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Climate Dynamics

, Volume 43, Issue 1–2, pp 469–481 | Cite as

Influence of two types of El Niños on the East Asian climate during boreal summer: a numerical study

  • Zesheng Chen
  • Zhiping Wen
  • Renguang Wu
  • Ping Zhao
  • Jie Cao
Article

Abstract

The sea surface temperature anomaly pattern differs between the central Pacific (CP) and eastern Pacific (EP) El Niños during boreal summer. It is expected that the respective atmospheric response will be different. In order to identify differences in the responses to these two phenomena, we examine the Community Atmosphere Model Version 4 simulations forced with observed monthly sea surface temperature during 1979–2010 and compare with the corresponding observations. For CP El Niño, a triple precipitation anomaly pattern appears over East Asia. During EP El Niño, the triple pattern is not as significant as and shifts eastward and southward compared to CP El Niño. We also examine the influence of CP La Niña and EP La Niña on East Asia. In general, the impact of CP (EP) La Niña on tropics and East Asia seems to be opposite to that of CP (EP) El Niño. However, the impacts between the two types of La Niña are less independent compared to the two types of warm events. Both types of El Niño (La Niña) correspond to a stronger (weaker) western North Pacific summer monsoon. The sensitivity experiments support this result. But the CP El Niño (La Niña) may have more significant influence on East Asia summer climate than EP El Niño (La Niña), as the associated low-level anomalous wind pattern is more distinct and closer to the Asian continent compared to EP El Niño (La Niña).

Keywords

CP El Niño CP La Niña CAM4 AMIP 

1 Introduction

El Niño-Southern Oscillation (ENSO) is one of the largest sources of interannual variability in the tropical troposphere. Usually, ENSO events can be classified according to their onset time, propagation characteristics and zonal sea surface temperature (SST) distribution (e.g. Fu et al. 1986; Enfield and Luis 1991; Wang 1995; Horii and Hanawa 2004; Larkin and Harrison 2005; Wang and Fiedler 2006; Kao and Yu 2009). The positive phase of ENSO corresponds to El Niño. According to zonal SST distribution, the typical El Niño is associated with maximum warm SST anomaly in the eastern Pacific and cold SST anomaly in the western Pacific (e.g. Rasmusson and Carpenter 1982). In recent studies, a different type of El Niño featuring maximum warm SST anomaly in the central Pacific has been identified. It is alternatively named dateline El Niño (Larkin and Harrison 2005), El Niño Modoki (Ashok et al. 2007; Weng et al. 2007), central Pacific El Niño (Yu and Kao, 2007; Kao and Yu, 2009; Yeh et al. 2009) and warm pool El Niño (Kug et al. 2009). In this study, these two types of El Niño events are denoted as central Pacific El Niño (CP El Niño) and eastern Pacific El Niño (EP El Niño), respectively.

Kao and Yu (2009) indicated that the CP El Niño has most of its surface wind, SST, and subsurface anomalies confined in the central Pacific and tends to originate, develop and disappear in the tropical central Pacific in situ and is not necessarily followed by the negative phase. Kug et al. (2009) demonstrated that zonal advective feedback plays a crucial role during CP El Niño, while thermocline feedback is a key process during EP El Niño. And it is reported that CP El Niño is associated with two cells of anomalous Walker circulation with ascent over the equatorial central Pacific, instead of a single cell associated with EP El Niño. For CP El Niño, the teleconnections, such as the positive phase of Pacific-Japan (PJ) pattern and the Pacific North American (PNA) pattern, are different from those during EP El Niño (e.g. Ashok et al. 2007; Weng et al. 2007). Thus, the two types of El Niños may exert different influences on regional climate. Feng and Li (2011) reported that CP El Niño events are accompanied by a significant reduction in spring rainfall over southern China, while there is enhanced spring rainfall associated with EP El Niño. It is shown that the Yangtze River Valley suffers more rain and lower temperature during the boreal summer of CP El Niño, but it suffers the opposite situation during the EP El Niño scenario (Weng et al. 2007, 2011). Yuan and Yang’s study (2012) pointed out the impact of CP El Niño on East Asian climate is more significant than that of EP El Niño during the developing summer, and, however, EP El Niño exerts a stronger influence on East Asia during the decaying summer. Besides, some studies report that there are different impacts of two types of El Niños on northwestern Pacific tropical cyclones activities (Chen and Tam 2010; Wang et al. 2012).

Most of the aforementioned studies rely on linear statistical methods, such as partial correlation and regression. It is reported that CP El Niño is rarely observed before the 1980s, and its frequency increases in the past three decades (Ashok et al. 2007; Yeh et al. 2009; Lee and McPhaden 2010). Some studies attribute the recent increase in CP El Niño frequency to anthropogenic and natural climate variability (Ashok et al. 2007; Yeh et al. 2009). Besides, Yeh et al. (2009) concluded that the ratio of occurrence of the CP El Niños to the EP El Niños increases in the global-warming scenario as compared to the corresponding twentieth-century climate simulation by analyzing the Couple Model Intercomparison Project phase three multi-model dataset (Meehl et al. 2007). However, the number of CP El Niños observed during boreal summer is still small. As will be mentioned later, only 3 years can be identified as CP El Niños during boreal summer in our study period. As such, the robustness of the obtained results is an issue that needs to be addressed. The present study performs numerical experiments to identify the impact of two types of El Niños on East Asia climate during boreal summer.

Few studies have been done on the impacts of negative phase of ENSO Modoki (La Nina Modoki) during boreal summer. Kao and Yu (2009) argued that the warm and cold phases of CP-ENSO tend to have similar physical characteristic and similar patterns. And it is expected that the influence of La Nina Modoki, characterized by anomalous cooling in the central Pacific and flanked by anomalous warming in the eastern and western Pacific (Ashok and Yamagata 2009), may be opposite to that of El Niño Modoki (Diaz et al. 2001). Feng and Li (2011) indicated that there is a strong asymmetry in the relationship between South China rainfall, typical ENSO and ENSO Modoki events during boreal spring. Although South China spring rainfall is influenced by typical ENSO and ENSO Modoki events, their relationships are only statistically significant during the positive events. Kug and Ham (2011) explored the existence of two types of La Niña events. They found that the SST and precipitation patterns between the two types of La Niña are much less distinctive or less independent compared to the two types of warm events and there is a strong asymmetric character between warm and cold events. Thus, is there an asymmetric influence on East Asian between warm and cold events during summertime?

The purpose of this work is to extend the analysis of Weng et al. (2007) using numerical modeling results. In our study, we will define the two types of El Niños during boreal summer (see Sect. 2). We will make use of 6 ensemble simulations of the Community Atmosphere Model version 4 (CAM4, Neale et al. 2013), run with monthly observed SST (Hurrell et al. 2008) during 1979–2010. Besides, we have designed some experiments to further explore the simultaneous influence of equatorial Pacific SST anomaly pattern on East Asia climate during boreal summer. In addition, the impacts of negative phase of ENSO (CP and EP La Niña) will also be investigated.

The remainder of this manuscript is organized as follows: Sect. 2 presents the data sets and methods used in this study, and Sect. 3 shows the anomalies of two types of ENSO. Section 4 examines the asymmetry influences of CP ENSO. Finally, discussions and concluding remarks are provided in Sect. 5.

2 Data and methods

2.1 Observational data

Multiple datasets are used in this study for the period from January 1979 to December 2010. These include monthly SST from the Hadley Centre of the U.K. Met Office (HadISST, Rayner et al. 2003), monthly atmospheric field from the ECMWF reanalysis data (ERA-Interim, Dee et al. 2011), and precipitation from the Global Precipitation Climatology Project (GPCP, Adler et al. 2003). Some previous studies have explored the Pacific Decadal Oscillation (PDO, Mantua et al. 1997; Zhang et al. 1997, 1998) related SST anomalies (e.g. Zhu and Yang 2003a, b) and their impact on East Asian Climate (Zhu and Yang 2003a, b; Yang et al. 2005; Xu et al. 2005). Besides the direct impact, the PDO may provide a background modulating the interannual ENSO’s impact on East Asian Climate (Zhu and Yang 2003a, b; Zhu et al. 2007; Yang and Zhu 2008). The present study focuses on the period 1979–2010 corresponding to the warm phase of PDO.

As mentioned earlier, sea surface temperature anomaly (SSTA) patterns are important to isolating the two types of El Niño. Although the Niño 3.4 SST index (Trenberth 1997) is widely used to identify El Niño events, it cannot distinguish the EP and CP El Niño (Trenberth and Stepaniak 2001). In order to define the two types of El Niño, the boreal summer [June–July–August (JJA)] Niño 3 and Niño 4 SST index shown in Fig. 2 are used in this study. The JJA Niño 3 SST index is defined by the mean SSTA averaged over the region (150°–90°W, 5°S–5°N, right solid box in Fig. 1). Similarly, the JJA Niño 4 SST index is defined using SST over the region (160°E–150°W, 5°S–5°N, left solid box in Fig. 1). The JJA SSTA is defined as deviation from a climatological (1979–2010) mean SST.
Fig. 1

Representation of the regions employed to calculate the indices used in this study, including Niño3 SST index, Niño4 SST index and western north Pacific summer monsoon index

Fig. 2

The evolutions of the Niño3 and Niño4 SST indices during boreal summer from 1979 to 2010

Following Yeh et al. (2009), a CP El Niño (La Niña) event is defined if Niño4 SST index is above 0.5 °C (below −0.5 °C) and Niño4 SST index is greater (smaller) than Niño3 SST index, and an EP El Niño (La Niña) event is defined if Niño3 SST index is above 0.5 °C (below −0.5 °C) and Niño3 SST index is greater (smaller) than Niño4 SST index. According to above criteria, there are 3 CP El Niño years (1994, 2002 and 2004) and 6 EP Niño years (1982, 1983, 1987, 1991, 1997 and 2009). In addition, 4 CP La Niña years and 6 EP La Niña years are defined (listed in Table 1). Figure 3a shows the SSTA composite for CP El Niño events for the JJA mean. As expected, the anomalies display a triple structure with positive SSTA in the central Pacific and negative SSTA in the east and west Pacific. The SSTA composite for CP La Nina events is opposite to that during CP El Niño (Fig. 3c).
Table 1

The definitions of CP and EP El Niño (La Niña) and the respective selected years during 1979–2010

Category

Criteria (JJA)

Years

Central Pacific

Niño4 SST index >0.5

1994, 2002, 2004

El Niño

Niño4 SST index >Niño3 SST index

Eastern Pacific

Niño3 SST index >0.5

1982, 1983, 1987, 1991, 1997, 2009

El Niño

Niño3 SST index >Niño4 SST index

Central Pacific

Niño4 SST index <−0.5

1989, 1998, 1999, 2008

La Niña

Niño4 SST index <Niño3 SST index

Eastern Pacific

Niño3 SST index <−0.5

1984, 1985, 1988, 2000, 2007, 2010

La Niña

Niño3 SST index <Niño4 SST index

Fig. 3

Composites of sea surface temperature anomalies (SSTA) for a CP El Niño, b EP El Niño, c CP La Niña and d EP La Niña during boreal summer (JJA) Anomalies that are significant at the 90 % level are shaded

2.2 Model data

CAM4 is the seventh generation atmospheric general circulation model (AGCM) developed with significant community collaboration at the National Center for Atmospheric Research (Neale et al. 2013). It is part of the Community Climate System Model (CCSM4, Gent et al. 2011). CAM4 exhibits significant changes and improvements in climate simulation compared to CAM3 (Collins et al. 2006) due to the moderate changes in model configuration. The finite volume dynamical core is the default option in CAM4, and the default horizontal resolution is 0.9° latitude by 1.25° longitude, and the default number of levels is 26 (Neale et al. 2013).

The present study uses a 6-member ensemble of CAM4 simulations run forced with monthly observed SSTs (Hurrell et al. 2008) from 1979 to 2010 (referred as CAM4-AMIP runs, and this model output datasets can be downloaded from website: http://www.earthsystemgrid.org/dataset/ucar.cgd.ccsm4.output.html). The CAM4-AMIP runs will be analyzed base on ensemble mean. To further identify the effect of two types of ENSO during boreal summer, we conduct 5 extra experiments using CAM4 model: one is a 50-year integration forced with climatological mean seasonal cycle of SST, referred as control run (CAM4-CTL) and the other four 50-year integrations were conducted with climatological mean seasonal cycle of SST plus a global JJA SSTA (see Fig. 3) of CP El Niño (La Niña) and EP El Niño (La Niña) from May to September (referred to as CAM4-CPEL; CAM4-CPLA; CAM4-EPEL and CAM4-EPLA), respectively. The 5 additional experiments run at a lower horizontal resolution (about 1.9° latitude by 2.5° longitude) due to computational resource limitation. Although the integrations are 50 years, only the last 30 years simulation results are discussed in this paper. Both the observation and CAM4 AMIP simulation results are composited and analyzed according to CP El Niño (La Niña) and EP El Niño (La Niña) years defined and shown in Table 1. To quantify the ability of the CAM4 model simulation, we select some simulated variables and compare to those in observation. Figure 4 illustrates the Taylor diagram (2001) displaying a statistical comparison with observations for seven selected variables of the global pattern of summer climatology over the tropics and extra-tropics (60°S–60°N). It is clear that the spatial correlation coefficients between simulations and observations are above 0.70. In addition, the ratios of simulated mean spatial deviation to observations range from 0.98 to 1.25. Overall, both of the CAM4 AMIP run and control run can well capture the spatial feature of the summer climatology in observations. A more comprehensive and detailed description about the CAM4 mean climate simulation can be found in Neale et al. (2013).
Fig. 4

Taylor diagram displaying a statistical comparison with observations of seven selected variables of the global pattern of summer climatology

3 Anomalies of two types of ENSO

3.1 Atmospheric response to two types of El Niños

As mentioned earlier, the spatial feature of SSTA differs between the CP El Niño and EP El Niño during boreal summer. It is natural to expect that the respective atmospheric response will be different. In order to identify the differences in responses to these two phenomena, we will examine CAM4 AMIP simulations and compare with the corresponding observations. In this section, we will mainly analyze the precipitation and low-level wind response to these two phenomena during the boreal summer.

According to the composite analyses of GPCP precipitation dataset, during CP El Niño, below normal precipitation appears over the Maritime Continent and equatorial eastern Pacific and above normal precipitation appears over the equatorial central Pacific. The above normal precipitation anomaly over the central Pacific extends westward and northward to the western North Pacific (WNP) region. In East Asia area, there is a triple precipitation anomaly pattern: the South China Sea, southern China and north of Japan suffer more precipitation, but the Yangtze River Valley and southern Japan suffer less precipitation (see Fig. 5a). This anomalous precipitation pattern in observations is similar to the corresponding pattern shown by previous studies (Weng et al. 2007; Yuan and Yang 2012).
Fig. 5

Composites of summer precipitation anomalies for two types of El Niños. Left column corresponds to Central Pacific El Niño. Right column corresponds to Eastern Pacific El Niño. Top, middle, and bottom panels in each column are observation, CAM4-AMIP, and experiment, respectively. For ad, Anomalies that are significant at the 90 % level are stippled

For the EP El Niño, however, the spatial feature of precipitation is different from the CP El Niño situation. The equatorial central to eastern Pacific experiences wet conditions and the Maritime Continent experiences dry conditions. There is also a triple precipitation anomaly pattern in East Asia area: more rainfall over the lower reaches of the Yangtze River valley and east of Philippines, and less rainfall around the Taiwan Island (Fig. 5b). But this pattern is not as significant as CP El Niño situation and it shifts eastward and southward compared to CP El Niño. This distinct result implies that the influence of EP El Niño on East Asia climate during boreal summer is less significant than CP El Niño, due to an eastward and southward shift in its significant influent zone to the Pacific Ocean compared to CP El Niño.

The JJA precipitation anomaly composites are shown in Fig. 5c, d using the CAM4 AMIP runs data from January 1979 to December 2010. Although there are some differences between the observations and CAM4 AMIP runs, patterns of the observed precipitation anomalies in CP and EP El Niño can be captured by CAM4 AMIP run. And the triple precipitation anomaly pattern in EP El Niño is rather distinct. Figure 5e, f show the CAM4-CPEL and CAM4-EPEL sensitivity modeling results, the precipitation anomalies feature are similar to those in CAM4 AMIP runs.

Figure 6 presents the different impacts of the two types of El Niños on 850 hPa wind anomalies. For CP El Niño (Fig. 6a), there are low-level westerly (easterly) anomalies over the western-central (eastern) Pacific. And the two wind anomalies meet near 150°W. This tropical wind anomaly pattern indicates the presence of two cells of anomalous Walker circulation with the joint ascending branch in the central equatorial Pacific (near 150°W) (Ashok et al. 2007; Weng et al. 2007). In addition, the low-level wind anomalies exhibit a cyclone over subtropical western North Pacific, an anticyclone over Japan and a cyclone over Northeast Asia. This anomalous cyclone-anticyclone-cyclone pattern in East Asia corresponds to the positive phase of Pacific-Japan pattern (PJ, Nitta 1987) or negative phase of the East Asia–Pacific pattern (EAP, Huang and Li 1988). As indicated by Weng et al. (2007), this pattern implies that the western North Pacific subtropical high may intensify and advance northward from its climatological mean. Besides, in response to the central Pacific warming, a large-scale cyclonic wind anomaly forms over subtropical western North Pacific, Wu et al. (2011) proposed that local air-sea interaction could maintain the low-level anomalous cyclonic circulation over subtropical North Pacific. They found the northeasterly anomalies associated with anomalous subtropical cyclone could advect more cold and dry air to the WNP, and the ocean would lose more heat because of the increases in the sea-air temperature and humidity differences. In turn, positive heat flux anomalies induce more surface heating and contribute to anomalous cyclonic circulation over subtropical western Pacific. More tropical cyclones (TCs) may occur there (Chen and Tam 2010), and western North Pacific summer monsoon may likely be stronger than normal (Weng et al. 2007). Thus, the area from the Yangtze River Valley to southern Japan suffers less precipitation, north of Japan and the area from South China Sea to Philippines suffer more precipitation.
Fig. 6

Same as Fig. 5, but for 850 hPa wind anomalies. For ad, Anomalies that are significant at the 90 % level are shaded

However, for EP El Niño (Fig. 6b), there are westerly wind anomalies across the whole equatorial Pacific, which implies that there is one cell of anomalous Walker circulation with the ascending branch in the equatorial eastern Pacific and descending branch in the equatorial western Pacific. The cyclone-anticyclone-cyclone wind anomaly pattern can be seen although it is not as significant as CP El Niño. In comparison, the anomaly pattern shifts eastward and southward to the Pacific Ocean. The wind anomaly pattern appears to explain the corresponding anomalous precipitation pattern quite well. Chen and Tam (2010) reported that less TCs occur in the north part of WNP while more TCs form in the south-eastern part of WNP during EP El Niño. And such TCs activities over the WNP region can be attributed to an anomalous anticyclonic circulation in the subtropics and a cyclonic shear associated with the equatorial westerly anomalies in the southeast part of the WNP.

The above mentioned 850 hPa anomalous wind pattern can be generally captured by CAM4 AMIP run results, especially in the tropics and subtropics. But for CP El Niño, the EAP pattern is not distinct in the CAM4 AMIP run, as only the cyclonic wind anomalies in subtropical western Pacific can be well simulated. Furthermore, the subtropical western North Pacific cyclone wind anomalies in CP El Niño sensitivity experiment tend to be northward compared to the observations and AMIP runs. Sun and Yang (2005) conducted AGCM simulations to identify the impact of East Asian Climate to the conventional ENSO events. They found during the summer when an El Niño event develops, there is an anomalously negative geopotential height center over Northeast China, the Korean peninsula and the Sea of Japan. The subtropical high over the Western Pacific is weaker and shifts eastward. In this study, the CAM4 AMIP EP El Niño composite results seem to be consistent with those of Sun and Yang (2005). But the 850 hPa anticyclonic wind anomalies over subtropical western Pacific and cyclonic wind anomalies near Japan seem to be slightly eastward compared to Sun and Yang (2005).

As mentioned earlier, the CAM4 Central Pacific El Niño (CPEL) experiment cannot capture the cyclone-anticyclone-cyclone wind anomaly pattern found in observations. Considering the SST as boundary conditions for CAM4 model, warm SSTA around Japan may excite an anomalous cyclone in situ. This cyclone may merge with subtropical cyclone excited by central Pacific warming, so the subtropical cyclonic wind anomalies in the CPEL sensitivity experiment are slightly northward. But the warm SSTA around Japan may be a result of less rainfall and more solar radiation, instead of a forcing. Wu et al. (2006) concluded that the SST anomalies in the midlatitude are significantly impacted by the atmospheric forcing. Specifying the SST in AGCM may produce excessive SST forcing in regions outside of tropics. The remote CP El Niño forcing in the midlatitude region may be cancelled by excessive response to local SST forcing. To demonstrate this, we conducted another experiment forced with climatological mean seasonal cycle of SST plus a tropical JJA SSTA (−20°S to 20°N) of CP El Niño from May to September (referred as CAM4 CPEL-Tropical, Fig. 7). The result of this experiment confirms our speculation. The removal of SST anomalies east of Japan improves the simulations of precipitation and wind anomalies around Japan. The triple wind pattern is more distinct compared to CAM4 CPEL experiment.
Fig. 7

The simulation results of CP El Niño (Tropical) sensitivity experiments. 30 years composite of mean precipitation anomalies and 850 hPa wind anomalies (compared to the last 30 years control runs ensemble mean)

3.2 Atmospheric response to two types of La Niñas

In this study, we also examine the influence of CP La Niña (i.e. negative phase of CP ENSO) on East Asia. During the CP La Niña, the equatorial central Pacific suffers less rain while the Maritime Continent and eastern Pacific suffer more rain. Besides, the South China Sea and northeast Asia experiences dry condition while the Yangtze River Valley experiences wet condition (Fig. 8a). Wang et al. (2012) concluded that central Pacific cold event during the summertime would suppress the TC genesis in the southeastern part of WNP, and the TC lifetime is short. These finding may partly explain the dry condition over subtropical western Pacific. Similarly, an anticyclone-cyclone-anticyclone wind anomaly pattern, which indicates the positive phase of EAP pattern, is distinct in East Asia area (Fig. 9a). When cold SST anomalies appear in the central Pacific, boreal summer CP La Niña would excite or promote the western Pacific anticyclone, which may enhance the moisture transport from the western tropical Pacific into subtropical frontal region, thus abundant summer rainfall are over the subtropical monsoon front, the Yangtze River Valley region of China. Not surprisingly, the impact of CP La Niña (Fig. 8a) on tropics and East Asia seems to be opposite to that in CP El Niño (Fig. 5a). However, south China experiences normal or more rain condition in CP La Niña rather than less rain condition. Thus, there appears an asymmetry influence on south China between the CP El Niño and La Niña. Besides, the anticyclonic wind anomaly over WNP region in CP El Niña is comparatively weak and slightly southward compared to CP El Niño’s situation. Fan et al. (2013) found that the cooling over central tropical Pacific is crucial in developing and maintaining the summertime northeast Pacific anticyclones, associated with the EASM precipitation. They argue that monitoring and predicting the evolution of sea surface temperature anomalies in central tropical Pacific, especially in spring to summer, may greatly improve the prediction of EASM circulation. The central Pacific cooling effect can further be identified by our AGCM simulations. Both CAM4-AMIP (Fig. 8c) run and the CAM4-CPLA (Fig. 9e) simulation can well capture the subtropical anticyclone near the Philippines (Fig. 9c). And meridional triple wind anomaly pattern (Fig. 9a) in CAM4-CPLA (Fig. 9e) simulation is rather distinct.
Fig. 8

Composites of summer precipitation anomalies for two types of La Niñas. Left column corresponds to Central Pacific La Niña. Right column corresponds to Eastern Pacific La Niña. Top, middle, and bottom panels in each column are observation, CAM4-AMIP, and experiment, respectively. For ad, Anomalies that are significant at the 90 % level are stippled

Fig. 9

Same as Fig. 7, but for 850 hPa wind anomalies. For ad, Anomalies that are significant at the 90 % level are shaded

For EP La Niña, the equatorial central to eastern Pacific experiences dry conditions and the Maritime Continent experiences wet conditions (Fig. 8b). There is also a triple precipitation anomaly pattern in East Asia area: less rainfall over Japan and east of Philippines, and more rainfall around the Taiwan Island (Fig. 8b). This negative-positive–negative anomalous rainfall pattern during EP La Niña is similar but with opposite sign compared to EP El Niño scenario (Fig. 5b). And this pattern is not as significant as CP La Niña situation and shifts eastward compared to CP La Niña. This result further confirms that the influence of EP ENSO on East Asia climate during the boreal summer is less significant than CP ENSO, due to eastward and southward shift of the influence zone compared to CP ENSO. Similarly, the wind anomalies (Fig. 9b) of EP La Niña over tropics and East Asia also seem to be opposite to those in EP El Niño (Fig. 6b). And an asymmetry influence on south China can also be found between the EP El Niño and La Niña. The observed 850 hPa wind anomaly pattern in tropics can be generally simulated by CAM4 AMIP run (Fig. 9d) and CAM4 EPLA (Fig. 9f) experiment. Only the CAM4-EPLA can roughly capture the wind anomaly feature in East Asia and this feature is slightly northward compared to observations (Fig. 9b).

4 Asymmetry influence of CP ENSO

The above analysis shows that CP El Niño (La Niña) and EP El Niño (La Niña) have different effects on summer (JJA) rainfall and temperature over East Asia, with CP El Niño (La Niña) having a more significant influence on East Asia climate compared to EP El Niño (La Niña). For a better comparison, the western North Pacific monsoon index (WNPMI) defined by Wang and Fan (1999) is used to quantify the different impacts between CP El Niño (La Niña) and EP El Niño (La Niña). The WNPMI is defined as the difference of 850 hPa westerly between a southern region (100°–130°E, 5°–15°N, south dash box in Fig. 1) and a northern region (110°–140°E, 20°–30°N, north dash box in Fig. 1). Since the WNPMI is always out of phase with the East Asian summer monsoon (Wang and Lin 2002) and in phase with the South China Sea summer monsoon (Wang et al. 2009) on interannual timescale, a large positive (negative) WNPMI may be likely to relate to more (less) rainfall in the South China Sea area and less (more) rainfall in the Yangtze River valley area. Figure 10 shows the computed western North Pacific summer monsoon index from 1979 to 2010 for both of ERA-Interim Reanalysis data and CAM4 AIMP runs. The correlation coefficients between the observation and CAM4 AMIP ensemble mean is about 0.72. Although there are some inconsistencies between observation and CAM4 AMIP ensemble mean, the internal variation of WNPMI can be captured by CAM4 AMIP runs. Weng et al. (2007) reported that the western North Pacific summer monsoon during CP (EP) El Niño is likely stronger (weaker) than normal. But in this study, the composite mean of WNPMI anomaly is 2.51 (−1.98) for CP El Niño (La Niña) and 0.01(−0.52) for EP El Niño (La Niña). The corresponding CAM4-AMIP run result is quite consistent with the observation, with its composite average anomaly of WNPMI around 2.81(−1.96) for CP El Niño (La Niña) and 0.28 (−0.69) for EP El Niño (La Niña). It seems that both types of El Niño (La Niña) correspond to a stronger (weaker) western North Pacific summer monsoon. In comparison, the CP El Niño (La Niña) may have more significant influence on East Asia summer climate than EP El Niño (La Niña), as the associated low-level anomalous wind pattern is more distinct and closer to the Asian continent compared to EP El Niño (La Niña).
Fig. 10

six-member ensemble mean (dash line) and ensemble member range (gray shading) for western north Pacific summer monsoon anomalies (m/s; anomalies are formed by subtracting the 1979–2010 mean from each run from its time series of annual values) for observed SST forcing; black line is observations

As mentioned earlier, CP El Niño mainly occurs since the late 1970s, only 3 CP El Niño years (1994, 2002 and 2004) and CP La Niña years (1989, 1998, 1999 and 2008) during boreal summer are defined in this study. Surprisingly, these CP El Niño years are all associated with enhanced western North Pacific summer monsoon, while 2 out of the 4 CP La Niña years (1998 and 2008) are associated with weak western North Pacific summer monsoon and the other two are associated with slightly positive WNPMI. It seems that the positive phase of CP ENSO (i.e. CP El Niño) may have more robust influence on East Asia compared to the negative phase of CP ENSO (i.e. CP La Niña). However, the CAM4 AMIP ensemble mean result presents that the western North Pacific summer monsoon is stronger (weaker) than normal during the selected CP El Niño (La Niña) years.

To further identify the simultaneous impact of different equatorial Pacific SSTA pattern on East Asia, five additional CAM4 sensitivity experiments have been conducted. The behavior of western north Pacific summer monsoon under the anomalous conditions described by the four SSTA patterns of experiments is accessed through the construction of probability distribution functions (PDFs) that sample all the simulations of WNPMI anomalies (compared to the control run) in the respective CAM4 experiments (Fig. 11). The PDFs of the simulated WNPMI for CP El Niño are far above those of control experiment, and the simulated WNPMI tends to below those of control experiment during CP La Niña. Particularly, 25 out of the 30 members (about 83.3 % in total) in CAM4 CPEL simulations correspond to positive WNPMI anomalies and 19 out of 25 members (76 %) tend to correspond to strong western north Pacific summer monsoon (WNPMI anomaly lager than 1.0). And the performance of WNPMI in CAM4 CPEL-Tropical experiments (Fig. 11e) is quite similar to the CPEL experiments (Fig. 11a). The PDF results of two types of warm events indicate that the influences of CP and EP El Niño on East Asia are quite independent. For CAM4 CPLA experiment, 18 out of 30 members (about 60 % in total) are associated with positive WNPMI anomalies, and 12 out of 18 members (about 66.7 %) are associated with weak western north Pacific summer monsoon. Besides, the PDFs for EP El Niño (La Niña) are not well separated and the simulated mean WNPMI is only slightly more (less) than the control experiment. For EPEL sensitivity simulations, although 18 out of the 30 members (about 60 %) correspond to positive WNPMI anomalies, only 7 of 18 members (about 38.9 %) correspond to strong positive WNPMI anomalies. Although only about 12 members correspond to negative WNPMI anomalies, 10 out of 12 (83.3 %) correspond to strong negative (smaller than −1.0) WNPMI anomalies. For EPLA sensitivity simulations, 19 out of the 30 members (about 63.3 %) are associated with weak western north Pacific summer monsoon, and only 7 of 19 members (about 36.8 %) are associated with strong negative WNPMI anomalies. Overall, the simulations demonstrate the CP type ENSO may exert more significant influence on East Asia than the EP type ENSO. Besides, the impact of CP El Niño is likely to be more robust than that of CP La Niña. The impacts between the two types of La Nina are less independent compared to the two types of warm events, there is an asymmetric influence on East Asian between warm and cold events during summertime.
Fig. 11

The probability distribution functions of Western North Pacific summer monsoon index anomalies (compared to the last 30 years control runs ensemble mean) corresponding to a the Central Pacific El Niño, b Eastern Pacific El Nino, c Central Pacific La Niña and d Eastern Pacific La Niña, e CP El Niño (Tropical) experiments

5 Discussions and concluding remarks

In this study, we calculate the boreal summer (JJA) Niño 3 and Niño 4 SST index and define two types of El Niño (i.e. CP and EP El Niño) and La Niña (i.e. CP and EL La Niña) by using monthly HadISST dataset. To further identify the different impacts of two types of El Niños (La Niñas), we make use of CAM4 AMIP runs and compare with the corresponding observations. Besides, we conduct 5 additional CAM4 simulations including four sensitivity experiments designed according to the corresponding composite SSTA pattern and one control experiment forced with the monthly evolving climatological SST.

For CP El Niño, there is a triple precipitation anomaly pattern in East Asia area: the South China Sea, southern China and north of Japan suffer more precipitation, but the Yangtze River Valley and southern Japan suffer less precipitation. In addition, the low-level wind anomalies exhibit a cyclone over subtropical western North Pacific, an anticyclone over Japan and a cyclone over Northeast Asia. The triple precipitation anomaly pattern can be explained by low-level cyclone-anticyclone wind anomaly pattern. But this triple pattern in both precipitation and wind anomalies during EP El Niño is not as significant as CP El Niño situation and it shifts eastward and southward compared to CP El Niño. In this study, we have also examined the influence of CP La Niña on East Asian climate, which is comparatively less explored. For CP La Niña, the South China Sea and northeast Asia experience dry condition while the Yangtze River Valley experiences wet condition. Similarly, an anticyclone-cyclone-anticyclone wind anomaly pattern is distinct in East Asia area. The low level anticyclone over WNP may enhance the moisture transport from the western tropical Pacific into subtropical frontal region, and thus more summer rainfall is expected over the subtropical monsoon front, the Yangtze River Valley region of China. The impact of CP (EP) La Niña on tropics and East Asia seems to be opposite to that in CP (EP) El Niño. Those spatial features can be generally captured by CAM4 simulations. Thus, we conclude that the CP El Niño (La Niña) may have more significant influence on East Asia summer climate than EP El Niño (La Niña), as the associated low-level anomalous wind pattern is more distinct and closer to the Asian continent compared to EP El Niño (La Niña).

From the corresponding composite results, there seem to be an asymmetry influence on south China between the CP (EP) El Niño and CP (EP) La Niño. For example, although south China may experiences more rain condition during CP El Niño, normal rain condition rather than less rain condition appears during CP La Niña. The physical reasons for the asymmetry of the influences between the CP (EP) El Niño and CP (EP) La Niño need further investigation.

To quantify the difference in the influence between CP El Niño (La Niña) and EP El Niño (La Niña), the western North Pacific summer monsoon index defined by Wang and Fan (1999) is used in this work. Both types of El Niño (La Niña) correspond to a stronger (weaker) western north Pacific summer monsoon. But the influence of EP El Niño (La Niña) on East Asia climate during boreal summer is less significant than CP El Niño (La Niña), in association with the eastward and southward shift in its significant influence zone to the Pacific Ocean compared to CP El Niño (La Niña). The impact between the two types of La Nina seem to be less independent compared to the two types of warm events, there is an asymmetric influence on East Asian between warm and cold events during summertime. Besides, the impact of CP El Niño is likely to be more robust than that of CP La Niña. The CAM4 sensitivity experiments support this hypothesis.

Kug et al. (2009) indicated that although two types of La Niña can be defined based on some criteria, their zonal SSTA distribution slightly changed and it is quite difficult to well separate them into two groups during boreal winter. In this study, we have analyzed the impacts of CP and EP La Niñas during boreal summer. It seems that there is different influence on East Asia between the two types of La Niña. Furthermore, the results based on observational composites may not be robust due to the small sample. Numerical studies may help to clarify this issue, but only one atmospheric model (i.e. CAM4) is used in this study. Much more investigation is needed in the future.

Notes

Acknowledgments

This research is jointly supported by the National Natural Science Foundation of China (Grant No. 41175076) and the National Key Basic Research Program of China (Grant No. 2009CB421404). RW acknowledges the support of a Hong Kong Research Grants Council grant (CUHK403612) and the National Natural Science Foundation of China (41275081). ZC acknowledges the support of the high-performance grid computing platform of Sun Yat-sen University.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Zesheng Chen
    • 1
  • Zhiping Wen
    • 1
  • Renguang Wu
    • 2
  • Ping Zhao
    • 3
  • Jie Cao
    • 4
  1. 1.Center for Monsoon and Environment Research/Department of Atmospheric SciencesSun Yat-sen UniversityGuangzhouPeople’s Republic of China
  2. 2.Institute of Space and Earth Information Science/Department of PhysicsChinese University of Hong KongShatin, Hong KongPeople’s Republic of China
  3. 3.Chinese Academy of Meteorological SciencesBeijingPeople’s Republic of China
  4. 4.Department of Atmospheric SciencesYunnan UniversityKunmingPeople’s Republic of China

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