On the Second-Year Warming in Late 2019 over the Tropical Pacific and Its Attribution to an Indian Ocean Dipole Event

After its maturity, El Nino usually decays rapidly in the following summer and evolves into a La Nina pattern. However, this was not the case for the 2018/19 El Nino event. Based on multiple reanalysis data sets, the space-time evolution and triggering mechanism for the unusual second-year warming in late 2019, after the 2018/19 El Nino event, are investigated in the tropical Pacific. After a short decaying period associated with the 2018/19 El Nino condition, positive sea surface temperature anomalies (SSTAs) re-intensified in the eastern equatorial Pacific in late 2019. Compared with the composite pattern of El Nino in the following year, two key differences are evident in the evolution of SSTAs in 2019. First, is the persistence of the surface warming over the central equatorial Pacific in May, and second, is the re-intensification of the positive SSTAs over the eastern equatorial Pacific in September. Observational results suggest that the re-intensification of anomalous westerly winds over the western and central Pacific, induced remotely by an extreme Indian Ocean Dipole (IOD) event, acted as a triggering mechanism for the second-year warming in late 2019. That is, the IOD-related cold SSTAs in the eastern Indian Ocean established and sustained anomalous surface westerly winds over the western equatorial Pacific, which induced downwelling Kelvin waves propagating eastward along the equator. At the same time, the subsurface ocean provided plenty of warm water in the western and central equatorial Pacific. Mixed-layer heat budget analyses further confirm that positive zonal advection, induced by the anomalous westerly winds, and thermocline feedback played important roles in leading to the second-year warming in late 2019. This study provides new insights into the processes responsible for the diversity of El Nino evolution, which is important for improving the physical understanding and seasonal prediction of El Nino events.