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.

观测结果表明，存在两种类型的厄尔尼诺事件：一种是东部热带太平洋中心升温的EP-ElNiño事件，另一种是热带中部太平洋太平洋CP-ElNiño事件具有较大的正SST异常。当前大多数数值模型都无法准确识别厄尔尼诺现象的不同类型。本研究研究了ENSO预测系统NFSV-ICM的动态特性，该系统将中等复杂度ENSO模型（ICM）与基于非线性强迫奇异矢量（NFSV）的趋势扰动预测模型相结合。该系统能够在预测中区分不同类型的厄尔尼诺现象。Hindcasts显示，NFSV-ICM系统不仅可以捕获EP-ElNiño事件的成熟阶段，还可以捕获CP-ElNiño事件的成熟阶段的SST异常的水平分布及其振幅。NFSV-ICM还能够描述与两种类型的厄尔尼诺现象相关的SST异常的演变，至少需要两个季节的提前期，而ICM的相应预报最多只能是一个季节的提前期。次。这些改进与ICM通过基于NFSV的趋势扰动对大气和海洋过程的修改有关。特别是，强烈修改了温跃层和纬向平流反馈，并改善了EP-和CP-ElNiño事件的出现条件。