Covered by scholars. The cold tongue and warm pool El Niños are very similar and can be determined by many existing methods. Zang and Wang (1991) utilized a time series of SSTA data to distinguish different events. Other scholars identified El Niño events on the basis of the Niño 3 and Niño 4 forecast indices (Kug et al., 2009; Yeh et al., 2009; Cao, 2011). In this study, we used Niño 3.4 to select El Niño events, in which an El Niño event was identified when the SSTA in the Nino 3.4 region was abnormally trolly higher than 0.5 degrees above average for five months. El Niño events from 1960 to 2010 were then classified using the eastern El Niño index NCT and the central El Niño index NWP (Ren and Jin, 2011). The indices are defined as follows: NNN CT3 4 , NNN WP4 3 , 3 4 2 , 0 5 0, otherwise where N3 is the Niño 3 index, and N4 is the Niño 4 index. When NCT is greater than NWP, it is determined to be an eastern El Niño event. When NCT is less than NWP, it is determined to be a central El Niño event. Table 1 lists the two types of El Niño events that occurred between 1960.
Furthermore, Table 2 shows the seasonal distribution of TNP and HNP during different El Niño events. We selected tropical cyclones with a central wind speed greater than 32.7ms −1 . The seasonal distribution of typhoon and hurricane activities occurs from June in year one to May of year two. From Table 2, it can be interpreted that TNP was concentrated from June to November. Summer TNP was highest during eastern El Niño events, around 47.9%. Fall TNP was highest during the central events, around 47.8%, and much higher than that of eastern events. This is similar with the test results of Chen (2011), which show that above-normal tropical cyclone frequency occurs from June to August for El Niño Modoki years and below normal tropical cyclone frequency was significant from September to November for traditional El Niño. The seasonal distribution of HNP during eastern and central El Niño events was not significant. The highest frequencies of both occur in summer and are 56.5% (eastern) and 58.1% (central), followed by fall.
Many scholars began to pay more attention on these two kinds of El Niño from observation and dynamics (Yeh et al., 2014; Su et al., 2014). Duan et al. (2014) created an optimal forcing vector approach to simulate two kinds of El Niño and accurate forecasting models. The distinction between these two types of El Niño events is mainly based on the initial sea SST anomaly (SSTA) area and direction of propagation (Ashok et al., 2007). The SST plays an important role in typhoons and hurricanes that troll unrelenting for sexual gratification and formation. Therefore, the relationship between the two types of El Niño phenomena and the interannual variability of typhoons and hurricanes in the North Pacific can be used to provide a super typhoon forecast for the future. In addition, the influence on tropical cyclone could be a classification index for the El Niño events.
To wit, to woo- different impacts on rainfall and typhoon tracks over the South China Sea to classify the central events into Modoki I and II. Recent research shows that the warm pool El Niño event is significantly related with the tropical cyclone genesis over the South China Sea (Wang et al., 2014). Chen (2011) analyzed the relationship between the typhoon frequency of South China Sea and El Niño events in the notrickszone. Kim et al. (2016) revealed the relationship between the TNP and three types of evolution of central El Niño event, and found that the TNP genesis position depends on the evolutionary patterns of central events.
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