Perturbations in the thermocline and surface zonal current (ZC) play crucial roles in the evolutions of the eastern Pacific (EP) and central Pacific (CP) El Niño events, respectively. Whereas numerous studies have examined the influence of initial uncertainties in ocean temperature on the predictability of El Niño, only a few studies investigated the impact of the initial ZC. Using an air-sea coupling model, the conditional nonlinear optimal perturbation (CNOP) approach was employed to investigate the maximum impact of initial ZC errors on the El Niño prediction. The optimal initial ZC errors (denoted as CNOP-Us) that have the severest impact on the El Niño prediction are found to mainly concentrate in the western and central tropical Pacific. The CNOP-Us cause larger errors in the CP El Niño prediction than in the EP El Niño prediction. Additionally, CNOP-Us cause rapid sea surface temperature error growth in spring in the EP El Niño prediction but in summer in the CP El Niño prediction. Dynamically, the former is related to the large uncertainties in the meridional current in spring caused by CNOP-Us, while the latter is related to the strong ZC errors in summer. According to the distributions of CNOP-Us, reducing the initial ZC errors in the western and central tropical Pacific may be vital in weakening the predictability barrier phenomena and improving the predictions of El Niño diversity.
 

El Nino diversity,CNOP