FY 2020

El Niño Southern Oscillation evolution modulated by Atlantic forcing

Chikamoto, Y., Z.F. Johnson, S.-Y. Wang, M.J. McPhaden, and T. Mochizuki

J. Geophys. Res., 125(8), e2020JC016318, doi: 10.1029/2020JC016318, View online (2020)

Abstract. The El Niño–Southern Oscillation (ENSO) exerts a strong influence on tropical Atlantic variability, but it is also affected by Atlantic forcing. Previous research has proposed three Atlantic precursors for ENSO: the North tropical Atlantic, the equatorial Atlantic, and the entire tropical Atlantic. However, the relative importance of these Atlantic precursors for ENSO remains unclear. Here, we present evidence from a set of multimodel partial ocean assimilation experiments that equatorial Atlantic cooling is the main contributor for weakening equatorial zonal winds in the Indo‐Pacific sector and subsequent ocean warming in the tropical Pacific. Opposite tendencies occur for a warmer equatorial Atlantic. The equatorial Atlantic affects the interbasin climate seesaw between the Atlantic and Pacific through an atmospheric zonal Wavenumber 1 pattern. However, model mean state biases and systematic errors prevent a precise assessment of the response times for the equatorial Pacific trade winds to Atlantic forcing.

Plain Language Summary. El Niño—an unusual surface warming of the tropical Pacific—may be more predictable than previously thought if the prediction of Atlantic climate, and its remote impact on the Indo‐Pacific region can be improved. In this study, we found that sea surface cooling in the equatorial Atlantic weakens western Pacific trade winds and triggers subsequent tropical Pacific warming through a positive feedback of atmosphere‐ocean interactions. This process increases the chance of an El Niño event 7 months later. By assimilating observed ocean data in this simulation, we found that El Niño predictive skill relies not only on the tropical Pacific climate state but also on the Atlantic mean state and its remote impact on the tropical Pacific. Our result suggests that improving model performance in the Atlantic ocean and its remote impacts are crucial for enhancing El Niño predictions.