Abstract

The Indian Ocean witnessed a weak positive Indian Ocean dipole (IOD) event from the boreal summer to autumn in 2015, while an extreme El Niño occurred over the tropical Pacific. This was different from the case in 1997/98, when an extreme El Niño and the strongest IOD took place simultaneously. The analysis here suggests that the unique sea surface temperature anomaly (SSTA) pattern of El Niño in 2015 might have contributed to the weak IOD that year. El Niño in 2015 had a complex SSTA pattern, with positive warming over the central and eastern tropical Pacific. Such a combination of the classic El Niño (also known as cold-tongue El Niño) and the recently identified central Pacific El Niño (also known as El Niño Modoki II) had opposite remote influences on the tropical Indian Ocean. The classic El Niño reduced the strength of the Walker circulation over the tropical Indian Ocean, but this was offset by El Niño Modoki II. This study points out that the IOD can be strongly modulated by combined El Niño types in some circumstances, as in 2015.

1. Introduction

The Indian Ocean dipole (IOD) is known as an air–sea coupled mode in the tropical Indian Ocean Basin at the interannual time scale (Saji et al. 1999; Webster et al. 1999), which has remote impacts on climate variability in Africa, South Asia, East Asia, and the Pacific region (e.g., Saji and Yamagata 2003a,b; Ashok et al. 2004b; Behera et al. 2005; Cai et al. 2005; Yu et al. 2005; England et al. 2006; Wang et al. 2006; Du et al. 2013; Liu et al. 2013; Zhao et al. 2016). IOD features a seesaw distribution of sea surface temperature anomalies (SSTAs) crossing the tropical Indian Ocean Basin, with positive (negative) SSTAs over the southeastern tropical Indian Ocean off Java–Sumatra and negative (positive) SSTAs over the western tropical Indian Ocean; it is associated with corresponding zonal wind anomalies along the central equatorial Indian Ocean. IOD has phase locking in the boreal autumn, in contrast to El Niño’s phase locking in the boreal winter. Previous studies illustrated that both dynamic and thermodynamic feedback mechanisms (Bjerknes 1966, 1969; Xie and Philander 1994; Webster et al. 1999; Li et al. 2003; Liu et al. 2011, 2014) are responsible for the evolution of an IOD event. State-of-the-art climate models have some capability in simulating and predicting IOD remote impacts as well as its development (Luo et al. 2007, 2008). However, assessments based on phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively) identified some key shortcomings behind the strong diversity of these models in simulating observed IOD amplitude and phase (Saji et al. 2006; Liu et al. 2011, 2014; Zheng et al. 2013; Weller and Cai 2013).

It was found that almost half of the positive IOD events co-occurred with El Niño (Meyers et al. 2007), and it seems a positive IOD occurred more frequently with El Niño events since the mid-1970s, based on observations (Annamalai et al. 2005; Roxy et al. 2011). Previous studies pointed out that there is an intrinsic interaction between El Niño and IOD via the Walker circulation (Luo et al. 2010; Cai et al. 2011; Zhang et al. 2015) as well as the off-equatorial anticyclonic circulation (Yu et al. 2005; Drbohlav et al. 2007). Researchers suggested that an IOD event may be more predictable if it occurs simultaneously with an El Niño (Song et al. 2007; Zhu et al. 2015). For example, in 1997 the extreme positive IOD in the Indian Ocean co-occurred with an unprecedented strong El Niño in the Pacific (Saji et al. 1999; Webster et al. 1999). Ashok et al. (2007) called the substantial warming that develops in the central Pacific an El Niño Modoki. Wang and Wang (2013) and Wang and Wang (2014) further separated El Niño Modoki into El Niño Modoki I and II. The warm sea surface temperature (SST) anomalies originate in the equatorial central Pacific and subtropical northeastern Pacific for El Niño Modoki I and II, respectively. Wang and Wang (2014) found that El Niño Modoki I favors the development of a positive IOD event, while El Niño Modoki II is favorable for the development of a negative IOD according to the Bjerknes feedback. Under global warming scenarios, the frequencies of extreme El Niño events and extreme IODs are expected to increase in response to a slowdown of the Walker circulation (Cai et al. 2014a,b).

In this paper, we use reanalysis data as well as observations to address possible mechanisms responsible for the weak IOD during 2015 associated with the extreme El Niño in the tropical Pacific Ocean. The rest of the paper is organized as follows. In section 2, we introduce the datasets used in this research. In section 3, we show diagnosis results, which are discussed in section 4. Finally, we summarize the main findings in section 5.

2. Data

The SST data are from the Met Office Hadley Centre Sea Ice and Sea Surface Temperature dataset (HadISST; Rayner et al. 2003); the period used is between December 1981 and May 2016. The wind field data are from the NCEP–NCAR Reanalysis-1 (Kalnay et al. 1996); the period used is from January 1948 to May 2016. The ocean subsurface temperature data are from the NCEP Global Ocean Data Assimilation System (GODAS); the period used is from January 1980 to February 2016. The climatological annual cycle for each variable is calculated based on the available data period, and the interannual anomalies are obtained by subtracting the climatological annual cycles from monthly mean variables. We use the Niño-3 index for identifying ENSO. The IOD mode index (DMI) is calculated based on Saji et al. (1999): namely, the difference of SSTA between (10°S–10°N, 50°–70°E) and (0°–10°S, 90°–110°E). For extreme El Niño events or extreme IOD events, two standard deviations are used.

3. Results

a. IOD evolution in 2015

Figure 1 presents the evolution of DMI in 2015. The IOD in 2015 began to develop in the boreal summer with a relatively weak amplitude, peaked in the fall season with the maximum value reaching 0.8°C, and rapidly decayed in December. Considering the strength during the evolution and the peak time, the IOD in 2015 is defined as a weak positive IOD event. In the tropical Pacific region, an extreme El Niño developed in 2015. El Niño grew stronger until November, with the Niño-3 index approaching 2.7°C, which was much higher than its historical composite value.

Fig. 1.

Time series of IOD (red) and ENSO (blue) indices for 2015 (solid) and composite mean of 1997 and 1982 (dashed). The IOD index is defined as the difference of SSTA (°C) between (10°S–10°N, 50°–70°E) and (0°–10°S, 90°–110°E). The ENSO index is defined as the average SSTA of (5°S–5°N, 150°–90°W).

Fig. 1.

Time series of IOD (red) and ENSO (blue) indices for 2015 (solid) and composite mean of 1997 and 1982 (dashed). The IOD index is defined as the difference of SSTA (°C) between (10°S–10°N, 50°–70°E) and (0°–10°S, 90°–110°E). The ENSO index is defined as the average SSTA of (5°S–5°N, 150°–90°W).

In general, a strong El Niño event tends to be accompanied by a strong IOD event (Luo et al. 2010). Figure 1 shows the evolution of the composite DMI and Niño-3 index for extreme events during 1982/83 and 1997/98. In 2015, the strength of the IOD was weaker, particularly in October and November.

Figure 2 shows the seasonal evolution of SSTAs and surface wind anomalies in 1997 and 2015 and their differences. The IOD in 2015 featured a very weak and limited region of negative SSTAs offshore of Sumatra and Java, in contrast to the strong and wider negative SSTA area in 1997. At the same time, the sea surface wind field also presented a much less organized pattern. The southeasterly wind anomaly along Sumatra–Java and the easterly wind anomaly along the equatorial Indian Ocean, which were the typical features during normal IOD events, did not fully develop during the boreal summer in 2015. In the mature phase of the IOD (the boreal fall season), the easterly anomaly occupied the central-to-eastern equatorial Indian Ocean from 80° to 100°E, while the western equatorial Indian Ocean was controlled by significant westerly wind anomalies (Fig. 2).

Fig. 2.

Seasonally averaged SSTA (°C) for (left) 1997, (center) 2015, and (right) the difference between 2015 and 1997 in (top)–(bottom) boreal spring (MAM), boreal summer (JJA), boreal fall (SON), and boreal winter (DJF). The arrows indicate the surface wind field. The purple contours indicate the significant area at the 90% confidence level.

Fig. 2.

Seasonally averaged SSTA (°C) for (left) 1997, (center) 2015, and (right) the difference between 2015 and 1997 in (top)–(bottom) boreal spring (MAM), boreal summer (JJA), boreal fall (SON), and boreal winter (DJF). The arrows indicate the surface wind field. The purple contours indicate the significant area at the 90% confidence level.

b. Comparison between 2015 and 1997

In 2015, the tropical Pacific experienced a strong El Niño event, which originated in the second half of the year 2014 and was one of the strongest El Niño events in history. However, the tropical Indian Ocean did not witness a strong positive IOD event, as it did in 1997. This raises the question of why the tropical Indian Ocean had different SSTA spatial patterns associated with seemingly similar extreme El Niño events in 1997 and 2015. Considering an extreme El Niño existed in the tropical Pacific region in both 1997 and 2015, their detailed structure differences may provide useful information for understanding the possible mechanism responsible for the weak positive IOD event in 2015.

The SSTA distribution in the tropical Indian Ocean exhibited differences between 1997 and 2015 (Fig. 2). The spatial distribution of SSTA in 2015 showed a positive IOD pattern, with the negative SSTAs covering a limited area to the west of Sumatra and the positive SSTAs covering the western-to-central tropical Indian Ocean. In 1997, the positive IOD also showed an SSTA seesaw pattern in the tropical Indian Ocean, with stronger negative SSTAs over the region to the west of Sumatra. The SSTA differences between these two years indicate a negative IOD-like pattern. In the tropical Pacific, the difference map shows significant warm SSTAs over the central Pacific, expanding into the northeastern subtropical Pacific region. Consistent with the above SSTA differences, the surface wind differences also present significant northward wind crossing the equator, prevailing from the central to the eastern Pacific (Fig. 2).

The Walker circulation confirmed the dramatic and distinct atmospheric responses to the SSTA differences. In 1997, there were two pairs of fully developed anomalous Walker circulation cells, with one descending center over the Maritime Continent and two rising centers over the eastern tropical Pacific Ocean and western tropical Indian Ocean, respectively (Fig. 3). The conditions were different in 2015. The rising branch over the Pacific shifted from the eastern Pacific to the central tropical Pacific. The difference in the anomalous Walker circulation over the Indian Ocean exhibited a negative IOD–like pattern that ultimately blocked the further development of a positive IOD event in 2015.

Fig. 3.

As in Fig. 2, but for the Walker circulation (m s−1) along the equator at different pressure levels.

Fig. 3.

As in Fig. 2, but for the Walker circulation (m s−1) along the equator at different pressure levels.

Figure 4 shows the distribution of thermocline depth anomaly, denoted by the 20° isothermal depth, in 1997 and 2015. The significant equatorial downwelling Kelvin wave reached the eastern Indian Ocean in the spring season and split into the strong coastal Kelvin waves in the autumn season in 1997, associated with a deepening thermocline and cold SSTAs. In contrast, a weaker equatorial downwelling Kelvin wave and weaker coastal Kelvin waves were found in 2015, which indicates a weaker IOD event.

Fig. 4.

Seasonally averaged thermocline depth anomaly (m; shading) for (left) 1997 and (right) 2015 in (top)–(bottom) boreal spring (MAM), boreal summer (JJA), and boreal winter (DJF).

Fig. 4.

Seasonally averaged thermocline depth anomaly (m; shading) for (left) 1997 and (right) 2015 in (top)–(bottom) boreal spring (MAM), boreal summer (JJA), and boreal winter (DJF).

4. Discussion

Our analysis revealed that there was a weak IOD event accompanied by an extreme El Niño event in 2015, which was beyond our common understanding that a strong El Niño favors strong positive IOD development through the dynamic connection (Song et al. 2008; Luo et al. 2010; Guo et al. 2015; Zhu et al. 2015). Why was there a weak IOD event in the tropical Indian Ocean associated with an extreme El Niño event in the Pacific in 2015? Here, we argue that the unique El Niño SSTA pattern in 2015 really was the main reason.

Wang and Wang (2013) and Wang and Wang (2014) suggested that there are two different types of central Pacific El Niño (or El Niño Modoki) events. Their second type of central Pacific El Niño [El Niño Modoki II (EM-II)] displays an asymmetric distribution, with the warm SSTAs extending from the northeastern Pacific to the central equatorial Pacific, and shows great impacts on rainfall in southern China and typhoon landfall activity as well as on the IOD event. Since EM-II is associated with an increased Walker circulation in the Indo-Pacific region, which increases precipitation over the tropical eastern Indian Ocean and the Maritime Continent, it results in surface westerly wind anomalies off Java–Sumatra; EM-II is therefore unfavorable for positive IOD development through the Bjerknes feedback (Liu et al. 2011, 2014).

The SSTA distribution in 2015 was shown as the combination of the classic El Niño and EM-II. Figure 2 displays a significant warm SSTA signal in the northeastern Pacific from the boreal spring. In the following summer, the warm signal from the northeastern Pacific extended into the central equatorial Pacific, accompanied by significant warming over the eastern equatorial Pacific. Under such circumstances, the Walker circulation in the tropical Indian Ocean also presented the mixed feature between the classic El Niño and EM-II. The classic El Niño reduced the Walker circulation over the tropical Indian Ocean, and EM-II strengthened it, which offset the loading from the classic El Niño. The observation reflected the combined effect of the two remote forcing factors from the Pacific: namely, weaker easterly wind along the equatorial Indian Ocean, which was unfavorable for the development of a positive IOD event. For example, the westerly wind anomaly prevailed over the western equatorial Indian Ocean, and the easterly wind anomaly prevailed over the central-to-eastern Indian Ocean during the boreal fall season (Fig. 2). According to the Bjerknes feedback theory, the westerly wind anomaly along the equatorial Indian Ocean was against the development of a positive IOD event, which resulted in a weaker positive IOD event in 2015. We further calculated the Bjerknes feedback strength during IOD events in 1997 and 2015, respectively. Table 1 shows the value of Bjerknes feedback components based on the Bjerknes feedback index (Liu et al. 2011). The Bjerknes feedback processes include the equatorial zonal wind response to SST R(u, t), the thermocline response to the equatorial zonal wind R(d, u), and the ocean subsurface temperature response to the thermocline variation R(t, d). The term R means the feedback processes, u is the zonal wind anomaly at the central equatorial Indian Ocean, t is the SSTA at southeast Indian Ocean, and d is the anomalous thermocline depth at southeast Indian Ocean. Bjerknes feedback processes were stronger in 1997 than in 2015 for R(u, t) and R(d, u), but not for R(t, d). The Bjerknes feedback strength of the positive IOD event also indicated that internal dynamic processes were weaker in 2015, which further suggests that EM-II was unfavorable for positive IOD development through modulating the atmospheric circulation.

Table 1.

Bjerknes feedback strength during IOD events in 1997 and 2015.

Bjerknes feedback strength during IOD events in 1997 and 2015.
Bjerknes feedback strength during IOD events in 1997 and 2015.

Besides the type of El Niño in 2015, some other factors might also contribute to the weak IOD that year. Zhang et al. (2015) suggested that the SSTAs being farther west than normal during the central Pacific El Niño was unfavorable for positive IOD development. This argument may be correct, though the identification of the exact SSTA location is somewhat sensitive. Other possible reasons for the weak IOD in 2015 may include the decadal variability of the IOD event (Ashok et al. 2004a; Tozuka et al. 2007) and the Asian summer monsoon variation (Cai et al. 2013). A weak positive IOD event associated with a strong El Niño event took place in 1982, and the SSTA distribution in 1982 showed a different spatial distribution compared with that in 2015: namely, there was no EM-II event in 1982. One possible explanation for the weak positive IOD event in 1982 might be the decadal variability of IOD (Tozuka et al. 2007).

5. Summary

In this study, we aimed to reveal the evolutionary features of a positive IOD event in 2015 accompanying an extreme El Niño event over the tropical Pacific. The results indicated that there was an anomalous weak positive IOD event in 2015. Our analysis suggested that the abnormal distribution of SSTAs over the tropical Pacific contributed to the weak positive IOD development in 2015. The tropical Pacific featured a mixture of the classic El Niño and El Niño Modoki II, which led to two competing anomalous Walker circulations over the tropical Indian Ocean. Consequently, the westerly wind anomaly dominated the western equatorial Indian Ocean, while the easterly wind anomaly prevailed over the central-to-eastern Indian Ocean. The westerly anomaly weakened the positive IOD development through exciting the downwelling Kelvin waves. It should be kept in mind that we provide a possible mechanism to explain the surprisingly weak IOD in 2015 when an extremely strong El Niño happened in the Pacific. Future work, particularly numerical experiments, is needed to verify this mechanism.

Acknowledgments

We thank the anonymous reviewers for their constructive comments and suggestions on the earlier versions of this manuscript. GODAS data are provided by the NOAA/OAR/ESRL Physical Sciences Division (PSD), Boulder, Colorado, and can be downloaded at their website (http://www.esrl.noaa.gov/psd/). This research is jointly funded by the Global Change and Air–Sea Interaction Program (GASI-IPOVAI-03, Dr. Lin Liu; GASI-IPOVAI-02, Dr. Weidong Yu), the Basic Scientific Research Fund for National Public Institutes of China (GY2015P04), the National Natural Science Foundation of China (41376037, 41306030, 41375094, and 41406028), NSFC-Shandong Joint Fund for Marine Science Research Centers (U1606405), 973 project (2012CB955601), Open Fund of the Key Laboratory of Ocean Circulation and Waves, Chinese Academy of Sciences (KLOCAW1501, Dr. Guang Yang), and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA11010102).

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Footnotes

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