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

## TL;DR

This paper introduces a novel climate network-based index that significantly improves the accuracy of forecasting El Nino's onset and magnitude approximately one year in advance, validated across extensive historical datasets.

## Contribution

The study presents a new network-based forecasting index that enhances prediction accuracy for El Nino's onset and magnitude compared to previous methods.

## Key findings

- High-accuracy forecasts of El Nino onset and magnitude up to one year ahead.
- The new index outperforms traditional methods in predicting El Nino strength.
- Validation across datasets spanning over a century confirms robustness.

## Abstract

El Nino is probably the most influential climate phenomenon on interannual time scales. It affects the global climate system and is associated with natural disasters and serious consequences in many aspects of human life. However, the forecasting of the onset and in particular the magnitude of El Nino 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 the similarity of low frequency temporal temperature anomaly variations between different sites in the El Nino 3.4 region. We find that significant upward trends and peaks in this index forecast with high accuracy both the onset and magnitude of El Nino approximately 1 year ahead. The forecasting procedure we developed improves in particular the prediction of the magnitude of El Nino and is validated based on several, up to more than a century long, datasets.