Therefore, it is valuable to predict ENSO early and accurately to minimize these effects. However, predicting the strength of ENSO remains a challenge due to its complexity (Sun et al., 2016;Timmermann et al., 2018). Also, the increasing diversity of ENSO behavior since 2000 has led to a growing interest in the type of ENSO events (Geng et al., 2020). ENSO can be mainly divided into Eastern Pacific (EP) and Central Pacific (CP) types (Yeh et al., 2009), based on the distribution of the Sea Surface Temperature Anomaly (SSTA) during its maturation phase. However, some events that the SSTA is relatively high over the central and eastern Pacific Ocean cannot be classified as CP or EP types. Zhang et al. ( 2019) classified ENSO into EP, CP, and a mixture of the two (MIX) types of EI Niño (La Niña). To the best of our knowledge, the definition of ENSO type has not come to an agreement. Because the effects of different ENSO types vary greatly, for example, different EI Niño events have a different impact on US winter temperatures (Yu et al., 2012) and the East Asian climate (Yuan & Yang, 2012). Hence, the prediction of ENSO type is important for improving the quality of climate forecasts.

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