1. Introduction
In the past two decades, major progress has been made in understanding and modeling the coupled ocean–atmosphere interactions in the tropical Pacific, in particular the salient feature of the El Niño–Southern Oscillation (ENSO) phenomenon (McPhaden et al. 1998; Neelin et al. 1998; Wallace et al. 1998). Moreover, it has been recognized that the tropical Pacific climate has an abundance of coupled air–sea phenomena (Jin 2001). The observed spectra for tropical sea surface temperature (SST) exhibit more structures from intraseasonal to interdecadal time scales than just a single spectral peak. Also, many studies have reported the coexistence of various coupled modes in intermediate coupled models (Zebiak 1984; Mantua and Battisti 1995; Perigaud and Dewitte 1996; Dewitte et al. 2007) and complex coupled models (Philander et al. 1992), as well as in observed data (Jin et al. 2003; Tozuka and Yamagata 2003; Kang et al. 2004; Bejarano and Jin 2008).
Particularly, there have been investigations of different types of ENSO events according to onset time and propagation characteristics (Wang 1995; Xu and Chan 2001; Horii and Hanawa 2004; Sooraj et al. 2009b). In addition, some recent studies have argued that there exist more than one type of El Niño (or ENSO), based on spatial distributions of SST (Larkin and Harrison 2005a,b; Ashok et al. 2007; Weng et al. 2007; Kao and Yu 2009). The National Oceanic and Atmospheric Administration (NOAA) revised the definition of El Niño “as a phenomenon in the equatorial Pacific Ocean characterized by a positive sea surface temperature departure from normal in the Niño-3.4 region (i.e., 5°S–5°N, 170°–120°W) greater than or equal in magnitude to 0.5°C averaged over three consecutive months.” Based on this definition, Larkin and Harrison (2005a,b) identified a number of additional El Niño events, which they called “date line El Niño” because the SST maxima associated with these events are located near the international date line. They showed that the impact of the date line El Niño is quite different from that of the conventional El Niño over the United States (Larkin and Harrison 2005a) and globally (Larkin and Harrison 2005b).
Recently, Ashok et al. (2007) argued that anomalous warming events, which are distinguished from conventional El Niño events, occur in the central equatorial Pacific. They called these events “El Niño modoki (pseudo–El Niño).” Their El Niño modoki pattern is defined based on the second EOF mode of monthly tropical Pacific SST anomalies, which shows a warming over the central equatorial Pacific with cold centers on both sides of the warm center along the equator. They pointed out that these El Niño modoki events significantly influence the temperature and precipitation over many parts of the globe, but in ways quite different from the conventional El Niño events (Ashok et al. 2007; Weng et al. 2007). Furthermore, they demonstrated that these events appear to be more frequent and persistent occurrences during recent decades.
Although the aforementioned studies used different names and emphasized somewhat different aspects of these El Niño events, it seems that they are looking at the same phenomenon with a slightly different point of view. We found three common features from these studies: (i) There is a distinctively different interannual SST variation from the conventional El Niño over the central Pacific, (ii) the SST variation over the central Pacific exhibits stronger variance in recent decades, and (iii) their global impact is significant and quite different from that of the conventional El Niño. Actually, the selected event years are mostly consistent in these studies. However, the definition and its interpretation of this phenomenon are diverse (i.e., eastern Pacific cold SST), indicating that our understanding is not yet adequate. In particular, the dynamical processes responsible for the phenomenon to develop and decay are not fully addressed. In fact, it is still unclear whether the phenomenon is dynamically different from the conventional one. Therefore, in this study we examine a dynamical process of this phenomenon, distinctive from that of the conventional El Niño. Section 2 gives a brief description of the data used in this study. In section 3, we describe major features of the new phenomena, underscoring their distinctions from those of the conventional El Niño. In section 4, we address a major dynamical process by using ocean assimilation data. A summary and a discussion are given in section 5.
2. Data
We use monthly mean atmospheric and oceanic circulation data, in addition to precipitation, SST, and ocean temperature data. The Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) data are used to verify the climate model’s performance for the period 1981–2001. The data are produced by merging rain gauge data, five kinds of satellite estimates, and a numerical model predictions(Xie and Arkin 1996). The atmospheric circulation data are the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (Kalnay et al. 1996). They have a horizontal resolution of 2.5° × 2.5°. Though the reanalysis data have their own uncertainty, we found that the present results are quite consistent with those using the other reanalysis datasets (e.g., NCEP–DOE reanalysis data). Our major conclusions are not sensitive to the reanalysis datasets.
The SST data are the improved Extended Reconstructed Sea Surface Temperature version 2 (ERSST V2) (Smith and Reynolds 2004) from the National Climate Data Center (NCDC). This data analysis uses monthly and 2° spatial resolution superobservations, which are defined as individual observations averaged onto a 2° grid. For SST and atmospheric circulation data, the period is 36 years from 1970 to 2005. Note that the main conclusion of the present study is not critical to the data period because most warm pool (WP) El Niño events occur since 1990. The ocean temperature and oceanic circulation data are from the NCEP Global Ocean Data Assimilation System (GODAS) product (Behringer and Xue 2004). It is available at ⅓° × ⅓° resolution in the tropics, and has 40 vertical levels with 10-m resolution near the sea surface. For precipitation and oceanic circulation data, the period of 26 years from 1980 to 2005 is used because of their availability. Anomalies presented in this study are detrended after removing the monthly-mean climatology.
3. Warm pool El Niño and cold tongue El Niño
Figure 1 displays all El Niño events during 1970–2005. An event is included in Fig. 1 if either Niño-3 SST (averaged SST over 5°S–5°N, 90°–150°W) or Niño-4 SST (averaged SST over 5°S–5°N, 160°E–150°W) is greater than its corresponding standard deviation. Because the peak season of each event is slightly different, a broad seasonal mean from September to the following February [SOND(0)JF(1)] is taken to select these El Niño events. As a result, there are 12 El Niño events during this period. Though each El Niño event has a unique spatial pattern, we can classify them into three groups based on the zonal location of the equatorial SST. First, some El Niño events show stronger SST anomalies in the eastern Pacific, which extend to the central Pacific (middle column in Fig. 1). The 1972–73, 1976–77, 1982–83, and 1997–98 El Niño events belong to the first group. For these events, Niño-3 SST is an appropriate index to measure their intensity. Hereafter we will refer to these El Niño events as cold tongue (CT) El Niño events. Note that the SST pattern of the CT El Niño is quite similar to that of the conventional El Niño, as shown by many studies (Rasmusson and Carpenter 1982; Harrison and Larkin 1998). Interestingly, the three strongest El Niño events since 1950 are all in this group.
Unlike the CT El Niño events, some El Niño events have larger SST anomalies in the central Pacific, while the eastern Pacific SST anomaly is still positive but small. The events of 1977–78, 1990–91, 1994–95, 2002–03, and 2004–05 fall under this group. For these events, Niño-4 SST is appropriate to measure their intensity. We call them WP El Niño events, because the action center of several atmospheric variables as well as of the SST anomaly is located in the warm pool area, and it is related to the extension of the warm pool area, which we will show later. It is interesting that most of the WP El Niño events happened in and after 1990, indicating that this type of El Niño is very active in recent decades. There are three more events, which have features between the CT and WP El Niño events: the 1986–88 El Niño events and 1991–92 events. Their maximum SST anomalies are located between 120° and 150°W.
To justify our classification, normalized Niño-3 and Niño-4 SSTs are compared in Fig. 2. For the WP El Niño, its Niño-4 (Niño-3) SST is always greater than (less than) its standard deviation. However, the Niño-3 SST of the CT El Niño is much bigger than its Niño-4 SST. This big contrast of the SST pattern has a distinctive implication on our understanding of the tropical Pacific ENSO.
To illustrate the distinctions in characteristics of WP and CT El Niño events, a composite analysis is carried out. Figure 3 shows SST composites of both types from the developing phase to decaying phase. In the case of the CT El Niño, large SST anomalies develop in the eastern Pacific during the developing summer, June–August (JJA)]. The maximum value of the warm SST is located in the coastal region of the eastern boundary. As the El Niño develops further, the SST pattern is mostly stationary in spite of a slightly westward shift of the maximum SST. Over the western Pacific, there is a cold SST anomaly, which is slowly moving to the east as El Niño develops.
During boreal summer, the SST anomaly of the WP El Niño is mostly confined in the central Pacific. A less significant cold SST anomaly is also found near the eastern boundary. The general feature is similar to that of the El Niño modoki (Ashok et al. 2007), but quite different from that of the CT El Niño. The warm SST anomaly slowly develops by the boreal winter without any significant movement and then this warm SST anomaly is rapidly reduced within one season, as seen in Fig. 3d. The cold SST anomaly over the eastern Pacific disappears during boreal winter and reemerges during the following spring. Also, there is a cold SST anomaly over the western Pacific similar to that of the CT El Niño. However, its location is shifted to the west compared to that of the CT El Niño, possibly because of the westward shift of the Philippine Sea anticyclone. We will discuss it later.
As shown in Fig. 3, the SST pattern of the WP El Niño is distinctively different from that of the CT El Niño. To measure dissimilarity between these two types of El Niño events, pattern correlation based on the 3-month mean SST anomaly is calculated accordingly over the tropical Pacific domain (20°S–20°N, 120°E–80°W). The pattern correlation is highest (about 0.7) at the peak phase of both types of El Niño events, but its value is very small during the developing phase and even negative during the following season of the peak. This implies that the two types have different SST patterns and their evolutions are quite different.
Since two types of El Niño are characterized by the distinctive SST pattern, the associating atmospheric responses are also expected to be different. Figure 4 shows precipitation composites of the two types of El Niño events. Due to the limitation of precipitation data, only two and four events are used for the CT and WP El Niño composites, respectively. The precipitation evolution is quite different between the two composites. The pattern correlation is always less than 0.5. The major pattern difference is as follows: First, the center of positive anomaly associated with the WP El Niño is shifted to the west, consistent with the SST anomaly. Second, the anomalous precipitation is zonally elongated to the eastern Pacific along the equator in the CT El Niño composite, while the anomaly is confined to near the international date line in the WP El Niño composite. Third, the north–south (off equator–equator) dipole pattern of precipitation is clear in the CT El Niño composite, but not so in the WP El Niño composite, which shows no negative precipitation off the equator but weak positive precipitation north of the equator. A striking difference appears during the decaying phase, March–May (MAM(1): The CT El Niño composite shows a basically positive anomaly in the equatorial region and negative anomaly off the equator in the Northern Hemisphere. However, it seems that the sign for precipitation is just the opposite over the tropical Pacific: the pattern correlation is about −0.8 during MAM(1), indicating an opposite sign for the precipitation anomaly.
Because the precipitation composites are not based on all 12 events due to data availability, we further examine vertical motions using the NCEP–NCAR reanalysis data that cover all the events. Figure 5 shows composites of the vertical (pressure) velocity at 500 hPa, which confirm major differences of the two types of El Niño events. This indicates that these features are quite robust. In general, the differences between the two types of El Niño events are more distinctive in precipitation and vertical motion compared to those in SST. Thus, the pattern correlations are always lower than 0.5, which is less than that for SST.
It is also interesting that the magnitude of vertical motion is comparable between the WP and CT El Niño composites, even though the maximum value of the CT El Niño is 1.5 times larger that of the WP El Niño. Note that the maximum SST anomaly of the CT El Niño is about three times that of the WP El Niño, as shown in Fig. 3. This is because the central Pacific SST anomalies are much more effective at inducing anomalous convection compared to the eastern Pacific SST anomalies owing to their warmer background SSTs. This makes the WP El Niño have comparable global impacts to the CT El Niño in spite of its relatively small SST anomaly. Different patterns of anomalous convection can lead to differences in the atmospheric circulation, and one may expect distinctive atmospheric teleconnections (e.g., Hoerling et al. 1997; An et al. 2007). This is because the tropical precipitation is a main source for the tropical–extratropical teleconnection. Differences in global impacts of the two types of El Niño will be a future research subject.
Figure 6 shows composites of zonal wind anomaly at 925 hPa. In the case of the CT El Niño, anomalous zonal wind shows clear eastward propagation from the western Pacific. It also shows that the center of the anomalous zonal wind migrates to the south, as seen in previous studies (Harrison and Vecchi 1999; Vecchi and Harrison 2006; Vecchi 2006). During the mature phase of the CT EL Niño from December to February [D(0)JF(1)] there are strong westerlies over the central-eastern Pacific but significant easterlies over the equatorial eastern Pacific, which are linked to the cool sea surface over the northwestern Pacific (Weisberg and Wang 1997a,b; Wang et al. 2001) and the Indian Ocean SST (Kug et al. 2005, 2006a,b; Kug and Kang 2006). In contrast, the center of the anomalous zonal wind is located relatively to the west and its zonal scale is smaller in the WP El Niño composite. Also, anomalous easterlies are not found over the western Pacific, different from the CT El Niño. However, anomalous easterlies appear over the eastern Pacific. The easterlies can suppress SST warming over the eastern Pacific by anomalous upwelling via Ekman transport and by excessive evaporation due to enhanced trade winds. These differences between the two types of El Niño events are quite consistent with the difference in precipitation, indicating that both types of El Niño events are strong, coupled air–sea phenomena.
The anomalous low-level wind generates an anomalous oceanic state in the tropical Pacific Ocean. Figure 7 shows sea level anomalies during the mature phase of the two types of El Niño events. For the CT El Niño composite, the seesaw pattern in sea level is clear; namely the thermocline is deepening (shoaling) over the eastern (western) Pacific. Note that changes in sea level can be considered as changes in the thermocline depth within first-order approximation. The deepening thermocline induces a strong warm vertical advection by mean upwelling in the eastern Pacific (Kang et al. 2001; An and Jin 2001). Thus, the warm SST anomaly is dominant in the eastern Pacific. Also, the steep zonal slope of sea level leads to a strong discharge of equatorial heat content to off-equatorial regions by poleward geostrophic currents, leading to the transition from El Niño to La Niña (Jin 1996, 1997a,b).
On the other hand, in the case of the WP El Niño, the positive sea level anomaly is located over the central Pacific, and its maximum near 150°W coincides with a nodal point of zonal wind anomaly as shown in Fig. 6c. Usually the climatological-mean thermocline over the tropical central Pacific is relatively deeper than that in the tropical eastern Pacific so that subsurface temperature below the mixed layer in the tropical central Pacific is less sensitive to changes of the thermocline depth. In this regard, the sea level anomaly in the tropical central Pacific may not efficiently produce a warm SST anomaly. Furthermore, anomalous easterlies over the tropical eastern Pacific induce shoaling of the thermocline and play a role of cooling, rather than warming, over the tropical eastern Pacific. Thus, other mechanisms are required in order to understand the cause of the warm SST anomaly of the WP El Niño. In addition, there are anomalous easterlies over the eastern Pacific; as a result, the sea level anomaly is small over the eastern Pacific, indicating that the thermocline there does not support SST warming.
Since the maximum elevation of sea level is located at 150°W, the zonal gradient of sea level is directed away from this maximum. The eastward (westward) gradient leads to poleward (equatorward) transport of heat (or warm water) by meridional divergence (convergence) of the geostrophic currents (Meinen and McPhaden 2000, 2001; Kug et al. 2003). Thus, both components compensate each other in terms of total heat content (i.e., a zonally averaged value of thermocline depth, sea level, or vertically integrated upper-ocean temperature) exchanges between the equatorial and off-equatorial regions. This indicates that the discharge process of the equatorial heat content is not efficient, so the discharge process suggested in Jin (1997a,b) cannot serve as the phase-transition mechanism. Note that the eastward gradient of sea level is quite strong in the case of the CT El Niño. Therefore, the discharge process associated with the CT El Niño is effective, which leads to a phase transition from the warm phase to cold phase, following the recharge oscillator paradigm (Jin 1997a,b).
To examine the heat exchange between the equator and off-equator regions, evolution of the zonal mean sea level over the Pacific basin (120°E–80°W) is shown in Fig. 8. According to the recharge oscillator theory (Jin 1997a,b), the positive anomaly of equatorial heat content leads El Niño by about a quarter cycle of the ENSO period and the heat content anomaly is discharged after the peak phase of El Niño. In the CT El Niño composite, it follows the theoretical expectation well. During the developing phase, a strong positive heat content prevails in the equatorial region, but a strong negative heat content also exists north of the equator. Note that the magnitudes of both heat content anomalies are almost the same, implying that the equatorial heat content comes from the off-equatorial region. After the peak phase of the CT El Niño, the equatorial heat content is rapidly discharged so that a strong negative anomaly appears. Note that the magnitude of a negative sea level anomaly in the decaying phase is larger than that of the positive sea level anomaly in the developing phase because the ENSO cycle tends to show asymmetric behavior owing to its nonlinearity (An et al. 2005). At the same time, the zonal-mean sea level anomaly north of the equator develops with a similar magnitude as the equatorial one but with the opposite sign. Note that the heat content anomaly south of the equator has the same sign as the equatorial one. It seems that the mass (or heat content) exchange associated with ENSO only happens between the equator and the region north of the equator, as mentioned by Kug et al. (2003). Kug et al. also argued that the meridional location of the zonal wind stress anomaly and western boundary current contribute to this asymmetric mass exchange.
The evolution of zonal-mean sea level is quite different in the WP El Niño case. First, the transport of equatorial heat (i.e., the drain off the equator from the zonal-mean equatorial sea level) is quite weak during the decaying phase. The heat content anomaly does not become negative after the WP El Niño peak phase. Therefore, it is hard for a cold event to follow the WP El Niño event, in contrast to the CT El Niño. This weak discharge is related to the zonal location of wind stress and the corresponding sea level distribution, as discussed earlier. Another major difference from the CT El Niño is the hemispheric asymmetry. In the region north of the equator, the sign of the heat-content anomaly is always negative, indicating that mass exchange does not happen there. However, in the Southern Hemisphere there is a significant positive anomaly during the decaying phase of the WP El Niño. It seems that the mass exchange associated with the WP El Niño happens in the Southern Hemisphere, which is quite distinctive from that of the CT El Niño. From these analyses, it is clear that the transition mechanisms and dynamical structures of the two types of El Niño events are significantly different.
4. Physical process of the warm pool El Niño
In the previous section, we showed that the WP El Niño has a distinctive spatial pattern and time evolution from those of the CT El Niño. In this section, we investigate how the WP El Niño develops and decays by using ocean assimilation data. Because assimilation data was not available before 1980, only four WP El Niño events are used for composite analyses here.
To examine oceanic structures of the WP El Niño, Fig. 9 shows evolution of the sea level anomaly and mixed layer current anomaly from the developing phase to the decaying phase. The mixed layer is defined as the top 50 m of the surface layer. During JJA(0) of the developing year, a weak sea level anomaly appears in the central Pacific. Associated with the sea level anomaly is an off-equatorial eastward current in the western to central Pacific and an equatorial eastward current east of the date line. Presumably, the equatorial current is related to the zonal pressure gradient along the equator, which is balanced by oceanic damping. The off-equatorial eastward current is the geostrophic current due to the meridional pressure gradient. Note that there is also an equatorial eastward current, which is related to the negative sea level anomaly in the western North Pacific and the westerly wind anomaly shown in Fig. 6a. All of these anomalous eastward currents indicate warm advection by the mean temperature gradient. Therefore, they contribute to the developing warm SST anomaly. This is related to the so-called zonal advective feedback (An and Jin 2001).
During August–October [ASO(0)], the anomalous eastward currents in the previous season develop further, enhancing the SST anomaly. In particular, as the sea level anomaly develops, the anomalous currents in the central Pacific are intensified. Also, it is noted that the anomalous eastward current is extended to where the sea level anomaly is maximum. Because the sea level is maximum along the equator, the geostrophic current is eastward. This geostrophic current contributes to the warm SST development. In addition, the positive sea level anomaly indicates anomalous subsurface warming. Thus, the mean upwelling brings anomalous warm water from subsurface to the surface, indicating anomalous warm advection.
The WP El Niño has its peak phase around November–December. During the peak season in October–December [OND(0)], the anomalous current and sea level still remain. However, a weak westward current anomaly appears near the international date line, which leads to decaying warm SST by cold advection. This westward current is related to two components. One is the westward gradient of the equatorial sea level. This westward gradient can force the westward current west of the maximum positive sea level anomaly since the Coriolis parameter is zero at the equator. The other is the reflected upwelling Kelvin wave from the western boundary. The anomalous westerly wind over the western Pacific produces upwelling Rossby waves off the equator that reflect at the eastern boundary as upwelling Kelvin waves and alter the equatorial current. We note that the sea level anomaly is meridionally at a local minimum in the westward current region. The local minimum sea level corresponds to the westward current by geostrophic constraint.
After the peak phase of the WP El Niño, the equatorial eastward currents gradually weaken and westward currents gradually strengthen during D(0)JF(1). The westward current is further developed and appears in the whole equatorial region during February–April [FMA(1)]. At that time, the zonal mean sea level is weakly positive or nearly zero. Also, the zonal gradient of equatorial sea level is quite weak. However, the sea level off the equator is positive so that the meridional gradient of sea level is equatorward. This meridional distribution of sea level corresponds to a strong equatorial westward current due to the equatorial geostrophic constraint. This westward current plays a noticeable role in the demise of the WP El Niño.
Figure 10 shows the evolution of each advection term for the Niño-4 SST. The warming tendency of the Niño-4 SST is strongest in September [S(0)], and the cooling tendency is strongest in April [A(1)]. Note that the magnitude of the cooling tendency is larger than that of the warming tendency, indicating that the demise of the WP El Niño is relatively faster. The sum of the nine advection terms seems to capture the overall pattern of the observed tendency of the Niño-4 SST. The timing of the strongest warming and cooling is consistent with the observed one. However, the oceanic advection tendency is mostly positively biased from the observed one, in particular when the SST anomaly is large from September to March [S(0)–M(1)]. Presumably, this is because atmospheric heat flux and oceanic small-scale eddies play a role in damping the warm SST anomaly. In particular, the atmospheric damping is quite strong in this region because atmospheric convection is sensitive to small SST warming (cf. Kang and Kug 2002) and blocks solar radiation with anomalous cloud cover.
Zonal advection terms significantly contribute to the SST tendency. In particular, the zonal advection term when the anomalous current and mean temperature gradient (−u′∂x
The meridional advection is dominated by the term related to the mean current and the anomalous temperature gradient (−
From the analysis of oceanic advection, it is revealed that the zonal advection is very important for the evolution of the WP El Niño, which is quite different from the conventional El Niño, or the CT El Niño. Previous studies pointed out that the vertical advection by mean upwelling is dominated in the developing and decaying of the SST anomaly associated with the conventional El Niño (Battisti 1988; Kang et al. 2001; An and Jin 2001). However, this process in the WP El Niño composite is relatively weak, and it does not contribute much to the phase transition of the WP El Niño (Fig. 10a). Therefore, we conclude that the two types of El Niño events evolve through different dynamical feedbacks.
To examine further detailed structures of SST evolution, the budget analysis is now applied separately to the eastern (5°S–5°N, 180°–150°W) and western (5°S–5°N, 150°E–180°) boxes of the Niño-4 area. For the eastern box, the terms of −u′∂x
For the western box, the SST evolution is somewhat different from that of the Niño-4 SST box and the eastern box. The zonal advection term (−
Based on the budget analysis, we can summarize how the SST anomaly associated with the WP El Niño develops and decays. It seems that the sources of SST development are zonal advection by the anomalous current and vertical advection by the anomalous vertical temperature gradient. The equatorial sea level (heat content) anomaly leads subsurface warming and an eastward current, which lead SST warming. Once the SST warming is produced, the mean zonal and meridional currents extend the SST anomaly westward and poleward, contributing to a larger spatial scale of the SST anomaly. This large-scale SST anomaly induces precipitation and wind stress anomalies, which enhance the sea level anomalies and cause further development. This warming tendency by oceanic advection is balanced by atmospheric and oceanic damping processes during the mature phase of the WP El Niño. After the mature phase, the zonal advection by the anomalous current plays a significant role for the rapid termination by the damping processes; namely, the westward current induced by the change of sea level distribution leads to strong cold advection (see Fig. 9). The warm SST anomaly first decays in the eastern part of the Niño-4 region because the mean zonal current still advects anomalous warm SST from the east in the western part of the Niño-4 region, which is responsible for the westward retreat of the SST anomaly. Once the SST anomaly is weakened, two advection terms by the mean currents are weakened because their magnitudes are proportional to the SST magnitude. As a result, the WP El Niño is rapidly terminated.
One may wonder why the WP El Niño is not accompanied by a strong SST anomaly over the eastern Pacific. We believe that this is because of its spatial structure. Here, we suggest a possible mechanism. Figure 11a shows evolution of the equatorial zonal wind stress anomalies associated with the WP El Niño. The strong westerly wind stress anomaly occurs in the western and central Pacific (130°E–160°W), including the Niño-4 region. On the other hand, there is an easterly wind stress anomaly over most of the Niño-3 region. This structure of wind stress is governed by the simple dynamics of the Gill-type solution (Gill 1982). Since the precipitation anomaly is located near the date line, the Rossby and Kelvin wave responses produce low-level westerlies to the west of the forcing and easterlies to the east of the forcing, respectively. Furthermore, an in-phase relation is observed between precipitation and zonal wind stress (Clarke 1994). The westerly anomaly can enhance SST warming by equatorial downwelling, and the easterly anomaly can suppress the warming by upwelling.
In addition to the upwelling, the wind stress anomaly can affect SST anomaly by changing wind speed. Figure 11b shows the anomalous magnitude of wind stress. Note that the magnitude of wind stress is proportional to the square of the wind speed. Because trade winds prevail over most of the Pacific basin, the westerly (easterly) wind stress anomaly decreases (increases) wind speed. However, since the climatological westerly wind migrates to the east during boreal winter, the westerly anomaly can increase the wind speed rather than decrease the wind speed in the western Pacific. As shown in Fig. 11b, the anomalous pattern of the wind stress magnitude is different from that of the zonal wind stress itself. The magnitude is significantly reduced over most of the Niño-4 region, while the magnitude is increased over the western and eastern Pacific. The decreased wind speed can enhance SST warming by less evaporation and less vertical oceanic turbulent mixing; similarly, the increased wind speed can suppress SST warming by evaporation and vertical mixing. This easterly wind stress anomaly over the eastern Pacific plays a role in damping the SST anomaly. Also, the increased wind speed over the western Pacific prevents the warm SST anomaly from propagating farther westward. In summary, this pattern of wind stress also favors the WP El Niño SST warming.
5. Summary and discussion
In this study, El Niño events are classified into two groups: warm pool El Niños and cold tongue El Niños. The main characteristics of the two are highlighted as follows:
The CT El Niño has a large SST anomaly in the Niño-3 region but relatively small SST anomaly in the Niño-4 region, while the WP El Niño has its SST anomaly mostly confined to the Niño-4 region. Therefore, two Niño indices should be used to measure their intensities, respectively.
The SST, precipitation, atmospheric vertical motion, and surface zonal wind anomalies associated with the WP El Niño are quite different from those of the CT El Niño. They are shifted to the west compared to those associated with the CT El Niño. Also, their zonal scales are smaller than those of the CT El Niño. However, the atmospheric response to the SST anomaly is stronger during the WP El Niño, indicating stronger teleconnections and remote impacts.
The east–west seesaw pattern of sea level is dominant in the CT El Niño, whereas the sea level anomaly is mostly located in the central Pacific in the WP El Niño. Due to these sea level distribution differences, the transport process of equatorial heat is not as efficient in the WP El Niño. In contrast, strong heat transport during the mature phase of the CT El Niño can easily trigger a transition to La Niña.
While vertical advection is a key process to the development and decay of SST anomalies in the CT El Niño, zonal advection plays a crucial role in the SST evolution of the WP El Niño. In particular, the zonal advection by anomalous currents is most important for the decay of the WP El Niño.
The WP El Niño accompanies anomalous westerlies over the western-central Pacific and anomalous easterlies over the eastern Pacific. The anomalous easterlies play a role in suppressing SST warming in the eastern Pacific through upwelling, excess evaporation, and vertical turbulent mixing.
Previous studies also reported distinctive cold events as well as warm events in the central Pacific based on their linear definitions. As demonstrated here, the warm events can be well separated into the WP El Niño and CT El Niño based on their SST anomaly patterns. However, it is found that cold events are not easily separated because conventional La Niña events are already shifted to the west compared to the El Niño events. Figure 12 shows individual cold events, which are defined in the same way as the El Niño described in section 2. Though their zonal locations are slightly changed, it is quite difficult to separate them into groups. Most of SST anomaly patterns are similar to those of mixed El Niño events (right panels in Fig. 1). Thus, it can be considered that the WP El Niño is more a stochastic event than an oscillatory phenomenon (cf. Kessler 2002). This is possibly related to the transition mechanism of the WP El Niño. As shown in Fig. 8, the discharge of the WP El Niño is quite weak. The zonal-mean sea level cannot overshoot to a negative sea level anomaly; instead it simply returns to its climatological mean state after its mature phase, in contrast to the CT El Niño. As a result, a cold event hardly ever follows a WP El Niño.
Because the WP El Niño tends to occur mostly in its warm phase, its occurrence and existence can modulate the climate mean state in the tropical Pacific. In other wards, frequent occurrences of WP El Niños contribute to an accumulative warming of the mean state. In fact, the occurrence years of the WP El Niño match well with the warming period of the long-term SST (more than 5 yr) over the central Pacific. For example, during the periods of 1990–95 and 2001–06, there are long-lived SST anomalies in the central Pacific. Their SST patterns are similar to that of the WP El Niño. Related to these warming periods, we found from wavelet analysis that there is distinctive decadal SST variability with 10–15-yr time scale in the central Pacific (not shown). This decadal variability is different from the so-called Pacific decadal oscillation (Latif and Barnett 1994; Graham 1994; Zhang et al. 1997). Likely, this decadal variability is related to the WP El Niño. Further investigation on the relation between the WP El Niño and tropical decadal variability is under way.
It is found that the WP El Niño events occur frequently in recent decades. This is consistent with previous studies (Larkin and Harrison 2005a,b; Ashok et al. 2007). However, it is not clear yet what is responsible for the frequent occurrence of the WP El Niño. It is known that stochastic forcing can excite a damped low-frequency mode in the observational data (e.g., Wang et al. 1999). Furthermore, a state-dependent noise (i.e., multiplicative noise) can lead the so-called eddy-induced instability, which can emerge from a low-frequency mode (Jin et al. 2007). There is clear evidence that the activity of intraseasonal variations is state dependent on ENSO (Hendon et al. 2007; Kug et al. 2008; Tang and Yu 2008) and low-frequency flow (Kug et al. 2009a,b; Sooraj et al. 2009a), so it can be regarded as a multiplicative noise in the tropical Pacific air–sea coupled system. Recently, Kug et al. (2008) reported that intraseasonal variability has increased over the tropical Pacific, and its interaction with ENSO has intensified in recent decades. According to the theoretical framework (Jin et al. 2007), the intensified interaction between ENSO and intraseasonal variability can lead to an amplified conventional ENSO. In addition, it can emerge as a new coupled mode, which was a damped mode when the interaction is weak. Therefore, it is possible that the frequent occurrence of the WP El Niño is related to recent changes in intraseasonal variability and its coupling with low-frequency flow. This hypothesis should be investigated more in further studies.
As shown in Fig. 4, the two types of El Niño events presented here have distinctive anomalous precipitation patterns. This implies that their teleconnections will be quite different. The impact of the WP El Niño SST anomaly over the Niño-4 region (or central Pacific) and its difference from the conventional El Niño have been well documented in previous studies (Larkin and Harrison 2005a,b; Ashok et al. 2007; Weng et al. 2007). The detailed structures of the “new type of El Niño” reported in these publications are somewhat different from those of the WP El Niño described in this study, but the difference is not significant because the composite events are almost the same. Therefore, we will not go into detailed discussion on the impact of the WP El Niño here. Interested readers are referred to the publications cited above. However, further studies are necessary to examine how the WP El Niño may influence regional climate differently from the CT El Niño.
Acknowledgments
The work was supported by NSF Grants ATM-0652145 and ATM-0650552 and NOAA Grant GC01-229. S.-I. An was supported by a grant from the Ministry of Environment of the Korean government and by the SRC program of the Korea Science and Engineering Foundation. J.-S. Kug is partly supported by KORDI (PP00720).
REFERENCES
An, S-I., and F-F. Jin, 2001: Collective role of thermocline and zonal advective feedbacks in the ENSO mode. J. Climate, 14 , 3421–3432.
An, S-I., W. W. Hsieh, and F-F. Jin, 2005: A nonlinear analysis of ENSO cycle and its interdecadal changes. J. Climate, 18 , 3229–3239.
An, S-I., J-S. Kug, A. Timmermann, I-S. Kang, and O. Timm, 2007: The influence of ENSO on the generation of decadal variability in the North Pacific. J. Climate, 20 , 667–680.
Ashok, K., S. K. Behera, S. A. Rao, H. Weng, and T. Yamagata, 2007: El Niño Modoki and its possible teleconnection. J. Geophys. Res., 112 , C11007. doi:10.1029/2006JC003798.
Battisti, D. S., 1988: Dynamics and thermodynamics of a warming event in a coupled tropical atmosphere–ocean model. J. Atmos. Sci., 45 , 2889–2919.
Behringer, D., and Y. Xue, 2004: Evaluation of the global ocean data assimilation system at NCEP: The Pacific Ocean. Preprints, Eighth Symp. on Integrated Observing and Assimilation Systems for Atmosphere, Oceans, and Land Surface, Seattle, WA, Amer. Meteor. Soc., 2.3. [Available online at http://ams.confex.com/ams/pdfpapers/70720.pdf.].
Bejarano, L., and F-F. Jin, 2008: Coexistence of equatorial coupled modes of ENSO. J. Climate, 21 , 3051–3067.
Clarke, A. J., 1994: Why are surface equatorial ENSO winds anomalously westerly under anomalous large-scale convection? J. Climate, 7 , 1623–1627.
Dewitte, B., C. Cibot, C. Périgaud, S-I. An, and L. Terray, 2007: Interaction between near-annual and ENSO modes in a CGCM simulation: Role of the equatorial background mean state. J. Climate, 20 , 1035–1052.
Gill, A. E., 1982: Atmosphere–Ocean Dynamics. Academic Press, 662 pp.
Graham, N. E., 1994: Decadal-scale climate variability in the tropical and North Pacific during the 1970s and 1980s: Observations and model results. Climate Dyn., 10 , 135–162.
Harrison, D. E., and G. A. Vecchi, 1999: On the termination of El Niño. Geophys. Res. Lett., 26 , 1593–1596.
Hendon, H. H., M. Wheeler, and C. Zhang, 2007: Seasonal dependence of the MJO–ENSO relationship. J. Climate, 20 , 531–543.
Hoerling, M. P., A. Kumar, and M. Zhong, 1997: El Niño, La Niña, and the nonlinearity of their teleconnections. J. Climate, 10 , 1769–1786.
Horii, T., and K. Hanawa, 2004: A relationship between timing of El Niño onset and subsequent evolution. Geophys. Res. Lett., 31 , L06304. doi:10.1029/2003GL019239.
Jin, F-F., 1996: Tropical ocean–atmosphere interaction, the Pacific cold tongue, and the El Niño–Southern Oscillation. Science, 274 , 76–78.
Jin, F-F., 1997a: An equatorial ocean recharge paradigm for ENSO. Part I: Conceptual model. J. Atmos. Sci., 54 , 811–829.
Jin, F-F., 1997b: An equatorial ocean recharge paradigm for ENSO. Part II: A stripped-down coupled model. J. Atmos. Sci., 54 , 830–847.
Jin, F-F., 2001: Low-frequency modes of tropical ocean dynamics. J. Climate, 14 , 3874–3881.
Jin, F-F., J-S. Kug, S-I. An, and I-S. Kang, 2003: A near-annual coupled ocean-atmosphere mode in the equatorial Pacific Ocean. Geophys. Res. Lett., 30 , 1080. doi:10.1029/2002GL015983.
Jin, F-F., L. Lin, A. Timmermann, and J. Zhao, 2007: Ensemble-mean dynamics of the ENSO recharge oscillator under state-dependent stochastic forcing. Geophys. Res. Lett., 34 , L03807. doi:10.1029/2006GL027372.
Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437–471.
Kang, I-S., and J-S. Kug, 2002: El Niño and La Niña sea surface temperature anomalies: Asymmetry characteristics associated with their wind stress anomalies. J. Geophys. Res., 107 , 4372. doi:10.1029/2001JD000393.
Kang, I-S., S-I. An, and F-F. Jin, 2001: A systematic approximation of the SST anomaly equation for ENSO. J. Meteor. Soc. Japan, 79 , 1–10.
Kang, I-S., J-S. Kug, S-I. An, and F-F. Jin, 2004: A near-annual Pacific Ocean basin mode. J. Climate, 17 , 2478–2488.
Kao, H-Y., and J-Y. Yu, 2009: Contrasting eastern-Pacific and central-Pacific types of ENSO. J. Climate, 22 , 615–632.
Kessler, W. S., 2002: Is ENSO a cycle or a series of events? Geophys. Res. Lett., 29 , 2125. doi:10.1029/2002GL015924.
Kug, J-S., and I-S. Kang, 2006: Interactive feedback between the Indian Ocean and ENSO. J. Climate, 19 , 1784–1801.
Kug, J-S., I-S. Kang, and S-I. An, 2003: Symmetric and antisymmetric mass exchanges between the equatorial and off-equatorial Pacific associated with ENSO. J. Geophys. Res., 108 , 3284. doi:10.1029/2002JC001671.
Kug, J-S., S-I. An, F-F. Jin, and I-S. Kang, 2005: Preconditions for El Niño and La Niña onsets and their relation to the Indian Ocean. Geophys. Res. Lett., 32 , L05706. doi:10.1029/2004GL021674.
Kug, J-S., B. P. Kirtman, and I-S. Kang, 2006a: Interactive feedback between ENSO and the Indian Ocean in an interactive coupled model. J. Climate, 19 , 6371–6381.
Kug, J-S., T. Li, S-I. An, I-S. Kang, J-J. Luo, S. Masson, and T. Yamagata, 2006b: Role of the ENSO–Indian Ocean coupling on ENSO variability in a coupled GCM. Geophys. Res. Lett., 33 , L09710. doi:10.1029/2005GL024916.
Kug, J-S., F-F. Jin, K. P. Sooraj, and I-S. Kang, 2008: State-dependent atmospheric noise associated with ENSO. Geophys. Res. Lett., 35 , L05701. doi:10.1029/2007GL032017.
Kug, J-S., K. P. Sooraj, F-F. Jin, J-J. Luo, and M. Kwon, 2009a: Impact of Indian Ocean dipole on high-frequency atmospheric variability over the Indian Ocean. Atmos. Res., doi:10.1016/j.atmosres.2008.10.022, in press.
Kug, J-S., K. P. Sooraj, D. Kim, I-S. Kang, F-F. Jin, Y. N. Takayabu, and M. Kimoto, 2009b: Simulation of state-dependent high-frequency atmospheric variability associated with ENSO. Climate Dyn., doi:10.1007/s00382-008-0434-2, in press.
Larkin, N. K., and D. E. Harrison, 2005a: On the definition of El Niño and associated seasonal average U.S. weather anomalies. Geophys. Res. Lett., 32 , L13705. doi:10.1029/2005GL022738.
Larkin, N. K., and D. E. Harrison, 2005b: Global seasonal temperature and precipitation anomalies during El Niño autumn and winter. Geophys. Res. Lett., 32 , L16705. doi:10.1029/2005GL022860.
Latif, M., and T. P. Barnett, 1994: Causes of decadal climate variability over the North Pacific and North America. Science, 266 , 634–637.
Lau, N-C., S. G. H. Philander, and M. J. Nath, 1992: Simulation of ENSO-like phenomena with a low-resolution coupled GCM of the global ocean and atmosphere. J. Climate, 5 , 284–307.
Mantua, N. J., and D. S. Battisti, 1995: Aperiodic variability in the Zebiak–Cane coupled ocean–atmosphere model: Air–sea interactions in the western equatorial pacific. J. Climate, 8 , 2897–2927.
McPhaden, M. J., and Coauthors, 1998: The tropical ocean global atmosphere observing system: A decade of progress. J. Geophys. Res., 103 , 14169–14240.
Meinen, C. S., and M. J. McPhaden, 2000: Observations of warm water volume changes in the equatorial Pacific and their relationship to El Niño and La Niña. J. Climate, 13 , 3551–3559.
Meinen, C. S., and M. J. McPhaden, 2001: Interannual variability in warm water volume transports in the equatorial Pacific during 1993–99. J. Phys. Oceanogr., 31 , 1324–1345.
Neelin, J. D., D. S. Battisti, A. C. Hirst, F-F. Jin, Y. Wakata, T. Yamagata, and S. E. Zebiak, 1998: ENSO theory. J. Geophys. Res., 103 , 14261–14290.
Périgaud, C., and B. Dewitte, 1996: El Niño–La Niña events simulated with Cane and Zebiak’s model and observed with satellite or in situ data. Part I: Model data comparison. J. Climate, 9 , 66–84.
Périgaud, C., S. E. Zebiak, F. Mélin, J-P. Boulanger, and B. Dewitte, 1997: On the role of meridional wind anomalies in a coupled model of ENSO. J. Climate, 10 , 761–773.
Philander, S. G. H., R. C. Pacanowski, N-C. Lau, and M. J. Nath, 1992: Simulation of ENSO with a global atmospheric GCM coupled to a high-resolution, tropical Pacific Ocean GCM. J. Climate, 5 , 308–329.
Rasmusson, E. M., and T. H. Carpenter, 1982: Variations in tropical sea surface temperature and surface wind fields associated with the Southern Oscillation/El Niño. Mon. Wea. Rev., 110 , 354–384.
Smith, T. M., and R. W. Reynolds, 2004: Improved extended reconstruction of SST (1854–1997). J. Climate, 17 , 2466–2477.
Sooraj, K. P., D. Kim, J-S. Kug, S-W. Yeh, F-F. Jin, and I-S. Kang, 2009a: Effects of the low-frequency zonal wind variation on the high-frequency atmospheric variability over the tropics. Climate Dyn., doi:10.1007/s00382-008-0483-6, in press.
Sooraj, K. P., J-S. Kug, T. Li, and I-S. Kang, 2009b: Impact of El Niño onset timing on the Indian Ocean: Pacific coupling and subsequent El Niño evolution. Theor. Appl. Climatol., doi:10.1007/s00704-008-0067-8, in press.
Tang, Y., and B. Yu, 2008: MJO and its relationship to ENSO. J. Geophys. Res., 113 , D14106. doi:10.1029/2007JD009230.
Tozuka, T., and T. Yamagata, 2003: Annual ENSO. J. Phys. Oceanogr., 33 , 1564–1578.
Vecchi, G. A., 2006: The termination of the 1997–98 El Niño. Part II: Mechanisms of atmospheric change. J. Climate, 19 , 2647–2664.
Vecchi, G. A., and D. E. Harrison, 2006: The termination of the 1997–98 El Niño. Part I: Mechanisms of oceanic change. J. Climate, 19 , 2633–2646.
Wallace, J. M., E. M. Rasmusson, T. P. Mitchell, V. E. Kousky, E. S. Sarachik, and H. Von Storch, 1998: On the structure and evolution of ENSO-related climate variability in the tropical Pacific: Lessons from TOGA. J. Geophys. Res., 103 , 14169–14240.
Wang, B., 1995: Interdecadal changes in El Niño onset in the last four decades. J. Climate, 8 , 267–285.
Wang, B., A. Barcilon, and Z. Fang, 1999: Stochastic dynamics of El Niño–Southern Oscillation. J. Atmos. Sci., 56 , 5–23.
Wang, B., R. Wu, R. Lukas, and S. I. An, 2001: A possible mechanism for ENSO turnabout. Dynamics of Atmospheric General Circulation and Climate, IAP/Academia Sinica, Eds., China Meteorological Press, 552–578.
Weisberg, R. H., and C. Wang, 1997a: A western Pacific oscillator paradigm for the El Niño-Southern Oscillation. Geophys. Res. Lett., 24 , 779–782.
Weisberg, R. H., and C. Wang, 1997b: Slow variability in the equatorial west-central Pacific in relation to ENSO. J. Climate, 10 , 1998–2017.
Weng, H., K. Ashok, S. K. Behera, S. A. Rao, and T. Yamagata, 2007: Impacts of recent El Niño Modoki on dry/wet conditions in the Pacific rim during boreal summer. Climate Dyn., 29 , 113–129. doi:10.1007/s00382-007-0234-0.
Xie, P., and P. A. Arkin, 1996: Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. J. Climate, 9 , 840–858.
Xu, J., and J. C. L. Chan, 2001: The role of the Asian–Australian monsoon system in the onset time of El Niño events. J. Climate, 14 , 418–433.
Zebiak, S. E., 1984: Tropical atmospheric–ocean interaction and the El Niño/Southern Oscillation phenomenon. Ph.D. thesis, MIT, 261 pp.
Zhang, Y., J. M. Wallace, and D. S. Battisti, 1997: ENSO-like interdecadal variability: 1900–93. J. Climate, 10 , 1004–1020.
SST anomalies of El Niño events during 1970–2005. The anomalies are averaged from September to the following February. Shading indicates normalized anomalies; contour interval is 0.3 K. The El Niño events are classified into (left) WP El Niño, (middle) CT El Niño, and (right) mixed El Niño. The green boxes indicate (left) Niño-4, (middle) Niño-3, and (right) Niño-3.4 regions.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
Normalized Niño-4 SST (dark bar) and Niño-3 SST (light bar) of each El Niño event shown in Fig. 1.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
SST anomaly composites of the (left) CT El Niño and (middle) WP El Niño during (a) JJA(0), (b) SON(0), (c) D(0)JF(1), and (d) MAM(1). Light and dark shadings indicate the 90% and 95% confidence levels, respectively. Confidence levels are calculated from a Student’s t test. (right) Pattern correlation between 3-month-averaged WP and CT El Niño anomalies over 20°S–20°N, 120°E–90°W; the x axis indicates months from June to May [J(0)–M(1)].
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
As in Fig. 3 but for precipitation (mm day−1) composites.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
As in Fig. 3 but for pressure velocity (Pa s−1) composites at 500 hPa.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
As in Fig. 3 but for zonal wind (m s−1) composites at 925 hPa.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
Sea level (cm) composites of (a) the CT El Niño and (b) the WP El Niño from November to the following January. Light and dark shadings indicate the 90% and 95% confidence levels, respectively.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
Composites of sea level (cm) averaged over 140°E–90°W for (a) CT El Niño and (b) WP El Niño events.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
Composites of sea level (contour) and mixed layer current (vector) for the WP El Niño. Light and dark shadings indicate the 90% and 95% confidence levels for sea level, respectively. Only currents with velocity greater than 8 cm s−1 are shown.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
Composites of each term in the SST equation for the WP El Niño in the boxes of (a) 5°S–5°N, 150°E–150°W; (b) 5°S–5°N, 150°E–180°; and (c) 5°S–5°N, 180°–150°W. The thick solid and dashed black lines indicate SST tendency and total advection of the nine advection terms, respectively. Red, green, and blue lines indicate vertical, zonal advection, and meridional advection, respectively. Solid and dashed lines indicate contributions by the anomalous current and anomalous temperature distribution, respectively. For example, the green solid line indicates zonal advection by the anomalous zonal current and the mean zonal temperature gradient. Dotted lines indicate nonlinear advection terms.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
WP El Niño composites of (a) zonal wind stress and (b) magnitude of wind stress averaged over 5°S–5°N. Light and dark shadings indicate the 90% and 95% confidence levels, respectively.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
SST anomalies of the selected La Niña events. SST anomalies are averaged from September to the following February. Shading indicates normalized anomalies; contour interval is 0.3 K.
Citation: Journal of Climate 22, 6; 10.1175/2008JCLI2624.1
