Data_Sheet_2_Emerging Skill in Multi-Year Prediction of the Indian Ocean Dipole.pdf

• Main Authors: F. Feba, Karumuri Ashok, Matthew Collins, Satish R. Shetye
• Format: Dataset
• Language: unknown
• Published: 2021
• Subjects: Climate Science; Climate Change Processes; Climatology (excl. Climate Change Processes); Carbon Sequestration Science; Indian Ocean (Dipole); decadal prediction; CanCM4; MIROC5; Southern Ocean; IOD and Southern Ocean; Antarctic Circumpolar Current (ACC); decadal prediction in tropics; Antarctic; Indian; Antarc*
• Online Access: https://doi.org/10.3389/fclim.2021.736759.s002; https://figshare.com/articles/dataset/Data_Sheet_2_Emerging_Skill_in_Multi-Year_Prediction_of_the_Indian_Ocean_Dipole_pdf/16684951

The Indian Ocean Dipole is a leading phenomenon of climate variability in the tropics, which affects the global climate. However, the best lead prediction skill for the Indian Ocean Dipole, until recently, has been limited to ~6 months before the occurrence of the event. Here, we show that multi-year prediction has made considerable advancement such that, for the first time, two general circulation models have significant prediction skills for the Indian Ocean Dipole for at least 2 years after initialization. This skill is present despite ENSO having a lead prediction skill of only 1 year. Our analysis of observed/reanalyzed ocean datasets shows that the source of this multi-year predictability lies in sub-surface signals that propagate from the Southern Ocean into the Indian Ocean. Prediction skill for a prominent climate driver like the Indian Ocean Dipole has wide-ranging benefits for climate science and society.