Jurnal Ekologi.
Masyarakat dan Sains E-ISSN: 2720-9717 Volume 6.
Nomor21, 2025
ECOTAS
https://journals.
org/index.
php/ems https://doi.
org/10.
55448/ems Artikel Riwayat Artikel:
Masuk: 09-05-2025 Diterima: 09-08-2025 Dipublikasi: 11-10-2025 Cara Mengutip:
Yuliardi.
Amir.
Sugeng Hartono.
Luhur Moekti Prayogo.
Agung Tri Nugroho.
Diah Ayu Rahmalia, dan Ratna Juita Sari.
AuSea Surface Temperature Trends .
3Ae 2.
at the CentralAeWest Java Border: Climate Change IndicatorAy.
Jurnal Ekologi.
Masyarakat Dan Sains 6 .
: 189-97.
https://doi.
org/10.
55448/j94 Lisensi:
Hak Cipta .
2025 Jurnal Ekologi.
Masyarakat dan Sains Artikel ini berlisensi Creative Commons AttributionNonCommercial 4.
International License.
Sea Surface Temperature Trends .
3Ae 2.
at the CentralAeWest Java Border:
Climate Change Indicator Amir Yarkhasy Yuliardi1 .
Sugeng Hartono2.
Luhur Moekti Prayogo3.
Agung Tri Nugroho1.
Diah Ayu Rahmalia1.
Ratna Juita Sari1 Study Program of Marine Science.
Faculty of Fisheries and Marine Science.
Universitas Jenderal Soedirman.
Purwokerto Study Program of Marine Science.
Faculty of Fisheries and Marine.
Universitas PGRI Ronggolawe.
Tuban Study Program of Aquatic Resources Management.
Faculty of Fisheries and Marine Science.
Universitas Jenderal Soedirman.
Purwokerto Penulis koresponden: amiryarkhasy@gmail.
Abstrak: Penelitian ini menganalisis variabilitas suhu permukaan laut (SST) di perairan Cilacap dan Pangandaran.
Laut Selatan Jawa, periode 1993Ae2022 menggunakan data satelit Marine Copernicus.
Analisis mencakup tren jangka panjang, fluktuasi antar-tahunan, dan pola musiman yang berkaitan dengan dinamika oseanografi regional seperti ENSO dan upwelling musiman.
Hasil menunjukkan tren pemanasan SST sebesar 0,06 A 0,02 AC per dekade yang mengindikasikan pengaruh perubahan iklim regional.
Variabilitas antartahunan menyoroti pendinginan signifikan pada 1997 (La Niy.
dan pemanasan ekstrem pada 1998 dan 2010 (El Niy.
Pola musiman menunjukkan SST tertinggi terjadi MaretAe Mei saat monsun barat, dan terendah AgustusAeSeptember akibat upwelling.
Upwelling berperan penting dalam mengatur suhu laut dan mendukung produktivitas hayati.
Temuan ini menekankan pentingnya pemantauan SST untuk pengelolaan sumber daya laut yang adaptif terhadap iklim di wilayah pesisir selatan Jawa.
Kata Kunci: Laut Selatan Jawa.
Perubahan Iklim.
Suhu Permukaan Laut.
Tren Pemanasan.
Variabilitas Suhu Abstract: This study analyzes the variability of sea surface temperature (SST) in the coastal waters of Cilacap and Pangandaran.
South Java Sea, during the 1993Ae2022 period using satellite data from Marine Copernicus.
The analysis covers long-term trends, interannual fluctuations, and seasonal patterns related to regional oceanographic dynamics such as ENSO and seasonal upwelling.
The results show a warming trend of SST 06 A 0.
02 AC per decade, indicating the influence of regional climate change.
Interannual variability highlights significant cooling in 1997 (La Niy.
and extreme warming in 1998 and 2010 (El Niy.
Seasonal patterns reveal the highest SST from March to May during the west monsoon, and the lowest SST in AugustAeSeptember due to Upwelling plays an important role in regulating sea temperatures and supporting biological productivity.
These findings underscore the importance of SST monitoring for climate-adaptive marine resource management in the southern coastal region of Java.
Keywords: Climate Change.
Sea Surface Temperature.
South Java Sea.
Temperature Variability.
Warming Trend oceanAeatmosphere interactions, particularly in tropical regions (Laurindo et al.
, 2022.
Cheng et , 2.
Variations in SST, both seasonal and long-term, can influence atmospheric circulation patterns and contribute to the development of major climate phenomena such as the El NiyoAe INTRODUCTION There have been many studies regarding Sea surface temperature (SST) over recent The parameter is studied due to its critical role in understanding the dynamics of Yuliardi.
Amir.
Sugeng Hartono.
Luhur Moekti Prayogo.
Agung Tri Nugroho.
Diah Ayu Rahmalia, dan Ratna Juita Sari.
AuSea Surface Temperature Trends .
3Ae2.
at the CentralAeWest Java Border: Climate Change IndicatorAy.
Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) (Deser et al.
, 2009.
Roxy et , 2.
Some studies have reported a warming trend in the western Indian Ocean and across Indonesian waters.
For instance, the Indian Ocean warm pool has experienced a temperature increase of approximately 0.
7 AC between 1901 and 2012 (Roxy et al.
, 2.
Similarly, regions in eastern Indonesia, such as the Sawu Sea and its surroundings, have shown signs of warming, which are suspected to be linked to weakened upwelling processes due to declining wind intensity and altered ocean circulation patterns (Cahyarini et al.
, 2014.
Lee, 2.
Indonesia, as part of the Indo-Pacific Warm Pool, plays a crucial role in modulating global climate variability (Siswandi et al.
, 2022.
Zhou et , 2.
Changes in sea surface temperature within this region not only influence local rainfall patterns but also contribute to the dynamics of large-scale atmospheric circulations, including the Hadley and Walker cells (Sprintall et al.
, 2014.
De Deckker, 2.
Elevated SSTs in the region enhance evaporation rates and intensify atmospheric convection, ultimately triggering transcontinental climate disturbances such as droughts, floods, and shifts in the intensity of tropical storms in distant parts of the globe (Robinson, 2021.
Singh et al.
, 2.
Rising SSTs in Indonesian coastal waters far-reaching Beyond potentially exacerbating marine environmental stressors such as coral bleaching, warming trends can also affect fisheries, marine productivity, and the sustainability of coastal ecosystems (Pelu.
Hidayat & Ramadhan, 2.
Moreover.
SST changes serve as vital indicators for detecting long-term climate change signals in tropical regions like Indonesia, where marine climate stability is essential for ecological and socioeconomic resilience.
Continuous research regarding SST is urgent in Indonesian coastal waters.
Hence, a scientific investigation was conducted in one research area, namely the Border of Central Java and West Java which consists of Cilacap and Pangandaran waters.
The area is part of the key coastal regions along the southern coast of Java Island, directly bordering the Indian Ocean.
It is influenced by a variety of oceanographic dynamics, including seasonal upwelling, the south Java current, regional influences of the AsianAe Australasian monsoon system, and unique tidal characteristics (Aldrian & Susanto, 2003.
Umasangaji & Ramili, 2021.
Yuliardi & Prayogo.
Wijaya et al.
, 2.
There is a lack of specific studies analyzing the long-term trends of sea surface temperature (SST) in the Cilacap and Pangandaran waters despite its strategic location.
It is noteworthy as the availability of historical data allows us for the detection of both the direction and magnitude of SST changes relevant to local climate change By applying a linear trend analysis of SST, the study aims to contribute to the development of climate adaptation policies tailored to the coastal The primary objective is to examine the linear trend of SST in its waters from 1993 to 2022, with a focus on identifying the rate of sea temperature change and assessing its implications as an indicator of climate change in the southern coastal region of Java.
MATERIALS AND METHODS
Location The study was conducted in the Border of Central Java and West Java, specifically in Cilacap and Pangandaran waters, directly adjacent to the Indian Ocean.
The region is characterized by complex oceanographic dynamics, driven by seasonal monsoons, the southward-flowing Java Current, and periodic upwelling phenomena (Wen et al.
, 2023.
Wijaya et al.
, 2.
The study focused on a fixed latitudinal transect at 88AS, with four observation points distributed longitudinally from west to east, parallel to the Cilacap coastline.
These observation points were designated as follows:
Point A .
88AS, 108.
62AE).
Point B .
88AS,
88AE).
Point C .
88AS, 109.
12AE), and Point D .
88AS, 109.
38AE) (Figure .
This spatial designed to longitudinal variations in sea surface temperature (SST) across the western to eastern sectors of Cilacap waters, enabling the detection of potential spatial differences in the observed warming Dataset The sea surface temperature (SST) data used in this study were obtained from the Copernicus Marine Environment Monitoring Service (CMEMS), specifically from the Product ID:
MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015
_012,
Dataset ID:
dataset-armor-3d-repweekly_202012 (Greiner et al.
, 2.
This dataset is derived from the ARMOR3D Level 4 global multi-observation reprocessed and analyzed product, which integrates three-dimensional fields of temperature, salinity, sea level height, geostrophic currents, and mixed layer depth.
The data are provided on a regular grid with a spatial Jurnal Ekologi.
Masyarakat Dan Sains 6 .
: 189-97.
https://doi.
org/10.
55448/j94d1w11.
resolution of 1/8A .
125A) and 50 vertical levels extending from the sea surface to the ocean floor.
For the purpose of this study, we extracted weekly SST data at the surface level .
m dept.
covering the period from January 1993 to January 2022.
subset of the data was taken at four observation points (Figure .
coast were then averaged spatially to generate a single representative time series for the study To reduce short-term variability and highlight the long-term trend, the anomaly time series was smoothed using a 12-month moving Trend analysis was conducted using simple linear regression on the smoothed SST anomaly time series.
Time was converted into decimal years, such that January 1993 becomes 1993.
February 1993 becomes 1993.
08, and so forth.
The linear regression model is formulated as:
Analysis The analysis of sea surface temperature (SST) trends in the study was conducted using a quantitative statistical approach.
The process began with the extraction of SST data at 0 m depth from the Copernicus dataset, covering the period from January 1993 to January 2022.
Monthly climatology was calculated by averaging SST values for each calendar month across the entire observation period.
Subsequently.
SST anomalies were computed as the difference between the observed monthly SST and the corresponding climatological mean for that The SST anomaly for time index i is calculated as:
Where is the SST anomaly at time , is the slope representing the rate of temperature change per year, is the intercept, and is time in decimal years.
The trend coefficient was then scaled by a factor of 10 to express the trend in units of degrees Celsius per decade (AC/decad.
, which is more suitable for climatological The standard deviation of the trend was also calculated to assess variability and confidence in the results.
Where represents the time index for each month in the time series.
The monthly anomalies from the four observation points along the Cilacap Figure 1.
Map of the study area off the southern coast of Cilacap.
Central Java.
Indonesia.
Four sea surface temperature (SST) sampling stations, labeled A.
C, and D, are marked with red triangles.
These stations were selected to investigate the temporal variability of SST in the coastal waters of the study region.
Yuliardi.
Amir.
Sugeng Hartono.
Luhur Moekti Prayogo.
Agung Tri Nugroho.
Diah Ayu Rahmalia, dan Ratna Juita Sari.
AuSea Surface Temperature Trends .
3Ae2.
at the CentralAeWest Java Border: Climate Change IndicatorAy.
Figure 2.
Annual mean sea surface temperature (SST) at four longitudinal coordinate points in the Cilacap waters from 1993 to 2022.
Each panel (AAeD) represents a specific location with the following coordinates: A .
62A E).
B .
88A E).
C .
12A E), and D .
38A E).
approximately 23AC during certain years.
This pattern reflects the influence of the monsoonal 3 RESULT AND DISCUSSION cycle over the southern Java region.
The southeast 1 SST Linear Trend monsoon .
ry seaso.
enhances surface cooling Figure 3A illustrates the weekly sea surface through strong wind-induced upwelling, whereas temperature (SST) dynamics in the research area the northwest monsoon .
et seaso.
introduces from 1993 to early 2022.
The SST fluctuations warmer water masses from the west (Umasangaji exhibit a consistent seasonal pattern each year, and Ramili, 2021.
Widagdo et al.
, 2.
with peak temperatures typically occurring during Moreover, the SST time series indicates the the second half of the year, particularly from presence of interannual variability superimposed October to December, while the lowest on the seasonal cycle, suggesting modulation by temperatures are observed between May and July.
both regional and global climatic processes.
SST values generally range from 25AC to 29AC.
Figure 3.
(A) Weekly mean sea surface temperature (SST) at the surface .
epth = 0 .
in the Cilacap waters from January 1993 to January 2022.
(B) Weekly SST anomalies with a 12-month moving average .
hick red lin.
and linear trend line .
lack lin.
as deviations from the monthly climatological Figure 3B presents the sea surface means, to capture medium- to long-term temperature anomalies (SST anomal.
, calculated The anomaly time series reveals Jurnal Ekologi.
Masyarakat Dan Sains 6 .
: 189-97.
https://doi.
org/10.
55448/j94d1w11.
several pronounced extreme events, including a sharp negative anomaly reaching -3.
5AC in mid1997 and positive anomalies exceeding 3AC during 1998 and 2010.
These extreme deviations are associated with strong ENSO episodes (Mawren et al.
, 2.
The 12-month moving average .
epicted as a thick red lin.
effectively smooths seasonal components, enabling clearer identification of long-term tendencies.
The superimposed linear trend line .
n blac.
indicates a positive SST anomaly trend of 0.
06 A 0.
02 AC
per decade over the nearly three-decade observation period.
Although this trend appears moderate, the persistent warming of surface waters may carry substantial ecological and climatological implications, especially in sensitive coastal environments such as Cilacap.
This finding aligns with broader regional patterns, where sea surface temperatures across Indonesian waters have shown a consistent warming trend, averaging around 0.
19 A 0.
04 AC per decade over the past 33 years (Iskandar et al.
, 2.
The observed warming trend of 0.
06 AC per decade adds further evidence to regional ocean warming in the southern Java region.
This trend aligns with global findings on sea surface temperature increases under ongoing climate change (Xu et al.
, 2.
It indicates that despite substantial interannual and seasonal variabilityAi mainly driven by monsoonal forcing and ENSO eventsAia persistent long-term warming signal is Ecologically, this trend may lead to shifts in fish species distribution, reduced primary productivity due to enhanced water column stratification, and increased coral bleaching risk (Setiawati et al.
, 2024.
Sarre et al.
, 2.
such, these results are critical for informing climate adaptation strategies and the sustainable management of coastal zones, especially in the context of long-term environmental change.
Annual Variability Figure 4 presents annual boxplots of sea surface temperature (SST) in Cilacap waters from 1993 to 2022, offering a quantitative depiction of Overall, the median annual SST values range between 27.
5AC and 29AC, indicating relative stability with a slight upward trend during the last decade.
Early years such as 1993 to 1995 exhibit narrower temperature distributions, while 1996 and 1997 display pronounced cooling, reflected by low minimum values approaching 23AC and numerous negative outliers.
These conditions are consistent with the impacts of a strong La Niya event, which is known to drive significant surface cooling across the southern Java region.
Figure 4.
Annual boxplot of sea surface temperature (SST) in the Cilacap waters from 1993 to 2022.
The horizontal line within each box represents the median, while the upper and lower edges indicate the third and first quartiles, respectively.
Vertical lines .
show the range of minimum and maximum values, and circles denote outliers.
Yuliardi.
Amir.
Sugeng Hartono.
Luhur Moekti Prayogo.
Agung Tri Nugroho.
Diah Ayu Rahmalia, dan Ratna Juita Sari.
AuSea Surface Temperature Trends .
3Ae2.
at the CentralAeWest Java Border: Climate Change IndicatorAy.
Interannual variability is clearly evident in the length of the whiskers and interquartile ranges, which reflect intra-annual temperature Certain years, such as 1997, 2002, and 2015, exhibit significant outliers below the normal range, indicating extreme temperature events potentially associated with oceanic dynamics or global climate phenomena.
contrast, post-2010 years show more stable temperature distributions with an upward shift, reflecting the influence of global warming trends as previously illustrated in Figure 3B.
The median SST for the past five years consistently exceeds 28.
5AC, reinforcing the indication of long-term warming in this region.
The annual SST variation depicted in Figure 4 also suggests that although seasonal cycles dominate monthly scales, interannual climate drivers such as El Niyo and La Niya play a major role in producing extreme temperature anomalies during specific years.
These changing dynamics can significantly impact local marine ecosystems, including shifts in primary productivity, changes in fish species distribution, and increased thermal stress on marine organisms such as coral reefs (Pinkerton et al.
, 2021.
Staudinger et al.
, 2021.
Voolstra et al.
, 2.
3 Seasonal Variability Figure 5 illustrates the seasonal fluctuation of SST in the Cilacap waters, reflecting regional monsoonal wind patterns and upwelling activity.
The SST pattern shows peak temperatures occurring between March and May, with average values exceeding 29AC.
A significant temperature decline begins in June and reaches a minimum of 8AC in September, followed by a gradual increase toward the end of the year.
The sharp cooling observed from June to September is closely associated with seasonal upwelling events along the southern coast of Java (Wijaya et al.
During this period, the dominance of the southeast monsoon winds drives surface water masses offshore .
urface current export toward the northwes.
, which is compensated by the upward movement of deeper, cooler water to the surface .
(Wen et al.
, 2.
Figure 5.
Monthly average sea surface temperature (SST) in the Cilacap waters during the period 1993Ae SST variability in Cilacap highlights a strong Seawater originating from deeper layers is connection between atmospheric dynamics, ocean typically colder and richer in nutrients, leading to circulation, and upwelling processes.
a marked decrease in sea surface temperature comprehensive understanding of these patterns is during the upwelling season.
This phenomenon essential for effective coastal resource accounts for the lowest SST values observed in management and for improving the predictability August and September.
The upwelling mechanism of annual fisheries productivity.
not only contributes to surface cooling but also plays a pivotal role in shaping coastal marine 4 CONCLUSION ecosystem dynamics (Vinayachandran et al.
This study reveals a warming trend in sea The upward transport of nutrient-rich surface temperature (SST) in the Cilacap and waters enhances primary productivity, thereby Pangandaran coastal waters, with an estimated supporting the marine food web (Satar et al.
increase of 0.
06 A 0.
02 AC per decade over the As a result, this period is often associated period 1993Ae2022, based on satellite observations with increased fish catches in the southern waters from Marine Copernicus.
Despite the presence of of Java, including the Cilacap region (Wujdi et al.
both seasonal and interannual variability, the Wen et al.
, 2.
Overall, the seasonal Jurnal Ekologi.
Masyarakat Dan Sains 6 .
: 189-97.
https://doi.
org/10.
55448/j94d1w11.
observed warming indicates a signal of regional climate change.
Extreme events such as the 1997 La Niya and the 1998 and 2010 El Niyo episodes had substantial impacts on annual SST variability.
Seasonally, peak SSTs are recorded between March and May, coinciding with the dominance of westerly winds, whereas the lowest temperatures occur from August to September, associated with seasonal upwelling that brings colder, deeper water to the surface.
The upwelling does not only drive localized cooling but also enhances water productivity.
Overall, the observed long-term warming trend and seasonal dynamics are crucial considerations for marine resource management and climate adaptation Based on the current research, further research is is recommended to focus on assessing the implications of these changes on marine ecosystems and fisheries in the southern Java for sustainable development of the built environment in coastal cities.
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The author also extends sincere appreciation to the reviewers for their constructive comments and valuable suggestions, which have significantly improved the quality of this manuscript.
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