Analisis Seasonal Sea Level Variability Menggunakan Data Multi Mission Satelit Altimetri Jason Series (Studi Kasus: Perairan Indonesia Bagian Barat)

Ardianti, Agnes Risky (2019) Analisis Seasonal Sea Level Variability Menggunakan Data Multi Mission Satelit Altimetri Jason Series (Studi Kasus: Perairan Indonesia Bagian Barat). Other thesis, Institut Tekonologi Sepuluh Nopember.

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Abstract

Kenaikan muka air laut atau sea level rise akibat perubahan iklim adalah masalah serius bagi dunia yang telah terbukti secara ilmiah. Studi mengenai perubahan muka air laut dapat dilakukan dengan berbagai metode, salah satunya satelit altimetri. Pengamatan kenaikan muka air laut di Indonesia dengan menggunakan satelit altimetri menunjukkan angka kenaikan relatif tinggi dan sangat bervariasi. Wilayah Laut Jawa dan Selat Karimata dengan kontribusi Laut China Selatan bagian selatan mengalami rata-rata kenaikan sebesar 74,3 mm tercatat mulai tahun 2002-2018. Kenaikan tertinggi terjadi di wilayah perairan selatan Jawa dan Sumatra sedangkan Laut China Selatan mengalami kenaikan muka air laut terendah. Variasi tinggi muka air laut tersebut dipengaruhi oleh fenomena laut di Samudera Pasifik bagian barat, Samudera Hindia bagian timur, dan Laut Cina Selatan yang terjadi pada waktu tertentu contohnya ENSO atau El-Nino Southern Oscillation, IOD atau Indian Ocean Dipole atau Dipole Samudera Hindia dan angin muson. Penggunaan data dari satelit altimetri untuk menghitung SLA terkoreksi dari data Jason-1, Jason-2, dan Jason-3 sehingga didapatkan data time series tahun 2002 hingga 2018. Pola tren dan seasonal diperoleh ketika melakukan dekomposisi data time series tersebut. Komponen tren pada daerah penelitian menunjukkan kenaikan linier sedangkan variasi komponen seasonal dianalisis menggunakan hubungan antara SLA dengan indeks ENSO dan karakter angin muson. Indeks yang digunakan adalah MEI atau Multivariate ENSO Index. Data SLA yang dikorelasikan dengan MEI adalah data bi-monthly atau data rata-rata tiap pertengahan bulan 1 ke bulan 2, contoh Januari-Februari, Februari-Maret, dan seterusnya. Data SLA terlebih dahulu dihilangkan komponen tren-nya sehingga pola terbebas dari pola naik-turun atau disebut detrended. Koefisien korelasi menghasilkan nilai -0,228, yang artinya korelasi antara SLA dengan ENSO sangat rendah dengan hubungan saling bertolak belakang. Apabila nilai indeks naik maka SLA turun dan sebaliknya. Sedangkan, untuk komponen seasonal dari karakter muka air laut peraiaran bagian barat Indonesia didominasi oleh faktor annual berupa musim penghujan yang tinggi pada bulan November hingga Januari awal dengan intensitas tertinggi pada tahun 2006 karena puncak IOD atau Indian Ocean Dipole positif yang terjadi. Musim semi-annual terjadi pada bulan Juli hingga Oktober dengan pola naik-turunnya SLA disebabkan oleh perbedaan pola ‘hujan palsu’ yang terjadi di daerah belahan bumi utara dan selatan yang masuk dalam cakupan daerah penelitian. Pola Juli-Agustus mempengaruhi pola ‘hujan palsu’ di wilayah belahan bumi utara sedangkan pola Agustus-September dan September-Oktober terjadi pada daerah bumi belahan selatan. Musim kemarau terjadi pada bulan Februari-Juni.
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Sea level rise caused by global climate change has become an important issue that has been widely documented by scientific studies. One of the most effective methods for monitoring sea level change is satellite altimetry, which provides continuous observations of sea level variations over time. Altimetry observations indicate that sea level in the Java Sea, Karimata Strait, and the southern South China Sea increased by an average of 74.3 mm during the period 2002–2018, accompanied by considerable spatial and temporal variability. The highest sea level rise occurred in the southern waters of Java and Sumatra, while the lowest increase was observed in the southern South China Sea. These variations are influenced by regional oceanographic and climatic conditions, including the western Pacific Ocean, the eastern Indian Ocean, and the South China Sea, as well as large-scale climate phenomena such as the El Niño–Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Asian–Australian monsoon system. This study utilizes sea level anomaly (SLA) data derived from the Jason-1, Jason-2, and Jason-3 satellite missions to construct a continuous time series from 2002 to 2018. Time-series decomposition was applied to separate the trend and seasonal components of the SLA data. The trend component indicates a gradual linear increase in sea level throughout the study area, while the seasonal component requires further interpretation in relation to ENSO and monsoon variability, particularly the tropical monsoon. To examine the relationship between SLA and ENSO, the SLA time series was first detrended. The resulting correlation coefficient of -0.228 indicates a weak negative relationship, suggesting that higher ENSO index values are generally associated with lower SLA values, although this pattern is not consistently observed. In contrast, the seasonal component exhibits a more regular pattern associated with the monsoon cycle. The annual cycle is characterized by a rainy season that peaks during November and December, with the strongest seasonal signal occurring in 2006. A semiannual cycle is observed from July to October, during which SLA exhibits alternating increases and decreases. This pattern reflects the study area's location across both the Northern and Southern Hemispheres, where the timing of seasonal sea level changes differs slightly. In the Northern Hemisphere, SLA generally rises and falls between July and August, whereas in the Southern Hemisphere similar variations occur between August and October. The July–October period corresponds to the monsoon transition season, while the dry season generally extends from February to June.

Item Type:	Thesis (Other)
Additional Information:	RSG 551.46 Ard a-1 2019
Uncontrolled Keywords:	sea level rise, altimetri, tren, variabilitas seasonal.
Subjects:	T Technology > TC Hydraulic engineering. Ocean engineering > TC424 Water levels T Technology > TD Environmental technology. Sanitary engineering > TD171.75 Climate change mitigation
Divisions:	Faculty of Civil Engineering and Planning > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Agnes Risky Ardianti
Date Deposited:	22 Jul 2026 07:17
Last Modified:	22 Jul 2026 07:17
URI:	http://repository.its.ac.id/id/eprint/64974

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