Modulation of ETCCDI-based extreme rainfall indices by ENSO and the Indian Ocean Dipole over topographically complex North Sumatra, Indonesia

DOI: https://doi.org/10.3846/gac.2026.26129

Abstract

This study examines the characteristics of extreme rainfall in North Sumatra Province, Indonesia, and its teleconnections with the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). The analysis uses a blended daily rainfall dataset from 1990 to 2024, combining station observations from the Indonesian Agency for Meteorology, Climatology, and Geophysics (BMKG) with the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) satellite data. Validation of CHIRPS against 61 station records shows strong reliability, with an average Pearson correlation (r) of 0.83 and a Root Mean Square Error (RMSE) of 53.1 mm over 20 years. Analysis of extreme rainfall indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) reveals a significant influence from global climate phenomena. The La Niña phase of ENSO and the negative phase of the IOD are consistently associated with wetter conditions, characterized by higher annual rainfall totals (PRCPTOT), increased maximum 1-day (RX1day) and 5-day (RX5day) precipitation, and longer Consecutive Wet Days (CWD). Conversely, the El Niño and positive IOD phases lead to drier conditions and an increased risk of meteorological drought, as evidenced by significantly higher counts of Consecutive Dry Days (CDD). Notably, a sharp decline in extreme-frequency events observed since 2020 contradicts typical La Niña patterns, suggesting a shift in teleconnections. Spatially, the highest rainfall intensity and duration are concentrated in the western and southern coastal and mountainous regions, while the northeastern lowlands are comparatively drier. These findings underscore the strong modulation of regional hydro-climatic extremes by large-scale climate drivers and provide a quantitative basis for enhancing climate change adaptation and disaster mitigation strategies in one of Indonesia’s most vulnerable provinces.

 

Keywords:

extreme rainfall, CHIRPS, hazard, El Niño, climate, weather
Published in Issue
October 7, 2026
Abstract Views
39

How to Cite

Nur, M., Khomsin, Pratomo, D. G., & Sawal, M. (2026). Modulation of ETCCDI-based extreme rainfall indices by ENSO and the Indian Ocean Dipole over topographically complex North Sumatra, Indonesia. Geodesy and Cartography, 52(S1), S18–S24. https://doi.org/10.3846/gac.2026.26129

Share

References

Aldrian, E., & Susanto, R. (2003). Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature. International Journal of Climatology, 23(12), 1435–1452. https://doi.org/10.1002/joc.950

Aldrian, E., Sein, D., Jacob, D., Dümenil, G. L., & Podzun, R. (2005). Modelling Indonesian rainfall with a coupled regional model. Climate Dynamics, 25, 1–17. https://doi.org/10.1007/s00382-004-0483-0

Alexander, L. V. (2016). Global observed long-term changes in temperature and precipitation extremes: A review of progress and limitations in IPCC assessments and beyond. Weather and Climate Extremes, 11, 4–16. https://doi.org/10.1016/j.wace.2015.10.007

Ayehu, G. T., Tadesse, T., Gessesse, B., & Dinku, T. (2018). Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia. Atmospheric Measurement Techniques, 11(4), 1921–1936. https://doi.org/10.5194/amt-11-1921-2018

Cai, W., van Rensch, P., Cowan, T., & Hendon, H. H. (2011). Teleconnection pathways of ENSO and the IOD and the mechanisms for impacts on Australian rainfall. Journal of Climate, 24(15), 3910–3923. https://doi.org/10.1175/2011JCLI4129.1

Chang, C. P., Wang, Z., McBride, J., & Liu, C.-H. (2005). Annual cycle of Southeast Asia Maritime continent rainfall and the asymmetric monsoon transition. Journal of Climate, 18(2), 287–301. https://doi.org/10.1175/JCLI-3257.1

D’Arrigo, R., & Wilson, R. (2008). El Niño and Indian Ocean influences on Indonesian drought: Implications for rainfall and crop productivity forecasting. International Journal of Climatology, 28(5), 611–616. https://doi.org/10.1002/joc.1654

Dinku, T., Funk, C., Peterson, P., Maidment, R., Tadesse, T., Gadain, H., & Ceccato, P. (2018). Validation of the CHIRPS satellite rainfall estimates over eastern Africa. Quarterly Journal of the Royal Meteorological Society, 144(S1), 292–312. https://doi.org/10.1002/qj.3244

Donat, M. G., Alexander, L. V., Yang, H., Durre, I., Vose, R., Dunn, R. J. H., Willett, K. M., Aguilar, E., Brunet, M., Caesar, J., Hewitson, B., Jack, C., Klein Tank, A. M. G., Kruger, A. C., Marengo, J., Peterson, T. C., Renom, M., Oria Rojas, C., Rusticucci, M., & Kitching, S. (2013). Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset. Journal of Geophysical Research: Atmospheres, 118, 2098–2118. https://doi.org/10.1002/jgrd.50150

Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoel, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations – a new environmental record for monitoring extremes. Scientific Data, 2, Article 150066. https://doi.org/10.1038/sdata.2015.66

Hamada, J. I., Yamanaka, M. D., Matsumoto, J., Fukao, S., Winarso, P. A., & Sribimawati, T. (2002). Spatial and temporal variations of the rainy season over Indonesia and their link to ENSO. Journal of the Meteorological Society of Japan. Ser. II, 80(2), 285–310. https://doi.org/10.2151/jmsj.80.285

Hendon, H. H. (2003). Indonesian rainfall variability: Impacts of ENSO and local air-sea interaction. Journal of Climate, 16(11), 1775–1790. https://doi.org/10.1175/1520-0442(2003)016<1775:IRVIOE>2.0.CO;2

Kurniadi, A., Weller, E., Min, S. K., & Seong, M. G. (2021). Independent ENSO and IOD impacts on rainfall extremes over Indonesia. International Journal of Climatology, 41(6), 3640–3656. https://doi.org/10.1002/joc.7040

Li, J., & Heap, A. D. (2014). Spatial interpolation methods applied in the environmental sciences: A review. Environmental Modelling & Software, 53, 173–89. https://doi.org/10.1016/j.envsoft.2013.12.008

Lu, B., & Ren, H.-L. (2020). What caused the extreme Indian Ocean Dipole event in 2019? Geophysical Research Letters, 47(11), Article e2020GL088615. https://doi.org/10.1029/2020GL087768

McGill, R., Tukey, J. W., & Larsen, W. A. (1978). Variations of box plots. The American Statistician, 32(1), 12–16. https://doi.org/10.1080/00031305.1978.10479236

McKinney, W. (2010). Data structures for statistical computing in Python. Proceedings of the 9th Python in Science Conference, 56–61. https://doi.org/10.25080/Majora-92bf1922-00a

Saji, N., Goswami, B. N., Vinayachandran, P. N., & Yamagata, T. (1999). A dipole mode in the tropical Indian Ocean. Nature, 401, 360–363. https://doi.org/10.1038/43854

Saji, N. H., & Yamagata, T. (2003). Possible impacts of Indian Ocean dipole mode events on global climate. Climate Research, 25, 151–169. https://doi.org/10.3354/cr025151

Santoso, A., McPhaden, M. J., & Cai, W. (2017). The defining characteristics of ENSO extremes and the strong 2015/2016 El Niño. Reviews of Geophysics, 55(4), 1079–1129. https://doi.org/10.1002/2017RG000560

Siswanto, van der Schrier, G., & van den Hurk, B. (2022). Declining trends of extreme rainfall indices over Java Island, Indonesia. International Journal of Climatology, 42, 6456–6473.

Supari, T. F., Juneng, L., & Aldrian, E. (2017). Observed changes in extreme temperature and precipitation over Indonesia. International Journal of Climatology, 37(4), 1979–1997. https://doi.org/10.1002/joc.4829

Supari, T. F., Salimun, E., Aldrian, E., Sopaheluwakan, A., & Juneng, L. (2018). ENSO modulation of seasonal rainfall and extremes in Indonesia. Climate Dynamics, 51, 2559–2580. https://doi.org/10.1007/s00382-017-4028-8

Trenberth, K. E. (1997). The definition of El Niño. Bulletin of the American Meteorological Society, 78(12), 2771–2778. https://doi.org/10.1175/1520-0477(1997)078<2771:TDOENO>2.0.CO;2

Waliser, D. E., & Gautier, C. (1993). A satellite-derived climatology of the ITCZ. Journal of Climate, 6(11), 2162–2174. https://doi.org/10.1175/1520-0442(1993)006<2162:ASDCOT>2.0.CO;2

Yamanaka, M. D. (2016). Physical climatology of Indonesian maritime continent: An outline to comprehend observational studies. Atmospheric Research, 178–179, 231–259. https://doi.org/10.1016/j.atmosres.2016.03.017

View article in other formats

CrossMark check

CrossMark logo

Published

2026-10-07

How to Cite

Nur, M., Khomsin, Pratomo, D. G., & Sawal, M. (2026). Modulation of ETCCDI-based extreme rainfall indices by ENSO and the Indian Ocean Dipole over topographically complex North Sumatra, Indonesia. Geodesy and Cartography, 52(S1), S18–S24. https://doi.org/10.3846/gac.2026.26129

Share