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.

Nonlinear forcing singular vector (NFSV)-based assimilation is adopted to determine the model tendency errors that represent the combined effect of different kinds of model errors; then, an NFSV-tendency error forecast model is formulated. This error forecast model is coupled with an intermediate complex model (ICM) and makes the ICM output closer to the observations; finally, an NFSV-ICM forecast model for ENSO is constructed. The competing aspect of the NFSV-ICM is to consider not only model errors but also the interaction between model errors and initial errors because of the mathematical nature of the NFSV-tendency errors. Based on the prediction experiments for tropical SSTAs during either the training period (1960–96; i.e., when the NFSV-ICM is formulated) or the cross-validation period (1997–2016), the NFSV-ICM is determined to have a much higher forecast skill in predicting ENSO that, specifically, extends the skillful predictions of ENSO from a lead time of 6 months in the original ICM to a lead time of 12 months. The higher skill of the NFSV-ICM is especially reflected in the predictions of SSTAs in the central and western Pacific. For the well-known spring predictability barrier (SPB) phenomenon that greatly limits ENSO forecasting skill, the NFSV-ICM also shows great abilities in suppressing its negative effect on ENSO predictions. Although the NFSV-ICM is presently only involved with the NFSV-related assimilation of SSTs, it has shown its usefulness in predicting ENSO. It is clear that the NFSV-based assimilation approach is effective in dealing with the effect of model errors on ENSO forecasts.

The Northern Hemisphere (NH) often experiences frequent cold air outbreaks and heavy snowfalls during La Niña winters. In 2022, a third-year La Niña event has exceeded both the oceanic and atmospheric thresholds since spring and is predicted to reach its mature phase in December 2022. Under such a significant global climate signal, whether the Eurasian Continent will experience a tough cold winter should not be assumed, despite the direct influence of mid- to high-latitude, large-scale atmospheric circulations upon frequent Eurasian cold extremes, whose teleconnection physically operates by favoring Arctic air invasions into Eurasia as a consequence of the reduction of the meridional background temperature gradient in the NH. In the 2022/23 winter, as indicated by the seasonal predictions from various climate models and statistical approaches developed at the Institute of Atmospheric Physics, abnormal warming will very likely cover most parts of Europe under the control of the North Atlantic Oscillation and the anomalous anticyclone near the Ural Mountains, despite the cooling effects of La Niña. At the same time, the possibility of frequent cold conditions in mid-latitude Asia is also recognized for this upcoming winter, in accordance with the tendency for cold air invasions to be triggered by the synergistic effect of a warm Arctic and a cold tropical Pacific on the hemispheric scale. However, how the future climate will evolve in the 2022/23 winter is still subject to some uncertainty, mostly in terms of unpredictable internal atmospheric variability. Consequently, the status of the mid- to high-latitude atmospheric circulation should be timely updated by medium-term numerical weather forecasts and sub-seasonal-to-seasonal prediction for the necessary date information and early warnings.