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El Nino is probably the most influential climate phenomenon on interannualtime scales. It affects the global climate system and is associated withnatural disasters and serious consequences in many aspects of human life.However, the forecasting of the onset and in particular the magnitude of ElNino are still not accurate, at least more than half a year in advance. Here,we introduce a new forecasting index based on network links representing thesimilarity of low frequency temporal temperature anomaly variations betweendifferent sites in the El Nino 3.4 region. We find that significant upwardtrends and peaks in this index forecast with high accuracy both the onset andmagnitude of El Nino approximately 1 year ahead. The forecasting procedure wedeveloped improves in particular the prediction of the magnitude of El Nino andis validated based on several, up to more than a century long, datasets.

Forecasting the magnitude and onset of El Nino based on climate network