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

The El Niño Southern Oscillation (ENSO) is an tropical Pacific phenomenon influenced by climate anomalies in other regions of the world. We compare the relative impacts of regions external to the tropical Pacific on ENSO with a new unifying multi-model framework. This framework adapts analogue forecasting to identify the improvement in ENSO forecast skill when including information from regions outside the equatorial Pacific. We use this methodology to investigate the relative influence on ENSO of each of the tropical Atlantic, tropical Indian, and north and south tropical Pacific Oceans, as 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 6-18 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.