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Journal of the Meteorological Society of Japan Vol. 81., No.1, pp. 41-56, 2003
 Copyright 2003, Meteorological Society of Japan(MSJ). Permission has been provided
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A Look at the Relationship between the
ENSO and the Indian Ocean Dipole
Karumuri Ashok # , Zhaoyong Guan * , and Toshio Yamagata †
Institute for Global Change Research, 3173-25, Showamachi, Kanazawa-Ku, Yokohama City,
Kanagawa 236-0001, Japan
ABSTRACT
Using observed sea surface temperature data from 1871-1998, and observed wind data from 1958-1998, we
have confirmed that the recently discovered Indian Ocean Dipole (IOD) is a physical entity. Many IOD
events are shown to occur independently of the El Niño. By estimating the contribution from an appropriate
El Niño index based on sea surface temperature anomaly in the eastern Pacific, we have shown that the major
fraction of the IOD Mode Index is due to the regional processes within the Indian Ocean. Our circulation
analysis shows that the Walker circulation during the pure IOD events over the Indian/Pacific Ocean is
distinctly different from that during the El Niño events. Our power spectrum analysis, and wavelet power
spectrum analysis show that the periodicities of El Niñ o and IOD events are different. The results from the
wavelet coherence analysis show that, during the periods when strong and frequent IOD events occurred, the
Indian Ocean Dipole Mode Index is significantly coherent with the equatorial zonal winds in the central Indian
Ocean, suggesting that these events are well coupled. During the periods when there seems to be some
relationship between the equatorial zonal winds in the central Indian Ocean and ENSO index, we do not see
any significant coherence between the Indian Ocean Dipole Mode Index and the equatorial zonal winds in the
central Indian Ocean, except after 1995, suggesting that most of the IOD events are not related to ENSO.
1. Introduction
The El Niño/Southern Oscillation (ENSO) has
been recognized as an important manifestation of the
tropical ocean-atmosphere-land coupled system. The
recently discovered Indian Ocean Dipole (IOD; Saji et
al., 1999; Behera et al., 1999; Webster et al, 1999) is
another important manifestation of the tropical air-sea
interaction. The Indian Ocean Dipole Mode Index
(IODMI; denoted by I IODM ) is defined as the sea
surface temperature anomaly (SSTA) difference
between the tropical western Indian Ocean (50o E70o E, 10o S- 10o N; henceforth referred to as the Box A
for convenience) and the tropical southeastern Indian
Ocean (90o E- 110o E, 10o S-equator, named as Box B)
(Fig.1). El Niño and IOD events account for 30% and
12% of the tropical Indian Ocean SST variability
respectively (Saji et al., 1999). It means that both of
the aforementioned phenomena explain most of the
tropical Indian Ocean variability.
The IOD events have a strong influence on the
climate of not only the immediate neighboring regions
such as East Africa and Indonesia (Saji et al., 1999),
but also the Indian summer monsoon region (Ashok et
al., 2001), East Asia (Saji and Yamagata, 2002b, Guan
et al., 2002), the Mediterranean, Australia, and Brazil
(Saji and Yamagata, 2002b).
---------------------------------------------*
Also at Nanjing Institute of Meteorology, Nanjing 210044, China
Also at Department of Earth & Planetary Science, Graduate
School of Science,
The University of Tokyo, Tokyo 113 0033, Japan
Tel: +81-45-778-5523 Fax: +81-45-778-5707
#
Email for correspondence: ashok@jamstec.go.jp
†
Since some of the positive IOD events
coincidentally occur with some strong El Niño events,
as
in
1997,
an
interesting
issue
on
dependence/independence of the two phenomena, in
addition to another interesting issue on the physical
existence/non-existence of the IOD, has been raised
(Allan et al., 2001). In this study, using the sea surface
temperature (SST) and wind data, we claim that the
Indian Ocean Dipole (IOD) is a physical mode of the
tropical Indian Ocean, and not a statistical artifact.
We also reconfirm that the IOD is an inherent mode of
the Indian Ocean, as demonstrated by Saji et al.
(1999).
The monthly mean GISST data (Rayner et al.,
1996) from 1871-1998 has been used to compute the
NINO3 SST index (area-averaged over the area 5o N5o S, 150o W-90o W, denoted by I NINO 3 ), I IODM and
other necessary quantities. The NECP -NCAR 40-year
(1958-1997) reanalysis data (Kalnay et al, 1996) have
been used for the wind analysis. NCEP/NCAR wind
data has been used widely for the last few years in
tropical climate research (e.g. Krishna Kumar et al.,
1999, Murtugdde et al., 2000, Wang et al., Ashok et
al., 2001, Xie et al., 2002). Though the NCEP/NCAR
precipitation data is underestimated, the circulation
features are reasonable, as noted by Annamalai et al.
(1999), who have also shown that the NCEP/NCAR
wind data exhibit realistic large-scale interannual
variations in the tropics, especially in the monsoon
1
region. Hence, for the present study dealing with
large scale circulation features in the Indo-Pacific
region, NCEP/NCAR wind data is appropriate.
In section 2 of this study, we show that IOD
events as defined by Saji et al. (1999) do indeed exist.
We show the circulation features of the so-called pure
positive IOD events, i.e. those positive IOD events
that are not associated with any El Niño signal in the
Pacific. In section 3, we carry out correlation, powerspectrum, and wavelet variance analyses on the IOD
internal processes, and the temporal localization of the
influences.
2. The IOD as an inherent mode, and its
characteristic patterns
The IOD is basically characterized as the SSTA
(Sea Surface Temperature Anomaly) of opposite signs
prevailing over the Boxes A and B (Saji et al., 1999).
During some years such as 1924, 1972 etc., it can be
Fig. 1 : The time-series of SSTA (in unit of oC) averaged over Box A (50oE-70oE, 10o S- 10oN; shown in red) and over Box B
(90oE- 110oE, 10o S-equator; clear bars) during the dipole months. The sign of the SSTA over box A and that over Box B are
opposite during these months. The thin black solid line is the Indian Ocean Dipole Mode Index, I IODM . The normalized
equatorial zonal wind index (to be multiplied by 1.5; in m⋅s-1) defined by Saji et al.(1999), from 1958-1998, is shown as the
dashed line.
and ENSO’s SST indices. We also perform the
wavelet coherence analysis on these SST indices as
well as the central Indian Ocean zonal winds that are
important for the wave dynamics and coupling of the
Indian Ocean (Xie et al., 2001, Rao et al., 2002) to
find out the relative influences of the external and
seen that the I IODM is significant, though the bulk of
the contribution to it comes from only one box (Fig.1).
Nevertheless, the strong SSTA zonal gradient acts as a
dipole, virtually. The SSTA assumes a dipole -like
pattern when the area-averaged anomalies are plotted
2
(figure not shown). Such events are also very
important owing to the impact of this zonal gradient
on the climate of the surrounding regions like the
Indonesian and African rainfall (Saji et al., 1999), and
the Indian summer rainfall (Ashok et al., 2001).
is not valid. It is interesting to note that there are some
years when a warm ENSO event (El Niño) is
associated with a positive IOD event (as in 1997),
while there are some years when the El Niño events
co-occur with a negative IOD event (e.g. 1909, 1992).
Table 1: Dipole month statistics (I NINO 3 is the NINO3 index and I IODM is the IOD index. The term ‘single month’
designates lone dipole months that do not have another preceding or succeeding dipole month)
Total Number of Total Number of the
Months when
Single months
the months
months when both
the only
Single months
that co-occur
during when the
the I IODM and
I IODM is
I IODM is
I NINO 3 are
with ENSO
significant
significant
significant
April-November
169
46
123
38
11
SeptemberNovember
71
25
46
13
4
April-August
98
21
77
25
7
Rao et al. (2002) found that, between 1877-1997,
there occurred 14 ‘strong’ (i.e. during each of these
years, the magnitude of the I IODM was more than its
annual standard deviation) positive and 19 ‘strong’
negative IOD events. They show that 35% of these
IOD events co-occur with ENSO events having the
same phase of the corresponding IOD. Here, we will
present a more detailed IOD occurrence statistics by
stratifying the data on a monthly basis. To facilitate an
easy discussion, we designate the term ‘dipole month’
for any month between April-November for which the
I IODM is significantly strong (magnitude of the I IODM
of that month should be more than its monthly
standard deviation). Similarly, an ENSO month
designates any month when the magnitude of the
I NINO 3 exceeds the respective monthly standard
deviation. The term ‘single month’ designates lonely
dipole months that do not have another preceding or
succeeding dipole month.
Of the 1536 months during our study period, the
IOD type of SSTA can be seen in the Indian Ocean
during 498 months (see Fig. 1). Table 1 presents some
monthly statistics of the I IODM . It shows that during
April-November months of the study period, 27% of
the dipole months are associated with simultaneous
ENSO months. During the months of April-August,
only about 21% of the dipole months are associated
with ENSO months. During September-November, the
dipole months co-occurring with an ENSO month
amount to 35% of the total dipole months, in
agreement with Rao et al. (2002). We note that the
co-occurrence refers to the simultaneous occurrence of
the positive IOD phenomenon with an El Niño, or that
of a negative IOD phenomenon with a La Niña.
Actually, there are some years when this relationship
Similarly, some cold ENSO events (La Niña), such as
in 1967, are accompanied by positive IOD events.
Table 1 shows that the number of the designated
dipole months is more during April-August, the
developing season of the IOD (Saji et al., 1999), than
those during the SON, the mature phase of the IOD
events (Saji et al., 1999). Also, ENSO events
generally tend to be stronger during SON, as
compared to the period between April-August. These
factors also indicate that not all IOD events may have
been triggered by the ENSO. The fact that the number
of the dipole months is more during April-August is
understandable, as some of them do not develop into
fully mature IOD events. However, the societal
influence of these events may be substantial. Even the
single months with significant IOD type of SSTA are
important in the sense that they may have implications
for the summer climates of the eastern Africa, the
Indonesian archipelago, and India. Particularly, in the
case of the Indian summer monsoon, the influences of
the IOD and ENSO events are opposite (Ashok et al.,
2001). Even a single dipole month may influence the
monsoon circulation and rainfall through modulation
of the intraseasonal meridional movement of the
rainfall band over India.
The above discussion shows that the majority of
the dipole months, and so the IOD events by
extension, are independent of ENSO. The significant
correlation between the I IODM and I NINO 3 during some
periods is largely due to the simultaneous occurrence
of some of the IOD events and the ENSO events.
Using the NCEP/NCAR 40-year reanalysis, an
interesting feature is obtained by the study of
anomalous velocity potential patterns at different
levels during the summer (JJAS) of 1961 (Fig.2a and
2b). During this typical IOD year, two separate
3
Fig. 2: The anomalous atmospheric field in 1961 during
summer months (JJAS) (a) Velocity potential at 850 hPa.
(b) Velocity potential at 200 hPa, in m2⋅s-1 (c) Streamfunction
at 850 hPa. (d) Streamfunction at 200 hPa. The non-divergent
wind vectors are in m⋅s-1. The contour interval is 1×106m2⋅s-1.
Fig. 3 : Same as in Fig.2, but during 1997.
Pacific, and a single Walker circulation system over
the Indian Ocean. Of the two Walker circulations
over the Pacific, one can be seen between the western
and the central Pacific, and the second one between
the central and eastern Pacific. There is no indication
of a strong, basin-wide ENSO over the Pacific. The
corresponding anomalous rotational winds at 850 hPa
and 200 hPa at the equator do not show any signs of
El Niño (Figs. 2c and 2d). Similarly, only a weak
Walker circulation in the Pacific complements the
strong anomalous Walker circulation over the Indian
Ocean during the 1994 IOD event (figure not shown).
The above suggests that the tropical Indian Ocean can
sustain strong IOD events without support from the El
Niño induced subsidence. During the IOD event of
1997 (Ueda and Matsumoto, 2000), a single Walker
circulation covers the whole Pacific Basin (Figs. 3 a,
b). The basin-wide westerly rotational winds over the
Pacific at 850 hPa during this year, topped by the
easterly rotational winds at 200 hPa, are suggestive of
a strong El Niño (Fig.3a-d). Though the circulation
over the Indian Ocean is similar during 1961 and
1997, it is entirely different over the Pacific.
Yamagata et al. (2002 a,b), after compositing the
zonal mass flux for the period of SeptemberNovember for the ‘pure IOD’ events (without cooccurrence of strong El Niño events), and ‘all IOD’
events (all the IOD events, including those cooccurring with ENSO events), found that the zonal
mass flux in the meridional plane to the east of the
120ºE is very weak during the pure IOD events as
compared that for all IOD events. Here, we look into
the zonal cross-section of the Indo-Pacific Walker
circulation during pure ENSO years, pure IOD years,
and years of the co-occurrence. During the autumn
season of the ‘pure’ positive IOD years (such as 1961,
1967, and 1994), a strong well-defined single Walker
cell can be seen over the equatorial Indian Ocean (Fig.
4a-c). Over the Pacific, the Walker circulation is either
two-celled as in 1961, or very unorganized as in 1967
and 1994. In contrast, during the same season of the
‘pure’ El Niño years (without any co-occurring IOD
events) such as in years of 1957, 1976, and 1987, we
see relatively diffused multiple Walker cells over the
equatorial Indian Ocean (Fig. 4d-f). Even when both
the events co-occur, only a single strong Walker cell
can be seen over the equatorial Indian Ocean if the
IOD event is very strong such as in 1972, 1982 and
1997 (Fig. 4g-h). This feature of the IOD is
consistent with strong surface divergent easterly winds
over the equatorial Indian Ocean during the positive
IOD events; such strong surface easterlies over the
equatorial Indian Ocean cannot be found in the
aforementioned pure ENSO years.
The time-longitude diagram of the 850 hPa zonal
wind averaged over the latitudinal belt of -5o S to 5o N
is plotted in Fig.5a. We can see the co-occurrence of
Walker circulation systems can be seen over the
4
. Fig.4 : Con’d
Fig. 4: (a-i) The height-longitude anomalous Walker
circulation during September-October-November (SON),
derived from the non-rotating zonal component of the
velocity and the vertical velocity, during the years 1961,
1967, 1994, 1957, 1976, 1987, 1972, 1982, 1997
respectively. The colored contours in the background
represent the divergent zonal winds (m⋅s-1); negative
(positive) contours represent easterlies (westerlies)
etc., even after removing the ENSO signal. Since the
IOD starts earlier in the boreal spring and early
summer, ENSO events such as in 1972 and 1997
appear to be initiated by the eastward propagation of
the westerly anomalies in the Indian Ocean.
3. Relation between IOD and El Niño
Here we will study the statistical relation
between the I IODM and I NINO 3 in more detail. We
decompose the sea surface temperature anomalies
(SSTA) over the tropical Indian Ocean in the
following fashion:
SSTAIO = [SSTAIO ] + SSTA*IO ,
(1)
where SSTAIO is the monthly anomaly from the
mean climatology, and [SSTAIO ] is the area-averaged
SSTA over the equatorial Indian Ocean (50o E-110o E,
10o S- 10o N). The time series of [SSTAIO ] is the alltropical Indian Ocean index, denoted as IATIO. The
SSTA*IO
Fig.4 : Con’d
the IOD events with El Niño events during years such
as 1972, 1982, and 1997. The ENSO -related zonal
wind can be calc ulated by regressing the winds on to
the NINO3 index. This part is subtracted from the
total zonal wind, and the remainder is plotted in Fig.
5b. The easterly wind anomalies that are indicative of
the positive IOD event over the eastern Indian Ocean
are still strong during the years such as 1972, 1997
represents the spatially non-uniform
component of anomalous SST in this region. The
correlation between the time series of the IATIO and that
of the SSTAIO is positive everywhere and statistically
significant in the whole tropical Indian Ocean, as the
value at the 99% level of confidence is 0.07 (figure
not shown). The correlation exceeds 0.80 in the
central area of the tropical Indian Ocean. This means
that the SSTA varies in phase everywhere in the
tropical Indian Ocean in general, which is consistent
with the first principal mode derived by the EOF
analysis of SSTA in the tropical Indian Ocean (Saji et
al., 1999). Lagged correlations between IATIO and
5
Fig. 5 : (a) The time-longitude distribution of the zonal wind anomalies (averaged over -5 oS to 5 oN). The contour interval is 2 m⋅s-1.
The dashed lines represent negative values. The contours with value between –2 m⋅s-1 and 2 m⋅s-1 are not plotted. (b) similar to Fig. 5a,
but for the ENSO-independent wind.
Table 2: The lagged correlation between the I NINO 3 and IATIO ( I NINO 3 is the NINO3 index and IATIO is the
mean SSTA, averaged over the whole tropical Indian Ocean)
IATIO lagging to
I NINO 3 (Months)
-8
-5
0
2
3
4
5
6
15
18
Correlation
0.00
0.11
0.46
0.56
0.59
0.60
0.60
0.59
0.10
-0.01
I NINO 3 are presented in Table 2, from which we see
that the biggest correlation reaches the highest value
of 0.60 when IATIO lags the I NINO 3 by about 4 months.
Therefore, any analysis based on the signal obtained
from the SSTA averaged over the whole tropical
Indian Ocean does always strongly involve the ENSO
signal. This factor has mislead some researchers into
believing that the Indian Ocean is just a slave to the
Pacific phenomenon; the original IOD index (Saji et
al., 1999) was introduced as difference of SST.
Although the correlation between the I IODM and
the I NINO 3 over the 128 years is 0.3, the correlation
between these two quantities changes from time to
time, as we can see from the 31-year sliding
correlations between these two quantities (Fig. 6).
The moving correlation values fall from 0.42 during
1882-1912 to a very low value of 0.09 during 1912-
Fig. 6: The 31-year moving correlations between the
normalized I IODM , and normalized I NINO 3 for the period
from 1871 through 1998.
1943. In the last two decades the correlations have
risen up. Out of the 33 strong IOD events that
occurred between 1877-1997, 9 IOD events have
occurred during 1882-1912 period, a period when the
IOD-ENSO correlations were very weak (Fig. 7; see
6
also Rao et al, 2002). The relatively low values of the
variability is statistically interconnected, and that,
Fig. 7: (a) Time-series of the indices I IODM (solid) and IAIODM (dashed), for the period from 1871 through 1998. (b) time
series of the normalized SON-seasonal means of the I IODM (solid), the normalized IAIODM (dashed), and the SOIindependent normalized IAIODM (+ signed); all the time series are for the period from 1871 through 1998.
correlations between 1890-1957 generally support the
point suggested by Saji et al. (1999) that the Indian
Ocean Dipole may occur independently of the El
Niño. There is also no consistent association between
the phases of the ENSO and IOD. The IOD events,
despite being associated with the ENSO events in
some years, may be generated independently of
ENSO.
In order to assess the ENSO influence on the
I IODM , we have carried out a lag-correlation analysis
between the I NINO 3 and I IODM . We present in Table 3,
the correlation matrix between the I IODM and the
I NINO 3 for all the calendar months. Each element C ij
in this table represents the correlation value between
the 'i'th month of the I NINO 3 and 'j'th month of
the I IODM . Significant correlations are apparently found
(above the significant value of 0.17 at 95%
confidence). As we have discussed in the earlier
sections, however, this reflects the simultaneous
occurrence of some strong IOD and ENSO events.
The monthly-stratified simultaneous correlation
reaches a high of 0.5 during November, indicating a
relatively strong statistical association between these
events; however, it means that about 25% of their
Fig. 7 b
7
furthermore, in any of these basins, above 75% of the
variability originates from the intra-basin
mechanisms.
the IOD variability is ENSO-independent, we further
removed component related to the Southern
Oscillation from the IAIODM time series for SON (Fig.
Table 3: The correlation matrix between I NINO 3 , the NINO3 index and I IODM , the IOD index. Each element represents
the correlation between the time-series of I IODM for the i-th month in 128 years and that of I NINO 3 for the j-th month.
The bold values are significant at 95% level.
MONTH
I
O
D
M
I
I
N
D
E
X
1
2
3
4
5
6
7
8
9
10
11
12
1
2
NINO3 INDEX
3
4
5
6
7
8
9
10
11
12
0.11 0.09 0.11 0.12 0.01 0.00 -0.02 -0.05 -0.03 0.04 0.00 0.01
0.00 0.06 0.06 0.15 0.11 0.14 0.05 0.06 0.05 0.10 0.10 0.12
-0.11 -0.08 -0.12 -0.07 -0.07 -0.01 -0.02 0.05 0.06 0.08 0.07 0.08
-0.10 -0.10 -0.12 -0.12 -0.17 -0.19 -0.16 -0.12 -0.10 -0.08 -0.06 -0.09
0.15 0.18 0.14 0.15 0.08 0.06 0.02 0.04 -0.03 0.01 0.02 0.03
0.18 0.20 0.20 0.26 0.24 0.23 0.22 0.23 0.18 0.18 0.19 0.18
0.08 0.14 0.17 0.32 0.37 0.43 0.33 0.34 0.28 0.26 0.26 0.29
0.06 0.14 0.16 0.27 0.27 0.34 0.31 0.35 0.30 0.30 0.33 0.33
0.02 0.08 0.16 0.27 0.34 0.37 0.36 0.40 0.40 0.42 0.43 0.44
0.05 0.12 0.16 0.25 0.32 0.37 0.38 0.43 0.43 0.46 0.48 0.48
-0.04 0.05 0.10 0.22 0.29 0.35 0.40 0.48 0.49 0.51 0.50 0.49
-0.11 -0.02 0.05 0.16 0.19 0.30 0.30 0.32 0.31 0.34 0.36 0.34
In order to further verify this, it is useful to
estimate the contribution of the I NINO 3 to the I IODM .
Let us separate the latter as follows:
~
I IODM = I AIODM + r ( I IODM ,I NINO3 ) ⋅ ó ⋅ I NINO3 (2)
~
where I NINO 3 is the I NINO 3 normalized using its
standard deviation. ó is the standard deviation of the
I IODM anomalies
(=0.38o C).
The
quantity
r ( I IODM ,I NINO3 ) denotes the correlation between
the I IODM and I NINO 3 . Using the data spanning over 128
years, the r ( I IODM ,I NINO3 ) is estimated as 0.3.
Using relation (2), we define a new quantity
IAIODM to designate the residual of the I IODM after
removing the El Niño signal. Even when the
normalized I NINO 3 reaches an extremely high value of
5 (Figure not shown), its contribution to the I IODM will
be only about 0.55o C. A comparison between the
time-series of the I IODM with that of the IAIODM (Fig. 7a)
indicates that they are almost identical except for
slight differences, which in turn means that the
contribution of the El Niño to the I IODM is very small.
Because the IOD peaks during September-OctoberNovember (SON), we further repeated the above
exercise for this season during the period 1871-1998.
The seasonally stratified correlation is 0.53. But the
time series of the IAIODM is more or less similar to that
of the I IODM (Fig.7b). To confirm that the majority of
7b). Even then, the IAIODM is not much different from
the I IODM . This exercise supports the fact that the IOD
is basically an independent mode that is unique to the
Indian Ocean.
Yamagata et al. (2002a,b) proposed a hypothesis
to explain the apparent high correlation between the
IOD and ENSO indices during the boreal fall. By
compos iting the SST as well as the sea surface height
during the ‘pure’ as well as ‘all’ IOD and ENSO
events, they showed that mature ENSO signal intrudes
into the eastern Indian Ocean around the Australian
continent through the coastal wave-guide (Clarke and
Liu, 1994; Meyers, 1996). This effect influences the
SST in the eastern Indian Ocean near the west coast of
Australia during the boreal fall (so-called ClarkeMeyers effect). Just as in the eastern Equatorial
Pacific, the change in the SST gives rise to the
seasonal air-sea interaction in this region and expands
westward. This is different from the cooling of
Sumatra related to the basin-wide IOD phenomenon,
but apparently enhances the IOD-ENSO correlation
during the boreal fall.
After removing the long-term trends from I IODM ,
I NINO 3 , and IATIO, we analyze the periodicities of the
three indices using power-spectrum analysis together
with the red-noise test for statistical significance
(figures not shown). The significant periodicities are
presented in Table 4. Above the 95% level of
confidence, both of the I NINO 3 and IATIO show a
8
periodicity of 43.5 months. But the I IODM has the most
dominant periodicity of 62.5 months, whereas the
I NINO 3 does not have any significant peak at this
periodicity. Thus, the IOD and ENSO occur basically
on different time scales, and the former is less
frequent than the latter. Since only 12% of the IOD
variations are statistically explained by ENSO
variations (Behera et al., 2002), the present results
again support the fact that the IOD is basically a mode
unique to the Indian Ocean. We claim, therefore, that
the IOD and ENSO are, in principle, due to the
inherent internal modes in the respective basin.
However, once occurred, this does not exclude the
interaction between two modes through the
atmospheric bridge.
Table 4: The periodicities (in months) of the
I NINO 3 , IATIO, and
the I IODM ( I NINO 3 is the NINO3 index, IATIO is the mean
SSTA, averaged over the whole tropical Indian Ocean,
and I IODM is the IOD index)
95% > α ≥ 90%
Confidence
Level( α )
α ≥ 95%
Periods in I NINO 3
43.5 ; 34.5 ; 17.9
16.4; 13.5
Periods in IATIO
43.5
58.8
Periods in I IODM
62.5
125.0;
10.1
25.6;
To study the localization of the IOD and ENSO
events in time, and to identify the dominant
periodicity during different decades, we have applied
the wavelet power spectrum analysis (Torrence and
Compo, 1998) to the time series of I IODM and I NINO 3 .
The IOD events occurred at the most dominant
periodicity of quasi-pentadal timescale during 18711885, during the 1960s and 1970s, and from the early
1990s till 1998 (figures not shown). Furthermore, the
I IODM exhibits a periodicity of 2 years during 19001905, the early half of the 1960s, and during 19931994, and also a 3-year periodicity during 1890-1895.
The decadal period is prominent during 1910-1935.
The I NINO 3 has a periodicity of 2-3 years during most
of the study period. The quasi-pentadal and decadal
periodicities are not as dominant as the period of 2
years. The variances of both I IODM and I NINO 3 , during
the period between 1920-1960, are relatively low as
compared to those during the other period.
Based on the fact that the Southern Oscillation
Index is correlated with the zonal and meridional
winds at 0.57 and –0.51, Murtugudde et al. (2000)
suggested that ENSO and IOD could be sometimes
related via the atmosphere. At the same time, they
note that many of the IOD events do not occur with
ENSO. Xie et al. (2002) find a strong correlation
between the indices of off-equatorial Rossby waves in
the south Indian Ocean, and ENSO during the selected
period of 1970-1999; they indicate that ENSO exerts
some effect on the Indian Ocean wind stress. It
appears, however, that the analysis area is ol cated
further south of the IOD activities; they appear to have
discussed another phenomenon (Rao, personal
communication). Rao et al. (2002) showed that the
interannual subsurface variability of the equatorial
Indian Ocean is dominated by the IOD. Rao et al.
(2002) further demonstrated that the equatorial ocean
waves in response to the equatorial Indian Ocean
zonal winds play a key role in the evolution of the
subsurface dipole. Here, we carried out wavelet
coherence analysis (Torrence and Webster, 1999) to
understand the relative relationships of the remote
forcing and the local processes in regard to the zonal
wind anomalies over the central Indian Ocean. In the
ensuing discussion, the area-averaged zonal wind
anomalies over the central Indian Ocean (70º-90ºE,
5ºS to 5ºN), used by Saji et al. (1999) and Rao et al.
(2002), will serve as an index to represent the
equatorial zonal winds over the Indian Ocean (see
Fig.1 for the time series). We refer to this index as the
equatorial Indian Ocean zonal wind anomalies
(EIOZWA).
From 1958 till the end of 1977, the variances of
I IODM and the EIOZWA are significantly coherent at
periodicities of 1.5-6.5 years (Fig. 8a), indicating a
strong coupling between them. On the other hand,
the I NINO 3 is coherent with the EIOZWA between
1958-1965 with a periodicity of about 7-8.5 years
(Fig. 8b). During this period, if the IOD events were
forced by the equatorial winds modulated by the
ENSO, the coherence peaks should have the same
periodicity in both cases. However, this is not the
case, as shown in Figs. 8a and Fig. 8b. This suggests
that IOD and ENSO events are not related during this
period, at least in a linear manner. The less significant
wavelet coherence between the I IODM and I NINO 3 also
attests this fact (Fig. 8c).
During 1978 to 1987, another sustained I NINO 3 EIOZWA variance coherence peak can be seen with
peak periodicity varying between 3.5-4.5 years.
Noticeably, there is no sustained coherence peak
between the I IODM and the EIOZWA during this
period. As we move further in time, from 1989
through 1997 it is seen that the I IODM is tightly
coupled to the EIOZWA at periodicities between
quasi-biennial and quasi-pentadal timescales (Fig. 8a).
The I NINO 3 , on the other hand, is coherent with the
EIOZWA at periodicities of 1.5-3.5 years after 1995
(Fig. 8b). Apparently, during this period, there
appears to be some interaction of the Pacific events
9
with the coupling processes in the Indian Ocean
through the atmospheric bridge, as probably happened
during the IOD event of 1997 (Ueda and Matsumoto,
2000). The wavelet coherency between the I IODM and
I NINO 3 (Fig. 8c) also brings out this aspect.
Fig. 8: (a) The wave coherency for the period from 1958-1997
between (a) the I IODM time series and the EIOZWA (b)
I NINO 3 and the EIOZWA (c) I IODM and I NINO 3 . Values
greater than 0.82 (significant at 95% confidence level,
obtained from 1000 Monte-Carlo simulations of the white
noise) are shaded.
It is interesting to observe that the strong IOD
events occur only when the IODMI-EIOZWA
coherence is significant, and that, a strong coherence
between the I NINO 3 and EIOZWA is not necessary for
the existence of the IOD events. This again suggests
that the IOD events are regional coupled phenomenon,
and may be independent from the ENSO events, as
suggested by Saji et al. (1999) and Rao et al. (2002).
4. Concluding remarks
The present analysis of the observed data
demonstrates that the physical existence of the IOD is
beyond doubt. This shows quite a contrast to
Dommenget and Latif (2002) and Hastenrath (2002).
The present result is also supported by the recent
studies using Ocean GCMs, Atmospheric GCMs, and
coupled GCMs, all of which resolved the expected
dynamics (Vinayachandran, 2002, Iizuka et al, 2000,
Ashok et al., 2001, Rao et al., 2002, Guan et al., 2002,
Yu et al., 2002, Yu and Lau, 2002), and the recent
surface and subsurface ocean data studies
demonstrating that the evolution of the IOD is mostly
independent of the Pacific influence (Vinayachandran
et al., 1999, Rao et al., 2002, Yamagata et al.,
2002a,b).
We have shown that the strong positive IOD
events that occurred during the years such as 1961,
1967, and 1994 were not associated with El Niño in
the Pacific. This fact shows that the Indian Ocean can
sustain strong IOD events on its own, without the
external forcing. We also showed that the Walker
circulation over the Indian Ocean during the ‘pure’
IOD events is a single cell, while that during the pure
ENSO years such as 1957, 1976, and 1987 is multicelled and diffused.
It is also shown that, in general, the variance of
the IOD Index explained by the variations of NINO3
Index is very small, although the correlation between
these two indices reaches above 0.5 during the
autumn. This relatively high correlation is primarily
due to the co-occurrence of the ENSO and the IOD
events.
The whole tropical Indian Ocean shows a high
significant periodicity of 43.5 months, as does the
tropical Pacific. The Indian Ocean, however, shows
several other significant periodic variations as seen
from the periodicities of both the whole Indian Ocean
SSTA index and I IODM . In addition to the biennial
tendency as suggested by Saji et al. (1999), the IOD
Index has a more significant periodicity of 62.5
months that is different from the ENSO periodicities
of 43.5, 34.5 and 17.9 months.
Some recent studies indicate that the offequatorial Rossby waves are linked to ENSO (Xie et
al, 2002). However, as suggested by the slow
propagation speed of the Rossby waves, they appear to
have discussed something different from IOD. Rao et
al. (2002), however, have demonstrated the dominance
of the IOD events in modulating the equatorial
subsurface interannual variability via equatorial ocean
dynamics. Our wavelet coherence studies from 1958
through 1997 show that there is a tight coupling
between the I IODM and EIOZWA in the Indian Ocean
during the IOD-dominant decades. Also, sustained and
significant coherency can be seen between I NINO 3 and
EIOZWA during 1978-1987; no sustained peak can be
seen in the wavelet coherency between the I IODM and
EIOZWA for the same period because there are very
few IOD events during the same period. These factors
indicate that basin-wide coupled dynamics is essential
10
for the existence of the IOD. Our coherence studies
support Rao et al. (2002)’s argument that the IOD
events may arise owing to regional air-sea interaction,
rather than owing to external forcing. However, the
1997 event seems to be also connected to the
concurrent ENSO event in the Pacific via the
atmospheric bridge.
Since the IOD events may arise and exist
independently of ENSO, the Indian Ocean is an
important modulator of the tropical climate variability.
The influence of the IOD is not limited to the tropics;
it influences the global climate variability on time
scales ranging from years to decades through the
atmospheric teleconnections, as demonstrated in the
recent literature (Saji et al., 1999, Ashok et al, 2001,
Saji and Yamagata, 2002 a, b). Since the IODMI is
susceptible to contamination by mature ENSO signals
mostly owing to the Clarke-Meyers effect, it may be
better to use the partial correlation approach to isolate
the IOD impact on different climate phenomena, as
introduced by Saji and Yamagata (2002b).
Acknowledgments: The authors thank J. McCreary, G.
Meyers, B. N. Goswami, J. R. Kulkarni, A. S. Rao, S. K.
Behera, and S. Masson for the helpful discussions during
the course of this work. The authors are also grateful to N.
Nicholls for his critical comments that helped in the
improvement of this article. The authors also are grateful to
the reviewers for their useful comments, and to C. Torrence
for the wavelet analysis and wavelet coherence programs.
Many of the figures presented in this work have been
prepared using the GrADS software.
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