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Asymmetry in the Duration of El Niño and La Niña
YUKO M. OKUMURA AND CLARA DESER
Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, Colorado(Manuscript received 22 December 2009, in final form 10 May 2010)
ABSTRACTEl Niño and La Niña are not a simple mirror image, but exhibit significant differences in their spatial
structure and seasonal evolution. In particular, sea surface temperature (SST) anomalies over the equatorial
Pacific cold tongue are larger in magnitude during El Niño compared to La Niña, resulting in positive
skewness of interannual SST variations. The associated atmospheric deep convection anomalies are displaced
eastward during El Niño compared to La Niña because of the nonlinear atmospheric response to SST. In
addition to these well-known features, an analysis of observational data for the past century shows that there
is a robust asymmetry in the duration of El Niño and La Niña. Most El Niños and La Niñas develop in lateboreal spring/summer, when the climatological cold tongue is intensifying, and they peak near the end of thecalendar year. After the mature phase, El Niños tend to decay rapidly by next summer, but many La Niñaspersist through the following year and often reintensify in the subsequent winter. Throughout the analysis
period, this asymmetric feature is evident for strong events in which Niño-3.4 SST anomalies exceed one
standard deviation in December. Seasonally stratified composite analysis suggests that the eastward displacement of atmospheric deep convection anomalies during El Niño enables surface winds in the westernequatorial Pacific to be more affected by remote forcing from the Indian Ocean, which acts to terminate thePacific events.

1. Introduction
In the equatorial Pacific, prevailing easterly winds accumulate warm surface water to the west, lifting thethermocline in the east. The equatorial upwelling forcedby these easterly winds induces stronger surface coolingin the eastern Pacific because of the shallower thermocline. The resulting zonal gradient of sea surface temperature (SST), in turn, drives the equatorial easterly
winds that gather water vapor to fuel intense atmosphericdeep convection over the western Pacific warm pool.
Weakened (strengthened) easterly winds reduce (enhance) the eastern cooling and hence the zonal SST gradient, which positively feeds back to the surface windchanges. This so-called Bjerknes (1969) feedback is at theheart of interannual tropical Pacific variability, the El
Niño–Southern Oscillation (ENSO) phenomenon, whose
impact extends far beyond the tropical Pacific throughglobal atmospheric teleconnections (e.g., Trenberth et al.

Corresponding author address: Dr. Yuko M. Okumura, Climate
and Global Dynamics Division, NCAR, P.O. Box 3000, Boulder,
CO 80307.
E-mail: yukoo@ucar.edu
DOI: 10.1175/2010JCLI3592.1
Ó 2010 American Meteorological Society

1998; Alexander et al. 2002). Warm (El Niño) and cold
(La Niña) ENSO events tend to last approximately
1–2 years and recur every 3–8 years.
Various theories have been proposed to explain whatbrings turnabouts between El Niño and La Niña, including
ocean wave reflection at the western boundary (Schopf andSuarez 1988; Battisti and Hirst 1989), recharge/discharge ofwarm water volume due to Sverdrup transport (Jin 1997),
oceanic Kelvin waves forced by wind anomalies in thewestern Pacific (Weisberg and Wang 1997), and ocean
temperature advection by zonal currents associated withwave reflection at the western and eastern boundaries(Picaut et al. 1997). [See Neelin et al. (1998), Wang and
Picaut (2004), and Chang et al. (2006) for reviews of ENSO
mechanisms.] Despite their differences, these theories agree
that dynamical oceanic adjustments provide a slow restoring force to the unstable equatorial air–sea interactions.
Irregularity and noncyclic behavior of ENSO have also led
some authors to propose that ENSO is not a self-sustained
oscillatory mode but a stable mode triggered by stochastic
wind forcing (e.g., Lau 1985; Penland and Sardeshmukh
1995; Thompson and Battisti 2001; Kessler 2002).
El Niño and La Niña are strongly modified by the
background seasonal cycle. In particular, the equatorial1 NOVEMBER 2010

OKUMURA AND DESER

Pacific cold tongue exhibits a distinct annual variation
despite the semiannual solar forcing (Mitchell andWallace 1992; Xie 1994). The associated zonal SST
gradient across the equatorial Pacific and accompanying
easterly winds are strongest (weakest) in boreal summer–
fall (spring) when the intertropical convergence zone
(ITCZ) moves farthest from (closest to) the equator. (Inthis paper the seasons refer to those in the Northern
Hemisphere.) Both El Niño and La Niña develop in latespring–summer, when the climatological cold tongue isintensifying, and they peak mostly toward the end of thecalendar year, resulting in a December peak in monthly
SST anomaly variance. The physical processes responsible for this phase locking are still unclear but possibilities include nonlinear modulation of the annual cycle
by interannual displacement of the thermocline (Xie
1995), seasonal migration of the ITCZ and associatedatmospheric heating (Tziperman et al. 1997; Harrison
and Vecchi 1999), delayed negative feedback from theIndian Ocean (Annamalai et al. 2005; Kug and Kang
2006; Ohba and Ueda 2007; Yoo et al. 2010), and influence of the North Pacific Oscillation (Chang et al.
2007; Alexander et al. 2010). The fact that both El Niñoand La Niña amplify during the equatorial cold season
confirms that the presence of strong zonal SST gradient,easterly winds, and upwelling in the background state isfundamental for the Bjerknes feedback.
Historically, El Niño has drawn more attention than La
Niña, partly because it is associated with more severe climatic conditions, such as heavy rains in the coastal desert ofPeru and sometimes failures of the Indian monsoon. In
fact, composite analysis had only been attempted for
El Niño and not for La Niña until the late 1980s. After thecold phase of ENSO was named ‘‘La Niña’’ by Philander(1985) and its climatic impact caught public attention with
one of the strongest events on record in 1988–89 (e.g., Kerr
1988), researchers began to treat El Niño and La Niña ascomplementary phases of ENSO. Indeed, most observational studies use linear techniques such as regression
analysis, empirical orthogonal function (EOF) analysis,or warm-minus-cold composites to identify the canonical patterns and evolution of ENSO events, assumingthat La Niña is a mirror image of El Niño.
Interannual SST variations along the coast of Peru are
known to be strongly positively skewed (Deser andWallace 1987). Burgers and Stephenson (1999) show that
the SST anomaly skewness exhibits an intriguing geographical distribution, with large positive values in theeastern equatorial Pacific and small negative values in thewestern Pacific, reflecting that the SST anomalies associated with El Niño are larger in magnitude than those
associated with La Niña. This deviation from normality
led them to question the degree of linearity in the5827

equatorial Pacific ocean–atmosphere system. They suggest that the proximity of the thermocline to the surface isthe cause for the positive SST anomaly skewness inthe eastern equatorial Pacific, and that therefore nonlinear oceanic processes are responsible for the asymmetry in the strength of El Niño and La Niña. Jin et al.
(2003) propose that nonlinear thermal advection by
ocean currents contributes to the generation of largeramplitude El Niños compared to La Niñas. Meinen and
McPhaden (2000) show that for a given anomaly magnitude of warm water volume in the upper portion of theequatorial Pacific, positive values are associated withlarger-amplitude SST anomalies than negative values,
suggesting the importance of nonlinear processes.
Asymmetry in the spatial distribution of equatorial
Pacific rainfall anomalies between El Niño and La Niñawas highlighted in the study of Hoerling et al. (1997) on
ENSO teleconnections. They noted that maximum amplitude rainfall anomalies along the equator are locatedeast (west) of the date line during El Niño (La Niña),with a commensurate shift (approximately 358 of longitude) in the atmospheric Rossby wave trains forced bydiabatic heating changes. Hoerling et al. (1997) suggested that the zonal displacement is due to the nonlinear dependence of atmospheric deep convection on
total SSTs. On the periphery of the warm pool, even small
SST deviations excite large rainfall deviations becauseof the high background SST values. Thus, maximum
convection anomalies are shifted more than 5000 km westof the maximum SST anomalies (Deser and Wallace1990). Over the eastern cold tongue region, on the other
hand, large positive SST anomalies can induce convection
while negative anomalies have no further effect on thenormally dry conditions. Indeed, an atmospheric generalcirculation model (GCM) forced with perfectly symmetricpositive and negative SST anomaly patterns successfully
simulates the nonlinear atmospheric response that closely
resembles the observed patterns (Hoerling et al. 1997).
The associated zonal shift of surface wind anomalies, inturn, is suggested to cause stronger positive SST anomalies in the eastern Pacific during El Niño (Kang and Kug2002).
Thus, the asymmetry of El Niño and La Niña involves
nonlinear processes in both the ocean and atmosphere,
which may be amplified by air–sea interactions. An alternative linear view is that ENSO represents zonal excursions of the ocean temperature front between the western
warm pool and the eastern cold tongue by anomalous
advection: its eastward (westward) displacement results inlarge positive (negative) SST anomalies to the east (west)of the climatological front (Schopf and Burgman 2006).
Previous studies of ENSO asymmetry have focused on
the skewness of SST anomalies and its spatial pattern. It

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should be noted that this asymmetry in the magnitude of
positive and negative SST anomalies may also arise fromthe asymmetry in the duration of warm and cold phases of
ENSO when climatologies are defined as the time meanstate.
The asymmetry in the duration of El Niño and La
Niña has been noted in a few recent studies (Larkin andHarrison 2002; McPhaden and Zhang 2009; Ohba andUeda 2009). McPhaden and Zhang (2009) show that La
Niña tends to persist into the second year and reintensify
in winter in their composite analysis for 1980–2008, although this feature is not evident for the earlier period
1950–77. For both periods, El Niño tends to terminate
rapidly after the mature phase, as shown in earlier studies
by Rasmusson and Carpenter (1982) and others. Based on
the observational analysis for 1980–2002, Kessler (2002)
also points out that the transitions from La Niña to El Niñoare slower than those from El Niño to La Niña. Ohba andUeda (2009) suggest that these asymmetric transitions
between El Niño and La Niña can be attributed to thenonlinear response of surface winds to Indo-Pacific SST
anomalies, although they did not clarify the relative role ofthe Indian Ocean SST anomalies associated with ENSO.
In the present study, we examine in greater detail theasymmetry in the duration of El Niño and La Niña, using
a suite of observational and reanalysis datasets spanningthe past 27–109 yr. We address the following questions.
Is there a robust asymmetry in the duration of the two
ENSO phases throughout the observational record? How
do ocean–atmosphere anomalies evolve in association
with the asymmetric duration of El Niño and La Niña, andwhat causes this asymmetric evolution? Do SST changes
in the Indian Ocean associated with El Niño and La Niñahave any impact on the asymmetric wind anomalies in the
Pacific? These are very important issues for climate prediction because long-lasting La Niña can exert persistentclimatic impact on the Indo-Pacific and distant regions
through atmospheric teleconnections (e.g., Ropelewski
and Halpert 1989; Cole et al. 2002; Hoerling and Kumar
2003).
The datasets and analysis methods used in this study
are described in section 2. In section 3, it is shown that
there is a robust asymmetry in the duration of the two
ENSO phases throughout the past century, especially forstrong events. Through seasonally stratified composite
analysis, we identify a pronounced asymmetry in thesurface wind anomalies that develop in late fall over the
far western Pacific, leading to the asymmetric evolutionof thermocline anomalies in the central-eastern portionof the basin in the following seasons. We discuss a possible role for the Indian Ocean in this asymmetric evolutionof surface wind anomalies over the far western Pacific.
The last section summarizes the main results.

VOLUME 23

2. Data and methods
To identify any robust asymmetry in the duration of
El Niño and La Niña, we analyze two monthly SST datasets spanning different periods: the Hadley Centre sea ice
and sea surface temperature (HadISST; Rayner et al.
2003) for 1900–2008 and the National Oceanic and Atmospheric Administration (NOAA) optimum interpolation sea surface temperature version 2 (OISST; Reynolds
et al. 2002) for 1982–2008. The HadISST is a long-term
global SST analysis available on a 18 grid from 1870 to thepresent. It is based on historical in situ ship and buoy observations with satellite data blended in after 1982. The
cold bias of bucket SST measurements prior to 1942 iscorrected for, and missing grids are filled by optimal interpolation based on EOF analysis. The OISST combines
satellite data with in situ observations and is available
on a 18 grid from December 1981 to the present. The long,spatially complete data of HadISST helps us assess therobustness of asymmetry throughout the historical record,
while the extensive spatiotemporal coverage of satellite
observations used in the OISST allows for better resolution of SST variations with small amplitude and spatial
scale (e.g., Okumura and Xie 2006).
Several other monthly ocean–atmosphere variables areanalyzed in conjunction with the SST field: surface windvelocities and tropospheric air temperature from the
National Centers for Environmental Prediction–National
Center for Atmospheric Research (NCEP–NCAR) reanalysis for 1948–2008 (Kalnay et al. 1996) and from the
NCEP–Department of Energy (DOE) reanalysis II for
1979–2008 (Kanamitsu et al. 2002), precipitation fromthe Climate Prediction Center Merged Analysis of Precipitation (CMAP) for 1979–2008 (Xie and Arkin 1996),
and sea surface height and surface wind stress from the
Simple Ocean Data Assimilation (SODA) analysis versions 2.0.2 and 2.0.4 for 1958–2001 and 2002–2007, respectively [see Carton and Giese (2008) for the descriptionof the earlier version]. It should be noted that a representation of the Pacific ITCZ and associated meridional winds
is substantially improved in the NCEP–DOE reanalysis II
compared to the original NCEP–NCAR reanalysis presumably due to improved model physics of boundary layer
and convection (Wu and Xie 2003). The two versionsof the SODA analysis use different wind products (theEuropean Centre for Medium-Range Weather Forecasts reanalysis in version 2.0.2 and the Quick Scatterometer data in version 2.0.4) but do not exhibit any
apparent discontinuity in the equatorial Pacific acrossthe two periods, and thus we merge them to form a single
record for 1958–2007. The results shown in the following
section do not change significantly by limiting the data
period to 1958–2001.

1 NOVEMBER 2010

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5829

FIG. 1. Time series of the Niño-3.4 index based on the HadISST for 1948–2008 (color bars) and the OISST for 1982–
2008 (black line). El Niño and La Niña years are marked from Jan0 to Dec11 by thick horizontal red and blue bars,
respectively. Thin horizontal color lines indicate one standard deviation of the Niño-3.4 index in December based on
the HadISST (0.94). Both the HadISST Niño-3.4 index and its standard deviation are calculated for the base period
1900–2008.

For each variable, monthly anomalies are calculated bysubtracting the climatological monthly means over the
analysis period. When two or more variables are analyzed
together, a common data period is used to calculate theclimatologies. The monthly anomalies are smoothed using a 1–2–1 filter. We choose not to remove linear trends
from the data records since they are not consistent for thedifferent data periods and may arise from interdecadal
variability in the short records spanning the recent few
decades. The SST trend in the central-eastern equatorial
Pacific is small over the past century relative to the amplitude of El Niño and La Niña (;60.28C). Although thetropical Indian Ocean shows a significant warming trendof ;1.08C from 1900 to 2008, we confirm that it does not
significantly affect the composite anomalies for El Niñoand La Niña.

As will be shown in the next section, the asymmetry inthe duration of El Niño and La Niña is evident only forstrong events. Based on the fact that most strong ENSO
events peak toward the end of the year, El Niño and
La Niña years are defined as those for which the 1–2–1
smoothed SST anomalies averaged over the Niño-3.4 region (58S–58N, 1208–1708W, hereafter called the Niño-3.4
index; Fig. 1) in December exceed 1 standard deviation
and are below 21 standard deviation, respectively. Thismethod picks out all strong cases of El Niño and La Niñaevents according to the definition of Trenberth (1997)
that is used in NOAA’s operational ENSO forecast andmany previous studies. Composite analysis is conducted
for these El Niño and La Niña years separately. The
El Niño/La Niña and subsequent years are denoted as‘‘year 0,’’ ‘‘year 11,’’ . . . and the months of these years as

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TABLE 1. El Niño and La Niña years defined according to the HadISST for 1900–2008. In December of these years the absolute value of
the Niño-3.4 index exceeds one standard deviation (0.94). The set of years used in the composites based on the HadISST for 1900–47 (theHadISST and NCEP–NCAR reanalysis for 1948–2008) are listed in the first (second) row. The set of years used in the composites based on
the OISST, NCEP–DOE reanalysis II, and CMAP for 1982–2008 are set bold.
El Niño years
La Niña years‘‘Jan0’’, ‘‘Feb0,’’ . . . ‘‘Jan11,’’ ‘‘Feb11,’’ etc. We use the
HadISST to define El Niño and La Niña years for 1900–
2008 (Table 1). Twelve El Niños and 11 La Niñas are
identified for the period 1948–2008, and are indicated byhorizontal bars from Jan0 through Dec11 on the Niño-3.4
time series shown in Fig. 1. There are several cases inwhich the absolute value of the Niño-3.4 index exceeds
one standard deviation in December of two consecutive
years due to persistent warm or cold conditions (1940/41,
1949/50, 1986/87, and 1998/99). These consecutive El Niñoand La Niña years are regarded as single events inTrenberth’s (1997) definition, but are treated as separate
samples in our composite analysis because we are interested in how the ocean–atmosphere anomalies evolve
before and after each peak of equatorial SST anomalies.
The results shown in the following section are, however,not significantly affected by eliminating the second years
from the analyses. The main results also do not change forslight modifications of the year selection criteria (e.g.,
expanding the reference months to include November
and January) or by excluding the two extreme El Niños of
1982/83 and 1997/98 in the composite.

3. Resultsa. Duration of El Niño and La Niña
The long-lasting La Niña of 1998–2001 caused extensive
drought across the United States, southern Europe, andsouthwest Asia (e.g., Hoerling and Kumar 2003). An examination of the Niño-3.4 index time series for 1948–2008
reveals many other strong, persistent cold phases spanning more than 2 yr (1949–51, 1954–56, 1973–76, 1983–86,
and 2007–09; Fig. 1). During these persistent cold phases,
negative SST anomalies reintensify each winter, evidenced by the sawtooth shape of the Niño-3.4 time series.
Although there were two prolonged warm phases during
this period (1990–95 and 2002–05), none was as continuously strong as their cold counterparts. Indeed, there is nowarm phase in which the Niño-3.4 index remains above
0.3–0.4 for more than 2 yr. In 9 out of 11 La Niñas theNiño-3.4 index remained negative through year 11, while
11 out of 12 El Niños terminated rapidly by summer ofyear 11. The three major El Niños of 1972/73, 1982/83,

1902, 1905, 1911, 1918, 1925, 1930, 1940, 1941,
1957, 1965, 1972, 1977, 1982, 1986, 1987, 1991, 1994, 1997, 2002, 2006
1909, 1916, 1933, 1942,
1949, 1950, 1955, 1970, 1973, 1975, 1984, 1988, 1998, 1999, 2007

and 1997/98 were followed by a strong, persistent cold
phase.
Figure 2 shows the temporal evolution of the Niño-3.4
index for the composite El Niño (top) and La Niña(bottom) as well as for the individual years that comprisethe composites. In the composite La Niña, negative valuesof the Niño-3.4 index persist for more than 22 months(Mar0–Dec11), but in the composite El Niño positive
values last for only 15 months (Mar0–May11). In thesecond half of year 11, the Niño-3.4 indices for thecomposite El Niño and La Niña have the same sign andsimilar magnitudes. Most of the strong El Niños and La
Niñas that compose the composites develop in late spring.
Horii and Hanawa (2004) have pointed out that warm
events that commence in spring tend to grow larger andexhibit a more regular life cycle than those that commencein summer–fall. The El Niño of 1986–87 did not begin
until late summer and lasted through year 11 as manyof the summer–fall-type events in Horii and Hanawa’s(2004) analysis. The El Niño of 2006/07 also began in latesummer but terminated rapidly after the mature phase,triggered by intraseasonal variability emanating from theIndian Ocean (McPhaden 2008).
An expanded view of the composite evolution of SST
anomalies along the equator during El Niño and La Niñais shown in Fig. 3 for three different periods and two
datasets: 1900–47 (HadISST), 1948–2008 (HadISST), and
1982–2008 (OISST). For the periods after 1948, composite surface wind anomalies are also overlaid. The
greater persistence of La Niña compared to El Niño isapparent in all three periods and two datasets. In thecomposite El Niño, positive SST anomalies are replacedby negative SST anomalies starting in summer of year 11,
accompanied by a reversal of the zonal wind anomalies
west of 1708W. In the composite La Niña, on the other
hand, negative SST anomalies persist through year 11 in
the western-central Pacific and reintensify in winter. The
persistent negative SST anomalies in the western-central
Pacific are associated with persistent easterly wind anomalies west of 1708W, which would increase local upwelling and force upwelling Kelvin waves to the east. To theeast of 1458W, the negative SST anomalies weaken significantly after the mature phase and then reintensify
in the following fall–winter. In the La Niña composite

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FIG. 2. Time series of the Niño-3.4 index overlaid from Jan0 to
Dec11 for (top) El Niño and (bottom) La Niña during 1948–2008
based on the HadISST. Thick red and blue lines are composite timeseries.

based on the OISST and NCEP–DOE reanalysis II, thisdecay of negative SST anomalies in the eastern Pacific is
associated with anomalous westerly winds that intensify
east of 1208W after the mature phase, which would reduce local upwelling and warm the ocean mixed layer(Zhang and McPhaden 2006, 2008). As described inprevious studies, asymmetry is also found in the longitudinal structure of SST and wind anomalies. During themature phase, the positive SST anomalies associated with5831

El Niño are larger than the negative SST anomalies associated with La Niña east of 1008–1108W although thisasymmetric feature is less pronounced in the early partof the record (1900–47). Compared to the positive SST
anomalies associated with El Niño, the negative SST
anomalies associated with La Niña extend farther west
by approximately 108 of longitude in the western Pacific.
The associated wind anomalies are also shifted westward
in La Niña compared to El Niño.
The Hovmöller plots in Fig. 3 reveal several other interesting features consistent for different periods anddatasets. During year 0 of the composite La Niña, negative SST anomalies expand westward from the eastern
Pacific. A similar westward propagation is evident for thenegative SST anomalies that develop in year 11 of thecomposite El Niño. In contrast, the reintensification of
the negative SST anomalies toward the end of year 11 of
the composite La Niña occurs simultaneously across thebasin. The positive SST anomalies associated with thecomposite El Niño show a westward propagation similar
to that seen for La Niña in the early part of the record(1900–47). However, there is almost no westward movement during the later portion of the record (1948–2008
and 1982–2008) for El Niño, in contrast to La Niña.
Composites for different epochs of Pacific interdecadal
variability suggest that they tend to propagate westward(eastward) during cold (warm) epochs of the Indo-Pacificregion (not shown), consistent with earlier studies thatsuggest that the propagation characteristics of ENSO
changed after the Pacific-wide climate regime shift in late1970s (e.g., Fedorov and Philander 2000; Wang and An
2002; Trenberth et al. 2002). McPhaden and Zhang (2009)
discuss the asymmetry in the propagation characteristics
of El Niño and La Niña, which cannot be explained byexisting theories.
The time evolution of equatorial SST and wind anomalies for the two most recent persistent cold phases (1998–
2001 and 2007–09) is shown in Fig. 4. These plots reveal
remarkable SST and wind anomaly structures that repeat
2–4 yr in a row. The negative SST and easterly wind
anomalies intensify in winter and weaken in spring–earlysummer. The SST anomalies reintensify in late 2008/early2009 simultaneously across the basin, consistent with thecomposite La Niña (Fig. 3). However, the reintensified
equatorial cooling in late 1999/early 2000 exhibits pronounced westward propagation west of 1408W, while thesimultaneous reintensification across the basin occurredagain in late 2000/early 2001. As in the La Niña composite
based on the OISST and NCEP–DOE reanalysis II,
anomalous westerly winds develop east of 1408W after
the wintertime peaks of SST cooling in each year (early
1999, 2000, 2001, and 2008). In spring–summer of 2008,
these anomalous westerly winds are associated with ;18C

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FIG. 3. Longitude–time sections of composite SST anomalies along the equator (38S–38N) for (top) El Niño and (bottom) La Niña,based on the HadISST for (left) 1900–47 and (middle) 1948–2008, and on the OISST for (right) 1982–2008 (8C, color shading). Composite
surface wind anomalies (m s21, vectors) are overlaid in the (middle) and (right) based on the NCEP–NCAR reanalysis and the NCEP–
DOE reanalysis II, respectively.

SST warming off the South American coast. The heatbudget analysis by Nagura et al. (2008) for 08, 1408W
during 1998–2001, on the other hand, suggests that theseanomalous westerly winds weakened the westward equatorial ocean current and hence the meridional shear between the South Equatorial Current and North Equatorial
Counter Current, which in turn reduced tropical instability
wave activity. The associated decrease in horizontal heatadvection counteracted the warming due to a change inlocal upwelling, slowing down the transition from La Niñato El Niño.

b. Seasonal evolution of ocean–atmosphereanomalies in the Indo-Pacific region
Figure 5 shows bimonthly composite maps of SST,
surface wind, and precipitation anomalies for El Niñoand La Niña from Jun0 through Aug11 based on the
OISST, NCEP–DOE reanalysis II, and CMAP for 1982–
2008. Similar SST and wind anomaly patterns are foundin composites based on the HadISST and NCEP–NCAR
reanalysis for 1948–2008 (not shown). In the El Niñocomposite, a distinct equatorial peak of SST warming1 NOVEMBER 2010

OKUMURA AND DESER

5833

FIG. 4. Longitude–time sections of SST (8C, color
shading) and surface wind (m s21, vectors) anomalies
along the equator (38S–38N) for the persistent La Niñasof (left) 1998–2001 and (right) 2007–09. Based on the
OISST and NCEP–DOE reanalysis II.

develops in the Pacific by Jun0 and continues to intensify
until Dec0. Associated with the equatorial SST warming,
precipitation increases across the equatorial Pacific anddecreases over the Maritime Continent accompanied byanomalous westerly winds over the western portion of
the basin. The composite La Niña exhibits a similar
evolution of SST, wind, and precipitation anomalies in
the Pacific throughout the developing and mature phaseswith the sign reversed. After the mature phase in Dec0,
the equatorial warming associated with El Niño decays
rapidly and is replaced by weak equatorial cooling overthe central-eastern Pacific in Jun11. The equatorial cooling, easterly wind, and negative precipitation anomalies
associated with La Niña endure through the following
spring-summer in the western-central Pacific.
Compared to the El Niño composite, the Pacific precipitation anomalies in the La Niña composite aredisplaced westward by 108–158 in longitude and the large
equatorial wind anomalies extend farther into the western Pacific throughout the developing and mature phases(Fig. 5). From Oct0 to Dec0 the equatorial westerly wind
anomalies associated with El Niño rapidly weaken in the
far western Pacific, nearly disappearing west of 1608E.
The equatorial easterly wind anomalies associated with
La Niña do not show such a weakening. In many strong
El Niños, surface wind anomalies even become easterly
in the far western Pacific after the mature phase (notshown). This wind reversal is responsible for the termination of El Niño in Weisberg and Wang’s (1997)‘‘western Pacific oscillator’’ mechanism.
After the mature phase of El Niño in Dec0, the centerof positive precipitation and westerly wind anomalies
shifts south of the equator in the western-central Pacificand northerly wind anomalies appear north of the equator

FIG. 5. Bimonthly composite maps of SST (8C, color shading), surface wind (m s21, vectors), and precipitation [mm day21, positive (negative) contours in green (orange) at 61, 3, 5, . . .]anomalies for El Niño and La Niña from Jun0 to Aug11. The stippled region indicates the climatological precipitation .5 mm day21. Based on the OISST, NCEP–DOE reanalysis II, andCMAP for 1982–2008.

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FIG. 5. (Continued)

1 NOVEMBER 2010

5836

JOURNAL OF CLIMATE(Fig. 5). Harrison and Vecchi (1999) argue that thissouthward wind shift hastens the termination of El Niño.
Using an atmospheric GCM, Vecchi (2006) shows thatthe climatological seasonal movement of the western
Pacific warm pool south of the equator is responsible forthe southward shift of atmospheric convection and wind
anomalies near the end of year. Ohba and Ueda (2009)
argue that the meridional shift of the wind anomalies does
not occur during the mature phase of La Niña because of
the nonlinear atmospheric response to SST anomalies,
prolonging the equatorial easterly wind anomalies andhence the cold phase of ENSO. Our analysis, however,shows that a similar wind shift also occurs during La Niñatwo months later in Feb11 (Fig. 5). It is not clear why thesouthward wind shift during La Niña is absent in Ohba
and Ueda’s (2009) analysis, but it may be due to the different temporal smoothing (3-month running mean), windproduct (the European Centre for Medium-Range
Weather Forecasts Reanalysis), or analysis method (onesided lag regression).
It has long been known that ENSO variability exerts
a significant impact on the Indian Ocean (see Schott et al.
2009 for a recent review). In the El Niño composite,
positive SST anomalies appear over the western-central
tropical Indian Ocean in Jun0 and persist through thesummer of year 11 (Fig. 5). During El Niño, atmosphericdeep convection is suppressed over the tropical Indian
Ocean due to a change in the Walker circulation. The
resulting increase in incoming solar radiation is mainly
responsible for the warming of the Indian Ocean (Klein
et al. 1999), with ocean dynamics also playing an important role in the southwestern part of the basin (Xie et al.
2002). In the eastern part of the basin, on the other hand,anomalous southeasterly winds associated with the suppressed convection strengthen the climatological alongshore winds and coastal upwelling off the west coast of
Sumatra, inducing negative SST anomalies (Fig. 5). This
zonal SST dipole is most pronounced in Oct0 and thenthe eastern pole decays as the climatological winds
reverse from southeasterly to northwesterly (Tokinaga
and Tanimoto 2004). In Oct0, precipitation increases
over the positive SST anomalies in the western Indian
Ocean, suggesting an active role of the Indian Ocean
SST anomalies in modulating atmospheric circulation
during El Niño (Watanabe and Jin 2002). During La
Niña, the Indian Ocean exhibits a similar pattern andthe evolution of ocean–atmosphere anomalies as thoseduring El Niño with the sign reversed. Compared to the
El Niño composite, the cooling of the western-central
Indian Ocean is slightly weaker and delayed in the
La Niña composite. The alongshore northwesterly wind
anomalies and coastal SST warming off Sumatra are also
weaker during Aug0 and Oct0 in La Niña compared to

VOLUME 23

El Niño. The eastern Indian Ocean warming is more
pronounced off the northwest coast of Australia andpersists through the summer of year 11.
Figure 6 shows latitude–time sections of composite
SST, surface wind, and precipitation anomalies averaged
over the far western (1408–1708E) and western-central(1708E–1508W) Pacific. This figure confirms that theseasonal evolution of composite wind anomalies is quite
symmetric between El Niño and La Niña over the westerncentral Pacific throughout the developing and maturephases. In the El Niño (La Niña) composite, the centerof the wind anomalies shifts south of the equator in
Dec0–Jan11 (Jan11–Feb11), with anomalous northerly(southerly) winds developing north of the equator. In
the vicinity of the equator, the wind anomalies do not
weaken prior to the mature phase. The precipitation
anomalies are quite symmetric as well for El Niño and
La Niña although the center south of the equator is slightly
more pronounced during Dec0–Feb11 in the El Niñocomposite compared to the La Niña composite. In the
far western Pacific (1408–1708E), on the other hand, astrong asymmetry is evident in the ocean–atmosphereanomalies (Fig. 6). During El Niño, the positive precipitation anomalies vanish by Aug0–Sep0 and two centers ofnegative precipitation anomalies develop on both sides ofthe equator in Oct0–Nov0 as the SST anomalies change
from weak positive to negative. The westerly wind
anomalies start to weaken in Oct0 north of the equatorand in Nov0 in the vicinity of the equator, nearly disappearing by Jan11. During La Niña, on the other hand,the negative precipitation anomalies are about 1.5 times
as large as the positive precipitation anomalies for El Niñoand persist until fall of year 11. In this longitudinal band,the equatorial easterly wind anomalies continue tostrengthen until Mar11. The center of the easterly wind
anomalies moves north and south of the equator following the seasonal migration of the climatological rainband(e.g., north of the equator in summer–early fall and south
in late winter–spring).
The composite evolution of sea surface height, surface
wind stress, and SST anomalies along the equator isshown for El Niño, La Niña, and their sum in Fig. 7
based on the SODA analysis and HadISST for 1958–
2007. The sea surface height anomalies, a proxy for thethermocline depth anomalies, exhibit asymmetric evolution for El Niño and La Niña similar to that of the SST
anomalies. The sea surface height anomalies precede the
SST anomalies by approximately one month, indicativeof the subsurface influence on SSTs. During year 0 thesea surface height anomalies propagate eastward in both
El Niño and La Niña in contrast to the SST anomalies
that show westward (La Niña) or almost no phase propagation (El Niño). In the sum of El Niño and La Niña1 NOVEMBER 2010

OKUMURA AND DESER

5837

FIG. 6. Latitude–time sections of composite SST (8C, color shading), surface wind (m s21, vectors), and precipitation [mm day21,
positive (negative) contours in green (orange) at intervals of 1] anomalies in (left) the far western (1408–1708E) and (right) western-central(1708E–1508W) Pacific for (top) El Niño and (bottom) La Niña. The stippled region indicates the climatological precipitation .8mm day21.
Based on the OISST, NCEP–DOE reanalysis II, and CMAP for 1982–2008.

composites, easterly wind anomalies develop over the
far western Pacific in Nov0 due to the weakening of
the westerly wind anomalies during El Niño. These
easterly wind anomalies are associated with negative
sea surface height anomalies that propagate from thewestern to the central-eastern Pacific in Nov0–Feb11.
These features suggest that during El Niño the weakening of the westerly wind anomalies in Nov0 forces an
upwelling oceanic equatorial Kelvin wave that rapidly
terminates the equatorial warming. The timing of thiswind change indicates that it is not caused by the decayof the equatorial warming but rather the other way
around. Indeed, observational and modeling studies
suggest that in addition to Rossby wave reflection at thewestern boundary, wind changes in the western Pacificforce a large part of equatorial Kelvin waves that contribute substantially to the demise of El Niño in 1997/98(McPhaden and Yu 1999; Delcroix et al. 2000; Picaut
et al. 2002; Boulanger et al. 2003).

c. Impact of the Indian Ocean SST anomalies
Previous studies suggest that the basin warming of thetropical Indian Ocean is responsible for the weakening
or reversal of equatorial westerly wind anomalies over
the western Pacific at the mature phase of El Niño(Annamalai et al. 2005; Kug and Kang 2006; Ohba andUeda 2007; Yoo et al. 2010). The Indian Ocean warming
increases tropospheric temperatures by moist adiabatic
adjustment in deep convection and forces a baroclinic
atmospheric equatorial Kelvin wave into the Pacific.
The resulting equatorial low pressure anomaly induces
anomalous northeasterly winds over the northwest
tropical Pacific, causing surface wind divergence andsuppressed deep convection in the subtropics (Xie et al.
2009). It was shown in Fig. 5 that composite ocean–atmosphere anomalies over the Indian Ocean exhibit
a similar seasonal evolution between El Niño and La Niñawith the sign reversed. This raises the question, does the5838

JOURNAL OF CLIMATEVOLUME 23

FIG. 7. Longitude–time sections of composite sea surface height (cm, color shading), surface wind stress (N m22, vectors), and SST(8C, black contours at intervals of 0.4) anomalies along the equator (38S–38N) for (left) El Niño, (middle) La Niña, and (right) their sum.
The SST anomalies are smoothed in the longitudinal direction with a 1–2–1 filter. Based on the SODA analysis and HadISST for
1958–2007.

basin cooling of the Indian Ocean during La Niña exert
any influence on the Pacific?
The composite seasonal evolution of tropospheric temperature, surface wind, and precipitation anomalies along
the equator for El Niño and La Niña are compared inFig. 8 based on the NCEP–DOE reanalysis II and CMAP
data for 1982–2008. Over the Pacific, tropospheric temperatures exhibit positive (negative) anomalies starting inMay0 concurrent with the underlying SST changes during
El Niño (La Niña). Over the Indian Ocean, tropospherictemperature anomalies also follow closely the underlying
SST anomalies. Tropospheric warming (cooling) occurs
first over the western Indian Ocean in Jul0–Aug0 andstarts to expand eastward in Oct0–Nov0 as the cooling(warming) off Sumatra weakens. During El Niño, thisexpansion of the tropospheric warming from the Indian
Ocean to the Pacific induces anomalous surface easterly
winds at its eastern edge, weakening the anomalous
westerly winds between 1108 and 1608W. During La Niña,the tropospheric cooling over the Indian Ocean also
forces anomalous westerly winds at its eastern edge.
However, the surface wind anomalies in the western
Pacific are also influenced by the negative precipitation anomalies over the western half of the basin thatinduce easterly wind anomalies. Thus, the westerly wind

anomalies forced by the Indian Ocean compete withthe easterly anomalies induced by the Pacific rainfall
anomalies.
We conjecture that the reason why the Pacific influencewins out over the Indian Ocean influence during La Niñabut not during El Niño is that the Pacific precipitation
anomalies are located farther west during La Niña compared to El Niño, which in turn is due to the nonlinear
response of precipitation to SSTs (Fig. 9). Thus, the108–158 longitudinal shift of precipitation anomalies in the
Pacific between El Niño and La Niña events seems to
make a difference in the balance of local and remote wind
forcing over the western Pacific. This zonal shift of the
deep convection anomalies is also evident in the composite
analysis of cloudiness anomalies based on shipboard observations from the International Comprehensive Ocean–Atmosphere Dataset (Woodruff et al. 2008) before the
CMAP data period (not shown). The eastward displacement of precipitation anomalies during El Niño may alsoenable atmospheric circulation anomalies forced by negative SST and precipitation anomalies in the northwest
tropical Pacific to affect the equatorial winds. Analysis ofIndian Ocean SST anomalies for individual El Niño and
La Niña events suggests that the Pacific events tend to
decay more rapidly when the Indian Ocean SST anomalies1 NOVEMBER 2010

OKUMURA AND DESER

5839

FIG. 8. Longitude–time sections of composite tropospheric temperature (8C, color shading),
surface wind (m s21, vectors), and precipitation [mm day21, positive (negative) contours ingreen (orange) contours at 61, 3, 5, . . .] anomalies along the equator (38S–38N) over the Pacificand Indian Oceans for (top) El Niño and (bottom) La Niña. The tropospheric temperatures areaveraged between 850 and 250 hPa. The precipitation anomalies are smoothed in the longitudinal direction with a 1–2–1 filter. The gray vertical line at 1408E indicates the approximate
location of the western end of the equatorial Pacific. Based on the NCEP–DOE reanalysis II
and CMAP for 1982–2008.

are stronger and develop earlier (not shown). A recent
study by Izumo et al. (2010) shows that ENSO forecasts
can be significantly improved by including the state of the
Indian Ocean SST anomalies in a simple statistical model.
Finally, we suggest that the lack of a reversal in sign ofthe easterly wind anomalies in the western Pacific is responsible for the prolongation of La Niña into the next
year. The return to normal conditions or transition to El
Niño may be achieved via a buildup of the equatorial heat
content due to slow oceanic adjustment (e.g., Jin 1997;
Meinen and McPhaden 2000), as suggested by a gradualincrease in the equatorially averaged sea surface heightanomalies in the La Niña composite (Fig. 7) and individual multiyear La Niña events (not shown).

4. Summary
By analyzing a suite of ocean–atmosphere data for the
past 27–109 yr, we have shown that there is a strong
asymmetry in the duration of El Niño and La Niña. BothEl Niño and La Niña typically begin in late spring–summer and intensify through the equatorial cold season.
While most El Niños terminate rapidly after peaking
toward the end of the year, many La Niñas persist
through the following spring–summer and reintensify inwinter; some even last through a third year and again
strengthen during winter. The negative SST anomalies
associated with La Niña propagate eastward during year 0,
but the reintensified cooling near the end of year 11

5840

JOURNAL OF CLIMATEVOLUME 23

FIG. 9. Schematic diagram illustrating the hypothesized cause of the asymmetric wind response in the far western equatorial Pacific between (top) El Niño and (bottom) La Niña during
the mature phase. Pink (blue) shaded ellipses depict positive (negative) SST anomalies over the
Pacific and Indian Ocean during El Niño (La Niña). Red (blue) arrows indicate surface wind
anomalies forced by Pacific SST anomalies during El Niño (La Niña); black arrows indicate
surface wind anomalies forced by Indian Ocean SST anomalies. In the far western Pacific, theeasterly (westerly) surface wind anomaly induced by the atmospheric Kelvin wave response totropospheric heating (cooling) over the Indian Ocean balances (fails to balance) the westerly(easterly) surface wind anomaly forced by precipitation anomalies over the Pacific during
El Niño (La Niña). The lack of balance of the surface wind anomalies over the far western
Pacific during La Niña results from the westward shift of the Pacific precipitation anomaly
because of the nonlinear dependence of atmospheric deep convection on the absolute SST. The
net easterly surface wind anomaly over the far western Pacific during La Niña is hypothesized
to prolong the event.

occurs simultaneously across the Pacific. Although thisasymmetry in duration has been noted in a few recent
studies, we demonstrate that it is a robust feature of
ENSO variability throughout the past century.
The proposed mechanism for this asymmetric duration
is summarized in a schematic diagram (Fig. 9). Because of
the nonlinear response of atmospheric deep convection
to SSTs, the center of the anomalous precipitation isdisplaced 108–158 of longitude farther west during La
Niña compared to El Niño. Through the developing andmature phases of La Niña, the suppressed atmospheric
convection drives strong anomalous easterly winds overmuch of the western Pacific. El Niño exhibits a similar
structure with reversed sign, except that a month prior tothe mature phase, anomalous westerly winds begin to
weaken in the far western Pacific. As suggested fromprevious studies, the delayed basin warming of the Indian
Ocean increases tropospheric temperatures and forcesa baroclinic atmospheric Kelvin wave into the western
Pacific during El Niño. The easterly winds induced by this

Kelvin wave weaken the anomalous westerly winds over
the western Pacific. The same mechanism appears towork during La Niña, with the Kelvin wave forced by thebasin cooling of the Indian Ocean inducing anomalous
westerly winds at its eastern edge. However, the impact of
local precipitation changes is so large that the anomalous
equatorial winds remain easterly over the western Pacific.
The enhanced duration of zonal wind anomalies in thewestern Pacific during La Niña compared to El Niño inturn leads to the prolongation of La Niña conditions into
a second and sometimes even a third year. Preliminary
analysis of atmospheric GCM experiments support thishypothesis, the results of which will be reported in a separate paper.
Our analysis focuses on strong El Niños and La Niñas
for which the Niño-3.4 index exceeds one standard deviation at the mature phase (December). There is noapparent asymmetry in the duration of weaker warm andcold phases (see Fig. 1 for the Niño-3.4 time series for
1948–2008). During weaker warm phases, the equatorial1 NOVEMBER 2010

5841

OKUMURA AND DESER

SST anomalies are often centered in the central Pacificand do not extend to the South American coast (Ashok
et al. 2007; Kug et al. 2009; Kao and Yu 2009). Hoerling
et al. (2001) also suggest that atmospheric deep convection responds linearly to moderate positive andnegative SST anomalies. Thus, both the SST anomalies and the atmospheric deep convection response lackspatial asymmetry in weaker events. Warm events that do
not develop until late summer–fall tend to be weaker andpersist longer into the second year (Horii and Hanawa
2004). The late onset may delay and weaken the Indian
Ocean SST response and hence the remote negative
feedback to the western Pacific (Sooraj et al. 2009). The
timing, pattern, and magnitude of SST anomalies in boththe Pacific and Indian Oceans appear to be importantfactors controlling the persistence of individual El Niñoand La Niña events, as well as intraseasonal variability
that causes event to event differences (McPhaden 2008).
Coupled ocean–atmosphere models need to be examined for their ability to simulate not only the asymmetry
in amplitude, but also the asymmetry in duration of thewarm and cold phases of ENSO. A realistic simulation of
the climatological rainbands in the tropical Pacific and
ENSO-related SST anomalies in the Indian Ocean area prerequisite. A cursory look at the 2000-yr control integration of the Geophysical Fluid Dynamics Laboratory
Climate Model version 2.1 (GFDL CM2.1) indicates that
this model exhibits asymmetry in the duration of El Niñoand La Niña similar to what we have found in the observational record (Wittenberg 2009; see his Fig. 1) while a
century-long control integration of the Community Climate System Model version 3 (Neale et al. 2008; Zhang
et al. 2009) shows very weak ENSO asymmetry. Analysisof the Coupled Model Intercomparison Project phase 3
multimodel dataset by Ohba et al. (2010) indicates thatthe observed asymmetry in the duration of El Niño and
La Niña is poorly simulated in most coupled GCM except
in a few models including the GFDL CM2.1. Comparedto the models that simulate the transition of El Niños to
La Niñas after the mature phase, the models that simulate
more persistent El Niños show equatorial Pacific precipitation anomalies displaced farther west because of theunrealistically strong climatological cold tongue. In thesemodels, the basin warming of the Indian Ocean is alsomuch weaker than in the models of high El Niño-toLa Niña transitivity. Ohba et al. (2010) argue that the
westward shift of the Pacific precipitation anomalies
allows equatorial wind anomalies to persist longer over
the western Pacific, in agreement with our hypothesis.
These results reaffirm the importance of realistic simulation of the mean climate for realistic simulation of
ENSO. Long simulations of climate models that successfully simulate the observed ENSO asymmetries will

provide an opportunity to assess how these aspects of
ENSO may be modulated by climate change and variability with longer time scales.
Acknowledgments. Y. M. Okumura was supported
through the NOAA Climate and Global Change Postdoctoral Fellowship and the funding for visiting scientists at the Climate and Global Dynamics Division of
NCAR during the course of this study. The authors
thank G. Vecchi, S.-P. Xie, S. Minobe, and M. Ohba for
helpful discussion, J. M. Wallace and two anonymous
reviewers for their constructive comments and suggestions, Y. Shen and J. Fasullo for their help in obtaining the ocean reanalysis data, and A. Phillips andD. Shea for technical assistance. The datasets used inthis study were obtained online: the HadISST from the
Met Office Hadley Centre (http://hadobs.metoffice.com/
hadisst/), the OISST, NCEP reanalysis, NCEP–DOE
reanalysis II, and CMAP from the NOAA/Earth System
Research Laboratory Physical Science Division (http://
www.esrl.noaa.gov/psd/data/gridded/), and the SODA
analysis from the Asia–Pacific Data Research Center(http://apdrc.soest.hawaii.edu/).

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