Revised and Resubmitted to Journal of Climate November 2005 Abstract




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  1. The tropical Atlantic meridional mode and zonal mode have emerged as two dominant regional climate phenomena. Important progress has been made in understanding the underlying physics of these climate fluctuations. A general consensus is emerging that the thermodynamic feedback is a key element of the meridional mode dynamics, whereas the dynamic feedback is an important part of the zonal mode dynamics.
  2. The combined effect of remote influence of ENSO and the thermodynamic feedback can lead to useful seasonal prediction of the climate anomaly associated with the meridional mode during boreal spring.
  3. The potential that the tropical Atlantic coupled system can respond effectively changes in the MOC, because of the interaction between the STCs and MOC, has been demonstrated, raising the possibility that the Atlantic coupled system may be of particular importance to anthropogenic climate change.

Despite of the encouraging progress, many fundamental problems remain unanswered. The following is a list of some of the key issues and major uncertainties in TAV research:


  1. Although a number of oceanic processes have been proposed to play a role in the meridional mode, there is no consensus on which of these processes dominate. In particular, it remains uncertain whether any of these oceanic processes, through interacting with the atmosphere, can introduce a preferred time scale to TAV.

  2. Use prediction skill for the sea surface temperature (SST) anomaly in the equatorial Atlantic has not been demonstrated, indicating a lack of basic understanding of predictable dynamics associated with the Atlantic zonal mode. The extent to which the oceanic memory mechanism associated with the delayed oscillator operates in the Atlantic zonal mode remains undetermined.

  3. Many details concerning the role of tropical-extratropical exchanges via STCs and the MOC in TAV at decadal and longer time scales remain to be worked out. Currently, it is still unclear how changes in the MOC affect the pathways of the STCs, and how these changes in the STCs affect the SSTs, and finally how these SST changes can affect the coupled climate variability in the tropical Atlantic.



4. Indian Ocean Dipole (IOD)


Recent progresses in Indian Ocean research led to the discovery of an ocean-atmosphere coupled phenomenon known as the Indian Ocean Dipole (IOD) mode (Saji et al. 1999; Yamagata et al. 2003a, 2004), which is also known as the Indian Ocean Zonal (IOZ) mode (e.g. Webster et al. 1999; Clark et al. 2003). The IOD is characterized by an east-west dipole pattern in SST anomalies. The anomalous SSTs are found to be closely associated with changes in surface winds; equatorial winds reverse direction from westerlies to easterlies during the peak phase of the positive IOD events when SST is cool in the east and warm in the west (Fig. 13a). The air-sea interaction is evident from the lagged correlation among the equatorial zonal wind index (derived as in Saji et al. 1999), the anomalies of SST and heat content (Fig. 13a); the latter two are significantly correlated to the former at one season ahead. It is also found that the ocean conditions related to the IOD have significant lead correlation to the East African short rains (Behera et al. 2005a). Therefore, the surface wind anomalies are part of a basin-wide anomalous Walker circulation (Yamagata et al. 2002, 2003a) related to the ocean-atmsophere coupling of IOD. The anomalous response of the tropical atmosphere to the IOD SST anomalies, with the subsidence over colder pole and the upward motion over the warmer pole, is further supported by AGCM experiments (Guan et al. 2003; Ashok et al. 2003b). In the coupled feed-back process, those zonal wind anomalies affect the anomalies in upper ocean, elevating (deepening) the thermocline in the east (west), and thus giving rise to a subsurface dipole (Rao et al. 2002a; Feng and Meyers 2003; Shinoda et al. 2004a) as found in Fig. 13b.


The notion that the IOD is an independent physical mode inherent to the tropical Indian ocean-atmosphere coupled system has been discussed recently (Saji et al. 1999; Yamagata et al. 2003a 2004; Behera et al. 2005b). The independent nature of IOD events is observed in some years even in a simple visual analysis of the raw data; for example, strong, positive IOD events occurred in 1961, 1967 and 1994. The historical positive and negative IOD events that occur without the presence of El Niño or La Niña have been called “pure” events. The independent nature of the IOD is also seen in pure composites of SST anomalies (Yamagata et al. 2004) in the observed data (Fig. 14a, b). It may be noted that the SST anomalies are stronger in the pure IOD composite as compared to the all IOD composite. A dipole-like pattern emerges in the Indian Ocean in the composite for all ENSO years because of co-occurrence of some IOD events with ENSO. The Indian Ocean pattern almost disappears in a pure ENSO composite (Fig. 14c, d). A careful analysis shows that a significant number of the IOD events are independent of ENSO and only about 30% of them co-occur with ENSO (Rao et al. 2002a; Yamagata et al. 2003a, 2004). Therefore, the IOD can not be simply explained as a passive response to ENSO as in the case of TAV. Its distinctive characteristics require invoking regional ocean-atmosphere interaction.


Like other tropical phenomena, the evolution of the IOD is strongly locked to the annual cycle; the phenomenon typically develops during May/June, peaks in September/October and diminishes in December/January. Its development phase coincides with the onset of Indian summer monsoon, while its peak phase roughly coincides with the onset of boreal winter monsoon. We notice that the IOD peak phase is different from that of ENSO. There are further marked differences in the rainfall variability associated with IOD and ENSO. Behera and Yamagata (2003) showed that the IOD influences the Darwin pressure variability, i.e., one pole of the Southern Oscillation. This Indian Ocean influence on ENSO variability is also reported in a few recent studies (e.g. Wu and Kirtman 2004; Annamalai et al. 2005a). Positive IOD and El Niño have similar impacts in the Indonesian region owing to anomalous atmospheric subsidence, and thereby induce drought there. However, the variability in East African short rains during boreal fall are more likely to be associated with the IOD (Black et al. 2003; Saji and Yamagata 2003b; Behera et al. 2005a) rather than ENSO as indicated by previous studies (Ropelewski and Halpert 1987; Ogallo 1989; Hastenrath et al. 1993; Mutai and Ward 2000). The impact of the IOD is not limited only to the equatorial Indian Ocean. It is found that the IOD influences the global climate system (e.g. Saji and Yamagata 2003b) through changes in the global atmospheric circulation. For example, the IOD influences the Southern Oscillation in the Pacific (Behera and Yamagata 2003), rainfall variability during the Indian summer monsoon (Behera et al. 1999; Ashok et al. 2001), the summer climate condition in East Asia (Guan and Yamagata 2003; Guan et al. 2003), the African rainfall (Black et al. 2003; Clark et al. 2003; Behera et al. 2003b, 2005a; Rao and Behera 2005), the Sri Lankan Maha rainfall (Zubair et al. 2003) and the Australian winter climate (Ashok et al. 2003b). Fig. 15 distinguishes the global rainfall variability associated with the IOD from those of ENSO based on partial correlation and pure composite analysis of observed data (Saji and Yamagata 2003b, and Yamagata et al. 2004).


Discovery of the IOD has stimulated exciting research in other disciplines of science such as paleoclimate, marine biology and atmospheric chemistry. In a recent paper, Abram et al. (2003) reported that the scattered particulates from severe wildfires in the Indonesian region during the 1997 IOD event caused exceptional coral bleaching in the Mentawai Island (off Sumatra) reef ecosystem. They also traced the IOD signal back to the mid-Holocene period using the fossil coral records from the region, revealing the first evidence of paleo-IOD. In another context, Fujiwara et al. (1999) found that the variability in tropospheric ozone distribution over Indonesia is related to the IOD phenomenon.


a. Coupled air-sea feedback in the IOD


The evolution of the IOD during its development and peak phase clearly involves active ocean-atmosphere interaction. The coupled mechanism appears to be predominantly dynamical in nature, involving feedbacks between winds and SSTs through upper equatorial ocean dynamics (Fig. 13a). As noted earlier, during the peak phase of the positive IOD events SST is colder than normal in the east and warmer than normal in the west (Fig. 13b). The atmosphere responds to this anomalous SST with a basin-wide anomalous Walker circulation (Yamagata et al. 2002, 2003a) causing the equatorial winds to reverse direction from westerlies to easterlies. The anomalous winds lift (deepen) the thermocline in the east (west) giving rise to a basin-wide subsurface dipole as shown in Fig. 13b (Rao et al. 2002a; Feng and Meyers 2003). Since the seasonal southeasterly winds along the Java coast are also strengthened during the positive IOD events, the anomalous coastal upwelling combined with the shallow thermocline causes anomalous SST cooling near the coast, in addition to enhanced evaporative cooling in a larger area off shore (Behera et al. 1999). The deeper thermocline in the west forms through the Ekman pumping/Rossby wave mechanism (Murtugudde et al. 2000; Rao et al. 2002a; Xie et al. 2002; Feng and Meyers 2003) and generates a warm SST anomaly there. The SST gradient across the ocean is thus increased by mechanisms acting in both the east and the west, which leads to further enhancement of the atmospheric response. These oceanic and atmospheric conditions fit to the general description of a Bjerknes-type feedback (Bjerknes 1969), suggesting that the Bjerknes mechanism is a key for the IOD evolution. Behera et al. (1999), Yamagata et al. (2002) and Behera and Yamagata (2003) provide further observational evidence for the dipole pattern of OLR anomalies and sea level pressure anomalies associated with the IOD.

Coupled model studies are generally supportive of the independent nature of the IOD as an intrinsic physical mode and the importance of local ocean-atmosphere feedbacks in its evolution. We particularly note that various coupled general circulation models (CGCMs) are now successful in reproducing the IOD events and have provided a solid dynamical basis for its existence. Iizuka et al. (2000) found a remarkable similarity between the observed IOD and model IOD from their moderately high resolution CGCM. The model IOD in their results shows a quasi-biennial tendency and is largely independent of the model ENSO (e.g. Behera et al. 2005b). The characteristic of IOD and its independence from ENSO are also observed in the SINTEX-F1 simulation (Yamagata et al. 2004), which shows improvement in simulated ENSO power spectra owing to the high resolution atmospheric model (cf. Guiyalrdi et al. 2004). In addition, Yamagata et al. (2004) demonstrated that the coupled Rossby waves in southern equatorial Indian Ocean are associated with IOD, as in the observation (e.g. Xie et al. 2002; Rao and Behera 2005). Behera et al. (2003b, 2005a), after deriving an index for the East African short rains, have shown that the SINTEX-F1 coupled model (Luo et al. 2003, 2005a,b; Masson et al. 2004) reproduces an east-west SST dipole in the correlation between short rains index and SST anomalies in the Indian Ocean. The correlation evolves one season prior to the peak IOD season that coincides with the season of short rains.


The independent development of IOD is reported by most other CGCM studies (Yu et al. 2002; Gualdi et al. 2003; Lau and Nath 2004; Cai et al. 2004; Fisher et al. 2005) except for two exceptions (Baquero-Bernal et al. 2002; Yu and Lau 2004). The latter two studies suggest that IOD is primarily forced by ENSO. Based on an experiment in which ENSO is suppressed, Baquero-Bernal et al. (2002), in particular, suggest that the dipole mode only detected during boreal fall in their CGCM is not necessarily related to the ocean dynamics. Rather they claim that it is forced stochastically by the atmosphere. In contrast, Behera et al. (2005b), based on a similar experiment using the SINTEX-F CGCM, demonstrate that the subsurface Indian Ocean plays a significant role in the IOD development even in the absence of ENSO.


Cai et al. (2004), using the CSIRO Mark3 coupled model, have found that most of the model IOD evolves after the demise of model ENSO without simultaneous relationship between them. The strong association of their model IOD with the model ENSO at one year lag is attributed to the model bias caused by a too active intrusion of the Indonesian throughflow from the western tropical Pacific owing to coarse ocean model resolution. From a 900-year GFDL CGCM experiment, Lau and Nath (2004) found recurrent evolution of IOD patterns. As in the observation, some strong IOD episodes in their model occur even in the absence of ENSO. They suggest that the IOD evolution is attributable to multiple factors: internal air-sea positive feedback processes, remote influences due to ENSO, and extratropical changes in the Southern Ocean. Gualdi et al. (2003) found significant correlations between sea level pressure anomalies in the southeastern Indian Ocean and sea surface temperature anomalies in the tropical Indian and Pacific Oceans in both observations and a multi-decadal simulation. In particular, a positive SLP anomaly in the southeastern part of the basin is shown to produce favorable conditions for the development of an IOD event which was discussed in detail by Li et al. (2003).


As in the case of Pacific ENSO, CGCMs are proving to be useful in predictability experiments of the IOD. Using the NASA Seasonal–to–Interannual Prediction Project (NSIPP) coupled model, Wajsowicz (2004) has shown that ensemble hindcasts of the SST anomalies averaged over the two poles of the IOD are encouragingly good at 3 months lead-time for the decade 1993–2002 including extreme positive events in 1994 and 1997/98. The onset of the 1997/98 event is delayed by about a month, though the model ensemble correctly predicts the peak and decay phases. At 6 months lead–time, the forecast skill of the eastern pole deteriorates. Using the high resolution SINTEX-F prediction system, Luo et al. (2005c) have shown good skill in predicting the 1994 IOD event at 2-3 seasons lead. Retrospective ensemble forecasts for the past two decades show a winter prediction barrier due to the intrinsic strong seasonal phase-locking of IOD and a weak spring barrier associated with the Pacific variability.


The dynamically consistent long time series data obtained from CGCM simulations are useful for studies of low frequency variability (Ashok et al. 2004). Using output from a 200-year integration of the SINTEX-F1 CGCM, Tozuka et al. (2005) investigated the decadal climate variability in the tropical Indian Ocean. In their analysis, the first EOF mode of the band-pass (9-35 years) filtered sea surface temperature anomaly represents a basin-wide mode that has a close connection with the Pacific ENSO-like decadal variability. The second EOF mode shows a clear east-west dipole pattern. Since the pattern resembles the interannual IOD despite the longer time scale, the mode is named the decadal IOD. One of the most interesting suggestions is that the decadal air-sea interaction in the tropics could be a statistical artifact; the decadal IOD may be interpreted as decadal modulation of interannual IOD events (Tozuka et al. 2005). The appearance of the model decadal IOD is related to a) frequency modulation, b) amplitude modulation and, most importantly, c) asymmetric occurrence of positive and negative events. The origin of the decadal behavior of IOD both in models and observations needs to be clarified. Possible tropical and subtropical interactions through oceanic processes in response to monsoon variability, in addition to roles of the Indonesian throughflow, appear to be a key for the understanding of the decadal IOD.


b. Remote influence from the Pacific


The importance of the remote influence of Pacific ENSO on variability in the Indian Ocean has long been recognized. In fact, the conventional view was that the variability in the Indian Ocean sector is completely dominated by the remote influence of ENSO. Indeed, a basin-wide SST anomaly of almost uniform polarity that is highly correlated with ENSO in the Pacific is present as the most dominant interannual mode in the Indian Ocean (Cadet 1985; Klien et al. 1999). In most of cases, the basin-wide anomaly is first established in the west through the weakening of the Findlater jet and then spreads eastward as the warm ENSO matures. The weakening of the Indian summer monsoon is caused by the anomalous downdraft related to a warm ENSO episode. Compared to the zonal SST dipole anomalies associated with IOD, those ENSO-induced monopole SST anomalies dominate the basin and occur more frequently with longer persistence (see Fig. 1 in Yamagata et al. 2004). For these reasons, this pattern emerges as the leading mode in statistical analyses, such as Empirical Orthogonal Function (EOF) analysis, whereas the IOD often appears as the second mode.


It is quite rare for climate dynamists to discuss a second mode of variability. Hence, it is not a surprise that the concept of IOD needed some time to be accepted (cf. Allan et al. 2001; Hastenrath 2002). In fact, in the wavelet spectra of raw SST anomalies of eastern pole (100S-Eq., 900E-1100E) and western pole (100S-100N, 500E-700E), we do not find much coherence (Fig. 2 in Yamagata et al. 2003a); so, we are apt to deny the existence of IOD. However, as shown in Yamagata et al. (2003a), a remarkable seesaw is found between those two poles after removing the external ENSO effect (readers are referred to Fig 3 of their article), which is consistent with a few preceding studies that intuitively draw attention to some apects of such an inherent mode (e.g. Reverdin 1985; Reverdin et al. 1986; Hastenrath et al. 1993). This shows quite a contrast to other major oscillatory modes such as the Southern Oscillation and the North Atlantic Oscillation. Because those are the first dominant modes, a negative correlation is detected easily between the two poles even in raw data. On the other hand, the IOD appears as the second mode statistically in SST variability. Therefore, it is necessary to remove the first dominant mode to detect the sea-saw mode of IOD statistically. This is the basic reason why some statistical analyses fail to capture the IOD signal (cf. Dommenget and Latif 2002; Hastenrath 2002) even if the IOD appears as a seesaw mode dramatically in a physical space during typical event years. The above subtlety is demonstrated mathematically in Behera et al. (2003a). Another interesting divide is related to interpretation of the high correlation between ENSO and IOD phenomena. The correlation between DMI and Niño-3 index amounts to 0.53 for the peak IOD season of September-November (Nicholls and Drosdowsky 2000; Allan et al. 2001). Based on this significant correlation, one straightforward way to interpret this is that IOD events occur dynamically as a part of ENSO (Allan et al. 2001; Baquero-Bernal et al. 2002). However, we must notice that the correlation itself only denotes the statistical fact that one third of positive IOD events co-occur with El Niño events rather than their dynamical ralation. In other words, the non-orthogonality of two time series does not necessarily mean that the two phenomena are connected always in physical space.


The mechanisms through which ENSO exerts its influence on the Indian Ocean have not been clearly understood. One possible candidate is through changes in zonal Walker circulation. Yamagata et al. (2003), however, have demonstrated that an anomalous Walker cell exists only in the Indian Ocean during pure IOD events (Fig. 16). Although the linear analysis does not exclude completely the possible nonlinear physical interaction between the two climate signals, the above suggests the independent evolution of some IOD events. From a case study of the 1997-98 El Niño event, Ueda and Matsumoto (2000) suggested that the changes in the Walker circulation related to the El Niño could influence the evolution of IOD through changes in the monsoon circulation. Conversely, Behera and Yamagata (2003) showed that IOD modulates the Darwin pressure variability, i.e., one pole of the Southern Oscillation. How two major climate modes interact in the Indo-Pacific basin is a challenging problem.


The other proposed mechanism is through changes in the ocean circulation in response to ENSO-related changes in the atmosphere. From the pure El Niño composites, we find that cold SST anomalies of the Pacific origin entering the Indian Ocean propagate along the west coast of Australia (partly seen in right-bottom corners of Fig. 14d). This is understood on the basis of the oceanic finding in both theory and observations; the mature ENSO signal in the western Pacific intrudes into the eastern Indian Ocean through the coastal wave-guide around the Australian continent (Clarke and Liu 1994; Meyers 1996; Wijffels and Meyers 2004). The SST in the eastern Indian Ocean near the west coast of Australia during the boreal fall and winter is thus influenced by ENSO. This is known as the Clarke-Meyers effect. Schiller et al. (2000) confirmed this effect using a realistic ocean general circulation model. The changes in the SST may cause local air-sea interaction in boreal fall in this region (Hendon 2003), just like the annual coupled mode in the eastern Pacific (cf. Tozuka and Yamagata 2003). This phenomenon appears to be different from the cooling off Sumatra which is related to the basin-wide IOD phenomenon; IOD starts in May or June and involves active equatorial ocean dynamics. However, the air-sea interaction in the eastern Indian Ocean apparently enhances the IOD-ENSO correlation during the boreal fall. The eastern Indian Ocean is a unique region as crossroads of climate signals of both the Pacific Ocean and the Indian Ocean (Wijffels and Meyers 2004). The interaction of equatorial and coastal wave-guides influenced by the presence of the barrier layer is a complex phenomenon that still is not well understood.


c. Teleconnections


Like ENSO, the IOD can exert its influence on various parts of the globe via atmospheric bridge effects, interfering with other modes of climate variability. Saji and Yamagata (2003b) demonstrated that the positive IOD and El Niño have opposite influences in the Far East, including Japan and Korea; positive IOD events give rise to warm and dry summers, while negative IOD events lead to cold and wet summers. For example, the record-breaking hot and dry summer during 1994 (just like 1961) in East Asia was actually linked to the IOD (Guan and Yamagata 2003; Yamagata et al. 2003b 2004). It is well known that the summer climate condition over East Asia is dominated by activities of the East Asian summer monsoon system. Since the East Asian summer monsoon system is a subsystem of the Asian Monsoon (Wang and Fan 1999), it interacts with another subsystem, the Indian summer monsoon, via variations of the Tibetan high and the Asian jet (Rodwell and Hoskins 1996; Enomoto et al. 2003). The precipitation over the northern part of India, the Bay of Bengal, the Indochina and the southern part of China was enhanced during the 1994 positive IOD event (Behera et al. 1999; Guan and Yamagata 2003; Saji and Yamagata 2003b). Using the NCEP/NCAR reanalysis data (Kalnay et al. 1996) from 1979 through 2001 and the CMAP precipitation data from 1979 through 1999, several studies found that the equivalent barotropic high was strengthened over East Asia (e.g. Guan and Yamagata 2003; Yamagata et al. 2003b, 2004). The anomalous pressure pattern bringing unusually hot summer is well known to Japanese weather forecasters as a “whale-tail” pressure pattern. The tail part is equivalent barotropic in contrast to the larger baroclinic head part of the Pacific High. The IOD-induced summer circulation changes over East Asia are thus understood schematically through a triangular mechanism (Fig. 17). One process is that a Rossby wavetrain is excited in the upper troposphere by the IOD-induced divergent flow over the Indochina (Sardeshmukh and Hoskins 1988). This wavetrain propagates northeastward from the southern part of China. This is quite similar to Nitta’s PJ (Pacific-Japan) pattern (Nitta 1987) although the whole system is shifted a little westward. Another process is that the IOD-induced diabatic heating around the Bay of Bengal excites a long atmospheric Rossby wave to the west of the heating. The latter reminds us of the monsoon-desert mechanism that connects the circulation changes over the Mediterranean Sea/Sahara region with the heating over India (Rodwell and Hoskins 1996). Interestingly, this monsoon-desert mechanism was introduced by examining the anomalous summer condition of 1994 prior to the discovery of IOD (cf. Hoskins 1996). The westerly Asian jet acts as a waveguide for eastward propagating tropospheric disturbances to connect the circulation change around the Mediterranean Sea with the anomalous circulation changes over East Asia. This mechanism called the Silk Road process may contribute to strengthening of the equivalent barotropic high over East Asia (Enomoto et al. 2003). The scenario is confirmed by calculating the wave activity flux (cf. Plumb 1986; Takaya and Nakamura 2001) by Guan and Yamagata (2003).


The SINTEX-F coupled model simulation demonstrated the paramount influence of IOD on east African short rains; about 80% of extreme short rain years are related to IOD as in the observations (Behera et al. 2003b; Behera et al. 2005a). The DMI was successful in predicting anomalous short rains one season ahead in 92% of the years. The slow propagation of the air-sea coupled mode in the western Indian Ocean (Yamagata et al. 2004; Rao and Behera 2005; Behera et al. 2005a) provides us with a scope for the predictability of the IOD-induced short rains. The anomalous westward low-level winds in response to the anomalous zonal gradient of SST increase the moisture transport to the western Indian Ocean and enhance atmospheric convection in east Africa. The correlation analysis demonstrates that positive IOD (El Niño) events are related to enhanced (reduced) rainfall in east Africa as in the observations. Interestingly, the current coupled model captures even the higher impact of IOD on the Sri Lankan Maha rainfall as discussed by Zubair et al. (2003). In the Indonesian region, the model rain anomaly shows higher negative partial correlation with the IOD index as compared to that of ENSO.


In the Southern Hemisphere, the impact of the IOD is remarkable over Australia in a band from the northwest shelf to southeastern Australia (Saji and Yamagata 2003a, b; Ashok et al. 2003b) and Brazil (Saji and Yamagata 2003b); positive IOD events cause warm and dry conditions in a band from the northwest shelf to southeastern Australia and negative events cause cold and wet conditions (Fig. 15). The IOD teleconnection in the winter hemisphere is more due to a Rossby wavetrain (Chan et al. personal communication) and its impact on the weather phenomenon that Australian meteorologists call “northwest cloudband”. The study of teleconnection due to IOD events has just started and serious efforts to understand more about its mechanism are needed to improve predictability of regional climate over the globe.


d. Oceanic dynamics in the IOD

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