The Pacific Meridional Mode as an ENSO Precursor and Predictor in the North American Multimodel Ensemble

Although modeling and observational studies have highlighted a robust relationship between the Pacific meridional mode (PMM) and El Niño–Southern Oscillation (ENSO)—namely, that the PMM is often a precursor to El Niño events—it remains unclear if this relationship has any real predictive use. Bridging the gap between theory and practical application is essential, because the potential use of the PMM precursor as a supplemental tool for ENSO prediction has been implied but not yet implemented into a realistic forecast setting. In this study, a suite of sea surface temperature hindcasts is utilized from the North American Multi-model Ensemble (NMME) prediction experiment between 1982 and 2010. The goal is first to assess the NMME's ability to forecast the PMM precursor and second to examine the relationship between PMM and ENSO within a forecast framework. In terms of model performance, results are optimistic in that not only is PMM variability captured well by the multi-model ensemble mean, but it also appears as a precursor to ENSO events in the NMME. In forecast mode, positive PMM events predict eastern Pacific El Niño events in both observations and model forecasts with some skill, yet with less skill for central Pacific El Niño events. Conversely, negative PMM events poorly predict La Niña events in observations, yet the model forecasts fail to capture this observed representation.

This study highlights the common misconception that a reliable precursor may also be assumed a reliable predictor. Therefore, when using a forecast framework, even though a precursor—in this case, PMM—is shown to be reliable using a precursor approach, it is not necessarily also always useful as a predictor in forecast mode. Nevertheless, there proves to be considerable opportunity for improvement of the PMM–ENSO relationship in the NMME forecast models; accordingly, the predictive use of PMM for certain types of ENSO events may also see improvement.