Asymmetric patterns of ENSO phases in Indonesia between 1975‑2025 and corresponding impacts on rainfall variability

Abstract

El Niño‑Southern Oscillation (ENSO) is a climate phenomenon affected by anomalies in sea surface temperature in the central‑eastern Pacific and atmospheric pressure difference between Tahiti and Darwin. Such anomalies are called Oceanic Niño Index (ONI) and Southern Oscillation Index (SOI).  In this study, we used these indices to examine the behaviours of El Niño and La Niña in Indonesia  between 1975‑2025 focusing on periodicity and strength, and the impacts of ENSO asymmetry on rainfall patterns. The methods included the Pearson and lagged analyses to quantify correlations between climate variables. Fast Fourier Transform (FFT) and wavelet techniques were also used to determine the recurrent intervals of El Niño and La Niña. The results showed that the indices are well‑corresponded in Niño 3.4 and have a strong correlation of –0.76. It suggests that both are good indicators, correlated with rainfall anomaly at only moderate modes of –0.63 and 0.59 respectively, with 𝑝 ≤ 0.001, confirming statistical significance between the indices and rainfall variations. Strong impacts of El Niño occurred in June‑July‑August (JJA) and September‑October‑November (SON), where rainfall deficits led El Niño by 3 months before its peak in November‑December‑January (NDJ). The FFT analysis and wavelets revealed asymmetric patterns of the ENSO phases, where the recurrent intervals of El Niño and La Niña were respectively found to be 3.7‑5.2 years and 2.7‑3.8 years, classified into the short‑term interannual variations, with El Niño’s peaks attain a significantly larger intensity than those of La Niña. The FFT and wavelets showed secondary oscillation at time‑scales longer than 10 years, indicating the long‑term decadal variations hence the non‑stationary (time‑dependent) nature of ENSO variability. These suggest that strong El Niño tends to be more intense, leading to drier atmospheric conditions while strong La Niña occurs more frequently, indicating possible extreme weather for Indonesia in the future.