monthly Mean Sea Level
P Klang (1996-2000)
Month
Figure 4b
From figure 3b and 4b, the strong El Nino event in 1997 extremely affected the sea level in P Langkawi
and P Klang in the end of SW Monsoon until the NE monsoon and the lowering of sea level occured.
Given the fact that the SW monsoon winds is lighter than the NE monsoon winds thus the lowering of
water (LOW) occurs at the east coast of Peninsular Malaysia during the SW monsoon. When the water flows
from the Pacific Ocean to the Indian Ocean, it flows from a high pressure system to a low pressure system and
this condition is known as Indonesian Throughflow,
In K Kinabalu which is situated in the East Malaysia, the NE monsoon can be traced from the increase
of the sea level and during the La Nina years (figure 5a), the sea level increased more than the normal year (
non-ENSO year). However, the condition occurred and was clearly noticed in the end of the year (in the middle
of the NE monsoon). Nieuwolt (1981) showed the northward migration of the area of convergence ahead of the
SW monsoon caused the large amount of rainfall in west coast of East Malaysia. This event may caused the
increase in sea level . In contrast, the Kota Kinabalu sea level is not affected by the rainfall and low value of sea
level is observed in this study.
In 1997, the sea level in the NE monsoon decreased (figure 5b). This is due to the strong effect of El
Nino in the East Malaysia (Camerlengo, 1999). The same condition occured in Tawau (Figure 6a,b). This
findings is consistent with Camerlengo et. al (2000), which showed the onset of the NE monsoon season is
largely responsible for the increase of the number of rainfall on Sabah’s east coast. However, the rainfall value
of Kota Kinabalu and Tawau is small compared to the rainfall value of southern East Malaysia. This may
largely be attributable to their particular location in relation to the NE monsoon winds.
K Kinabalu (1988-1990)
280
260
240
1988
220
1989
1990
Month
Figure 5a
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
200
Jan
(cm)
Monthly Mean Sea Level
300
300
290
280
270
1988
260
1989
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
1990
Feb
250
Jan
(cm)
Monthly Mean Sea Level
Tawau (1988-1990)
Month
Figure 6a
300
(cm)
280
1996
260
1997
240
1998
220
1999
2000
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
200
Jan
Monthly Mean Sea Level
K Kinabalu (1996-2000)
Month
Figure 5b
300
290
1996
280
1997
270
1998
260
1999
Nov
Sep
Jul
May
2000
Mar
250
Jan
(cm)
Monthly Mean Sea Level
Tawau (1996-2000)
M onth
Figure 6b
CONCLUSION
From the results of this study, it can be concluded that the sea level during the NE monsoon increases
and it is clearly identified in the east coast of Peninsular Malaysia. The sea level is higher during the La Nina
year than the normal year. El Nino gives a strong impact to the sea level in the east coast of Sabah and the west
coast of Peninsular Malaysia and this warm and cool event is a significant event that affected the increase or
decrease of the sea level during the monsoon season.
ACKNOWLEDGMENTS
The research reported herein is funded by IRPA grant Vot: 74254. The author would like to thank to
Ministry of Science and Innovation (MOSTI), Department of Survey and Mapping Malaysia (DSMM), InterGovernmental Panel Climatic Change (IPCC) and Sultanah Zanariah Library (PSZ), University Technology
Malaysia for their support in this project.
REFERENCES
Azmy A. R., Isoda Y. and Yanagi T., (1991). Memoirs of the Faculty of Civil Enginering, Ehime University,
XII 148.
Camerlengo, A.L., Ambak, M.A., Saadon, M.A., Somchit, N. (2000). On The Rainfall Distribution In East
Malaysia. Journal Of Physics Sciences, 11, 119-128.
Camerlengo, A. L., Ahmad Khairi, A. W., Noor Baharim, H., (2004). On the Dynamics of the Wind-Driven
Circulation in Peninsular Malaysia During Both Monsoon Seasons, Physics Journal Of The Indonesian Physical
Society.
Gouy T. K., (1989). M. Sc. Thesis, School of Earth Science. Flinders University, University of South Australia.
Nieuwolt, S., (1981). The Climate of Continental Southeast Asia, Chapter 1, World Survey of Climatology.
Elsevier Scientific Publishing Co., Takahasi and Arakawa (eds.), 1-37).
Wai, N. M. (2004)., Variations Of the Malaysian Climate Induced By Global Warming and ENSO Events, M.
Eng Thesis, University Technology Malaysia.
RELATIONSHIPS OF SEA LEVEL VARIATION DURING
EL NIŃO AND LA NIŃA WITH CERTAIN
METEOROLOGICAL PARAMETERS
ANIE RAFLIKHA ABD MALEK AND NOOR BAHARIM HASHIM Ph.D
DEPARTMENT OF HYDRAULIC AND HYDROLOGY, FACULTY OF CIVIL ENGINERING,
UNIVERSITI TEKNOLOGI MALAYSIA
81310 SKUDAI, JOHOR
MALAYSIA
anieraflikha@yahoo.com, drbaharim@yahoo.com
ABSTRACT
The aim of this study is to elucidate the behavior of the sea level as well as its correlation
with certain meteorological parameters in Malaysia during both the cold and the warm ENSO
events. For this purpose, tidal records of 10 gauge stations as well as their respective
meteorological stations are analyzed. In this study, the behavior of the sea level during the
1986-87, 1991-95 and 1997-98 El Niño events in Malaysia is addressed.
Keywords: Sea level rise, El Niño, La Niña, EŃSO, correlation
INTRODUCTION
Issues and problems related and associated to sea level and their current potential
relationship with climate, have continued to receive a high level of national and international
attentions. In 1997-98 during El Niño event, a severe haze badly polluted the ASEAN air
environment and affected the tourism and economy of the countries, especially in Malaysia
and Singapore. Since then, Malaysian authorities give more attention to climate problems.
This study is considered as continuing effort from previous research on this issues.
From the previous study, relationship between mean sea level (MSL) and meteorological
parameters shows that, a positive correlation MSL and rainfall is noticed. While, an inverse
correlation between sea level and both temperature and sea level pressure is detected
(Camerlengo, 1999).
Objective of this paper is to gain a better understanding the correlation between the
variation in the sea level and three meteorological parameters; temperature, rainfall and sea
level pressure during the cold and warm ENSO events.
DATA
Annual mean sea level data and meteorological data; temperature, mean sea level pressure,
rainfall have been obtained from Department of Survey and Mapping Malaysia, and from
Malaysian Meteorological Service. Annual data of selected stations were analyzed to identify
and characterize the relationship between the datasets.
RESULT AND DISCUSSION
Correlation between the Annual Sea Level and the Mean Temperature
A negative correlation - with high annual temperature and low annual sea level – during warm EŃSO
event in East Malaysia is observed in Kota Kinabalu and Sandakan (Figure 1a). Similarly, lower
annual temperature and higher annual sea level are denoted during the 1988 and 1999 La Nińa event.
Kota Kinabalu
Sandakan
28.5
r=0.37
98
02
28.0
04
03
01
27.5
97
95
96
94
27.0
266
268
270
272
00
274
276
278
Te m p e r atu r e ( C)
Te m p e r atu r e ( C )
28.5
98
r=0.20
28.0
97
27.5
27.0
92
26.5
246
280
02
95
91
93
90
94
00
03
88
89
248
250
99 01
96
252
254
256
258
260
Annual Mean Sea Level (cm)
Annual Mean Sea Level (cm)
Figure 1a: Annual Mean Sea Level (cm) versus annual temperature (ºC ) in Sabah
The same pattern is observed in Peninsular Malaysia (Figure 1b), where the 1986-87 El Niño
shows the same behavior as the 1991-95 and 1997-98 warm event. Most stations have
positive correlation 012<r<0.24, except for Kota Bharu and Melaka, the negative correlation
is observed.
Tg Sedili
Kota Bharu
27.5
T e m p e r atu r e ( C )
98
r=0.20
02
27.5
04
03
92
01
00
95
27.0
87
91
90
97
88
94
96
99
93
T e m p ar atu r e ( C )
28.0
r=0.13
98
03
27.0
97
02
88
90
92
26.5
04
01
00
87
26.0
93 94
91
89
95
99
96
89
226
228
230
232
Annual Mean Sea Level (cm)
Johor Bharu
T e m p e r atu r e ( C )
27.5
r=0.14
27.0
97
26.5
86
96
91
93
282
01
92
94
85
25.5
280
00 99
88
90
87
89
84
238
240
242
244
Annual Mean Sea Level (cm)
04
95
02
03
284
286
288
Annual Mean Sea Level (cm)
290
246
Kukup
27.5
98
26.0
25.5
236
234
T e m p e r atu r e ( C )
26.5
224
98
r=0.13
27.0
97
00
26.5
26.0
25.5
392
87
91
394
94
396
90 02 92
93
398
86 04
8
03
400
99
96
01
95
89
402
404
406
Annual Mean Sea Level (cm)
Figure 1b: Annual Mean Sea Level (cm) versus annual temperature (ºC ) in Peninsular Malaysia
Melaka
98
28.0
r=0.05
02
0
27.5
97
01
96
87
27.0
03
90
91
94
9
26.5
86
92
95
89
00
88
99
85
T e m p e r atu r e ( C )
T e m p e r atu r e ( C )
Ipoh
28.5
28.5
02
04
97
27.5
280
285
290
26.5
210
295
86
93 89
88
99
215
Pulau Langkawi
r=0.12
03
01
96
27.5
92
94
91
215
90
93
220
00
95
89
99
88
225
Annual Mean Sea Level (cm)
230
T e m p e r atu r e ( C )
04
230
98
98
28.0
225
Kuantan
28.0
02
97
220
Annual Mean Sea Level (cm)
29.0
Te m pe ra ture ( C)
96
03
92
94
00
95
87 91
27.0
Annual Mean Sea Level (cm)
27.0
210
01
90
85
26.0
275
28.5
r=0.07
98
28.0
27.5
03
97
27.0
00
92
26.5
94
90
96
91
25.5
276
86
278
99
95
87
85
01
04
93
26.0
r=0.24
02
88
89
84
280
282
284
Annual Mean Sea Level (cm)
286
Figure 1b: Annual Mean Sea Level (cm) versus annual temperature (ºC ) in Peninsular
Malaysia (continued)
This may be attributed to the fact that a strong response to EŃSO forcing is observed in East
Malaysia. These results show that high temperature is associated with low sea level and high
sea level with low temperature (Camerlengo,1999).
Correlation between the Annual Sea Level and the Average Monthly Rainfall
The greatest effect of the warm EŃSO events is observed on 1986-87, 1991-95 and 1997-98.
During the warm event, low rainfall is observed in conjunction with low values of the annual
sea level. On the other hand, a high precipitation corresponds to a high annual sea level
during the 1988 and 1999 La Nina event. In East Malaysia, the correlation r, is between 0.43
and 0.58 (Figure 2a).
Sandakan
Kota Kinabalu
400
95
88
01
A ve r ag e Rain fall
(m m )
A ve r ag e Rain fall
(m m )
300
00
93
200
90
03
98
94
91
89
97
100
246
99
96
92
r=0.58
02
248
250
252
254
256
258
94
96
01
300
97
200
00
03
04
98
95 02
100
r=0.43
0
265
260
270
Annual Mean Sea Level (cm)
275
280
Annual Mean Sea Level (cm)
Figure 2a: Annual Mean Sea Level (cm) versus annual average rainfall (mm) in Sabah
The following relation is noticed: low rainfall with low sea level and high sea level with high
rainfall. In these cases, the 1986-87, 1991-95 and 1997-98 El Niño events are grouped on the
bottom left-hand side: low rainfall and low sea level. This is related to the relaxation of the
Northeast trade winds in the western Pacific and the eastward migration of the Indonesian
Low.
Melaka
Kota Bharu
250
94
300
200
99
00
A ve r ag e Rain fall
(m m )
Ave r ag e Rain fall
(m m )
400
93 95
98 02
90
92
88
97
91
100
04
87
0
224
96
01
03
89
226
r=0.59
228
230
232
Annual Mean Sea Level (cm )
95
200
94
89
01
00
96
150
86
97
99
93 03 98
91
r=0.52
90 04
280
285
290
295
Langkawi
Ipoh
300
03
87
95
93
99
91
85
86
97
01
98
02
r=0.43
93
215
220
03
95
90
94
98
93
88
01
200
96
89
90
94
00
88
04
200
A ve r ag e Rain fall
(m m )
Ave r ag e Rain fall
(m m )
88
85
Annual Mean Sea Level (cm)
300
100
210
02
87
100
275
234
92
225
Annual Mean Sea Level (cm )
230
100
210
91
97
89
02
92
215
220
96
99 00
r=0.35
04
225
Annual Mean Sea Level (cm)
Figure 2b: Annual Mean Sea Level (cm) average rainfall (mm) in Peninsular Malaysia
230
Kukup
Kuantan
250
93
03
87
94
92
04 95
91
90
85
200
01
88
300
A ve r ag e Rain fall
(m m )
A ve r ag e Rain fall
(m m )
400
99
98
86
89
84
00
02
r=0.18
96
87 93
91
04
95
96
01
02
200
86
92
94
97
03
00
88
89
99
150
90
98
r=0.12
97
100
276
278
280
282
284
100
390
286
395
95
85
200
86
94
97
84
91
89
92
02
03
88
200
01
00
r=0.002
282
284
286
288
290
04
91
410
96
95
01
02
92
00
88
94
03
89
97
99
150
99
98
90
100
280
96
04
93
87
Ave r age Rainfall
(m m )
Ave r age Rainfall
(m m )
250
87
405
Tanjung Sedili
Johor Bahru
300
93
400
Annual Mean Sea Level (cm)
Annual Mean Sea Level (cm)
98
100
236
238
90
240
r=0.26
242
244
246
Annual Mean Sea Level (cm )
Annual Mean Sea Level (cm)
Correlation between the Annual Sea Level and the Mean Sea Level Pressure
The correlation is moderately strong at Peninsular Malaysia (Figure 3b) compared to East
Malaysia (Figure 3a). This coincidence with El Niño events. On the other hand , low pressure
and high sea level are noticed during the 1988 and 1999 La Niña events. This may be
attributed to the facts that: an increase in sea-level pressure is observed during the EŃSO
events and a decrease in sea-level pressure is perceived during La Niña events in Malaysia.
Sandakan
Kota Kinabalu
1011
r=0.96
97
1011
1010
94
98
02
03
96
95
04
01
1009
M e an Se a L e ve l
Pr e s s ur e (hPa)
M e an Se a L e ve l
Pr e s s u r e (h Pa)
1012
97
r=0.53
93
1010
92
94
03
98
02
95
99
1009
91
90
89
01
96
88
00
00
1008
265
270
275
Annual Mean Sea Level (cm)
280
1008
246
248
250
252
254
256
Annual Mean Sea Level (cm)
Figure 3a: Annual Mean Sea Level (cm) mean sea level pressure (hPa) in Sabah
258
260
Tg Sedili
87
97
93
92
94
1010
04
89
95
98
03
01
88
90
1009
236
238
240
91
90
242
00
244
246
1008
210
215
220
225
Annual Mean Sea Level (cm)
M e an Se a L e ve l
Pr e s s u r e (h Pa)
M e an Se a L e ve l
Pr e s s u r e (h Pa)
r=0.77
87
86
92
02
0
91 94
90
96
95
04 98
89
01
99
88
1009
390
395
00
400
97
405
1011
03
90
91
1010
94
02
1009
210
98
215
04
r=0.38
95
88
00
96
89
99
220
M e an Se a L e ve l
Pr e s s u r e (h Pa)
M e an Se a L e ve l
Pr e s s u r e (h Pa)
93
01
99
230
246
r=0.57
1011
87
97
93
92
1010
90
94
91
02
89 04
03
95
86
01
98
88
96
85
225
00
Kuantan
1009
276
278
84
99
00
280
282
284
286
Annual Mean Sea Level (cm)
Kota Bharu
1012
r=0.57
97
87
86
02
93
94
92
90 85
91
04
98
89
84
282
03
95
01
96
88
00
284
286
288
Annual Mean Sea Level (cm)
M e an Se a L e ve l
Pr e s s u r e (h Pa)
M e an Se a L e ve l
Pr e s s u r e (h Pa)
1009
280
01
88
238
240
242
244
Annual Mean Sea Level (cm)
Johor Bharu
1011
1010
03
95
Annual Mean Sea Level (cm)
1012
90
04
02
94
1012
92
98
89
1009
236
410
Langkawi
1012
91
93
1010
96
1014
1013
r=0.76
92
87
Annual Mean Sea Level (cm)
97
230
Melaka
1011
1010
99
88 96
Kukup
93
01
98
00
1012
1011
95
89
85
Annual Mean Sea Level (cm)
97
04
02
03
1009
99
96
94
r=0.81
92 93
86
1010
02
91
87
97
r=0.78
1011
Ipoh
1011
M e an Se a L e ve l
Pr e s s u r e (h Pa)
M e an Se a L e ve l
Pr e s s u r e (h Pa)
1012
1011
02
87
1010
90
98
91 04
93
03
95
94
01
89
99
00
290
r=0.49
97
92
1009
224
226
228
96
98
88
230
232
Annual Mean Sea Level (cm)
Figure 3b: Annual Mean Sea Level (cm) average rainfall (mm) in Peninsular Malaysia
234
CONCLUSIONS
The main conclusions of this study are:
i)
a positive correlation between mean sea level and temperature is detected in
Peninsular Malaysia, compared to East Malaysia.
ii)
all stations in Malaysia showed a positive correlation between mean sea level and
rainfall
iii)
an inverse and negative correlation is noticed for all observed stations in Malaysia
ACKNOWLEDGEMENTS
This study is supported by an IRPA grant vot:74254 (2004-07) which is gratefully
acknowledged. Data for carrying out this study were provided by the Department of Survey
and Mapping Malaysia, and from Malaysian Meteorological Service. Thanks for their
cooperation to support this study.
REFERENCES
Camerlengo, A.L. (1999), “Sea Level Variations Due to Both El Niño and La Niña events
and Relation with Certain Parameters in Malaysia”, Asia Pacific J. Env. Dev. 6(2), 49-65.
Camerlengo, A.L., Wai, N.M., Ahmad Khairi Abdul Wahab, Noor Baharim Hashim,(2004), “
A Study On The Role Played By Global Warming And El Niño Events In The Mean Sea
Level Pressure Distribution Of Malaysia”, submitted to Pertanika Journal of Science and
Technology.
“Coastal: The Potential Consequences of Climate Variability and Change”, NOAA Coastal
Ocean Program, Decision Analysis Series Number 21.
Department of Survey and Mapping, Malaysia (1984-2004). Tidal Observation Records
Malaysian Meteorological Service (1951-2004), Monthly Summary of Meterological
Observations, issued under the authority of the Director General, Malaysian Meteorological
Service, Petaling Jaya, Malaysia.
Wai, N.M. (2004), “Variations of The Malaysian Climate Induced by Global Warming and EŃSO
events”, Master Thesis, Universiti Teknologi Malaysia
PRELIMINARY STUDY OF THE RESPONSE OF THE
MALAYSIAN SEA LEVEL DURING THE ENSO EVENTS
ANIE RAFLIKHA ABD MALEK, DR NOOR BAHARIM HASHIM, PhD
Department of Hydraulic and Hydrology, Faculty of Civil Engineering
University Technology Malaysia, 81310 Skudai, Johor
anieraflikha@gmail.com, drbaharim@yahoo.com
ABSTRACT
South China Sea (SCS) is the largest marginal sea in Southeast Asia and it is semi-closed
basin surrounded by South China, the Philippines, Borneo Island, and the Indo China
Peninsula. Geographical location caused the parameter like the sea surface temperature have
close relation with ENSO event. Sea level data from 8 tide gauge stations across Malaysia
were used in this study to determine the response of the sea level to the ENSO events. The
negative response to ENSO events of the Malaysian waters is noticed in this study.
Keyword: El Nino, La Nina, sea level , ENSO
INTRODUCTION
Malaysia covers an area almost 330 thousands square kilometers and consists of Peninsular
Malaysia and Borneo island (Sabah and Sarawak). Malaysia lies close to the equator between
latitudes of 1˚ and 7˚ N and longitudes of 100˚ and 119˚ E based on the geographical location
Malaysia is considered as one of the tropical countries with warm and wet climate.
During warm ENSO event, the abnormal warm water in the equatorial central and eastern
Pacific is rises to enhance cloudiness and rainfall in that region. At the same time, in
Indonesia, Malaysia and northern Australia the rainfall is reduced. The Walker Circulation
becomes weaker then normal.
Mean while during La Nina event, rainfall is enhanced over Indonesia, Malaysia and northern
Australia and wetter than normal conditions developed. The abnormal cold water rises to
suppressed cloudiness and rainfall in this region. The Walker Circulation becomes stronger
than normal.
In this study a rise in sea level, mainly due to global warming, all across Malaysia has been
detected. The following graphs proved the impact of ENSO to Malaysian sea level.
DATA
Annual sea-level data of 8 stations in Peninsular Malaysia and Sabah are analyzed. The
location of the stations are given in Figure 1.
Figure 1: Location of the selected stations in Peninsular Malaysia and Sabah
The data have been obtained from the Tidal Observation Record published by the DSMM.
The records cover more than 20 years of data and for several stations, the records only cover
for 17 years of data. This study is to enhance the confident level with more records of data
compared with previous study with less than 15 years of data.
RESULTS AND DISCUSSION
Annual Sea Level Variation
It has been observed that the response to ENSO forcing is stronger in East Malaysia than in
Peninsular Malaysia (Cheang, 1993). A decrease in the annual sea-level in Sabah; Kota
Kinabalu and Tawau during 1991 to 1994 may be attributed to the 1991-1995 warm ENSO
event (Figure 2). The same response has been observed during 1997-98 ENSO event.
Deviation (cm)
Annual Sea Level
Kota Kinabalu
9
7
5
3
1
-1
-3
-5
-7
88
02
89
03
90
91
92
93
94
95
Ye ar
96
97
98
99
00
01
Tawau
Deviation (cm)
Annual Sea Level
15
10
5
0
-5
-10
-15
88 89
90
91
92
93
94
95
96
97
98
99
00
01
02
03
04
Year
Figure 2: Annual sea level deviation ( in cm) from the mean and their error at selected
stations in Sabah
The sea level rise is detected during the La Nina event in 1988, 1989 and 1999. In Peninsular
Malaysia, the decrease of the sea-level is noticed in 1986-87, 1991-98 El Nino events
(Figure 3). This may explained by the fact that the response of Peninsular waters to ENSO is
moderate to weak (Quah, 1988).
Chendering
Deviation (cm)
Annual Sea Level
5
3
1
-1
-3
-5
85 86
04
87
88
89
90
91
92
93
94
95
96
97
98
99
00
01
02
03
Year
Tg Gelang
(cm)
3
1
-1
-3
84 85
-5 04
86
87
88
89
90
91
92
93
94
95
96
97
96
97
98
98
99
00
01
02
03
01
02
03
04
Ye ar
Deviation (cm)
Pulau Tioman
Annual Sea Level
Annual Sea Level
5
6
4
2
0
-2
-4
-6
-8
86 87
88
89
90
91
92
93
94
95
Ye ar
99
00
Johor Bahru
Deviation (cm)
Annual Sea Level
5
3
1
-1
-3
84 85
-5 03 04
86
87
88
89
90
91
92
93
94
95
96
97
98
99
00
01 02
Year
Deviation (cm)
Annual Sea Level
Pulau Langkawi
12
10
8
6
4
2
0
-2
-4
-6 86
-8
87
88
89
90
91
92
93
94
95
96
97
98
99
98
99
00
01
02
Year
Pelabuhan Klang
10
Deviation (cm)
Annual Sea Level
15
5
0
-5
84 85
-10 03 04
86
87
88
89
90
91
92
93
94
95
96
97
00
01
02
Ye ar
Figure 3: Annual sea level deviation ( in cm) from the mean and their error at selected
stations in Peninsular Malaysia
CONCLUSIONS
The main conclusion of this study are; the decrease of the sea level and negative deviation
during 19867-87, 1991-1995 and 1997-98 El Nino event is addressed. On the other hand, an
increase of the sea level during 1999 La Nina events with a positive deviation is noticed.
ACKNOWLEDGEMENTS
This is supported by an IRPA grant vot:74254 which is gratefully acknowledged. Thanks are
also extended to Department of Survey and Mapping Malaysia for their support.
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