Is El Niño only due to the noise or it is a self-sustained phenomenon?

On average every 4 years, the sea-surface temperature in the Eastern Equatorial Pacific is a few degrees higher than normal. This phenomenon, which reaches its maximum usually around Christmas is known as El Niño. This event has a strong influence on the climate all around the globe through well-known tele-connections. The occurrence of El Niño is related to extreme weather events, that affect people and properties. For these reasons is important to better understand the behavior of this climatic phenomenon. The property of EL Niño we have focused on during our project is related to the following research question: Is El Niño only due to external noise, or it is a self-sustained phenomenon, which amplitude is amplified by the noise?

To answer to this question, we have applied a Machine Learning tool called Reservoir Computer. After the training procedure, through feedback connections, the Reservoir model can be transformed into an autonomous evolving system. Our results show that the autonomous evolving Reservoir can delete the noise from the training data. The signal produced in output by the autonomous evolving Reservoir reflects the patterns of the training data, without noise. This method can therefore be used to understand if the EL Niño oscillations is only due to random noise, that excites a steady state, or it is a periodic phenomenon, which amplitude is randomly increased by external noise. To understand its limitations, our approach has been first applied to data produced by different models, that simulate EL Niño (Jin Timmerman, Zebiak Cane and CESM). After these first experiments, performed in a controlled scenario, our method has been applied to real data, to see what the self-evolving Reservoir model can tell us about the real EL Niño phenomenon.