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All Journal Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Al-Irsyad Journal of Physics Education
Rayhan Rafi
Sekolah Tinggi Meteorologi Klimatologi dan geofisika
Agriculture, Biological Sciences & Forestry Chemistry Education Physics

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OTOMATISASI DAN VALIDASI PEMROSESAN DATA GSMAP UNTUK MONITORING CURAH HUJAN HARIAN SPASIAL DI MALUKU UTARA Rayhan Rafi; Nadia Aurellia Amarullah; Kevin Rizky Crusia Kawilohi; Resti Maulina Chusnul Chortimah; Yosik Norman
Al-Irsyad Journal of Physics Education Vol 5 No 1 (2026): Al-Irsyad Journal of Physics Education
Publisher : Sekolah Tinggi Keguruan dan Ilmu Pendidikan Darud Da'wah Wal Irsyad Pinrang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58917/ijpe.v5i1.641

Abstract

Provinsi Maluku Utara merupakan wilayah kepulauan dengan variabilitas curah hujan yang tinggi, namun pemantauan kondisi meteorologis sering terkendala oleh keterbatasan jaringan pengamatan permukaan yang tidak merata. Pemanfaatan data satelit Global Satellite Mapping of Precipitation (GSMaP) menawarkan solusi alternatif untuk pemantauan hujan spasial, namun akurasinya perlu divalidasi terlebih dahulu terhadap kondisi lokal. Penelitian ini bertujuan untuk melakukan otomatisasi pemrosesan dan validasi akurasi estimasi curah hujan harian GSMaP v8 terhadap data Automatic Weather Station (AWS) di empat lokasi strategis: Labuha, Tobelo, Pelabuhan Ternate, dan Stageof Ternate. Validasi dilakukan menggunakan metode statistik Pearson Correlation (r), Root Mean Square Error (RMSE), dan Relative Bias (RB). Hasil analisis menunjukkan bahwa pada skala akumulasi harian, GSMaP memiliki hubungan linear yang moderat terhadap data observasi dengan nilai koefisien korelasi (r) gabungan sebesar 0,462. Tingkat kesalahan estimasi ditunjukkan oleh nilai RMSE sebesar 15,67 mm/hari dengan kecenderungan overestimate sebesar 11,4%. Akurasi GSMaP di wilayah ini teridentifikasi dipengaruhi oleh "efek pulau kecil" (small island effect) dan kesalahan sensor pada garis pantai (coastline error) yang signifikan di wilayah kepulauan. Penelitian ini menyimpulkan bahwa meskipun GSMaP mampu menangkap pola umum kejadian hujan harian, penggunaan data untuk analisis lanjutan di Maluku Utara memerlukan koreksi bias lebih lanjut.
Pemanfaatan Metode Merged-IMSRA dalam Peningkatan Estimasi Curah Hujan Berbasis Satelit saat Kejadian Mesoscale Convective System (MCS) di Bali: - Rayhan Rafi; Yosafat Donni Haryanto; Adi Mulsandi; Latifah Nurul Qomariyatuzzamzami
Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Vol. 7 No. 3 (2026): August (Inpres)
Publisher : Mataram University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/goescienceed.v7i3.2314

Abstract

Mesoscale Convective System (MCS) is one of the primary causes of extreme rainfall events in tropical regions, as occurred in Bali on 8–10 September 2025, which resulted in a significant hydrometeorological disaster. This study aims to evaluate the capability of the Merged Indian National Satellite System Multi-Spectral Rainfall Algorithm (M-IMSRA) in estimating the spatial and temporal distribution of rainfall during the MCS event. M-IMSRA was developed through several sequential stages: IMSRA (IMR), polynomial bias correction (IMC), event-based orographic correction using GSMaP MVK ratios, cloud growth correction, and assimilation of 31 BMKG AWS/ARG observation points using the Cressman scheme. Validation was conducted using the Pearson correlation coefficient (r), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and bias. The results show that M-IMSRA accurately mapped the spatial evolution of the MCS, with extreme rainfall accumulation (210–300 mm) concentrated in the central-eastern mountainous region of Bali during the peak phase, consistent with orographic lifting mechanisms. Statistical validation indicated moderate to very high correlation across all event phases (r = 0.663–0.941), accompanied by low RMSE and MAE values and a small, consistent bias (−0.08 to −0.36mm). It is concluded that M-IMSRA is an accurate rainfall estimation method with strong potential for operational implementation in hydrometeorological disaster monitoring and early warning systems in Indonesian archipelagic regions with limited surface observation networks.
Co-Authors Adi Mulsandi Kevin Rizky Crusia Kawilohi Latifah Nurul Qomariyatuzzamzami Nadia Aurellia Amarullah Resti Maulina Chusnul Chortimah Yosafat Donni Haryanto Yosik Norman