Abstract
Observations indicate that two types of El Niño events exist: one is the EP-El Niño with a warming center in the eastern tropical Pacific, and the other is the CP-El Niño 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 Niño. 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 Niño 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 Niño events but also CP-El Niño events. The NFSV-ICM is also able to describe the evolution of SST anomalies associated with the two types of El Niño 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 Niño events are improved. The NFSV-ICM therefore provides a useful platform for studying ENSO dynamics and predictability associated with El Niño diversities.
Highlights
The prediction and its predictability of ENSO have been studied for decades since the first coupled ENSO model was developed (Zebiak and Cane 1987)
Tao and Duan (2019) used the nonlinear forcing singular vector (NFSV)-assimilation approach to correct the intermediate-complexity ENSO model (ICM) ENSO model and reformulated an NFSVICM ENSO forecast system. They showed that the NFSVICM possesses much higher forecast skill of Niño3.4 index associated with ENSO events than the ICM
The present study further explores the ability of the NFSV-ICM to identify different El Niño types in predictions and identifies the origin of these improvements as well as the role of the NFSV-based tendency perturbations
Summary
The prediction and its predictability of ENSO have been studied for decades since the first coupled ENSO model was developed (Zebiak and Cane 1987). Duan et al (2014) contributed model errors with various sources to the model tendency and proposed the idea of using nonlinear forcing singular vector (NFSV) approach (Duan and Zhou 2013) as a tool to incorporate the impact of model errors on the tendency perturbation of the SST equation With such NFSVbased tendency perturbations, they successfully reproduced the El Niño diversities using the Zebiak-Cane model (Zebiak and Cane 1987) as well as the relevant air-sea states. Despite the fact that Tao and Duan (2019) already realized this point, they did not explore in detail to what extent the NFSV-ICM can predict/identify the types of El Niño They did not investigate how the NFSV-ICM improves the prediction skill on different ENSO types in terms of their dynamics and physics. Improving forecasts of El Niño diversity: a nonlinear forcing singular vector approach
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