The spring predictability barrier severely limits our ability to forecast the El Niño-Southern Oscillation (ENSO) from and across the boreal spring. Our observational analysis shows that the spring predictability barrier (SPB) can be largely reduced when information from both the ocean and atmosphere are effectively taken into account during the boreal spring. The correlation coefficient between the predicted and observed sea surface temperature anomalies over the equatorial central–eastern Pacific determined by a simple quaternary linear regression model is >0.81 for the period 1980–2016. The frame structure of the ENSO evolution is mostly controlled by variations in the oceanic heat content along the equatorial Pacific and the zonal wind stress over the tropical western Pacific during the boreal spring. These results indicate that to predict ENSO events with a long lead time, i.e., largely reducing the SPB, variations in both the ocean and atmosphere during the boreal spring should be well predicted first. While the oceanic information is mainly located in the equatorial Pacific and well characterized by the delayed oscillator and recharging oscillator models, variations in the atmosphere may contain information beyond this area and are more difficult to deal with.
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