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1 INTRODUCTION

The Indonesian Archipelago Sea Lanes (ALKI) are

important maritime corridors that facilitate domestic

and international navigation through Indonesia's

maritime territory. Among them, ALKI 2 crosses the

Makassar Strait, which connects the Sulawesi Sea in the

north with the Flores Sea in the south. This strait not

only functions as a commercial shipping lane, but also

plays an important role in regional ocean circulation,

especially as the main route of the Indonesian

Throughflow (ALKI).

The Indonesian archipelago sits at the heart of the

maritime crossroads between the Pacific and Indian

Oceans, where complex ocean-atmosphere interactions

shape regional climatic and oceanographic variability.

Among the key marine corridors facilitating domestic

and international trade across these waters is the

Archipelagic Sea Lane II (ALKI 2), which traverses the

Makassar Strait from the Sulawesi Sea in the north to

the Flores Sea in the south [1] [2]. This corridor plays a

dual role as a strategic shipping route and a conduit for

the Indonesian Throughflow (ITF), one of the world's

most important oceanic current systems.

With the planned development of Indonesia’s new

national capital—IKN Nusantara—in East Kalimantan,

the geopolitical and logistical importance of ALKI 2 is

further amplified. Proximity to this maritime corridor

suggests increasing demands on infrastructure and

navigation safety, particularly under dynamic marine

weather conditions [3]. As maritime operations

intensify, understanding the long-term variability and

patterns of wave and wind dynamics in this region

becomes critical to ensure sustainable development,

port security, and risk reduction for coastal

infrastructure.

The wave and wind climates of the Makassar Strait

are heavily modulated by the Southeast Asian

Multidecadal Wind-Wave Variability in Makassar Strait

along ALKI 2: ERA-Interim Based Assessment Supports

IKN Maritime Resilience

M.U. Pawara

, A.M.N. Arifuddin

, A. Apriansyah

, F. Mahmuddin

, A. Alamsyah

, S. Suardi

& M.Y. Raditya

1, 4

Institut Teknologi Kalimantan, Kalimantan, Balikpapan, Indonesia

West Sulawesi University, West Sulawesi, Majene, Indonesia

Hasanuddin University, South Sulawesi, Makassar, Indonesia

Toyohashi University of Technology, Aichi, Toyohashi, Japan

ABSTRACT: This study investigates the multidecadal variability of wave and wind dynamics along the

Indonesian ALKI 2 shipping lane in the Makassar Strait using ERA-Interim reanalysis data for 39 years (1979–

2017). Seven observation points (K1–K7) were analyzed from northern Kalimantan to the southern strait. Key

parameters include Significant Wave Height (SWH), Mean Wave Period (MWP), and 10-meter wind speed. The

results reveal significant spatial and seasonal variability influenced by the monsoon system and local topographic

effects. The northern points exhibit higher wave energy during DJF (December–February), while the southern

points are more active in JJA (June–August), consistent with the prevailing seasonal winds. Trend analysis shows

a weak but statistically significant increase in MWP at certain locations. These insights are critical for the

development of maritime infrastructure and risk mitigation strategies associated with Indonesia’s new capital

city (IKN Nusantara), located near this important shipping corridor.

http://www.transnav.eu

the International Journal

on Marine Navigation

and Safety of Sea Transportation

Volume 20

Number 1

March 2026

DOI: 10.12716/1001.20.01.16

154

monsoon system, characterized by a biannual reversal

of prevailing winds: the northwest monsoon (DJF) and

the southeast monsoon (JJA) [4]. These monsoons

influence the direction, height, and period of wind-

generated waves, contributing to substantial seasonal

variability across Indonesia’s maritime zones [5].

Moreover, localized effects such as bathymetry, coastal

geometry, and island shadowing compound the spatial

heterogeneity of wave dynamics.

Despite its strategic significance, studies explicitly

addressing the multidecadal variability of wave and

wind parameters along ALKI 2 are limited. Previous

research has typically focused on larger regional or

national scales [6], often overlooking corridor-specific

trends critical to infrastructure planning. This study

aims to fill that gap by offering a high-resolution

temporal and spatial analysis of wave and wind

patterns along ALKI 2 based on reanalysis datasets.

Reanalysis data products, such as ERA-Interim and

its successor ERA5, offer a robust foundation for long-

term marine climate assessment due to their consistent

assimilation of observational data and numerical

model outputs [7]. ERA-Interim, developed by the

European Centre for Medium-Range Weather

Forecasts (ECMWF), provides global coverage with a

suitable temporal span (1979–2017) and spatial

resolution for capturing climatological trends in wave

and wind behavior over decades [8]

The integration of statistical techniques such as

Seasonal-Trend decomposition using Loess (STL)

allows the separation of periodic seasonal behavior

from underlying trends and irregular components [9].

This approach is particularly valuable for identifying

monsoon-driven seasonality and long-term wave

climate shifts, both of which have critical implications

for design criteria in coastal engineering and marine

logistics.

Additionally, wave rose and wind rose diagrams

serve as effective tools for visualizing the directional

distribution and intensity of wave and wind forces.

These diagrams are essential for understanding

prevailing exposure risks and guiding the alignment of

port infrastructure, navigation lanes, and early

warning systems [10]. They also highlight the

asymmetric influence of seasonal monsoons across the

latitudinal transect of ALKI 2.

Climate change adds another layer of complexity,

as global warming is expected to alter wind patterns,

increase sea surface temperatures, and potentially

intensify tropical convection patterns [11]. These

changes could modify the wave climate in ways that

are not yet fully understood. Identifying early signals

of such shifts—through increased wave height, longer

wave periods, or changes in dominant direction—is

essential for proactive maritime resilience.

In light of these considerations, this study conducts

a comprehensive assessment of significant wave height

(SWH), mean wave period (MWP), and 10-meter wind

speed at seven observation points (K1–K7) spanning

the Makassar Strait. Using ERA-Interim data from 1979

to 2017, we explore monthly climatology, seasonal

variability, long-term trends, and spatial heterogeneity

to inform future planning.

The results provide key insights into the interaction

between monsoon-driven atmospheric dynamics and

marine conditions in ALKI 2. Furthermore, by

identifying patterns relevant to port safety, vessel

routing, and climate adaptation, this study offers a

valuable scientific foundation for infrastructure

planning in the new capital region. The research aims

to support integrated maritime policy and adaptive

management practices amid Indonesia's evolving

coastal and ocean governance landscape.

Figure 1. Study Area and Observation Points

2 DATA AND METHODS

2.1 Study Area and Observation Points

This study focuses on the Makassar Strait, a major

segment of the Indonesian Archipelago Sea Lane II

(ALKI 2), which stretches from northern Kalimantan to

the southern end of the strait. Seven observation points

(designated K1 to K7) were strategically selected along

the route to capture spatial variability in wind and

wave conditions. The geographic coordinates of these

points are:

− K1: 2.0° N, 119.5° E

− K2: 0.5° N, 119.5° E

− K3: 0.5°S, 118.5°E

− K4: 1.5°S, 118.0°E

− K5: 2.5°S, 118.0°E

− K6: 3.5°S, 117.5°E

− K7: 5.0°S, 117.5°E

These locations represent a north-south transect

along the shipping corridor and were selected to

encompass variations in bathymetry, shoreline

exposure, and proximity to monsoon wind regimes.

2.2 Data collection

We use the ERA-Interim reanalysis data provided by

the European Centre for Medium-Range Weather

Forecasts (ECMWF), which offers consistent global

atmospheric and oceanic parameters. The dataset from

January 1979 to December 2017 with a temporal

resolution of 6 h, and a spatial resolution of 0.25° × 0.25°

were employed. The following parameters are

extracted for the analysis:

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− Significant Wave Height (SWH)[M]

− Mean Wave Period (MWP)[S]

− Wind Speed 10 meters[MS]

2.3 Statistical and Seasonal Analysis

To assess seasonal patterns and long-term changes, we

apply the following analysis:

− Direction Analysis: Wind rose and wave rose

diagrams are constructed to assess the dominant

direction and intensity distribution of surface winds

and significant waves.

− Correlation Analysis: Pearson correlation

coefficient was calculated to examine the

relationship between SWH and MWP at K1 and K7

points.

− Seasonal Decomposition:We use Trend-Seasonal

decomposition using Loess (STL) to extract the

seasonal, trend, and residual components of the

SWH time series at K1 and K7 points.

Figure 2. Monthly average of Significant Wave Height (SWH)

from 1979 to 2017 at observation points K1 to K7 along the

ALKI 2 corridor in the Makassar Strait.

Figure 3. Monthly average of Mean Wave Period (MWP)

from 1979 to 2017 for stations K1 to K7.

3 RESULTS AND DISCUSSION

3.1 Monthly Variability in Wave and Wind Patterns

Figure 2 and Figure 3 depict the monthly climatology

of Significant Wave Height (SWH) and Mean Wave

Period (MWP) at all observation points (K1–K7). SWH

shows clear seasonal variations, with peaks generally

occurring during DJF (December–February), especially

at the northernmost points (K1–K2), driven by the

dominant northwesterly monsoon. In contrast, SWH

values decrease during the inter-monsoon period

(April–May), indicating calmer sea conditions.

The MWP follows a similar seasonal trend, with

higher values observed during DJF in K1 (up to 6.7 s),

and relatively lower values in the southern parts (K4–

K6) where topographic features may suppress wave

development.

Figure 4. Annual average of Significant Wave Height (SWH)

and Mean Wave Period (MWP) at all stations (K1–K7).

Figure 5. Seasonal distribution of Significant Wave Height

(SWH) for DJF, MAM, JJA, and SON at each observation

point.

3.2 Annual and Spatial Patterns

Figure 4 presents the annual averages of SWH and

MWP at all locations. The highest values occur at K1,

with a decreasing gradient towards the southernmost

point (K7). This gradient reflects the reduced direct

monsoon exposure and possible energy dissipation in

the strait.

In particular, K4 and K5 consistently show the

lowest wave energy levels, which can be attributed to

underwater topographic shielding or energy refraction

processes. This spatial insight is valuable for

identifying areas suitable for safe anchorage or

potential maritime infrastructure development.

Figure 6. Mean monthly wind speed (10 m above surface) for

each station (K1–K7) averaged over 1979–2017.

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Figure 7. Seasonal wind speed distribution for DJF, MAM,

JJA, and SON at all observation points.

3.3 Seasonal Trends and Monsoon Influence

Figure 5 and Figure 7 summarize the seasonal

distribution of wave and wind fields for DJF, MAM,

JJA, and SON. DJF conditions are dominated by high

wave energy in the north (K1–K2), consistent with the

strong northwest monsoon. During JJA (June–August),

the SWH and higher wind speeds shift to the south

(K6–K7), reflecting the influence of the southeast

monsoon.

The consistent pattern of seasonal reversals

underscores the importance of aligning maritime

logistics and operations with these climatological

windows to minimize exposure to adverse sea

conditions.

Figure 8. Rose wave diagram for each station (K1–K7),

showing the frequency and direction of significant wave

events.

Figure 9. Wind rose diagram showing the dominant surface

wind direction and speed distribution at all observation

points.

3.4 Wind and Wave Direction and Coastal Exposure

The wind rose and wave rose diagrams (Figures 8 and

9) show that the dominant wind direction is from east

to southeast (E–SE), which is consistent with the main

wave direction (SE–S). This strong relationship

indicates a consistent energy transfer mechanism

between the wind field and wave generation,

especially during JJA.

The eastern and southeastern exposures of the

Makassar Strait make certain locations more

vulnerable to direct wave action. This has a direct

impact on port locations, breakwater design, and

coastal vulnerability assessments around the capital

city.

3.5 Correlation Analysis Between SWH and MWP

Pearson correlation analysis was performed to

evaluate the statistical relationship between Significant

Wave Height (SWH) and Mean Wave Period (MWP) at

Points K1 and K7. As shown in Figure 10, Point K1

exhibits a very weak negative correlation (r = –0.04, p <

0.001), indicating a minimal linear relationship

between wave height and period in the northern

Makassar Strait. This behavior may reflect the

influence of a mixed wave system, including long-

period swells and locally generated short waves, which

are not uniform in energy scale.

In contrast, at Point K7, located in the southern

strait, the correlation is quite negative (r = –0.25, p <

0.001). The distribution pattern (Figure 10) shows that

as the wave height increases—usually during the

monsoon season—the wave period tends to decrease,

which is characteristic of locally generated wind

waves. The stronger anti-correlation in this region

supports the hypothesis that wave dynamics in the

southern part are more influenced by wind-driven

processes and coastal topographic constraints.

This divergent correlation pattern reinforces the

spatial heterogeneity in wave regime characteristics

across ALKI 2 and implies that engineering design or

safety protocols should take region-specific wave

behavior into account.

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Figure 10. Scatter plot of SWH versus MWP at Points K1 and

K7.

3.6 STL Decomposition of SWH Time Series

To further investigate the long-term and seasonal

patterns in wave activity, Seasonal Trend

decomposition using Loess (STL) was applied to the

SWH time series at Points K1 and K7. The

decomposition at K1 (Figure 11) highlights a strong

and regular seasonal cycle that peaks during DJF,

reflecting the influence of the northwest monsoon. A

smooth increasing trend in the long-term component

indicates a gradual intensification of wave energy over

the past four decades. The residual component shows

considerable high-frequency variability, likely due to

intermittent storm events.

In contrast, the STL results at K7 (Figure 11) show a

clear seasonal signal peaking during JJA, which is

consistent with the southeast monsoon pattern. The

long-term trend at this location also shows a slight

increase, although less pronounced than at K1. These

differences in seasonality and trend emphasize the

asymmetric influence of the monsoon system on the

northern and southern segments of ALKI 2.

STL analysis not only confirms the seasonal

dominance of different monsoons at different latitudes

but also provides evidence of potential long-term

climate influences on wave conditions—information

that is important for estimating risks and developing

adaptive maritime infrastructure near the IKN.

3.7 Implications for the Indonesian National Capital and

Maritime Planning

The strategic location of IKN Nusantara near ALKI 2

reinforces the need for strong maritime climate

knowledge. The seasonal variability identified in this

study—especially high wave conditions during DJF in

the north and JJA in the south—should form the basis

for scheduling marine logistics, port operations, and

coastal construction.

Figure 11. STL (Seasonal Trend Decomposition using Loess)

analysis of SWH at Point K1 (top) and Point K7 (bottom).

In addition, the increasing trend of wave periods at

critical points underscores the importance of

integrating long-term marine climate change scenarios

into national infrastructure strategies. Developing

early warning systems and adaptive maritime

planning around the IKN can significantly reduce

operational risks and increase resilience.

4 CONCLUSION

This study presents a comprehensive assessment of

wind and wave variability along the Indonesian

Archipelago Sea Lane II (ALKI 2) in the Makassar Strait

using ERA-Interim reanalysis data for 39 years. The

analysis reveals significant seasonal and spatial

variations in significant wave height (SWH), mean

wave period (MWP), and wind speed, which are

shaped by seasonal dynamics and local topographic

conditions.

The northern part (K1–K2) shows higher wave

energy during the northwest monsoon (DJF), while the

southern part (K6–K7) experiences increased activity

during the southeast monsoon (JJA). The strong

directional alignment between the dominant wind

direction and wave direction (E-SE and SE-SE

respectively) further confirms the wind-driven nature

of the waves in this corridor.

Statistical analysis shows a significant positive

correlation between SWH and MWP, particularly in

the northern straits, as well as an increasing trend in

MWP at the northernmost and southernmost stations.

This pattern suggests a gradual shift in wave

characteristics, potentially related to broader climate

change.

These findings have important implications for

maritime safety, coastal planning, and infrastructure

resilience—especially given the increasing strategic

importance of ALKI 2 as Indonesia’s new capital city,

IKN Nusantara, is being built. Understanding and

anticipating seasonal and long-term oceanographic

patterns is critical to ensuring sustainable and safe

maritime operations in this evolving region.

Future work should extend this research using

higher resolution datasets (e.g., ERA5), wave hindcast

models, and scenario-based projections under climate

158

change to better inform adaptive planning and policy

development.

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