The purpose of the paper is to take advantage of recent work on the study of resonantly forced baroclinic waves in the tropical Pacific to significantly reduce systematic and random forecasting errors resulting from the current statistical models intended to predict El Niño. Their major drawback is that sea surface temperature (SST), which is widely used, is very difficult to decipher because of the extreme complexity of exchanges at the ocean-atmosphere interface. In contrast, El Niño-Southern Oscillation (ENSO) forecasting can be performed between 7 and 8 months in advance precisely and very simply from (1) the subsurface water temperature at particular locations and (2) the time lag of the events (their expected date of occurrence compared to a regular 4-year cycle). Discrimination of precursor signals from objective criteria prevents the anticipation of wrong events, as occurred in 2012 and 2014. The amplitude of the events, their date of appearance, as well as their potential impact on the involved regions are estimated. Three types of ENSO events characterize their climate impact according to whether they are (1) unlagged or weakly lagged, (2) strongly lagged, or (3) out of phase with the annual quasi-stationary wave (QSW) (Central Pacific El Niño events). This substantial progress is based on the analysis of baroclinic QSWs in the tropical basin and the resulting genesis of ENSO events. As for cold events, the amplification of La Niña can be seen a few months before the maturation phase of an El Niño event, as occurred in 1998 and 2016.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited