Predicting and Understanding the Pacific Decadal Oscillation Using Machine Learning

• Published in: Remote Sensing
• Main Authors: Zhixiong Yao, Dongfeng Xu, Jun Wang, Jian Ren, Zhenlong Yu, Chenghao Yang, Mingquan Xu, Huiqun Wang, Xiaoxiao Tan
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2024
• Subjects: PDO; prediction; machine learning; model explanation; Science; Q; Arctic; Pacific; Oyashio
• Online Access: https://doi.org/10.3390/rs16132261; https://doaj.org/article/5f8004b058ac46f09a6f5879f38b265c

The Pacific Decadal Oscillation (PDO), the dominant pattern of sea surface temperature anomalies in the North Pacific basin, is an important low-frequency climate phenomenon. Leveraging data spanning from 1871 to 2010, we employed machine learning models to predict the PDO based on variations in sev...