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 (Mataram University, 2026)
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.