Extreme Rainfall Indices Trends in Indonesia During 1971-2020 - Tugiyo Aminoto; Nova Susanti; Rahma Dani; Akhmad Faqih (Postgraduate, University of Mataram, 2026)
This study investigates changes in the intensity, frequency, and duration of extreme rainfall events across Indonesia over the past 3 to 5 decades (1971–2020). Daily rainfall data of 172 Indonesian meteorological stations were examined, and only stations with more than 30 years of data were selected. This filtering process resulted in 101 validated time series used to calculate a subset of extreme rainfall indices based on ETCCDI (Expert Team on Climate Change Detection and Indices) standards. The analysis focuses on six main indices: PRCPTOT (total annual rainfall), SDII (average daily rainfall intensity), CWD (number of consecutive rainy days), R95p (percentile-based extreme rainfall), RX5day (cumulative maximum rainfall in 5 consecutive days) and CDD (number of consecutive dry days). The indices were computed using R programming, following the algorithm implemented in the RClimDex v1.0 software. Rainfall trends based on these indices were assessed using a non-parametric statistical framework, specifically the Mann–Kendall (MK) test in conjunction with Sen’s Slope Estimator. In cases where significant autocorrelation was present in the data, the Modified Mann–Kendall (MMK) test was applied to ensure the robustness of the trend analysis. Comparative analysis with previous studies shows that, while overall rainfall trends are broadly consistent, the slope values in this research have substantially narrower range. PRCPTOT ranged from −29.64 to 101.02 mm/decade compared to the earlier study (−140.31 to 449.26 mm/decade), and SDII exhibited weaker trends (−0.11 to 0.16 mm/day), indicating less pronounced intensification. Similarly, CDD, CWD, RX5day, and R95p displayed more moderate changes, this moderation may be attributed to the more recent reference period, which reflects climate dynamics that differ from those observed in earlier decades. These findings highlight the influence of methodological and spatial differences and emphasize the need for sustained monitoring to inform climate adaptation and mitigation.