[M-TT45] Artificial Intelligence in Earth and Environmental sciences

[MTT45-P07] Seasonal prediction of equatorial Atlantic variability using a hierarchy of data-driven models

*Ingo Richter¹, Shoichiro Kido¹, Kalpesh Ravindra Patil¹, Justin Lien², Yong-Yub Kim³ (1. JAMSTEC Japan Agency for Marine-Earth Science and Technology, 2. Tohoku University, Sendai, Japan, 3. University of Bergen, Bergen, Norway)

Keywords:equatorial Atlantic, Atlantic Zonal Mode, seasonal prediction, linear inverse models, deep learning