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<p>The El Niño Southern Oscillation (ENSO) is a tropical Pacific phenomenon influenced by climate anomalies in other regions of the world. We compare the impacts on ENSO from regions external to the tropical Pacific with a new unifying multi-model framework. This framework adapts analogue forecasting to identify the improvement in perfect-model ENSO forecast skill when including information from regions outside the equatorial Pacific. We use this methodology to investigate the relative influence on ENSO from each of the tropical Atlantic, tropical Indian, and north and south tropical Pacific Oceans, and the differences in how these influences are simulated by 12 state-of-the-art coupled climate models. In most models, ENSO forecast skill is improved by information from ocean regions external to the equatorial Pacific, implying that these regions contain independent variability that impacts ENSO evolution. Overall, the largest skill increases come from information in the Atlantic Ocean, followed by the Indian, south Pacific, then north Pacific Oceans. The influence on ENSO of these four ocean regions peaks between 6 and 18 months lead time. However, the magnitude of skill increase depends on the specific model, lead time and forecast initialisation month. We find almost no skill increase from information in any region poleward of 30°. Finally, we note that the GFDL-CM2.1 model used for many pacemaker studies exhibits the weakest remote influences on ENSO of any model we consider. Our results, and this method which may be applied to other models, lay the groundwork for contextualising and comparing studies of remote influences on ENSO in individual climate models.</p>

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Adapting analogue forecasting to compare ENSO remote influences across different models and regions

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月8日

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  • Jemma Jeffree,
  • Nicola Maher,
  • Dillon J. Amaya,
  • Dietmar Dommenget

摘要

The El Niño Southern Oscillation (ENSO) is a tropical Pacific phenomenon influenced by climate anomalies in other regions of the world. We compare the impacts on ENSO from regions external to the tropical Pacific with a new unifying multi-model framework. This framework adapts analogue forecasting to identify the improvement in perfect-model ENSO forecast skill when including information from regions outside the equatorial Pacific. We use this methodology to investigate the relative influence on ENSO from each of the tropical Atlantic, tropical Indian, and north and south tropical Pacific Oceans, and the differences in how these influences are simulated by 12 state-of-the-art coupled climate models. In most models, ENSO forecast skill is improved by information from ocean regions external to the equatorial Pacific, implying that these regions contain independent variability that impacts ENSO evolution. Overall, the largest skill increases come from information in the Atlantic Ocean, followed by the Indian, south Pacific, then north Pacific Oceans. The influence on ENSO of these four ocean regions peaks between 6 and 18 months lead time. However, the magnitude of skill increase depends on the specific model, lead time and forecast initialisation month. We find almost no skill increase from information in any region poleward of 30°. Finally, we note that the GFDL-CM2.1 model used for many pacemaker studies exhibits the weakest remote influences on ENSO of any model we consider. Our results, and this method which may be applied to other models, lay the groundwork for contextualising and comparing studies of remote influences on ENSO in individual climate models.