South Tropical Atlantic and South Atlantic Convergence Zone Actively Shape ENSO Diversity: Physical Pathways, Subsurface Modulation, and Long-Lead Prediction

Forecasting El Niño–Southern Oscillation (ENSO) diversity remains a central challenge, with skill deteriorating rapidly beyond 6-9 months and the spring predictability barrier limiting operational utility. The South American Monsoon System (SAMS) is typically viewed as a passive responder to Pacific variability, with its potential upstream influence on ENSO remaining largely unexplored.

In this work, we reposition the SAMS as an active agent in pantropical interactions through two complementary contributions. First, we apply causal discovery methods to identify a previously unrecognized atmospheric bridge linking the variability of the South Tropical Atlantic (STA) and convection in the South Atlantic Convergence Zone (SACZ) to ENSO diversity. STA sea surface temperature emerges as the longest-lead precursor of boreal winter ENSO patterns, operating at a six-season lead, while SACZ convection provides a complementary three-season pathway. Despite their distinct origins, both pathways act through a common set of physical mechanisms: subtropical Gill-type responses and extratropical quasi-stationary Rossby wave trains that weaken the South Pacific Subtropical High, precondition the southeastern tropical Pacific, and modulate the Walker circulation, initiating coupled feedbacks. Incorporating these predictors improves ENSO diversity correlation skill by approximately 0.15 over canonical indices. Second, we demonstrate that the Pacific's subsurface configuration acts as a gatekeeper for this trans-basin teleconnection. When ocean heat content is elevated, the oscillator signal weak, and the equatorial Pacific warm, STA-SACZ predictors add incremental value; conversely, when the thermocline slope is steep, the equatorial Pacific cold, or the target metric is La Niña duration, Pacific-internal dynamics dominate ENSO evolution.

These findings advance mechanistic understanding of cross-basin interactions and provide practical guidance for improving operational forecasts of ENSO and its diversity.