Improving forecasts of El Niño diversity: a nonlinear forcing singular vector approach

Observations indicate that two types of El Nino events exist: one is the EP-El Nino with a warming center in the eastern tropical Pacific, and the other is the CP-El Nino with large positive SST anomalies in the central tropical Pacific. Most current numerical models are not able to accurately identify the different types of El Nino. The present study examines the dynamic properties of the ENSO forecast system NFSV-ICM which combines an intermediate-complexity ENSO model (ICM) with a nonlinear forcing singular vector (NFSV)-based tendency perturbation forecast model. This system is able to distinguish the different types of El Nino in predictions. Hindcasts show that the NFSV-ICM system is able to capture the horizontal distribution of the SST anomalies and their amplitudes in the mature phase of not only EP-El Nino events but also CP-El Nino events. The NFSV-ICM is also able to describe the evolution of SST anomalies associated with the two types of El Nino up to at least two-season lead times, while the corresponding forecasts with the ICM are limited to, at most, one-season lead times. These improvements are associated with the modifications of the atmospheric and ocean processes described by the ICM through the NFSV-based tendency perturbations. In particular, the thermocline and zonal advection feedback are strongly modified, and the conditions of the emergence of both EP- and CP-El Nino events are improved. The NFSV-ICM therefore provides a useful platform for studying ENSO dynamics and predictability associated with El Nino diversities.