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Anatomy and Decadal Evolution of the Pacific Subtropical–Tropical Cells (STCs)*
ANTONIETTA CAPOTONDI AND MICHAEL A. ALEXANDERNOAA–CIRES Climate Diagnostics Center, Boulder, Colorado

CLARA DESER
National Center for Atmospheric Research, Boulder, Colorado

MICHAEL J. MCPHADENNOAA/Pacific Marine Environmental Laboratory, Seattle, Washington(Manuscript received 9 September 2004, in final form 25 February 2005)
ABSTRACTThe output from an ocean general circulation model driven by observed surface forcing (1958–97) is used
to examine the evolution and relative timing of the different branches of the Pacific Subtropical–Tropical
Cells (STCs) at both interannual and decadal time scales, with emphasis on the 1976–77 climate shift. The
STCs consist of equatorward pycnocline transports in the ocean interior and in the western boundary
current, equatorial upwelling, and poleward flow in the surface Ekman layer. The interior pycnoclinetransports exhibit a decreasing trend after the mid-1970s, in agreement with observational transport estimates, and are largely anticorrelated with both the Ekman transports and the boundary current transports
at the same latitudes. The boundary current changes tend to compensate for the interior changes at bothinterannual and decadal time scales. The meridional transport convergence across 9°S and 9°N as well as theequatorial upwelling are strongly correlated with the changes in sea surface temperature (SST) in thecentral and eastern equatorial Pacific. However, meridional transport variations do not occur simultaneously at each longitude, so that to understand the phase relationship between transport and SST variations it is important to consider the baroclinic ocean adjustment through westward-propagating Rossby
waves. The anticorrelation between boundary current changes and interior transport changes can also be
understood in terms of the baroclinic adjustment process. In this simulation, the pycnocline transportvariations appear to be primarily confined within the Tropics, with maxima around 10°S and 13°N, andrelated to the local wind forcing; a somewhat different perspective from previous studies that have emphasized the role of wind variations in the subtropics.

1. Introduction
Several recent studies have found evidence for climate variability on decadal time scales in both thetropical and extratropical Pacific (e.g., Trenberth 1990;
Tanimoto et al. 1993; Wang and Ropelewski 1995;
Mantua et al. 1997; Zhang et al. 1997; Deser et al. 2004).
A well-known example is the “shift” in the atmo-* Pacific Marine Environmental Laboratory Publication Number 2734.

Corresponding author address: Dr. Antonietta Capotondi,
NOAA–CIRES Climate Diagnostic Center, R/CDC1, 325 Broadway, Boulder, CO 80305.
E-mail: Antonietta.Capotondi@noaa.gov© 2005 American Meteorological Society

JCLI3496

sphere–ocean system that took place in 1976–77 (Nitta
and Yamada 1989; Trenberth and Hurrell 1994; Yasuda
and Hanawa 1997). Because of the longer time scales
involved in the oceanic adjustment compared to theatmosphere, oceanic processes are likely involved in
the origin of decadal time scales of climate variability.
Several mechanisms have been proposed to explain
decadal variability in the Tropics and extratropics.
Some mechanisms invoke air–sea interactions and adjustment of the ocean circulation through Rossby wave
propagation in midlatitudes (Latif and Barnett 1996);
others are based on tropical–subtropical interactions(Gu and Philander 1997; Kleeman et al. 1999; Solomon
et al. 2003) or rely on processes within the tropical band
(Knudson and Manabe 1998; Chang et al. 2001; Luoand Yamagata 2001; Timmermann and Jin 2002).

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FIG. 1. Meridional streamfunction computed from the NCAR
OGCM. Contour interval is 5 Sv. Thick arrows indicate the direction of the zonally averaged circulation.

Two of these mechanisms involve the subtropical–
tropical ocean circulation. The wind-driven upperocean circulation can be regarded as a shallow overturning cell, the subtropical–tropical cell (STC; McCreary and Lu 1994; Liu 1994), in which subtropicalwater subducts into the main thermocline, upwells at
the equator, and then returns to the subtropics in thethin surface Ekman layer (Fig. 1). The mechanism proposed by Gu and Philander (1997) relies on the subduction of surface temperature anomalies in midlatitudes and their downward and equatorward propagation along mean isopycnals. While observations show
evidence of thermal anomalies subducting in the main
thermocline in the northern midlatitudes (Deser et al.
1996; Schneider et al. 1999), these anomalies decay
away from the subduction region, and the thermocline variability found equatorward of ⬃18° appears
to be primarily associated with tropical wind forcing(Schneider et al. 1999; Capotondi et al. 2003). Thus, it
seems unlikely that the Gu and Philander (1997)
mechanism can significantly contribute to the modulation of equatorial SST anomalies on decadal timescales.
An alternative hypothesis is that changes in the winds
may spin up or slow down the STCs in both the Northern and Southern Hemispheres, thus changing the rate
at which water of constant properties is transported
toward the equator and consequently altering thestrength of equatorial upwelling. This mechanism contrasts with the Gu and Philander (1997) hypothesis,
which involves advection of thermal anomalies by themean circulation. Using an intermediate coupledmodel, consisting of a 3–1/2 layer shallow water model
coupled with a statistical atmosphere, Kleeman et al.
(1999) have shown that decadal variations of tropical
SSTs can be induced by changes in the subtropicalwinds. In their ocean model, the strength of the STCs isdetermined by the meridional transport divergenceacross 23°N and 23°S, equatorward of which subduction

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is suppressed. In turn, the meridional transport divergence is set by the Ekman transport divergence along
the same latitudes. Thus in their study, changes in equatorial SSTs are primarily related to changes in windstress and subduction rates in the subtropics (polewardof ⬃23°).
Subduction rates control the equatorward masstransport in the thermocline. Depending upon the longitude at which water subducts, fluid can reach theequator following a pathway in the ocean interior, or it
may reach the western boundary current first and thenflow equatorward through the western boundary current pathway (Liu et al. 1994). Thus, the STCs can beviewed as composed of different branches, which include the interior equatorward flow (IN), the equatorward flow in the low-latitude western boundary currents (BCs; consisting of the Mindanao current in the
Northern Hemisphere and the New Guinea Coastal
Current in the Southern Hemisphere), plus the equatorial upwelling branch (UPW), and the poleward Ekman transport in the surface Ekman layer (EKM).
Changes in the winds do not only alter the Ekman divergence and the rate of subduction in the subtropics,
but they also change the rate of equatorial upwelling.
To better understand how subtropical wind stressvariations can influence equatorial SSTs, Klinger et al.
(2002) forced the ocean component of the coupledmodel used by Kleeman et al. (1999) with idealized
wind fields and examined the evolution of the different
branches of the model STC (with the exclusion of thewestern boundary transport) from a zonally averaged
perspective. Their conclusions are that the interior
thermocline transport is weaker than the Ekman transport and equatorial upwelling. Moreover, the interiortransport lags the equatorial SST variations, a resultthat appears in disagreement with the hypothesizedcausal relationships between thermocline transport andSST variations. In Klinger et al.’s (2002) study, equatorial SSTs are almost coincident with, but slightly lag,changes in surface Ekman transport and equatorial upwelling, so that the surface and upwelling branches appear to be better predictors of the influence of subtropical winds upon equatorial SSTs. Thus, the study ofKlinger et al. (2002) raises some questions about theinterplay and relative timing of the different STC’s
branches, and their role in equatorial SST variations.
Using an ocean general circulation model (OGCM)
forced by observed winds, Nonaka et al. (2002) findthat equatorial winds (5°S–5°N) are as important as
extraequatorial winds (poleward of 5°) for the decadal
modulation of equatorial SSTs. The processes by which
extraequatorial winds affect equatorial SSTs involvethe spinup and spindown of the STCs, as described by

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Kleeman et al. (1999) and Klinger et al. (2002). Nonaka
et al. (2002) also note that wind stress variations poleward of 20°S and 25°N do not seem to play any significant role in forcing equatorial SST anomalies.
The mechanism of tropical decadal variability proposed by Kleeman et al. (1999) is supported by theobservational study of McPhaden and Zhang (2002,
hereafter MPZ). Using subsurface measurements, MPZ
have shown that the increase in equatorial SSTs overthe last 50 yr is associated with decreased zonally averaged equatorward transports at 9°S and 9°N in theocean interior. Because of the sparsity of subsurface
observations, the data were binned over time intervalsof approximately 10 yr, yielding four transport estimates over a 50-yr period. Thus, the phase relationshipbetween interior mass convergence and SST variations
could not be easily established. Since the available observations are unable to resolve the western boundary
currents, the western boundary current transports werecomputed as differences between the surface Ekman
transports and the interior transports. However, different wind products can produce very different estimatesof Ekman transports, introducing large uncertainties inthe estimates of both Ekman and boundary current
transports. MPZ also found that decadal changes inboundary current transports could not be detected
above the noise level of their calculation. Estimates ofthe Mindanao Current transport inferred from tidegauge data (Lukas 1988) showed, on the other hand,transport variations concurrent with El Niño–Southern
Oscillation (ENSO) events, and the modeling study ofSpringer et al. (1990) showed anticorrelated boundary
and interior transports around 5°N (S) over the period
1979–83. Using a model simulation for the period 1980–
2000, Lee and Fukumori (2003, hereafter LF03) haveshown the tendency for the boundary current transports to compensate the interior transport changes atboth interannual and decadal time scales, a result supported by satellite altimetry observations. The variability of the boundary current and interior transports, andthe possibility of a partial compensation of the two on
decadal time scales, can be very important for the heatbudget of the tropical Pacific (Hazeleger et al. 2004).
Another open question concerns the influence of theIndonesian Throughflow (ITF) in the mass balance ofthe tropical Pacific. The Mindanao Current is considered the major source of ITF water. Do transportchanges in the Mindanao Current affect the tropical
Pacific mass balance, or do they exit the Pacific basinthrough the ITF?
In this paper, we use an OGCM driven by observed
surface forcing to examine the evolution of the different branches of the Pacific STCs across a broad range

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of time scales from interannual to decadal–interdecadal. The advantages of using a realistic OGCM
include not only the availability of complete information in space and time, but also consistency between
variations in wind forcing and ocean circulation. The
OGCM we are using is global and includes an ITF, sothat ITF variations can be explicitly estimated from themodel. The specific questions we focus upon are as
follows: 1) What is the relative timing and phase relationship of the different branches of the STC? 2) Whatis the relationship between the STC components andtropical SST changes from both a zonally averaged andthree-dimensional perspective? And 3) what is the latitudinal range over which decadal changes in ocean circulation are significant? Do they extend to the subtropics, as described by Kleeman et al. (1999), or are they
limited to the tropical region?
We start our analyses by examining the zonally averaged equatorward transports at 9°S and 9°N, using amethodology very similar to the one adopted by MPZ.
After comparing the model’s transport estimates withthe observational estimates, we exploit the completeness of the model data and their consistency with thesurface wind forcing, to sharpen the observational perspective; in particular, we will examine the evolution of
the transports at a finer time resolution, as well as therelationship between interior transport and boundaryand Ekman transports. We then consider the threedimensional evolution of the STCs and examine therelative contribution of the different STC branches to
the SST changes while the system is adjusting. Bothinterannual and decadal–interdecadal time scales
will be examined, but our major focus will be on thedecadal–interdecadal variations, and in particular those
associated with the 1976–77 climate shift. Thus, ourstudy will extend the modeling study of LF03 (1980–
2000) by including the changes that took place acrossthe mid-1970s.
The paper is organized as follows: In section 2 we
describe the model used for this study; in section 3 weconsider the relationship between the different components of the STCs and equatorial SSTs; in section 4 we
examine the three-dimensional evolution of the STCs;
and in section 5 we determine the latitudinal range
about the equator over which upper-ocean changes associated with decadal variability are significant. Conclusions are given in section 6.

2. The OGCM
The OGCM used for this study is the National Center for Atmospheric Research (NCAR) ocean model(NCOM) that has been described in detail by Large et3742

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al. (1997), Gent et al. (1998), and Large et al. (2001).
The specific numerical simulation analyzed here is described in Doney et al. (2003). In this section we only
provide a brief summary of the basic model characteristics and information about the surface forcing used forthis simulation.
NCOM is derived from the Geophysical Fluid Dynamics Laboratory (GFDL) Modular Ocean Modelwith the addition of a mesoscale eddy flux parameterization along isopycnal surfaces (Gent and McWilliams
1990) and a nonlocal planetary boundary layer parameterization (Large et al. 1994). The model is global,
with a horizontal resolution of 2.4° in longitude andvarying resolution in latitude, ranging from 0.6° near
the equator to 1.2° at high latitudes. The model version
used for this study includes an anisotropic viscosity parameterization (Large et al. 2001) with enhanced viscosity close to ocean boundaries and much weaker viscosity in the ocean interior.
The surface forcing includes momentum, heat, andfreshwater fluxes for the period 1958–97. The windstress is computed from the reanalysis fields produced
at the (National Centers for Environmental Prediction)
NCEP–NCAR (Kalnay et al. 1996) using bulk formulas. The sensible and latent heat fluxes are computedfrom the NCEP winds and relative humidity and themodel’s SSTs using standard air–sea transfer equations(Large and Pond 1982; Large et al. 1997). Sensible andlatent heat fluxes depend on the difference between
SST and surface air temperature. Since SST and airtemperature closely track each other, when observed
air temperatures are used in the bulk formulas, as in thepresent model simulation, the model’s SST is relaxed
toward observations (Haney 1971). The relaxation timescale is usually short (30–60 days for typical mixed layer
depths), so that the SST in the model can be expected
to be strongly constrained by the surface forcing rather
than by the interior ocean dynamics. In the equatorial
region, however, ocean processes (in particular upwelling) have a controlling influence upon SST, and thesurface heat fluxes act to damp the SST anomalies. The
damping coefficients estimated for the model using aleast squares fit approach are negative over most of thetropical Pacific and correspond to damping time scales
longer than 30–60 days. For example, the damping timescale in the Niño-3 region, given the average mixed
layer depth of ⬃40 m in that area, is 130 days, a value
very close to that estimated from observations (126 ⫾ 3days) with a similar methodology (Niiler et al. 2004).
The NCEP forcing was chosen because of its multidecade history and global coverage. We recognize that theresults will be sensitive to the choice of the wind stress

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forcing, but we expect that our results would not qualitatively change with different forcings.
The numerical simulation is started from an initialcondition obtained from a preliminary mean seasonal
climatological integration, so that the initial model state
is not too different from the mean state characteristic of
the 40-yr experiment. To allow for deep ocean adjustment, the model was then run for two identical 40-yr
cycles, using the NCEP winds for 1958–97, the second
cycle starting from the conditions achieved at the end of
the first 40-yr segment. The mismatch between themodel state and the forcing at the beginning of thesecond cycle did not seem to produce any long-termtransient behavior. Here we analyze the output for thesecond 40-yr period using monthly and annual meanvalues. Some residual drift in temperature and salinity
appears to be confined to depths larger than approximately 500 m (Doney et al. 2003).

3. Anatomy of the STCs
a. The pycnocline transport components
From a three-dimensional perspective, the interiortransport of the STCs consists of water subducting into
the main thermocline along outcrop lines of isopycnals
and then flowing equatorward along the mean isopycnals. Since potential vorticity is a quasi-conserved
quantity, water parcels approximately follow lines of
constant potential vorticity, so that the potential vorticity structure strongly constrains the pathways of theflow. Figure 2 shows the mean potential vorticity on the
25 ␴␪ isopycnal, together with the mean velocities in theupper-to-middle pycnocline (the time-averaged velocities integrated from the bottom of the Ekman layer tothe depth of the 25 ␴␪ isopycnal). The model pycnocline
flow is qualitatively consistent with that predicted by
the ventilated thermocline theory (Luyten et al. 1983).
In the Northern Hemisphere, the presence of the intertropical convergence zone (ITCZ) in the 7°–12°N latitude band is associated with a tongue of high potential
vorticity in the eastern side of the basin, which acts as a“barrier” for the flow moving toward the equator. As aconsequence, the interior pathways connecting the subtropics to the equator in the Northern Hemisphere aremuch more convoluted than those in the Southern
Hemisphere (Johnson and McPhaden 1999). Comparison with the potential vorticity field computed fromobservations (Fig. 1b in MPZ) shows that the potential
vorticity structure on the 25 ␴␪ isopycnal in the model isvery similar to the one estimated from observations,although the potential vorticity ridge at 7°–12°N issomewhat weaker in the model than in observations.
Following MPZ, we compute the different compo-

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FIG. 2. Contours of mean potential vorticity over the 25 ␴␪ isopycnal. The arrows indicate
the averaged upper-ocean velocities, integrated from the base of the surface Ekman layer(⬃50-m depth) to the depth of the 25 ␴␪ isopycnal.

nents of the meridional transports along 9°S and 9°N.
The latitude of 9°N was chosen because it represents achoke point for the meridional geostrophic transport(Fig. 2), and 9°S was chosen for hemispheric symmetry.
Sections of mean meridional velocities along 9°N and
9°S are shown in Fig. 3. Along both latitudes, the poleward Ekman transport is confined approximately to theupper 50 m, and the interior equatorward flow is foundprimarily above the mean 26 ␴␪ isopycnal (thick solidlines in Figs. 3a and 3b), which is near the base of thepycnocline as defined in MPZ. Notice that at 9°N thelargest equatorward interior flow occurs between approximately 180° and 140°W. East of 140°W, the communication between the Tropics and extratropics is impeded by the potential vorticity barrier, while west of
the date line, the flow tends to be more zonal and will
primarily feed the Mindanao current. At 9°S the largest
interior flow extends from ⬃160° to ⬃90°W. Because of
the absence of a potential vorticity barrier in the Southern Hemisphere, an intense equatorward flow can befound almost all the way to the eastern boundary. Westof 160°W, currents are primarily westward and feed the
New Guinea Coastal Current.
The zonally averaged interior transport is estimatedby vertically integrating the meridional velocity from 50m (the approximate depth of the Ekman layer) to thedepth of the 26 ␴␪ isopycnal and then integrating zonally from the eastern edge of the western boundary
currents (137°E at 9°N and 160°E at 9°S) to the easternboundary. The western boundary current transport isestimated by integrating the meridional velocity fromthe surface to the depth of the 26 ␴␪ isopycnal and thenzonally from the western boundary to 160°E at 9°S and
137°E at 9°N. At 9°N the mean transport of the westernboundary current is 15.8 Sv (1 Sv ⬅ 106 m3 s⫺1), and theinterior transport is 5.4 Sv, while at 9°S the boundary
current and interior transports are 8 and 9.6 Sv, respectively.
The value of the mean boundary current transport at
9°N is close but slightly higher than observational esti-

FIG. 3. Sections of mean meridional velocity at (top) 9°N and(bottom) 9°S. Dark shading indicates northward velocities, andlight shading is for southward velocities. The poleward flow in theupper 50 m corresponds to the Ekman transport. The thick solidlines indicate the mean depth of the 26 ␴␪ isopycnal.

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mates: 13 Sv by Lukas et al. (1991) at 10°N based on
Acoustic Doppler Current Profiler (ADCP) measurements, 15 Sv by Wijffels et al. (1995) at 8°N based on an
inverse model of hydrography, and 14 Sv by Huang and
Liu (1999) based on the NCEP ocean model. The model’s interior transport at 9°N is very close to the 5-Sv
value estimated by Johnson and McPhaden (1999) at
8°N using hydrographic data over the period 1967–98
and is a little higher than the value of 4 Sv obtained by
Wijffels et al. (1995) and Huang and Liu (1999). The
mean interior transport at 9°N from all hydrographic
data over the period 1956–99 (MPZ) is ⬃7 Sv, higher
than all other estimates. Thus, the model interior meantransport seems to be within the observational values.
The mean model transports in the western boundary
current and interior at 9°S are smaller by a few Sverdrups than the available observational estimates (Lindstrom et al. 1987; Butt and Lindstrom 1994; Johnson
and McPhaden 1999; Huang and Liu 1999). For reference, the mean interior transport from MPZ is 14 Sv. A
similar discrepancy with observations was also found in
the model examined by LF03. The model’s underestimate of the western boundary current transport was
primarily attributed to its inability to properly resolve
the two branches of the western boundary current, the
New Guinea and New Ireland Coastal Undercurrents,
as identified by Lindstrom et al. (1987) and Butt andLindstrom (1994), due to the limited model horizontal
resolution. Similar limitations exist for the model usedin the present study, whose horizontal resolution is alsocoarse. In addition, as noted by LF03, the mean wind
forcing can have a large influence on the magnitude of
the pycnocline transport, and it is plausible that the
NCEP wind product underestimates the wind stress andwind stress curl in some regions.
The time series of the interior pycnocline transport
anomalies at 9°N and 9°S are shown in Fig. 4a. The
monthly anomalies have been obtained by subtracting
the monthly means from the monthly averages of the
OGCM output and then smoothing the resulting timeseries with a three-point binomial filter. In Fig. 4, themodel’s interior pycnocline transport anomalies arecompared with the observational estimates of MPZ,
computed for 1956–65, 1970–77, 1980–89, and 1990–99.
Unfortunately, the period spanned by the model simulation (1958–97) does not exactly overlap with the period covered by the observational study (1950–99), sothat it is not possible to compute averages from themodel over the exact same periods. For the model, we
compute averages for 1960–65, 1970–77, 1980–89, and1990–97, which are compared in Fig. 4a with the observational values of MPZ. Notice that the period 1990–99
considered by MPZ includes the 1997–98 El Niño, of

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which the model only captures the initial phase. This
may partially explain the model’s underestimate of thetransport decrease in the 1990s with respect to observations. Overall, however, the model transport anomalies are within the error bars of the observed values.
We then compute the meridional transport convergence in the interior pycnocline across 9°S and 9°N(Fig. 4b) and compare the values of transport convergence estimated by MPZ with the model averages overthe same four periods used for the individual transports
at 9°S and 9°N, as in Fig. 4a. The largest discrepancies
are found in 1956–65, and in the 1990s, where the periods considered for the model do not fully overlap withthe observational periods. However, the differences between model and observations tend to be within theobservational error, and the decrease in transport fromthe early 1960s to the 1990s is ⬃11 Sv in both the modeland observations. Thus, the model seems to provide a
realistic representation of the transport changes, whichmakes it a suitable diagnostic tool to understand theprocesses underlying the transport variability.
In Fig. 5 the equatorward mass convergence in theinterior pycnocline is compared with the changes in
SST in the central and eastern equatorial Pacific (9°S–
9°N, 90°W–180°), the same area considered by MPZ.
Both time series are based on monthly anomalies andcan be compared on all time scales, from interannual todecadal. Notice that SST is shown with the sign reversed for ease of comparison. Increased (decreased)mass convergence is associated with increased (decreased) upwelling and lower (higher) SSTs. As a result, the two time series are largely anticorrelated (correlation coefficient is ⫺0.91), but the largest correlation
is found when the SST leads the meridional mass convergence by 2 months, a result that seems to be in disagreement with the view that changes in the strength of
the STCs cause the SST changes. The slight lag between
interior mass convergence and SST variations relies primarily upon the zonally averaged perspective that wehave adopted and that has also been adopted in most of
the previous studies. When the three-dimensional evolution of the STCs is considered, the phase relationshipbetween equatorward thermocline transport and equatorial SSTs emerges more clearly, as discussed in section 4.

b. The surface Ekman transport
The meridional Ekman transport per unit longitude
can be computed from the surface zonal wind stress:
Mc ⫽ ⫺

␶x
,
␳of

共1兲

where ␶x is the zonal component of the wind stress, f is

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FIG. 4. (a) Interior pycnocline transport at (top) 9°N and (bottom) 9°S from the model. The
time series are based on monthly anomalies and are smoothed using a 3-point binomial filter.
The black horizontal lines are averages of the model pycnocline transports for 1960–65,
1970–77, 1980–89, and 1990–97. The black vertical lines show the standard deviations of themodel monthly anomalies over each period. The gray horizontal lines are the observational
estimates of MPZ for 1956–65, 1970–77, 1980–89, and 1990–99. The gray vertical lines indicate
one standard error for the observational estimates. (b) Meridional transport convergence in
the interior pycnocline across 9°S and 9°N. The horizontal black lines are the model averages
for 1960–65, 1970–77, 1980–89, 1990–97, while the horizontal gray lines are the observational
estimates of MPZ for 1956–65, 1970–77, 1980–89, and 1990–99. The error bars for the observational estimates are indicated by the vertical gray lines, while the vertical black lines show
the standard deviations of the model monthly anomalies over each period.

the Coriolis parameter, and ␳o is the mean density ofseawater. The Ekman transport is to the right of thewind stress in the Northern Hemisphere and to the leftof the wind stress in the Southern Hemisphere. Along
9°S and 9°N, ␶x is negative, so that the Ekman transports are poleward in both cases. Equation (1) has been
integrated across the basin to obtain the zonally averaged Ekman transport. Figure 6 shows the comparison
between the interior pycnocline transports at 9°S and
9°N and the surface Ekman transports along the same
latitudes. The Ekman transports are shown with thesign reversed for ease of comparison. At 9°S the Ekman
transport is highly correlated with the interior transport: the maximum correlation coefficient is ⫺0.80 andoccurs when EKM leads IN by 4 months. At 9°N the
maximum correlation coefficient is ⫺0.55 and isachieved when EKM leads IN by 9 months. The lags
between EKM and IN along both latitudes are consistent with the view that the Ekman transport adjusts
almost instantaneously to changes in the surface windstress, while interior transport variations result fromthe ocean adjustment through Rossby wave propaga-

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FIG. 5. Comparison between monthly anomalies of interior meridional mass transport convergence across 9°S and 9°N (solid line), and areally averaged SST variations over the central
and eastern equatorial Pacific (9°S–9°N, 90°W–180°; dotted line). SST is plotted with the sign
reversed for ease of comparison. The correlation between the two time series is ⫺0.91, and itis achieved when the SST leads the transport convergence by 2 months. The correlation issignificant at the 99% level, based on a t-test criterion with the number of degrees of freedom
estimated according to Trenberth (1984).

tion, a much slower process. The large correlation between IN and EKM along 9°S and 9°N is an indicationof the large influence of the local wind variations uponinterior transport changes, in agreement with the results of Nonaka et al. (2002). The relationship between
variations of STC strength and wind forcing will befurther examined in section 5.

c. Interior versus boundary current transports
What is the relationship between equatorward pycnocline transports in the interior and in the westernboundary currents? In Fig. 7 the interior transports arecompared with the boundary current transports along
9°S and 9°N. The maximum correlation coefficients between the BC and IN time series are ⫺0.76 (BC leadsinterior by 2 months) and ⫺0.95 (lag 0 months) at 9°N
and 9°S, respectively. The correlations around the
maximum values decrease slowly as a function of lag,and the lag of 2 months between BC and IN at 9°N isstatistically indistinguishable from 0. Thus, the transport changes in the boundary currents tend to compensate for the transport changes in the interior, especiallyat 9°S. The strong anticorrelation between boundary
current changes and interior changes has been noted byother authors (Springer et al. 1990; LF03; Hazeleger et
al. 2004; Wang et al. 2003a) in both realistic and idealized model simulations. LF03 have introduced a standard-deviation-based criterion to quantify the degree ofcompensation between IN and BC:C⫽␴IN ⫺ ␴N
⫻ 100,
␴IN

共2兲

where ␴IN and ␴N are the standard deviations of theinterior transport and the net (IN ⫹ BC) transports,
respectively. For the time series in Figs. 7a and 7b, thedegrees of compensation, as expressed by C, are 22%
and 69%, respectively. These values are comparablewith those estimated by LF03 at 10°N (31%) and 10°S
(62%) over the period 1980–2000.
LF03 have interpreted the anticorrelation in terms oftime-dependent Sverdrup balance, which results fromthe adjustment of the low-latitude gyre circulation tovarying Ekman pumping. Because of the finite adjustment time, one might expect the magnitude of theboundary current changes to depend upon the frequency of the forcing. We have examined the relationship between IN and BC at decadal (periods longer
than 8 yr) and interannual (periods shorter than 8 yr)time scales. Our results (not shown) do not indicate any
appreciable difference in levels of compensation in the
two time-scale ranges. On the contrary, at 9°N the levelof compensation is larger at interannual than decadal
time scales. The correlation and level of compensation
between BC and IN at decadal time scales are muchhigher at 13°N than at 9°N (not shown). As described in
more detail in section 5, the latitude of 13°N is characterized by a local maximum in Rossby wave activity(Capotondi et al. 2003), which results in large thermocline displacements and meridional transport variations.
The Mindanao Current is one of the largest sourcesof ITF. Is the increase in the Mindanao Current transport after the mid-1970s feeding the ITF, or is it mainly
affecting the mass balance of the tropical Pacific? Be-

15 SEPTEMBER 2005

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FIG. 6. Comparison between IN and EKM at (a) 9°N and (b)9°S. All time series are based on monthly anomalies and aresmoothed with a 3-point binomial filter. The Ekman transport
time series is shown with the sign reversed for ease of comparison.
At 9°N the maximum correlation coefficient between EKM and
IN is ⫺0.55 and is achieved when EKM leads IN by 9 months. At
9°S the max correlation coefficient is ⫺0.80, with EKM leading IN
by 4 months. The correlation between IN and EKM at 9°S issignificant at the 99% level, while that at 9°N is only significant at
the 95% level.

cause of the complex geometry of the Indonesian Archipelago, and the difficulty of tracking the pathways ofthe flow along the different passages, we examine thechanges in ITF on the Indian Ocean side, along 115°E,
from 20° to 9°S. The average ITF transport in themodel, integrated from top to bottom, is 7.8 Sv. Observational estimates of total and partial ITF transports,
using either direct or inverse methods, range from small
negative values (flow from the Indian Ocean to the
Pacific) to positive values close to 20 Sv (flow from the
Pacific to the Indian Ocean; see Godfrey 1996 for areview). Using an inverse calculation, Macdonald(1998) estimates an ITF of 10 ⫾ 10 Sv. Thus, the mean
ITF transport in the model is within the range of observational estimates. The model ITF varies seasonallywith a maximum in July–August of ⬃13.5 Sv and aminimum of ⬃4.5 Sv in January. Its seasonal variationis qualitatively consistent with that estimated by Meyers

3747

FIG. 7. Comparison between the evolution of the equatorward
pycnocline transports in the interior and in the western boundary
currents along (a) 9°N and (b) 9°S. All time series are based onmonthly anomalies and are smoothed with a 3-point binomial
filter. At 9°N the correlation coefficient is ⫺0.76, with BC leading
IN by 2 months. At 9°S the correlation coefficient is ⫺0.95 at lag
0. At both latitudes, correlations are significant at the 99% level.

(1996) from expendable bathythermograph (XBT) data
and those simulated by Masumoto and Yamagata(1996) and Lee et al. (2002).
The changes in the Indian Ocean outflow (integrated
from the surface to the depth of the 26 ␴␪ isopycnal andmeridionally across the section) between 1977–97 and
1960–76 indicate a small decrease of the outflow (⬃0.3
Sv) after the mid-1970s, in spite of the increased transport of the Mindanao Current. Thus, variations in ITF
cannot be expected to significantly alter the mass balance in the tropical Pacific. A similar conclusion wasreached by LF03 for the changes during 1980–2000 and
by MPZ for changes from the 1950s to the 1990s using
the NCEP winds and Godfrey’s Island Rule (Godfrey1989).

d. Upwelling
The model mean vertical velocity (w) field is characterized by intense upwelling in a narrow band along
the equator, extending from ⬃2°S to 2°N and from

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FIG. 8. (a) Mean vertical velocity over the period 1958–97 at
50-m depth. Contour interval is 0.5 ⫻ 10⫺3 cm s⫺1. (b) Verticalvelocity difference between Period2 (1977–97) and Period1(1960–76) at 50-m depth. Contour interval is 0.25 ⫻ 10⫺3 cm s⫺1.

175°E to 90°W (Fig. 8a), and continuing with lower
values to the eastern boundary and along the coast ofSouth America. The upwelling band along the equatoris bounded on either side by broader and weaker downwelling areas, which are associated with the nearequatorial tropical cells. In the vertical plane, the largest upwelling occurs in the 40–90-m depth range (Fig.
1), close to the base of the Ekman layer, which is located at ⬃50-m depth.
To characterize the variability in the w-field, we startby considering the changes associated with the 1976–77
climate shift. Since the STCs appear to slow down after
the mid-1970s, upwelling should also decrease after
1976. Figure 8b shows the differences in the w-field at
50 m between Period2 (1977–97) and Period1 (1962–75). The largest changes are found in the equatorial
upwelling band, where the vertical velocity is ⬃20%
weaker in Period2 versus Period1. This result is in disagreement with the findings of Klinger et al. (2002),
based on idealized experiments forced by trade windsof different intensities. Klinger et al. (2002) showed thatchanges in the STC’s strength are not associated withchanges in the intensity of the equatorial upwelling, butwith variations in the longitudinal extent of the upwelling region. On the contrary, in our OGCM simulation the longitudinal extent of upwelling remains approximately unchanged, while the amplitude of the upwelling exhibits a significant reduction. The idealized

VOLUME 18

wind stress anomalies used by Klinger et al. (2002) did
not include any anomalous forcing along the equator, afactor that may partially contribute to the differenceswith our results. The decreased upwelling along theequator and along the coast of South America in Fig. 8b
is accompanied by a decreased downwelling on eitherside of the equator, indicative of a reduced strength of
the tropical cells.
We can now consider the relationship between the
upwelling strength and changes in SST over the region
9°S–9°N, 90°W–180°. Two different upwelling time series have been estimated: the first one (UPW1) is anaverage of the vertical velocity over the upwelling band
(1°S–1°N, 90°W–180°), while the second time series(UPW2) is computed by averaging w over the same
region used for SST (9°S–9°N, 90°W–180°). Thus, thefirst time series only captures the evolution of the upwelling, while the second time series averages out recirculations associated with the near equatorial tropicalcells. The comparison between the SST evolution andthe evolution of UPW1 is shown in Fig. 9. UPW1 has acorrelation of 0.92 with SST and leads the SST by 1
month. When UPW2 is considered, the correlation
drops to 0.78 with upwelling leading SST by 4 months(not shown), thus suggesting that the SST in the 9°S–
9°N latitude band is primarily affected by upwellingvariations in the very narrow equatorial band rather
than by the average w changes in the 9°S–9°N region.

4. Three-dimensional evolution of the STCs
Several studies have examined the adjustment of theocean circulation to changing wind forcing (Anderson
and Gill 1975; Wang et al. 2003a; among others). In
their seminal study, Anderson and Gill (1975) considered the spinup of a stratified ocean to the sudden onsetof zonal wind stress, which was uniform in longitudeand varied sinusoidally in latitude. The initial phase of
the spinup away from the ocean boundaries consists ofa local response to the Ekman pumping: as a consequence of the mass divergence (convergence) in thesurface Ekman layer, the thermocline rises (deepens)
linearly in time. The condition of non-normal flow
through the eastern boundary is communicated to theinterior by free planetary waves. Barotropic Rossby
waves are faster than baroclinic Rossby waves and cancross the basin on a time scale of a few days. Thus, thebarotropic adjustment is relatively fast. After the wave
front has reached a given longitude, the steady Sverdrup balance is established at that longitude. The baroclinic adjustment is achieved through baroclinic Rossby
wave propagation, and it occurs on longer time scales,
as a result of the slower phase speed of the baroclinic

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3749

FIG. 9. Comparison of upwelling time series (areally averaged vertical velocity in 1°S–1°N,
90°W–180°; solid line; left axis) and SST anomaly time series (areally averaged SST over9°S–9°N, 90°W–180°; dotted line; right axis). The SST anomaly time series is shown with thesign reversed to facilitate the comparison. Correlation coefficient between the two time series
is ⫺0.92, with UPW leading SST by 1 month. The correlation is significant at the 99% level.
A vertical velocity of 1 ⫻ 10⫺3 cm s⫺1 corresponds to an upwelling transport of 22.5 Sv over
the region 1°S–1°N, 90°W–180°.

modes. The western boundary current is the last component of the circulation to undergo the baroclinic adjustment and reach the final steady state.
The adjustment time scales are largely dependent
upon the structure of the wind forcing. If, for example,
the wind stress differs from zero only over limited latitude and longitude ranges, the adjustment time will depend upon the distance of the anomalous wind stresspatch from the western boundary, and upon the average latitude of the patch, since the Rossby wave phasespeed decreases with latitude. The dependence of theadjustment time upon the latitude and longitude of theanomalous wind forcing has been described by Wang etal. (2003a) based upon numerical experiments forcedby idealized wind anomalies that were different fromzero only over a small region.
In section 3 we have seen that the changes in theboundary current are simultaneous with the changes in
the interior transport at 9°S and slightly ahead of thechanges in the interior transport at 9°N. Also, thechanges in the interior transport slightly lag the SST
variations. Are the phase relationships between the different branches of the STCs consistent with the natureof the adjustment process? In our model simulation, themean vertically integrated circulation (Fig. 10a) includes two tropical gyres characterized by anticlockwise
flow in the Northern Hemisphere (negative values ofthe barotropic streamfunction) and clockwise flow in
the Southern Hemisphere (positive streamfunction values). In Period2 the two gyres strengthen, leading tostronger boundary currents (Fig. 10b), so that thechanges in the low-latitude western boundary currents

appear to be associated with the adjustment of the horizontal gyres. If we examine the velocity difference inthe zonal-vertical plane (Fig. 11), we notice that thelargest velocity anomalies are found in the upper ocean,
primarily above the 26 ␴␪ isopycnal, indicating that the

FIG. 10. (a) Time-averaged barotropic streamfunction. Solid
contours are for positive values, and dashed contours are for negative values. Contour interval is 5 Sv. (b) Barotropic streamfunction differences between Period2 (1977–97) and Period1 (1965–76). Solid contours are for positive values, and dashed contours
are for negative values. Contour interval is 2 Sv.

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lated to the zonal gradients of the upper-layer depth
anomaly h⬘:␷⬘ ⫽g⬘ ⭸h⬘,
f ⭸x

共3兲

where g⬘ is the reduced gravity, and f is the Coriolis
parameter. The reduced gravity can be related to the
local Rossby radius of deformation ␭:g⬘ ⫽FIG. 11. Difference of meridional velocity section between Period2 (1977–97) and Period1 (1960–76), along 9°S. Contour interval is 0.5 cm s⫺1. Positive differences are dark shaded, while negative differences are light shaded. The dotted–dashed line indicatesthe mean depth of the 26 ␴␪ isopycnal. Notice the positive changes
in the surface Ekman transport and the negative changes in theinterior geostrophic transport, as well as the positive changes in
the upper-western boundary current.

boundary current changes are of baroclinic nature andmust result from first-mode baroclinic Rossby wave
propagation. Thus, to examine the adjustment of the
STCs under changing wind forcing, we seek evidence ofbaroclinic Rossby waves.
Figures 12a and 13a show the evolution of the depthof the 25.5 ␴␪ isopycnal, a density surface that lies in thecore of the main thermocline, along 13°N and 13°S,
respectively. The latitude of 13°N has been chosen instead of 9°N because the transport changes are larger,
and the relationship between interior and boundarytransports is clearer. We chose 13°S for equatorial symmetry. Results are very similar at 9°N and 9°S, althoughpropagation can be more easily visualized along 13°N
and 13°S because of the slower phase speed. Figures
12a and 13a show that the pycnocline depth anomalies
have a large zonal scale and extend from the westernboundary to ⬃110°W, which is west of the easternboundary. As shown by Capotondi and Alexander(2001), the signals west of 110°W along 9°N can be
reproduced using a simple Rossby wave model forcedby the same Ekman pumping field used to force the
OGCM. The pycnocline depth disturbances close to theeastern boundary, for example, the weak negative signals in 1964 and 1971 and the positive signals in 1983,
1987, and 1992–93, are likely associated with boundary
waves generated at the equator. These eastern boundary disturbances do not seem to propagate very far into
the interior, a result consistent with the observational
study of Kessler (1990).
If we view the ocean as a shallow-water system witha moving upper layer and a motionless bottom layer,
the anomalous meridional upper-layer velocity ␷⬘ is re-

␭2f 2
,
H0

共4兲

where H0 is the average upper-layer depth, so thatthe upper-layer anomalous transport V⬘ can be expressed asV⬘ ⫽ f␭2

⭸h⬘
.
⭸x

共5兲

The anomalous transports from Eq. (5) along 13°N and
13°S are shown in Figs. 12b and 13b, respectively, andcan be compared with the anomalous transports estimated from the OGCM by integrating the anomalous
meridional velocity from the base of the Ekman layer
to the depth of the 26␴␪ isopycnal along the same latitudes (Figs. 12c and 13c). The longitudinal distribution
and time evolution of the transport anomalies in Figs.
12c and 13c are remarkably similar to those in Figs. 12b
and 13b, clearly illustrating how the changes in transport at each longitude are associated with the passageof the baroclinic waves. It is also clear from Figs. 12b,
12c, 13b, and 13c that the changes in the boundary current result from the anomalous zonal gradients of thermocline depth, and the anticorrelation between interiortransport changes and boundary current changes can bevisualized as a consequence of the opposite sign of h⬘x at
the eastern and western sides of the thermocline depth
anomaly. At 13°N the boundary current anomalies
computed from the zonal gradient of h⬘ (Fig. 12b) are
weaker than those seen in Fig. 12c. The Mindanao Current originates from the bifurcation of the North Equatorial Current at the Philippines coast just to the northof 13°N. Thus, the width of the boundary current isrelatively small at this latitude, and the transportchanges can be easily underestimated using Eq. (5), bytaking a zonal derivative in a coarse-resolution model.
The boundary current changes from Eq. (5) are much
more similar to those diagnosed from the OGCM at
13°S (see Figs. 13b and 13c). The large zonal scale ofthe thermocline depth anomalies, which in most cases
extend almost all the way to the western boundary(Figs. 12a and 13a), seems to be the primary reason forthe small temporal lag between variations in boundary
current and interior transports described in section 3c.

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FIG. 12. (a) Evolution of the depth of the 25.5 ␴␪ isopycnal along 13.6°N, as a function of longitude and time, based on annual meanvalues. Orange shading is for positive values (deeper thermocline), while the blue shading is for negative values (shallower thermocline). (b) Upper-ocean meridional transport anomalies based on Eq. (5), relating the transport anomalies to the zonal gradients ofthe thermocline depth. (c) Upper-ocean transport anomalies computed from the OGCM by integrating the meridional velocity
vertically from the base of the Ekman layer to the depth of the 26 ␴␪ isopycnal.

As seen from the slope of the phase lines in Figs. 12b,
12c, 13b, and 13c, the transport anomalies also exhibit
westward propagation: changes in transport are not simultaneous along 13°N and 13°S, and they have different signs at different longitudes. For example, transport
anomalies in 1978 are positive east of ⬃160°W at 13°N
and negative west of that longitude (Fig. 12c). Thus, thezonal average of the interior transport anomalies caneasily distort the phase relationship between variationsin interior transport and other quantities. Figure 14
shows the lag-correlation between SST in the tropicalbox (9°S–9°N, 180°–90°W) and the interior mass convergence zonally averaged east of different longitudes.
The lag-correlations are displayed in Fig. 14 as a function of temporal lag and the longitude defining thewestern edge of the range where the interior mass convergence is computed. Correlations remain statisticallysignificant all the way across the basin, indicating thattransport changes in the eastern part of the basin along

9°S and 9°N are relevant for SST changes, and the lagcorresponding to the maximum correlation varies fromnegative values (SST leads interior mass convergence)
when the interior transports are zonally averaged
across the basin, to small positive values (interior massconvergence leads SST) when only the transports in theeastern part of the basin are considered. Thus, phaserelationships among the different STC components canbe largely affected by the zonal averaging procedure
because of the continually evolving nature of the STCs.
The lag between equatorial SST variations and zonallyaveraged interior transport convergence may also be
due to the neglect of the heat transport by the zonal
eddy component, where “eddy” refers to deviations
from the zonal average. The zonally averaged meridional heat transport due to changes in the strength of the
STCs can be written as关␷⬘T兴 ⫽ 关␷⬘兴关T兴 ⫹ 关␷⬘*T*兴,

共6兲

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JOURNAL OF CLIMATEVOLUME 18

FIG. 13. Same as in Fig. 12, but for 13.6°S.

where ␷⬘ is the anomalous (in time) meridional thermocline transport for unit longitude, T is the time average heat content for unit longitude, the square brackets indicate the zonal average, and the asterisks indicate
the deviation from the zonal average. The equatorward
mass convergence shown in Fig. 4 only accounts for the
first term on the right-hand side (rhs) of Eq. (6). The
second term, the eddy term, may also be significant(Hazeleger et al. 2004) and may alter the phase relationship between the equatorward heat transport andthe equatorial SST. However, when the zonal average iscomputed east of the western boundary, as described in
section 3a, the eddy term in Eq. (6) is about an order ofmagnitude smaller than the first term on the rhs. Also,
the two terms are exactly opposite in phase, so that wecannot expect the eddy component of the heat transport to change the phase relationship between zonallyaveraged transport and SST. A detailed heat budget
analysis is beyond the scope of the present study andwill be examined in future work.
LF03 argued that variations in the boundary current
and in the interior pycnocline transport may result fromdifferent forcing mechanisms: boundary current variations are part of the horizontal gyre adjustment andreflect the zonally integrated effect of the wind stresscurl anomalies, particularly those in the western part ofthe basin. Variations in the interior transport, on theother hand, were related by LF03 not only to windstress curl changes in the extraequatorial Tropics, butalso to changes in the near-equatorial wind stress. The
influence of the near-equatorial wind stress on thetransport at 10°N (S) is achieved through equatorial
Kelvin waves, which continue poleward along the eastern boundary as coastal Kelvin waves, radiating westward-propagating baroclinic Rossby waves. Our analysis illustrates and clarifies how both boundary and interior transport changes result from the baroclinic
adjustment process.

5. What is the latitudinal range of the decadal
STC changes?
The STCs are shallow overturning cells that extend
from the equator to the subtropics (Fig. 1). Do they

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FIG. 14. Lag correlation between areally averaged SST over theregion 9°S–9°N, 90°W–180° and equatorward mass convergenceacross 9°S–9°N in the interior pycnocline zonally averaged east ofvarying longitudes. The lag correlations are shown as a function of
temporal lag and the western edge of the longitude range where
the equatorward mass convergence is computed. Positive lags indicate that the equatorial mass convergence leads SST, and viceversa. The hatched areas indicate correlations that are not statistically significant at the 95% level. The statistical significance ofcorrelations has been determined using a t-test criterion, with thenumber of degrees of freedom estimated according to Trenberth(1984).

spin up and spin down as a whole, or are the transportchanges more pronounced in particular latitude ranges?
As seen in section 4, changes in the meridional pycnocline transport are primarily associated with changes inthe zonal slope of the thermocline. Thus, the spatial
distribution of the pycnocline depth changes can give us
an indication of the latitude range where transportvariations are significant.
Differences in pycnocline depth between Period2
and Period1 (Fig. 15) show that the largest depth
anomalies are generally confined to the 20°S–20°N latitude band. Within this band, the pycnocline is shallower
in the west after the mid-1970s and slightly deeper inthe east. Thus, the zonal slope of the tropical pycnocline is reduced after the mid-1970s, consistent with thedecreased meridional transport. A similar pattern wascomputed from subsurface observations by MPZ as thedifference between the pycnocline depth in 1990–99
versus 1970–77. Within the Tropics, the largest differences in pycnocline depth occur in the two bands cen-3753

tered around 10°S and 13°N. These latitudes correspond to the locations where the Ekman pumping ischaracterized by a large zonal coherency and can efficiently excite a vigorous Rossby wave field (Capotondi
et al. 2003). The differences in zonally averaged interior
pycnocline transports between Period2 and Period1
show a pronounced variation with latitude (Fig. 16,
left). The largest changes in interior transports arefound around 10°S and 13°N, the same locations oflargest pycnocline depth changes. The variations inboundary current transport tend to compensate thechanges in interior transport (Fig. 16, right), as described in section 3c. The largest changes are also foundaround 10°S and 13°N and are of opposite sign withrespect to those in the interior. Thus, the pycnoclinetransport changes exhibit a strong latitudinal dependence, and the largest anomalies can be related to the
local Ekman pumping (Capotondi et al. 2003).
Which wind stress anomalies are most influential indriving equatorial SST variations? Figure 17 shows thedifference in wind stress between 1977–97 and 1960–76.
Most of the changes in the zonal wind stress from Period1 to Period2 are confined to the 18°S–18°N latitude
band, with the largest differences located near 7°S and
10°N and between ⬃160° and 110°W. The changes inzonal wind stress are associated with the weakening of
the easterly trade winds in Period2 versus Period1, asshown by the wind stress differences in Fig. 17, so thatthe largest variations are found close to the latitudes
where the trade winds achieve their maximum amplitudes. The weakening of the trade winds and associatedstrengthening of the midlatitude westerlies are a manifestation of the Pacific decadal oscillation (PDO; Mantua et al. 1997; Zhang et al. 1997).
To better understand the relationship between zonal
wind stress and equatorial SST variations, we consider
the lag correlation between the upwelling index UPW1
(defined in section 3d) and the zonal wind stress. The
upwelling index is representative of subsurface processes that directly influence equatorial SSTs, and thezonal wind stress controls the meridional component of
the Ekman transport, which is the surface branch of the
STCs. To identify differences in the patterns of anomalous wind stress responsible for interannual and decadal
variations the lag-correlation analysis has been computed for the two frequency bands separately. Decadal
time scales have been isolated by low-pass filtering thedata using a Fourier filter with half-power at 7.5 yr,
while interannual time scales have been obtained bybandpass filtering the data with half-power at 1.5 and7.5 yr. The results are shown in Fig. 18. At interannual
time scales (Fig. 18a), the wind stress anomalies char-

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FIG. 15. Differences in pycnocline depth (described by the depth of the 25.5 ␴␪ isopycnal)between 1977–97 and 1960–76. Dark shading is for negative differences (shallower pycnocline
in Period2) whose absolute value is larger than 10 m, and light shading is for positive differences (deeper pycnocline in Period2) larger than 10 m. Contour interval is 10 m. The dotted–
dashed lines indicate the latitudes of 10°S and 13°N.

acterized by the highest correlations with UPW1 arelocated in the central and western equatorial Pacific,
with maximum values centered on the equator at⬃160°W. Maximum correlations are negative, indicat-

ing that positive upwelling anomalies are associatedwith anomalous equatorial easterlies. At decadal timescales (Fig. 18b), the correlation pattern has a broader
meridional scale, and the maximum correlations (⬎0.9)

FIG. 16. (top left) The interior and (top right) boundary transports as a function of latitude for Period1(1960–76; solid line) and Period2 (1977–97; dotted–dashed line). The differences (Period2 ⫺ Period1) of(bottom left) interior and (bottom right) boundary transports. Notice that the largest changes in bothinterior and boundary transports occur around 10°S and 13°N. The BC and IN transport changes are of
opposite sign.

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3755

FIG. 17. Differences in zonal wind stress between 1977–97 and
1960–76 (contours). Contour interval is 0.05 dyn cm⫺2. Solid contours are for positive values, while dashed contours are for negative values. Light shading is for zonal wind stress differences
larger (in absolute value) than 0.05 dyn cm⫺2, intermediate shading is for differences in the 1–2 dyn cm⫺2 range, and darker shading is for differences larger than 2 dyn cm⫺2. Arrows show thedifference in the total stress between the same two periods, indicating a weakening of the easterly trade winds.

are found to the north and south of the equator, close
to the areas of the largest low-frequency zonal windstress variations seen in Fig. 17. The maximum correlations are negative: anomalous westerlies (weaker
trade winds; positive anomalies) in the regions 12°S–
equator, 160°–110°W and 7°–15°N, 160°–130°W are associated with decreased equatorial upwelling (slower
STCs), and vice versa. The similarity between the correlation pattern in Fig. 18b and the zonal wind stressdifferences in Fig. 17 suggests that the largest correlations between UPW1 and ␶x in Fig. 18b are primarily
associated with the 1976–77 climate shift. However, asimilar correlation pattern is found also for the detrended low-pass-filtered anomalies, which only include
decadal variations (not shown).
The correlation pattern at decadal time scales emphasizes the importance of wind variations within the
20°S–20°N latitude band for the low-frequency changesof equatorial SSTs. This result is consistent with thefindings of Nonaka et al. (2002), who showed that windvariations outside the 25°S–20°N latitude band were
unimportant for equatorial SST variability; Fig. 18 allows us to more specifically identify relevant forcing
areas within the 20°S–20°N band. The correlation patterns in Fig. 18 support the theoretical study of Wang etal. (2003b), who showed that positive equatorial SST
anomalies coupled to cyclonic wind stress anomalies inthe eastern extraequatorial Tropics could produce oscillations with periods in the 10–15-yr range. Wang etal. (2003b) also showed that an ENSO-type oscillation(3–5 yr) could be generated from the coupling of positive SST anomalies and westerly wind stress in the central equatorial Pacific.

FIG. 18. (a) Max lag correlation between bandpass-filteredzonal wind stress and bandpass-filtered upwelling index (averageof the vertical velocity at 50-m depth over the area 1°S–1°N,
90°W–180°), and (b) low-pass-filtered zonal wind stress and upwelling index. The filtering has been performed using a Fourier
filter with half-power at 1.5 and 7.5 yr for the bandpass filter and7.5 yr for the low-pass filter. Dashed contours are for negativevalues, and solid contours are for positive values. Negative correlations indicate that negative wind stress anomalies are associated with increased upwelling, and vice versa. In (a) the contour
interval is 0.1, and only contours between ⫺0.4 and 0.4 are shown.
Correlations larger than 0.4 (in absolute value) are shaded. In (b)the contour interval is 0.2, and only values larger in absolute value
than 0.5 are shown. Correlations whose absolute value is larger
than 0.7 are shaded: light shading is for values between ⫺0.7 and⫺0.8, intermediate shading is for values between ⫺0.8 and ⫺0.9,
and darker shading is for absolute values larger than 0.9.

6. Conclusions
In this study we have used the output from an ocean
general circulation model (OGCM) forced with observed surface fields to examine the evolution of thedifferent branches of the Pacific subtropical–tropicalcells and their impact on equatorial SSTs. Using subsurface observations over the period 1950–99, McPhaden and Zhang (2002) have shown that the equatorward pycnocline transports in the ocean interioralong 9°S and 9°N have exhibited a decreasing trend
since the 1970s, concurrent with a rise in equatorial
SSTs. The transport variations in the model are similar
to those estimated from observations, thus making themodel a suitable diagnostic tool to better understandthe STC evolution and its relationship with equatorial
SST changes as well as changes in surface wind forcing.

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Using the model output (available at a monthly resolution), we have been able to sharpen the observational
perspective and have shown that the interior equatorward transports across 9°S and 9°N, as well as the massconvergence across those latitudes, are largely anticorrelated with equatorial SST changes at both interannualand decadal time scales. The interior pycnocline transports are also anticorrelated with the surface Ekman
transports along the same latitudes, suggesting a strong
connection with the local wind forcing. The poleward
Ekman transport (the surface branch of the STC) leads
by several months the changes in interior transport and
SST, and the equatorial upwelling is strongly anticorrelated with SST changes and slightly leads them. However, when zonally averaged transports are considered,
SST variations slightly lead (by ⬃2 months) the variations in interior transport, a result that seems in disagreement with the view that changes in the strength of
the STCs cause changes in upwelling and equatorial
SSTs. We should notice that correlations remain highover a broad range of lags, and small differences incorrelations may not be statistically significant.
A better understanding of the relative timing of thedifferent branches of the STCs can be gained by considering the three-dimensional evolution of the cells.
Changes in equatorward pycnocline transport result
from the baroclinic adjustment of the ocean circulation,
which is accomplished through the westward propagation of baroclinic Rossby waves: anomalous Ekman
pumping excites the baroclinic waves, which propagate
westward and modify the ocean density structure, inparticular the zonal gradient of thermocline depth, thus
allowing anomalous meridional flows. Baroclinic
Rossby wave propagation across the basin is a slow
process (transit times can be of the order of a few years
depending on the latitude), so that transport changes
are not simultaneous at each longitude, but changes inthe eastern part of the basin lead the changes in thewestern part. Variations in equatorial SSTs, spatiallyaveraged over the central and eastern Pacific, result
from an integrated effect of the equatorial mass convergence variations at each longitude, but the phaserelationship between transport changes and SSTchanges can be distorted by zonally averaging the equatorward transports.
Using the model output, we have been able to examine the evolution of the transports in the low-latitude
western boundary currents, which are poorly resolvedby the observational record. Variations in boundary
current transport are strongly anticorrelated with thechanges in equatorward transport in the interior, indicating a tendency for the boundary current to compensate for the interior transport changes. The compensa-

VOLUME 18

tion is not complete, but the degree of compensation
can be very large, as discussed by Lee and Fukumori(2003). They attributed the partial compensation to different forcing mechanisms for the interior and boundary current transports: while the boundary current
variations are associated with the adjustment of thehorizontal gyres to changes in Ekman pumping, theinterior transport changes may also result from variations in near-equatorial surface wind stress with no curl.
Our results highlight how changes in both interior andboundary currents are a consequence of the baroclinic
adjustment of the ocean to large-scale wind stress curl
variations, in agreement with the process study ofWang et al. (2003a).
The decadal evolution of the STCs appears to beforced by variations in the trade winds, whose largest
changes are confined within 20° of the equator. The
variations in pycnocline transport are also limited to the
20°S–20°N latitude band and exhibit a strong latitudinal
dependence, with the largest changes located along
those latitudes where the Ekman pumping can more
efficiently excite baroclinic Rossby waves because of its
large spatial coherency (Capotondi et al. 2003). Thus,
transport variations of the various branches of the STCs
can be largely related to local forcing within the Tropics, a somewhat different perspective from the one
originally proposed by Kleeman et al. (1999), wherechanges in mass convergence/divergence in the subtropics were viewed as the driving mechanism of the
STCs.
In summary, our results support the notion thatvariations in equatorward mass transport may drive
SST variations in the central and eastern equatorial
Pacific. However, some open questions remain. First,
what are the consequences of the large degree ofcompensation between interior and boundary transport
upon the equatorial heat balance? Second, what is theorigin of the decadal wind stress variations in the tropical Pacific that initiate the STC variations? Are theya response to tropical SST anomalies, the tropicalmanifestation of midlatitude atmospheric circulation changes, or simply the low-frequency tail of internal atmospheric variability? Further studies using
coupled simulations are needed to answer these questions.
Acknowledgments. We thank the NCAR Oceanography Section for making the model output available tous. Drs. Dongxiao Zhang, Tong Lee, and Zhengiu Liuand two anonymous reviewers have provided very useful insights for this study. AC and MJM acknowledge
NOAA’s Office of Oceanic and Atmospheric Researchand Office of Global Program for support.

15 SEPTEMBER 2005

CAPOTONDI ET AL.
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