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<p>Over most parts of India, about 75–90% of the annual rainfall is received during the Southwest monsoon season (June to September). The year-to-year variability of the Indian Summer Monsoon Rainfall (ISMR), which is primarily influenced by the intensity and phases of the El Niño–Southern Oscillation (ENSO), holds significant importance to these socio-economic sectors of the country. Therefore, monitoring and predicting the state of ENSO are essential for forecasting the performance of the ISMR each year. One of the most widely used SST-based ENSO indices is the Oceanic Niño Index (ONI). Recently, a modified version of ONI, known as Relative ONI or RONI, has been developed. The main objective of this study is to identify which of these two indices is more suitable for monitoring ENSO and for explaining ISMR variability, particularly in view of the warming trends in the global ocean. This study compares the evolution of ENSO using both SST-based indices (ONI &amp; RONI), and the Multivariate ENSO Index (MEI), which represents the anomalies in major atmospheric and oceanic parameters associated with the ENSO event, over the period 1979–2024. Overall, the phases of the ENSO Cycle are broadly consistent among all three indices, with differences typically observed in the timings of their onset and termination. Distinct discrepancies were evident in some years—like the 1994 El Niño and the 2024 La Niña events—where RONI and MEI identify the onset of the events earlier and more consistently than the conventional ONI, which failed to detect these ENSO events. Compared to the conventional ONI, both the MEI and RONI show stronger correlations with ISMR anomalies and large-scale circulation patterns, including changes in Walker circulation anomalies, thereby better capturing ENSO–monsoon teleconnections. Forecasts from the Monsoon Mission Coupled Forecast System (MMCFS) further showed improved predictive skill of ENSO using RONI, especially during the post-spring barrier period (June-December). Given its simplicity and its reliance solely on SST fields, RONI looks like a more reliable and operationally best option for ENSO monitoring and associating with the ISMR variability.</p>

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Revisiting ENSO Variability in Indian Summer Monsoon Rainfall: A Comparison of the Oceanic Niño Index (ONI) and the Relative Oceanic Niño Index (RONI)

  • 期刊论文

  • 发表日期：

    2026年3月7日

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  • C. T. Sabeerali,
  • O. P. Sreejith,
  • P. Rohini,
  • Arti Bandgar,
  • D. S. Pai

摘要

Over most parts of India, about 75–90% of the annual rainfall is received during the Southwest monsoon season (June to September). The year-to-year variability of the Indian Summer Monsoon Rainfall (ISMR), which is primarily influenced by the intensity and phases of the El Niño–Southern Oscillation (ENSO), holds significant importance to these socio-economic sectors of the country. Therefore, monitoring and predicting the state of ENSO are essential for forecasting the performance of the ISMR each year. One of the most widely used SST-based ENSO indices is the Oceanic Niño Index (ONI). Recently, a modified version of ONI, known as Relative ONI or RONI, has been developed. The main objective of this study is to identify which of these two indices is more suitable for monitoring ENSO and for explaining ISMR variability, particularly in view of the warming trends in the global ocean. This study compares the evolution of ENSO using both SST-based indices (ONI & RONI), and the Multivariate ENSO Index (MEI), which represents the anomalies in major atmospheric and oceanic parameters associated with the ENSO event, over the period 1979–2024. Overall, the phases of the ENSO Cycle are broadly consistent among all three indices, with differences typically observed in the timings of their onset and termination. Distinct discrepancies were evident in some years—like the 1994 El Niño and the 2024 La Niña events—where RONI and MEI identify the onset of the events earlier and more consistently than the conventional ONI, which failed to detect these ENSO events. Compared to the conventional ONI, both the MEI and RONI show stronger correlations with ISMR anomalies and large-scale circulation patterns, including changes in Walker circulation anomalies, thereby better capturing ENSO–monsoon teleconnections. Forecasts from the Monsoon Mission Coupled Forecast System (MMCFS) further showed improved predictive skill of ENSO using RONI, especially during the post-spring barrier period (June-December). Given its simplicity and its reliance solely on SST fields, RONI looks like a more reliable and operationally best option for ENSO monitoring and associating with the ISMR variability.