Scientists believe that El Niño events in the central Pacific can have far-reaching impacts on the global climate, making accurate predictions crucial for preparedness and risk reduction.
Chinese researchers have developed an artificial intelligence (AI) model powered by deep learning algorithms to predict the development and pattern of central Pacific El Niño events.
Based on convolutional neural network technology, researchers from the Institute of Atmospheric Physics (IAP) under the Chinese Academy of Sciences (CAS) developed a deep learning model for predicting the spatial pattern of sea surface temperature anomalies in the equatorial Pacific.
“This study demonstrates the potential of AI in improving predictions of significant climate events like El Niño that can have devastating effects around the globe,” said Huang Ping, a researcher at IAP and the corresponding author of the study recently published in the journal Advances in Atmospheric Sciences.
According to the study, the AI model surpasses traditional dynamical models in accuracy, particularly in predicting sea surface temperature anomalies in the west-central equatorial Pacific.
The study also suggests that a hybrid model that combines predictions from both the AI model and dynamical models achieves even higher accuracy for central and east Pacific El Niño events.
The research team plans to further leverage the power of deep learning to expand the application of AI models in seasonal climate forecasting to provide earlier and more accurate warnings of major weather events.
(With input from Xinhua)
