Quantifying the role of tropical Indian Ocean observations to central Pacific El Niño prediction

Abstract Over the past two decades, forecasting the El Niño–Southern Oscillation has become increasingly challenging, primarily due to the inherent difficulty in predicting Central Pacific (CP) El Niño events. In this study, we present a detailed analysis by explicitly quantifying the role of the tropical Indian Ocean (IO) on the initial uncertainty of CP-El Niño predictions. We identify optimal observation sites within the tropical IO that significantly reduce this uncertainty and validate their efficacy through observing system simulation experiments within a fully coupled climate prediction system. Our results demonstrate a remarkable achievement in the root mean squared errors of the prediction initial conditions using Community Earth System Model. This study not only enriches our understanding of the interplay between the tropical IO and CP-El Niño but also offers a concrete strategy for enhancing CP-El Niño forecasts, advancing seasonal prediction capabilities, and bolstering global resilience against the escalating frequency of CP-El Niño events.

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Publication Details

Journal
Environmental Research Letters
Published
2025-05-22
DOI
https://doi.org/10.1088/1748-9326/addbf3
Citations
1
Primary Topic
Geophysics and Gravity Measurements
Type
article
Field-Weighted Citation Impact
1.79

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article

Quantifying the role of tropical Indian Ocean observations to central Pacific El Niño prediction

Yi Li, Dake Chen, Michael J. McPhaden, Tao Lian et al.
1 citations
Environmental Research Letters
Geophysics and Gravity Measurements
1.79
article

Quantifying the role of tropical Indian Ocean observations to central Pacific El Niño prediction

Yi Li, Dake Chen, Michael J. McPhaden, Tao Lian, Xunshu Song, Youmin Tang, Xiaojing Li, Lei Zhou
article en
1 citations

Abstract

Abstract Over the past two decades, forecasting the El Niño–Southern Oscillation has become increasingly challenging, primarily due to the inherent difficulty in predicting Central Pacific (CP) El Niño events. In this study, we present a detailed analysis by explicitly quantifying the role of the tropical Indian Ocean (IO) on the initial uncertainty of CP-El Niño predictions. We identify optimal observation sites within the tropical IO that significantly reduce this uncertainty and validate their efficacy through observing system simulation experiments within a fully coupled climate prediction system. Our results demonstrate a remarkable achievement in the root mean squared errors of the prediction initial conditions using Community Earth System Model. This study not only enriches our understanding of the interplay between the tropical IO and CP-El Niño but also offers a concrete strategy for enhancing CP-El Niño forecasts, advancing seasonal prediction capabilities, and bolstering global resilience against the escalating frequency of CP-El Niño events.

Environmental Research LettersVol. 20(7)
University of Northern British Columbia (CA), Hohai University (CN), Shanghai Jiao Tong University (CN), Ministry of Natural Resources (CN), NOAA Pacific Marine Environmental Laboratory (US), Second Institute of Oceanography (CN)
National Natural Science Foundation of China, NOAA Pacific Marine Environmental Laboratory
Openalex Percentile: Top 17%
Geophysics and Gravity Measurements
1.79
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