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Interdecadal Dynamics of the North Pacific Ocean
GUILLERMO AUAD
Climate Research Division, Scripps Institution of Oceanography, La Jolla, California
(Manuscript received 16 September 2002, in final form 19 May 2003)
ABSTRACT
An isopycnal ocean model forced by NCEP–NCAR reanalysis wind stresses and heat fluxes is used to study
the interdecadal variability of the Pacific Ocean in the 1958–97 period. A reasonable agreement is found between
the model’s modes of variability and those obtained by other researchers from both 100 years of observations
and theoretical predictions. In agreement with previous observational work, decadal and interdecadal timescales
have different descriptions, and from this study it is suggested that they indeed have different dynamics. This
study focuses on the dynamics of the ocean’s interdecadal variability, that is, of timescales of about 20 yr. The
decadal timescale, that is, 10 yr, is briefly outlined and compared with previous studies. It is found that atmospheric
heat fluxes play a key role in establishing the interdecadal SST pattern in the midlatitudinal North Pacific. These
fluxes would excite a high baroclinic mode, igniting a series of events that move around the basin. In midlatitudes,
interdecadal SSTs are most sensitive to the heat flux forcing along the eastern boundary north of about 308N,
in the western North Pacific at about 408N, and along 208N eastward of the date line; in the eastern North Pacific
and north of 408N, interdecadal pycnocline anomalies move across the Gulf of Alaska and toward the Aleutian
Islands up to about the Kamchatka Peninsula, continuing to the southwest down to about 288N. In their path,
pycnocline oscillations induce SST changes in the Kuroshio–Oyashio Extension. On the other hand, in the eastern
Tropics, the wind stress curl would induce interdecadal pycnocline oscillations that (between 108 and 208N)
propagate as Rossby waves, similar to those observed there for annual and interannual timescales, which, after
crossing the date line, turn toward the north-northwest. All of these waves and/or events move or propagate
within areas where the mean flow is of smaller amplitude than the phase speed in the direction of motion. In
addition, the results presented here would suggest that a process similar to a servomechanism, and as envisaged
by other authors, is present along 408N, suggestive of an active ocean–atmosphere interaction over this area.
Major differences are found between decadal and interdecadal dynamics.
1. Introduction
Several components make up the climate variability
of the world ocean–atmosphere system. These components can have a preferred timescale, for example, El
Niño events occur every 2–7 years or they can have a
red spectrum. In reality, the picture is more complicated
because in some scenarios the ocean responds with a
preferred timescale to stochastic atmospheric forcing,
and whether this response is linked, somehow, to coupled ocean–atmospheric deterministic modes is currently a topic of active research.
The basic ideas of oceanic–atmospheric interaction for
subdecadal timescales were early envisaged by Bjerknes
(1964) for the Atlantic Ocean, and unveiled in the Pacific
by Latif and Barnett (1994). According to them, the atmospheric response to this anomaly involves a weakened
Aleutian low that will adjust the underlying ocean, further
increasing the SST positive anomaly: that is, a positive
Corresponding author address: Dr. Guillermo Auad, Climate Research Division, Scripps Institution of Oceanography, 9500 Gilman
Drive, Dept. 0224, La Jolla, CA 92093-0224.
E-mail: [email protected]
q 2003 American Meteorological Society
feedback. However, part of the atmospheric response also
includes a wind stress curl anomaly, which tends to spin
down the subtropical gyre, thus leading to an oscillatorytype behavior. The signature of the 20-yr cycle in sea
surface temperature (SST) has a maximum in the western
subpolar gyre between 458 and 508N (e.g., Pierce et al.
2001), which would owe its existence to an increased
poleward transport of positive SSTs by the Kuroshio Current and its extension. White and Barnett (1972) showed
that ocean and atmosphere can be locked to each other
by a continuous exchange of vorticity between both media. In the framework of their theory, coupled oceanic–
atmospheric Rossby waves emerge as the linking process
that allows this active air–sea interaction. There is more
recent modeling evidence of oceanic–atmospheric coupling at interdecadal timescales in the North Pacific (e.g.,
Barnett et al. 1999; Pierce et al. 2001; Miller and Schneider 2000), and depending on the authors and data used,
its timescale ranges from 18 to 30 yr [e.g., Robertson
(1996) finds an 18-yr oscillation in his 500-yr coupled
model run and a 30-yr signal in the Global Sea Ice Coverage and Sea Surface Temperature (GISST) dataset].
However, Frankignoul et al. (1997) argue in favor of a
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red spectrum with no preferred timescale and attribute
those spectral peaks to too short time series.
The interdecadal dynamics in the North Pacific Ocean
involves several oceanic and atmospheric components,
and one of them, sea level pressure (SLP) variations in
the Aleutian low region, leads to almost simultaneous
changes in the westerlies (i.e., at around 408N) and in
the associated wind stress curl pattern over the whole
midlatitudinal North Pacific with maximum amplitudes
north of 408N (Latif and Barnett 1996). These changes
in the wind stress curl field have been associated (e.g.,
Miller and Schneider 2000) with two modes of decadal
to subdecadal variability in the midlatitudinal Pacific
Ocean (Deser and Blackmon 1995). The latter authors
refer to one of them as the PNA (Pacific–North American pattern), typically a sea level pressure pattern
thought to be forced from the Tropics, in which the
stochastic atmospheric forcing, mainly through zonal
wind stress anomalies, induces a maximum oceanic response in SST in the central North Pacific region at
around 358N (e.g., Miller and Schneider 2000). The other mode, the Pacific (inter) decadal oscillation (PDO;
Mantua et al. 1997), typically defined in terms of SST,
has its maximum amplitude in the western subpolar gyre
(between 358 and 458N depending on the dataset or
model used), and has been associated with coupled phenomena between the ocean and atmosphere and has a
typical timescale of 20–50 yr.
There are still many questions to be answered about
the processes involved in the interdecadal dynamics of
the North Pacific Ocean. However, several of them need
to be answered first if one pretends to offer a reasonable
description of the processes that make up the oceanic–
atmospheric system: (i) it is still unknown how different
oceanic regions are dynamically linked to each other
for example, through the action of Rossby waves [the
modeling study of Barnett et al. (1999) at least indicates
that such a connection exists] and (ii) there is still debate
in the scientific community as to whether there is a
coupled response. In any case it will remain to be described how those oceanic and atmospheric feedback
processes take place and as to whether which gyre, subpolar or subtropical, responds more vigorously to changes in SLP of the Aleutian low. Some ideas have been
advanced on how the ocean connects back to the atmosphere (Peng et al. 1997), but this is still uncertain
(Miller and Schneider 2000).
There is some consensus on how the atmosphere forces the ocean. First, SLP variations of the Aleutian low
are almost immediately followed by changes in the wind
stress and wind stress curl since for these timescales
winds are dominantly geostrophic. From there, oceaniconly processes (wave propagation and/or advection) alter the heat budget of the western subpolar gyre and of
the central North Pacific. As noted by Mantua and Hare
(2002), very little is known about the PDO dynamics,
to the point that even its geographical extent is still
uncertain. Some progress has been made recently with
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the construction of proxy SST records from coral and
tree-ring data (Linsley et al. 2000; Evans et al. 2001,
respectively). These studies strongly suggest that the
geographical extent of the PDO goes far beyond the
midlatitudinal North Pacific Ocean, at least including
the Tropics and the Southern Hemisphere. Studies on
understanding the PDO are relevant due to the impact
that regime shifts can have on society through changes
in weather patterns (Cayan et al. 2001; Minobe 2000;
Dettinger et al. 2000) and in the abundance and distribution of commercial biota species (Anderson and Piatt
1999; Beamish 1993; T. Baumgartner et al. 2003, personal communication).
This study is motivated by the recent findings of Tourre et al. (2001), who found, from 100 years of SST and
SLP observations, that decadal (7–13-yr band) and interdecadal (periods longer than 13 yr) timescales have
different descriptions, and are statistically independent.
Their interdecadal SST signal is led by SLP by a few
years, unlike the decadal band in which changes in both
fields take place simultaneously. Their interdecadal signal thus has a well-defined structure and evolution and
has, indeed, an important contribution to the SST variability at 158N. They speculate that ENSO variability
could be modulated by this signal, as noted earlier by
Kirtman and Schopf (1998), while their decadal SST
mode exhibits a structure and evolution that resembles
those of ENSO. Our main goal is to investigate the
dynamics behind those two timescales with particular
emphasis on interdecadal oceanic processes in midlatitudes. However, we will also address a few aspects
related to decadal variability since it is necessary to
differentiate between both timescales.
A crucial task in this process will be to attempt to
link, in one consistent picture, the different components
of the interdecadal timescale that were studied with preferred detail by different authors. These include the Kuroshio Extension decadal variability (Deser et al. 1999),
the Aleutian low system (Peng et al. 1997), the wind
stress curl forcing of the North Pacific (Miller et al.
1998), and gyre-scale advection (Zhang and Levitus
1997). Comprehensive summaries of decadal and/or interdecadal variability in the Pacific Ocean were recently
presented by Mantua and Hare (2002) and Schneider et
al. (2002). This task, in turn, will hopefully lead to a
better understanding of the Pacific climate variability,
a key ingredient in any predictability study.
This paper is organized as follows. In section 2 we
describe the numerical and statistical methods used in
this study, in section 3 we present the results of applying
those methods, and section 4 is left for discussions. In
section 5 the conclusions are summarized.
2. Methods
a. Numerical methods: The OPYC model
The primitive equation ocean model, known as
OPYC, was developed by Oberhuber (1993) and applied
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by Miller et al. (1994a,b, 1997, 1998), Cayan et al.
(1995), and Auad et al. (1998a,b) to study monthly
through decadal-scale ocean variations over the Pacific
basin. Here we use an updated version of the model
with higher resolution than the nominally 48 resolution
grid used previously and a revised scheme for forcing
with monthly mean fluxes. The grid extends from 67.58S
to 67.58N and 1198E to 708W, with periodic boundary
conditions along the latitudes of the Antarctic Circumpolar Current. The model is constructed with 10 isopycnal layers (each with nearly constant potential density but variable thickness, temperature, and salinity)
that are fully coupled to a bulk surface mixed-layer
model and to a sea ice model with rheology. The resolution is 1.58 in the midlatitude open ocean with zonal
resolution gradually increased to 0.658 resolution within
a 108 band across the equator.
The forcing functions consist of a seasonal cycle and
of National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR)
reanalysis anomalies that are added to it. The monthly
mean seasonal cycle are from various sources and are
the same as Miller et al. (1994a,b). The wind stress climatology is derived from a combination of European
Centre for Medium-Range Weather Forecasts (ECMWF)
midlatitude fields and Hellerman–Rosenstein tropical climatology. The monthly mean seasonal cycle climatology
of turbulent kinetic energy input to the mixed layer is
estimated from the same datasets Oberhuber (1993). The
monthly mean seasonal cycle climatology of total surface
heat flux is computed during spinup (no anomalous forcing) by evaluating bulk formulas that use model SST
with ECMWF-derived atmospheric fields (air temperature, humidity, cloudiness, etc.); the daily mean seasonal
cycle is then saved (averaged over the last 10 yr of a 99yr spinup) and subsequently used as specified forcing
during the anomalously forced hindcasts.
Anomalous fields of wind stress, total surface heat
flux, and TKE are then added to the respective mean
seasonal cycles. Because there is no SST feedback to
any of the anomalous forcing fields, the model is not
constrained to reproduce the observed temperature variations. Near the equator, the anomalous heat fluxes are
both poorly known and generally serve as a damping
mechanism (but see Seager et al. 1995). Thus, Newtonian damping is employed within a 78 e-folding scale
around the equator, where the SST anomalies are
damped back to model climatology with 1–4-month
timescales [see Barnett et al. (1991) for a map of the
coupling coefficient]. The monthly forcing strategy of
Auad et al. (1998a,b) was used to properly weight
monthly mean forcing anomalies (Killworth 1996).
b. Statistical methods
After forcing the OPYC model with anomalous heat
and momentum fluxes, different variables are averaged
and saved every 15 days from 1958 to 1997. The mean
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climatologies are subtracted from these total fields in
order to obtain the anomalous fields. Then, every time
series at every grid point, for every variable (e.g., SST
and SLP), is low passed (Kaylor 1977) to eliminate all
oscillations with periods shorter than 6 yr.
Given the coupled nature of the signals that we aim
to study, we take advantage of the properties of the
singular value decomposition (SVD) technique (Bretherton et al. 1992) to separate our signal of interest. SVDs
decompose the covariance between two fields in the
same way that EOFs decompose the variance of one
single field. Mathematically, SVDs are simply the
‘‘EOFs’’ of a nonsquare matrix. It is thus possible that
a first SVD mode can account for say, 90% of the covariance, but that the variance of one or both of the
variables involved in the computation could not be a
major contributor to those variables’ variances. In the
present study, each mode’s variance and covariance decreases with increasing mode number.
3. Results
a. Model to observations comparison
To partly validate our model solutions we use Reynolds SSTs (Reynolds and Smith 1994). Correlation coefficients and standard deviations were computed for
model and observations for each grid point using SST
winter anomalies. The results are displayed in Fig. 1 for
periods longer than 6 yr. The spatially averaged 95%
confidence level is (Davis 1976) 0.41. The value of the
correlation coefficients shown in Fig. 1 does not change
significantly, and a 10%–20% reduction is noticed on
average if no bandpassing is applied. Low correlation
areas do not necessarily imply a poor model performance but are sometimes associated with low sampling
of the observations, for example, as in Auad et al. (2001)
and Huddleston et al. (2003, manuscript submitted to
Quart. J. Roy. Meteor. Soc.). The area without contours
(top panel), at about 208N, is a good example of this
since the sampling density there is among the lowest in
the North Pacific (see Auad et al. 2001, their Fig. 1).
Emphasizing this concept is the fact that when Reynolds
SSTs (which include satellite data in addition to ship
data) were replaced by the Comprehensive Ocean–Atmosphere Data Set (COADS) or Scripps Institution of
Oceanography (SIO) SSTs, the correlation coefficients
were about 10%–20% lower depending on the location.
The standard deviation maps show, for both model
and observations, maximum values in the 408–508N
band west of 1508W and along the eastern margin of
the basin. As noted by Pierce et al. (2001), from a suite
of coupled models, they have a tendency to trap SST
variance too close to the western margin of the basin,
probably due to the poor resolution of western boundary
dynamics. In fact, the middle panel of Fig. 1 is very
similar to the spectral densities computed by them for
their 20-yr signal in both model and observations (their
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FIG. 2. Regional averages of the model SST in the KOE (solid)
and CNP (dashed) regions. The CNP region leads by about 2–4 yr.
The time series were low passed with an 8-yr running mean filter.
(defined by them as 308–408N, 1808–2108E) leads the
SST variability in the Kuroshio–Oyashio Extension
(KOE) region (defined by them as 358–408N, 1508E–
1808) by 2–4 years (Fig. 2).
Unlike coupled models, oceanic–atmospheric feedbacks are absent in ocean models. However, a proper
modeling of the SST and mixed layer depth, assuming
a decent realism in the atmospheric forcing functions,
will result in implicit feedbacks (if any in nature). The
above model/observation comparisons (Fig. 1), along
with the results of the NCEP to COADS comparison of
wind stresses and heat fluxes in midlatitudes (Auad et
al. 2001) would suggest that, if feedback processes are
present in nature, then they will be implicitly and approximately reproduced by the solutions of the ocean
model.
FIG. 1. (top) Correlation coefficients between model and observed
SSTs. The data were low passed for periods longer than 6 yr. The
contour interval (CI) is 0.1, and the 90% confidence level (Davis
1976) is 0.49 on a spatial average. (middle and bottom) The SST
standard deviation for model and observations, respectively. The CI
are 0.2 and 0.1 for the middle and bottom panels, respectively. Data
from the 1958–97 time frame were used.
Fig. 8). In agreement with Auad et al. (2001), the midlatitudinal model SSTs are an overestimate of the observed ones by a factor of about 1.5 on a spatial average.
This can certainly be related to the model’s tendency to
slightly overestimate the amount of reemerged SST (Alexander et al. 1999). The correlations of Fig. 1 were
about 15% higher when data from the period 1982–97
(more sampling density because of the availability of
satellite data) were used, while heat storage correlations
(upper 400 m) were analyzed by Auad et al. (1998a,b)
for ENSO and decadal variability. Confirming the findings of Miller and Schneider (2000), the model SST
variability in the central North Pacific (CNP) region
b. Model mean flow in the KOE and vicinity
A description of the mean-flow structure in the KOE
area and its vicinity is necessary in order to advance an
understanding of the decadal and interdecadal dynamics
of the North Pacific Ocean. It will be shown later that
mean currents have a key role in establishing preferred
paths of propagation in the interdecadal band. In addition, the KOE area will be shown to be a very important component of the decadal and interdecadal dynamics, though for different reasons in both bands.
Based on the convergence latitude of the Kuroshio and
Oyashio and/or on the location of the maximum SST
variance, different authors have defined the Kuroshio–
Oyashio Extension with different bounding latitudes and
longitudes. For instance, Seager et al. (2001) define the
KOE boundaries in the box 37.58–42.58N, 1508E–1808;
Miller and Schneider (2000) in 358–408N, 1508E–1808;
Qiu and Kelly (1993) in 308–408N, 1418–1758E; and
Qiu (1995) in 258–408N, 1368E–1808, which also in-
DECEMBER 2003
cludes the southern recirculation area. Lysne and Deser
(2002) define three different KOE areas for three different datasets according to the location of the maximum
SST variance: 348–448N, 1408–1758E for the Navy
Coastal Ocean Model (NCOM) data; 308–418N, 1408–
1758E for the SIO dataset; and 318–428N, 1408–1758E
for the World Ocean Atlas 1998 (WOA98) dataset.
Surface velocities from the ocean model were used
to compute the mean flow fields (Fig. 3). An eastward
flow is evident in the 308–478N band with the axis of
the KOE being aligned along the 378N parallel, approximately. The model Kuroshio and Oyashio converge at about 408N, which is in fair agreement with
available observations (e.g., Reed et al. 1994; Stabeno
and Reed 1994). The model KOE axis is displaced about
28 to the north with respect to the real ocean but this is
reasonable given the model resolution of 1.58. Thus,
based on the location of the eastward flow (Fig. 3) and
on the location of maximum SST variance (Fig. 1, top
panel), we define the KOE within 398–448N, 1608E–
1808, which is within the boundaries given by the authors cited above. The eastward flow at and nearby the
KOE is approximately 20% too broad and 50% slower
when compared with the recent observations of Maximenko et al. (2002). The ocean model speeds are closer
to the observed values than those obtained from coupled
models and it will be shown later that, in order to obtain
a reasonable representation of the interdecadal ocean’s
dynamics, both the mean flow and the difference between the mean flow and Rossby wave speeds need to
be reasonably simulated.
c. SVD analysis of SSTs, wind stress curl, pycnocline
depth, and surface currents
1) BASIC
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MODAL DESCRIPTION
The active participation of all heat budget components has shown that the North Pacific Ocean has a
complex interplay of different physical processes from
interannual (Auad et al. 1998a) to interdecadal (Auad
et al. 1998b) timescales. The latter, plus the basin-scale
averages described in the previous section, in the light
of the findings of both Tourre et al. (2001) and White
et al. (1997), were suggestive of an active coupling between ocean and atmosphere. It thus becomes necessary
to better isolate the signal of interest (any dominant
coherent mode with a timescale in the 18–30-yr range),
which we know, given the complexity just mentioned,
involves a suite of mutually interacting variables: oceanic and atmospheric.
The North Pacific (all analyses are from 108S to 708N)
SST, wind stress curl, and pycnocline depth winter
anomalies were low passed (Kaylor 1977) with a cutoff
period of 6 yr, and detrended. We took advantage of the
model architecture, specifically its isopycnal character,
and integrated layer thicknesses from the surface down
to the bottom of layer four to obtain a well-behaved
proxy of pycnocline depth. In what follows, we will
refer to this variable as ‘‘h4,’’ which in midlatitudes
varies from about 150 m (subarctic) to 500 m (center
of the subtropical gyre). The first two SVD temporal
modes of the SST/h4 pair are shown in Fig. 4. The first
mode explains 92% of the squared covariance, while
the second mode explains 5%. However, the SST variance of the second mode is about half of the first mode
variance. The correlation coefficients between time series, an indicator of the degree of coupling between both
fields in each mode, is higher than 0.9 for both modes
in Fig. 4. One hundred Monte Carlo simulations were
carried out in which random noise time series, in the
same number and length as those used in the analysis
of our signal, were identically treated, that is, bandpassed, Hilbert transformed, and ultimately decomposed
into SVD modes. The resulting 95% confidence levels
for the first three modes are 20.2%, 18.7%, and 17.6%,
respectively. Our approach is to obtain the portion of
the variance of the wind stress curl and of the pycnocline
depth (h4) that is significantly (statistically) coupled to
the first mode SST. This will help to isolate the signal
from the noise. The decomposition in singular values
not only yielded orthogonal modes but, without any
requirement being imposed, separated the first two
modes by timescales. The first mode has a clear interdecadal timescale (roughly 20 yr), while the second
mode has a timescale of approximately 10 yr.
2) THE
SPATIAL STRUCTURE OF THE MODAL
OCEANIC FIELDS: SST
Figure 5 shows the first SVD mode, amplitude, and
phase of the SST/h4 pair (the same amplitude, phase,
and time behavior were obtained for the first mode of
the SST field when it was decomposed into SVD modes
and paired to either h4, surface velocity, wind stress
curl, surface heat fluxes, horizontal advection, or vertical mixing). A common feature to both fields is that,
in midlatitudes mainly west of the date line, the phase
changes mostly in the meridional direction. Figure 6
shows the time sequence of the reconstructed first SVD
modes of the SST (left column), h4 (middle column),
and of surface velocity (right column) fields. We have
chosen to show the time frame January 1974–January
1984 (from January 1976 for the velocity field) to display, every two years, the changing features of the welldocumented (e.g., Trenberth 1990; Miller et al. 1994a)
1976–77 climate ‘‘shift,’’ whose time span is 10 years
and approximately covers one-half of a cycle of the first
mode’s timescale.
The warm, deep (h4) waters occupying the northern
part of the KOE in 1974 are replaced by cooler and
shallower water depths (Fig. 6, middle column), while
along the eastern boundary, north of 308N, SSTs change
sign and are out of phase with those in the KOE. This
warming along the U.S. and Canadian coasts is accompanied by warming conditions elsewhere in the basin
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FIG. 3. Annually averaged model mean flow in the KOE region. The contours represent the
amplitude with a CI of 2 cm s 21 .
except the KOE and the subpolar region west of the
date line. Not only is there a good resemblance between
the interdecadal SST spatial structure of our first SVD
mode and that one of Tourre et al. (2001), but there is
also a good correspondence with the EOF modes obtained by Miller et al. (1994b), Nakamura et al. (1997),
and Deser and Blackmon (1995). This pattern also bears
a close resemblance to that one estimated by Mestas-
FIG. 4. Singular value decomposition modal time series between
the pair SST and h4: (a) time evolution of the first coupled mode
between SST (solid line) and h4 (dashed line) and (b) time evolution
of the second coupled mode between SST (solid line) and h4 (dashed
line).
Nuñez and Enfield (1999), their REOF5, and to the PDO
mode of Mantua et al. (1997).
3) THE
SPATIAL STRUCTURE OF THE MODAL
OCEANIC FIELDS: h4 (PYCNOCLINE DEPTH)
The time evolution of the spatial pattern of the first
h4 mode (Fig. 6, middle column) shows a progressive
deepening of the pycnocline along the eastern boundary
of the North Pacific Ocean. Simultaneously, the anomalously shallow area initially located north of 508N
moves westward and then toward the south until it collides with the anomalously shallow area, (almost) northward propagating, originally centered at 108N. The evolution of h4 (Fig. 6, middle column) shows a westward
propagation in the northernmost part of the basin, while
its evolution is concomitantly followed by the SST field.
This information is also present in the bottom panels of
Fig. 5, where a zonal change of phase characterizes the
area north of 508N.
In the Tropics, a zonal change of the h4 phase is
evident along the equator and in the northern part of it
(at about 158N). In this same area, large h4 amplitudes
are also present. The interpretation of spatial phases is
very complicated because they are all relative values
that sometimes, mainly in large domains such as ours,
go beyond one full cycle with its values given in the
21808/1808 range. Thus, we computed Hovmöller diagrams, h4 contours in the time–space domain, to identify the correct sense of propagation in areas where h4
shows a large variance. Figures 7 and 8 show the h4
field in the zonal and meridional directions, respectively.
Along 158 and 558N, h4 changes phase from east to
west with speeds of about 3.0 and 1.2 km day 21 , re-
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FIG. 5. (top) Amplitude and (bottom) phase of the first SVD mode of the SST/h4 pair. Contour interval for amplitudes is 0.01 and for
phases is 308.
spectively. The tropical wave is similar in its location
and path to the Rossby waves described for interannual
timescales by Kessler (1990), Xie et al. (2000), and Capotondi and Alexander (2001). According to them, these
Rossby waves could either originate from Ekman pumping or from reflected Kelvin waves on the eastern boundary of the Tropics. Given that our model horizontal resolution does not favor a proper representation of Kelvin
waves, we are more inclined to believe that the wind
stress curl is generating them. The meridional Hovmöller
diagrams (Fig. 8) show a southward displacement of
phases (anywhere between the 1608E and 1808 meridians)
north of about 278N and northward south of that latitude.
Meridional speeds, southward or northward, range between 0.6 and 0.8 km day 21 . All these senses of ‘‘propagation’’ take place on areas where the mean flow does
not oppose or favors the sense of propagation.
The two deeper areas (positive values) initially centered at 458 and 208N also move toward each other until
they form just one blob of deeper-than-normal h4, January 1980, which significantly decreases in size by January 1984 and is centered at about 308N. This mode
has an interesting feature, that is, the development of
deeper h4 in the eastern tropical Pacific in conjunction
with those along the eastern boundary. However, these
anomalies are smaller in comparison with those observed
in the central and western North Pacific, and are thus of
dubious significance. To interpret the interdecadal SVD
mode in terms of Rossby waves we need to consider at
least a second baroclinic mode, given that the mean flow
seems to have some role in determining the paths followed by the anomalies. The dispersion relation for baroclinic Rossby waves, propagating on a moving environment, can be written (e.g., Pedlosky 1979)
v 5 K·V 2
bk
,
k 1 l 2 1 R22
d
2
(1)
where v is the wave frequency, K is the wavenumber
vector, b is the meridional derivative of the Coriolis
parameter, V is the mean surface velocity vector, R d is
the Rossby radius of deformation, and k and l are the
zonal and meridional wavenumbers, respectively. Then,
if the wave propagates normal to the mean flow, its
effect is not felt on the wave while, if the wave propagates against it, it can only exist as long the frequency
remains positive. In (1), effects due to horizontal and
vertical gradients of the mean flow are ignored given
that their contributions, for the current model parameters
and settings, are small to a first approximation. Even
smaller are the contributions from the vertical gradient
of the anomalous flow.
We next evaluate (1) using a period of 20 yr for the
wave frequency, zonal and meridional mean flows (from
Fig. 3) of 6 and 21 cm s 21, respectively, a Rossby radius
of 15 km (Ripa 1986), and a value of b 5 1.7 3 10 211
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FIG. 6. Reconstructed time evolution of the first SVD modes of (left) SST, (middle) h4, and (right) surface velocity. Panels in each column
are two years apart and go from Jan 1974 (top three panels) to Jan 1984 (bottom three panels) covering 0.5 cycle approximately. This time
frame clearly shows the changes attained by the midlatitudinal North Pacific after the 1976 climate shift (Miller et al. 1994). Since tropical
ocean currents have the tendency to dominate the SVD first modes, we computed the SVD for the SST/surface velocity pair north of 208N.
The time series and explained covariance are very similar to the ones of Fig. 5. The CI for the left and middle columns are 0.28C (plus the
0.18C contour) and 10 m, respectively.
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FIG. 7. Hovmöller diagrams (lon–time) for pycnocline depth contours (h4) along (top) 158 (CI
5 4 m) and (bottom) 558N (CI 5 8 m).
m 21 s 21 . Assuming that the wavelength is much longer
than the Rossby radius we obtain a zonal wavenumber
of k 5 23.1 3 10 27 m 21 when a meridional wavelength
of 3700 km is used (measured from Fig. 8). These numbers lead to zonal and meridional phase speeds of 23.2
and 20.65 cm s 21 , respectively. The (almost) southward
propagating anomalies (Fig. 8) are the ones responsible
for the SST changes in the KOE area and, in fact, could
play a role in the frontal displacements reported by
Seager et al. (2001). The correlation coefficient between
interdecadal KOE h4 and KOE SST was 0.84 (zero lag)
and was the highest one found in the North Pacific basin.
Not only did h4 have a typical depth that was closer to
typical observations of pycnocline depth, but it was also
the isopycnal depth to which the KOE SST was most
sensitive.
4) THE
SPATIAL STRUCTURE OF THE MODAL
OCEANIC FIELDS: THE SURFACE VELOCITY FIELD
In general terms, midlatitudinal warming (cooling)
situations in SST are accompanied by deep (shallow)
h4 depths. The comparison of these depths with the first
mode surface velocity field (Fig. 6, right column) indicates that an important, if not dominant, geostrophic
component is involved in the physical processes defining the temporal/spatial structure of the interdecadal
mode. The velocity fields of the subtropical and subpolar
gyres evolve and change their sense of circulation almost simultaneously. From Fig. 6 (right column), it is
apparent that both gyres react with similar intensity,
which is in line with the findings of Tourre et al. (1999)
and White and Cayan (1998). The largest amplitudes of
the zonal currents are located along 358N between 1508E
and 1708W and between 388 and 508N from the coast
to 1508E for the meridional flow (mostly the Oyashio
area). These interdecadal modal flows are shown in Fig.
6 (right column) for the 1976–86 time frame. The most
salient feature is the reversal from 1976 to 1986 of the
subpolar gyre circulation, which goes from opposing
the mean currents to be aligned with them.
5) FORCING
In this section we attempt first to identify areas of
pycnocline forcing by surface heat fluxes and the wind
stress curl and second to close the loop of oceanic processes that we found, from Figs. 6–8, to move around
the KOE region from the eastern to the western North
Pacific. The wind stress curl and heat flux forcing (Fig.
9) act to vertically displace the isopycnal surfaces. In
some locations, as just off the U.S. and Canadian coasts,
they counteract each other with heat fluxes having a
dominant role; in the CNP and KOE both forcing agents
reinforce each other, leading to a shallower pycnocline
in the early 1980s (Figs. 6 and 9). In the central Pacific
along 158N, pycnocline depths have a sign that is not
in line with either wind stress curl forcing or lagged (by
2–4 yr) heat flux forcing. The Bering Sea also shows a
similar feature during the late 1970s and early 1980s,
thus suggesting that in both areas the local perturbation
of the pycnocline anomalies is of remote origin, as Figs.
7 and 10 also seem to suggest.
Given that these interdecadal pycnocline depths are
sensitive to both forcing agents and that the KOE area
is well known because of its SST’s sensitivity to thermocline fluctuations, we estimated the lagged correlations between the interdecadal h4 field and KOE SSTs.
Figure 10 shows that the maximum lagged correlation
between interdecadal KOE SST and h4 takes place at
zero lag in the KOE region, reaching a maximum value
of 0.93. This partly confirms the sense of propagation
found from the Hovmöller plots in Figs. 7 and 8; pycnocline fluctuations move around the KOE region in
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FIG. 8. Hovmöller diagrams (time–lat) of the h4 field along the (left) 1608E, (middle) 1708E, and (left)
1808 meridians (CI 5 4 m).
areas where the mean flow does not oppose the direction
of propagation. They start on the eastern boundary,
moving toward the Aleutian Islands through the Gulf
of Alaska and Bering Sea. Before arriving at the
Kamtchatka Peninsula, they turn toward the southwest
down to the KOE region. The other pathway lies in the
northern Tropics around 158N from the eastern to the
western boundary and then toward the northwest.
Sea level pressure and wind stress curl are two intimately related variables, and, in fact, Tourre et al.’s
(2001) modal SLP and our modal wind stress curl (Fig.
9, left column) show similar features. In both analyzes,
their observations and our modeling study, the increased
cooling of the KOE and CNP regions (bottom panels
in Figs. 6 and 9) is accompanied by an increased positive
wind stress curl (Fig. 9, left column) or, equivalently,
a strengthened SLP in the Aleutian low area. The maxima (minima) of the wind stress curl (SLP) then displaces to the southeast while SST anomalies show a
simultaneous warming (on the eastern and then northern
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FIG. 9. Reconstructed time series of the first modes of the (left) wind stress curl (CI 5 10 28 N m 22 ) of the meridional gradient of the
first mode of the (middle) ¹ 2SST (CI 5 10 213 8C m 23 ) and of the (right) surface heat flux (CI 5 4 W m 22 ). All SVDs yield the first modes
paired to SST or to wind stress curl (i.e., same spatiotemporal structure/behavior).
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FIG. 10. Lagged correlations between pycnocline depth (h4) and KOE SST (both low passed for periods longer than 12 yr). The time lag
is marked in every panel over the U.S. map and goes anticlockwise from 9 to 0 yr with h4 leading KOE SST. The 90% confidence levels
were computed according to Davis (1976) and are 0.60 on a spatial average. Deeper-than-normal pycnocline depths are defined as positive.
Contour labels go from 20.9 to 0.9 every 0.2 but including the zero correlation contour.
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FIG. 11. Hovmöller diagrams (lon–time) of (top) ¹ 2SST along 408N (CI 5 10 212 8C m 22 ) and
(bottom) the wind stress curl along 458N (CI 5 10 28 N m 22 ).
boundaries of the basin), also in agreement with their
observations. This correspondence between SST and
wind stress curl (SLP) is suggestive of active coupling
and feedback between ocean and atmosphere (Peng and
Witaker 1999), a feature also noted by Tourre et al.
(2001) from observations. At the bottom of Fig. 8 (left
column), we also notice an increased across-shore SST
gradient off the U.S. and Canadian coasts. It is then
worth investigating if a mechanism similar to that one
proposed by White and Barnett (1972), and recently
invoked by Pierce et al. (2001), is in operation, suggesting coupling between ocean and atmosphere through
a vorticity exchange between both fluids. Their theory
can be summarized by the following two vorticity equations, one for each media:
]¹ 2c a
]c
1 b a 5 C1= 3 t
]t
]x
]¹ 2c w
]c
1 b w 5 C2¹ 2 Q,
]t
]x
and
(2)
(3)
where c w and c a are the vertically integrated oceanic
and atmospheric streamfunctions and t, Q, and b are
the wind stress, the atmospheric heat flux (positive into
the ocean), and the meridional gradient of the Coriolis
parameter, respectively (all C are positive constants).
They next parameterize the relationship between atmospheric heat fluxes and the zonal flow as
¹ 2 Q 5 C3¹ 2
]c w
,
]y
(4)
which is a good approximation in the frontal areas of
subpolar oceans. We now consider that ocean and atmosphere are coupled (i.e., that c w 5 c a ) and, further,
given the results of our SVD of the SST/surface velocity
pair, that ocean currents flow approximately parallel to
isotherms. This requisite combined with (2), (3), and
(4) yields
= 3 t 5 2C4
]¹ 2SST
.
]y
(5)
Figure 9 shows the time evolution of the first SVD
mode wind stress curl (left column) and of the meridional gradient of the first SVD mode of 2¹ 2SST (middle
column) from January 1970 to January 1984 every two
years. This first mode is well significant and explains
48% of the total squared covariance. As before, both
modes are recovered if both variables are SVD paired
to the SST field. North of about 308N, subpolar areas,
there is a good correspondence in sign between both
fields, especially for areas where the variability is large.
From Figs. 6–10 an interdecadal pathway was described
that carries, on average, information from the eastern
to the western boundary. We focus now on how the
ocean carries information eastward and offer a possible
explanation on how it forces the atmosphere along 408–
508N. The interdecadal wind stress curl pattern of Fig.
9 (left column) changes almost simultaneously with the
one of negative meridional gradient of the first SVD
mode of ¹ 2SST (Fig. 9, middle column). Both variables
evolve almost simultaneously in time, despite the noise
that was generated in the computation of the meridional
gradient of ¹ 2SST. The eastward propagation of the
¹ 2SST along the 408–508N band is not only seen in the
coupled model experiments of Pierce et al. (2001), but
also in their observations. We thus constructed the Hovmöller diagram of the wind stress curl, shown in Fig.
11. The top and bottom panels give eastward speeds of
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FIG. 12. Amplitudes and phases of the second SVD mode (decadal timescale) of the SST–h4 pair for (left) SST and (right) h4. CIs for
amplitudes are 0.1 and for phases are 308. Both bottom panels show a westward propagation of the phase.
roughly 0.8 (SST Laplacian) and 1.7 km day 21 (wind
stress curl). In a coupled system these speeds should be
the same, but our ocean model lacks any explicit feedbacks. Our speed estimation for ¹ 2SST is 0.8 km day 21
and compares favorably with those estimated by Pierce
et al. (2001) from SST observations, 0.9 km day 21 , and
from their coupled model, 1.8 km day 21 . However, in
this study, the area of eastward propagation is located
more to the east (from 1658 and eastward) than in Pierce
et al. (2001).
These eastward phase speeds cannot exist at these
low frequencies (i.e., 20–30-yr timescale) under the restrictions imposed by (1) with no mean flow. However,
both model and real ocean have a nonzero mean flow,
which allows eastward propagation for waves with k ,
R 21
d . In the CNP, between 1808 and 2108E, the mean
flow is almost eastward with a speed of 6 cm s 21 approximately (from Fig. 3). Then, (1) becomes a thirdorder polynomial in k, whose only stable solution is an
eastward propagating wave with k 5 10 26 m 21 . The
resulting eastward phase speed is 0.9 km day 21 which
favorably compares to the 0.8 km day 21 obtained above
from our model, and to the 0.9 km day 21 obtained by
Pierce et al. (2001) from observations.
The atmospheric heat fluxes (Fig. 9, right column)
play a key role in establishing the SST patterns of Figs.
5 and 6 (left column). The evolution of both fields is
similar with heat fluxes leading SSTs by 4–6 yr. The
eastward displacement of the positive heat flux anomalies located initially in the CNP is probably related to
the eastward displacement of ¹ 2SST; then negative
anomalies take over. From 1976 through 1984 positive
anomalies develop and move poleward along the eastern
boundary from 408N and northwestward to the Aleutian
Island and Bering Sea area.
6) DIFFERENCES
BETWEEN INTERDECADAL AND
DECADAL VARIABILITY
The second mode of our SST-h4 has a timescale of
roughly 10 yr and its SST time evolution (Fig. 12) is
similar to the modal SST obtained by Tourre et al.
(2001). The SST and h4 phases progress to the west
(Fig. 12, bottom panels), and this is not seen in the
interdecadal (first) mode of either SST or h4. The main
feature of this SST mode, in both our model and their
observations, is the evolution of a dipole with centers
located, in both model and observations, at 438N, 1608E
and at 408N, 1558W (not shown). These two relative
maxima switch signs about every five years, and might
be partly responsible for the reported time lag of 4–6
yr (e.g., Miller and Schneider 2000) between the SSTs
of the CNP and KOE areas. The amplitude maxima in
the CNP area is reminiscent of recent descriptions of
the PNA pattern (Deser and Blackmon 1995). The main
difference between decadal and interdecadal variability
is the path followed by the isopycnal perturbations after
they are induced by the wind stress curl and/or surface
heat fluxes. Figure 13 shows that decadal KOE SST are
led by about 4 yr by decadal h4 variability in the CNP
and eastern North Pacific, which was reported earlier
from observations and coupled model experiments by
Schneider et al. (2002). On the other hand, interdecadal
variability goes around the KOE area, and in all cases,
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this propagation of information is favored by the mean
flow direction. A schematic of the mean circulation of
the North Pacific shows (Fig. 14) that the mean flow
direction coincides with the path followed by the h4
anomalies reported in this article. The eastward wind
drift along about 408N also coincides with the path followed by the ¹ 2SST anomalies and wind stress curl.
The interdecadal and decadal modes and their corresponding paths of propagation are in line with the
findings of Liu (1999), who describes two different pathways, that as noted before, are mostly determined by
the relative size of the wave speed to the background
flow. Specifically, the interdecadal mode would correspond to Liu’s ‘‘A’’ mode, strongly influenced by atmospheric heat fluxes (cf. SST and Q patterns from Figs.
6 and 9) and the mean flow; on the other hand, our
decadal mode resembles Liu’s ‘‘N’’ mode, mostly forced
by the wind stress curl in the eastern and central North
Pacific and having a dominant westward propagation.
We have computed the model’s vertical structure functions (not shown) following the method of Ripa (1986)
and found, in agreement with Liu’s modes, that the first
baroclinic mode, decadal timescale in this study, has
maximum amplitude at 800 m while the second baroclinic mode, interdecadal timescale in this study, exhibits maximum amplitude at 400 m and is 60% slower
than the first mode.
Next, it is important to note that decadal and interdecadal variability are also different in the heat budget
components that control their physics. On a basin-scale
average in the mixed layer and north of 158N, the horizontal advection term is negligible for decadal timescale variability, while it plays a major role in the interdecadal band (Table 1). At this latitude, this contribution is very likely due to Rossby wave activity,
through thermocline heave, for which geostrophic currents are normal to latitude circles. At this latitude, atmospheric heat fluxes can make an important contribution to the overall heat budget (e.g., Fig. 9 shows
some amplitudes in the 1970s and 1980s), since the
Newtonian damping of SST anomalies is constrained to
the 78S–78N; band that is, at 58N only one-half of the
SST anomalies are damped.
On a regional scale, the heat budget components show
that decadal-timescale SST force the overlying atmosphere (SST damping) in the KOE area (Fig. 15, bottom
panel) in agreement with the reports of Schneider and
Miller (2001) and Schneider et al. (2002). However, for
interdecadal timescales, the damping of SSTs to the atmosphere seems to take place in the Bering Sea/Aleutian
←
FIG. 13. Lagged correlations between the h4 field and the KOE
SST in the decadal band (6–13 yr). The time lag is marked in every
panel over the continental U.S. map and goes from 4 to 0 yr h4
leading KOE SST. The 90% confidence levels were computed ac-
cording to Davis (1976) and are 0.57 on a spatial average. Contours
equal and higher, in absolute value, than 0.4 are shown. The arrows
denote the time progression sense of the lag toward the zero-lag
correlation. A positive h4 represents a deeper than normal pycnocline
depth.
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FIG. 14. Schematic of the mean currents of the North Pacific Ocean (Stabeno and Reed 1985). These paths are very similar to the
propagation paths found in this study (map taken from the Internet at http://www.pmel.noaa.gov/bering/pages/npmap4.html).
Island area (Fig. 15, top panel). We are not aware that
the Bering Sea has been previously reported as an area
of oceanic forcing. However, it is in, or nearby, this
region where observations and models show that the
different interdecadal atmospheric fields are more energetic (Aleutian low system and its associated wind
stress curl). Similarly, the center of action of the decadal
mode is located in the KOE and CNP regions, as seen
in the modal wind stress curl pattern of this study and
in the modal SLP pattern of Tourre et al. (2001), which
have a similar description. The spatial structure of the
TABLE 1. Heat budget comparison for decadal and interdecadal
timescales (averaged north of 158N).
Timescale
Std dev ratio/timescale
d(SST)/dt/[d(SST)/dt]
Q/Hmix/[d(SST)/dt]
Horizontal advection/[d(SST)/dt]
Vertical mixing/[d(SST)/dt]
Horizontal diffusion/[d(SST)/dt]
Decadal
Interdecadal
(8–13 yr) (%) (13–40 yr) (%)
100
90
8
40
,1
100
50
81
48
,1
FIG. 15. First mode (i.e., interdecadal timescale) of the surface heat
flux (solid line) vs first-mode SST (dashed line) averaged for the (top)
Bering Sea area. (bottom) As in the top panel but for the second
mode (i.e., decadal timescale) averaged in the KOE area.
DECEMBER 2003
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interdecadal and decadal SST variances also contributes
to clearly differentiate between both timescales. Decadal
variability has maximum variance in the KOE and CNP
areas, that is, in the two areas where the dipole is located. Interdecadal variability, instead, has maximum
variability slightly north of the KOE area and along the
eastern boundary between Canada and northern Mexico.
The dominant forcing agent also differs between decadal
and interdecadal timescales. The former is mostly driven
by the wind stress curl (e.g., Schneider et al. 2002),
while the latter by atmospheric heat fluxes that have
maximum variability along the eastern boundary and in
the western half of the KOE, that is, where the interdecadal SST also shows maximum variability.
4. Discussion
Even though there is a good agreement between our
findings and those obtained from coupled models for
decadal timescales (e.g, Schneider et al. 2002), some
differences exist for interdecadal timescales as noted by
Pierce et al. (2001) from a set of experiments with four
different coupled models. For instance, ECHO2 apparently does not reproduce the observed interdecadal SST
variability along the eastern boundary. The reasons for
this disagreement might reside in how numerical models
can simulate high-order baroclinic modes and their interaction with the mean flow. It is particularly interesting
that ECHO2, on the other hand, properly simulates the
main features of the decadal variability, being that this
mode is almost independent of the mean flow.
The dynamics behind the horizontal displacement of
the interdecadal pycnocline perturbations is still uncertain. However, this author is more inclined to interpret
this mode in terms of wave propagation, given its similarities with Liu’s A mode (i.e., forcing and vertical
structure). Perhaps most important, its propagation path
coincides with that one of the mean circulation in the
North Pacific. We have found that the mean flow is very
irregular in some areas along these pathways, which is
not concomitantly reflected in the phase speeds obtained
from the Hovmöller diagrams. In turn, these propagation
speeds are different from mean flow speeds in most
locations and from the speed at which the atmospheric
forcing evolves.
The mean flow of the KOE would prevent a direct
propagation of interdecadal perturbations from the generation area to the KOE; instead, two different interdecadal perturbations develop and propagate around this
‘‘forbidden’’ area of strong eastward flow. One of them,
is a moving perturbation that propagates westward along
108–208N, while the other one, an originally northwestward propagating wave that moves from about
458N on the eastern boundary toward the subarctic, up
to about the Kamchatka Peninsula, and then turning
southwestward toward the KOE region. When both interdecadal perturbations arrive at the western boundary,
2499
they slowly turn, following the approximate direction
of the mean flow converging at around 258–308N.
The area occupied by the KOE would prevent any
westward propagation as long as the mean flow to the
east is faster than the phase speed to the west and the
vortex tube stretching does not counter the mean flow
effect in the dispersion relation. In models with weaker
mean flows westward propagation could occur but that
will not lead to realistic representations of the ocean
dynamics. For interdecadal timescales, in the ocean
model, since westward propagation is apparently inhibited by the mean flow, pycnocline depth perturbations
move poleward (westward) along the basin’s eastern
(northern) boundaries and westward along the 108–
188N. On both paths, the mean flow is, in general, in
the same direction as the propagation direction. For decadal timescales westward propagation seems to originate from the eastern and central North Pacific, migrating to the KOE area. These waves are fast enough
to counter the mean flow at the depth of the pycnocline
and/or have the effects of vortex tube stretching canceling out the mean flow contribution; as noted by Liu
(1999), these are probably first baroclinic Rossby waves.
The main shortcoming of this study is the relatively
large ratio between the timescale of interest to the time
series length. However, we are confident about the representativeness of our results, given the reasonable similitude in both the spatial structure and time evolution
that exists between our first two SVD modes, decadal
and interdecadal, of the SST-wind stress curl pair based
on 40 years of data and the SVD modes obtained from
100 years of observations by Tourre et al. (2001). This
comparison and also the one between our results and
those of Liu (1999) suggest that, even though our study
is closer to a case study, there is some representativeness
in our findings.
We have focused our attention on the midlatitudinal
North Pacific Ocean because of the poor sampling rate
of the observations in the South Pacific Ocean. However, the model interdecadal SSTs in the Southern Hemisphere are about the mirror image of those in the Northern Hemisphere for interdecadal SST (T. Baumgartner
et al. 2003, personal communication), a feature that is
in line with the findings of Garreaud and Battisti (1999)
on the interdecadal atmospheric symmetry in both
hemispheres. The tropical band, on one hand, showed
small amplitudes in the analyzed modal fields (SST,
pycnocline depth, or wind stress curl), but qualitatively
it is apparent that Rossby waves do exist in the northern
part of the Tropics between 108 and 208N. These waves
are similar to those reported by Kessler (1990) in the
annual and interannual bands. It is apparent from this
study that interdecadal SSTs in the KOE are originated
from Rossby waves having a meridional component
much larger than the zonal one (i.e., l k k), unlike the
decadal timescale. Part of the confusion about the characterization of decadal and interdecadal SST variability
can arise from the fact that some historical conclusions
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JOURNAL OF PHYSICAL OCEANOGRAPHY
were drawn from analyzes that included both timescales and the fact that decadal and interdecadal SSTs
have in common both a maxima in the KOE area and
its vicinity and CNP SSTs leading KOE SSTs by about
3–6 yr.
In the interdecadal band, the Bering Sea area would
be playing a similar role to that played by the KOE
region in the decadal mode. In its southern half, SST
anomalies are damped to the atmosphere, affecting the
sea level pressure of the Aleutian low system. If verified
from observations, this SST damping could play a major
role in the life cycle of the interdecadal variability in
the North Pacific. Of course, verification from observations and more specific numerical experiments need
to be carried out to asses the role of the Bering Sea in
the context of interdecadal variability in the North Pacific. The above points to the fact that in the real ocean
the picture is very likely more complicated, as noted by
Liu (1999), since many modes and timescales might be
present at one time: for instance, even though surface
net heat fluxes are dominant in determining the SST
variability, the wind stress curl has also a role in at least
perturbing the pycnocline depths in and near the Gulf
of Alaska. Southeastward of this location, the diabatic
forcing is dominant over the wind stress curl. Even
though our model lacks any feedbacks between ocean
and atmosphere, those mechanisms can be present in an
implicit way, given the good correspondence between
the model’s decadal and interdecadal SSTs and those
obtained from observations. This is also supported by
the fact that the model’s forcing functions, the NCEP
wind stress and heat flux, showed good correspondence
with observations in the extratropics (Auad et al. 2001).
The forcing of the interdecadal band is complicated.
Wind stress curl and heat fluxes have maximum amplitudes in different areas, but in general the effects of
the latter dominate the former, for example, at the eastern boundary, while in the KOE and CNP they reinforce
each other during the 1970s and 1980s. After the regime
shift of 1976–77, the warming of the areas occupied by
the Aleutian Islands and the southern half of the Bering
Sea led to both a warming of the atmosphere and to a
reversal of the meridional gradient of the SST in the
KOE area. Both situations, would combine to flip the
sign of the atmospheric forcing in about 10–13 yr, thus
leading to a quasi periodicity of 20–26 yr.
5. Conclusions
The results obtained in this study using an ocean model link the theoretical and observational findings on decadal and interdecadal variability in the North Pacific
of Liu (1999) and Tourre et al. (2001), respectively. Very
different approaches have been followed in all three
papers, but a consistent picture emerges from them. We
also obtained satisfactory results when comparing model SSTs on either a gridpoint-by-gridpoint basis or es-
VOLUME 33
timating the basin-scale SST average as in White et al.
(1997).
In agreement with the observational work of Tourre
et al. (2001), decadal and interdecadal variability are
two different phenomena, and from this study it is suggested that different dynamics control them. It is possible that the only difference between both timescales
lies in the dispersion properties of the first and second
baroclinic modes of the Rossby waves generated in the
northeastern corner of the basin. If the decadal waves
have a faster westward phase speed, first baroclinic
mode, they will be able to overcome the eastward mean
flow of the KOE at the pycnocline depth and travel
directly to this region. The Rossby waves in the interdecadal band, instead, have to go around the KOE because of their lower speed (second or third baroclinic
modes), given the restrictions imposed by the mean flow
field. The description of these two timescales and their
pathways are in line with the theoretical findings of Liu
(1999), who described a non-Doppler shift first baroclinic mode and an advective second baroclinic mode.
Interdecadal atmospheric heat flux variability is primarily responsible for the generation of pycnocline
depth oscillations in the eastern North Pacific Ocean in
midlatitudes. Very likely this is due to the excitation of
a second or third baroclinic mode that has maximum
amplitude at or near the surface. In midlatitudes, this
leads to the horizontal displacement, starting at about
458N, of pycnocline anomalies toward the north and
west. Before arriving at the Kamchatka Peninsula the
anomalies, following the mean flow, turn southwestward, which upon arrival in the KOE area leads to the
creation of SST anomalies. This propagation continues
up to about 288N where they encounter another field of
pycnocline anomalies moving northwestward. The latter
were induced by the arrival of a westward-propagating
Rossby wave along 158N, probably generated by the
wind stress curl in the northeastern part of the Tropics
(108–208N). This part of the cycle, from atmospheric
forcing at or near the eastern boundary to wave arrival
to the KOE area, takes about 5–6 years. From this study
alone it cannot be concluded that oceanic–atmospheric
coupling/feedbacks are either absent or present. However, the present results along with the modeling and
observational evidence of Pierce et al. (2001) would
suggest that a mechanism similar to that anticipated by
White and Barnett (1972) could be operating at and/or
near 408N. Further, our results here are consistent with
the results of Latif and Barnett (1994, 1996) in that
oceanic–atmospheric coupling takes place when the
midlatitudinal wind stress curl responds to changes in
the underlying SST field. Thus, the travel time from the
KOE to the CNP/eastern North Pacific area is of about
5–7 years, leading to a quasiperiodicity of about 20–26
yr, at least in the 1958–97 time frame.
Five main differences found between decadal and interdecadal variability in the North Pacific Ocean are (i)
the path followed by pycnocline oscillations from the
DECEMBER 2003
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AUAD
eastern and central North Pacific to the KOE area
(around and through the KOE for interdecadal and decadal variability, respectively), (ii) the horizontal advection term integrated north of 158N in the mixed layer
is important for the interdecadal heat budget but is a
minor contributor in the decadal band, (iii) oceanic forcing is geographically differentiated for both timescales
(SST anomalies are damped to the atmosphere in the
KOE and Bering Sea regions in the decadal and interdecadal bands, respectively), (iv) maximum SST variability takes place west of the date line at 458N and
along the eastern boundary in the interdecadal band and
in the CNP and KOE areas in the decadal band, and (v)
the interdecadal band is mostly forced by atmospheric
heat fluxes, unlike the decadal band which is mostly
driven by the wind stress curl.
In summary, it remains to verify the existence in nature of the interdecadal oceanic mechanism described
in this article, as well as to shed more light on its atmospheric component. Fundamental questions arise
from this study, given the similarity found between the
interdecadal SST pattern and that of the PDO: Does
Liu’s (1999) A mode describe the ocean dynamics of
the PDO? If so, is this mode interacting with the atmosphere in line with the early ideas of White and Barnett (1972)? Related to this, it has been reported (Auad
et al. 2003, manuscript submitted to J. Geophys. Res.)
that PDO-like SST patterns not only are obtained as a
result of simulating modern climate (e.g., the 1976–77
shift) but also when inferring the behavior of the North
Pacific during the termination of the last ice age. Thus,
it will be a key step toward a better understanding of
the dynamics of large-scale climate changes to obtain
long, reconstructed records of the PDO index at many
locations over the last, say, 20 000 yr. Coupled models
should be ideal for studying subdecadal coupled phenomena such as those reported in this article. However,
the author believes that several improvements need to
be made to them in order to obtain better representations
of the mean flow and of the SST variance in the interdecadal band. The decadal band is better represented by
coupled models since it is much less dependent on the
mean flow. It was/is the author’s intention to advance
a different perspective, that is, from an ocean model
forced by NCEP–NCAR reanalysis fluxes on interdecadal variability in the North Pacific Ocean. More research is needed in this direction, for example, the computation of the oceanic and atmospheric streamfunctions
in order to verify the existence of coupled oceanic–
atmospheric Rossby waves. It will be also important to
attack the coupled problem from the perspective of the
energetics of the system in order to quantify the importance of each process. The knowledge gained on
these processes will leave us in a better position to construct more accurate forecasting systems to aid society
in both planning and prevention.
Acknowledgments. Financial support was provided by
the National Oceanic and Atmospheric Administration
(NA17RJ1231 through the Experimental Climate Prediction Center and the Consortium for the Ocean’s Role
in Climate), the Department of Energy (W/GEC 00006), and the National Science Foundation (OCE-0082543). The views expressed herein are those of the
author and do not necessarily reflect the views of NOAA
or any of its subagencies. I especially thank Art Miller
and Warren White for their extensive and insightful
comments and reviews on the earlier drafts of this paper.
I also thank two anonymous reviewers for their important suggestions and remarks that helped to significantly
improve the quality of this paper.
REFERENCES
Alexander, M. A., C. Deser, and M. S. Timlin, 1999: The reemergence
of SST anomalies in the North Pacific Ocean. J. Climate, 12,
2419–2433.
Anderson, P. J., and J. F. Piatt, 1999: Community reorganization in
the Gulf of Alaska following ocean climate regime shift. Mar.
Ecol. Prog. Ser., 189, 117–123.
Auad, G., A. J. Miller, and W. B. White, 1998a: Simulation of heat
storages and associated heat budgets in the Pacific Ocean, 1, El
Niño-Southern Oscillation timescale. J. Geophys. Res., 103, 27 603–
27 620.
——, ——, and ——, 1998b: Simulation of heat storages and associated heat budgets in the Pacific Ocean, 2, Interdecadal timescale. J. Geophys. Res., 103, 27 621–27 635.
——, ——, J. O. Roads, and D. R. Cayan, 2001: Pacific Ocean wind
stress and surface heat flux anomalies from NCEP reanalysis and
observations: Cross-statistics and ocean model response. J. Geophys. Res., 106, 22 249–22 265.
Barnett, T. P., M. Latif, E. Kirk, and E. Roeckner, 1991: On ENSO
physics. J. Climate, 4, 487–515.
——, D. W. Pierce, R. Saravanan, N. Schneider, D. Dommenget, and
M. Latif, 1999: Origins of the midlatitude Pacific decadal variability. Geophys. Res. Lett., 26, 1453–1456.
Beamish, R. J., 1993: Climate and exceptional fish production off
the west coast of North America. Can. J. Fish. Aquat. Sci., 50,
2270–2291.
Bjerknes, J., 1964: Atlantic air–sea interaction. Advances in Geophysics, Vol. 10, Academics Press, 1–82.
Bretherton, C. S., C. Smith, and J. M. Wallace, 1992: An intercomparison of methods for finding coupled patterns in climate data.
J. Climate, 5, 541–560.
Capotondi, A., and M. A. Alexander, 2001: Rossby waves in the
tropical North Pacific and their role in decadal thermocline variability. J. Phys. Oceanogr., 31, 3496–3515.
Cayan, D. R., A. J. Miller, T. P. Barnett, N. E. Graham, J. N. Ritchie,
and J. M. Oberhuber, 1995: Seasonal-interannual fluctuations in
surface temperature over the Pacific: Effects of monthly winds
and heat fluxes. Natural Climate Variability on Decadal-to-Century Time Scales, National Academy Press, 133–150.
——, A. A. Kammerdiener, M. D. Dettinger, J. M. Caprio, and D.
H. Peterson, 2001: Changes in the onset of spring in the western
United States. Bull. Amer. Meteor. Soc., 82, 399–415.
Davis, R. E., 1976: Predictability of sea surface temperature and sea
level pressure anomalies over the North Pacific Ocean. J. Phys.
Oceanogr., 6, 249–266.
Deser, C., and M. L. Blackmon, 1995: On the relationship between
tropical and North Pacific sea surface temperature variations. J.
Climate, 8, 1677–1680.
——, M. A. Alexander, and M. S. Timlin, 1999: Evidence for a wind-
2502
JOURNAL OF PHYSICAL OCEANOGRAPHY
driven intensification of the Kuroshio Current Extension from
the 1970s to the 1980s. J. Climate, 12, 1697–1706.
Dettinger, M. D., D. S. Battisti, R. D. Garreaud, G. J. McCabe, and
C. M. Bitz, 2000: Interhemispheric effects of interannual and
decadal ENSO-like climate variations on the Americas. Present
and Past Interhemispheric Climate Linkages in the Americas
and their Societal Effects, V. Markgraf, Ed., Cambridge University Press, 1–16.
Evans, M. N., M. A. Cane, D. P. Schrag, A. Kaplan, B. K. Linsley,
R. Villalba, and G. M. Wellington, 2001: Support for tropicallydriven Pacific decadal variability based on paleoproxy evidence.
Geophys. Res. Lett., 28, 3689–3692.
Frankignoul, C., P. Muller, and E. Zorita, 1997: A simple model of
the decadal response of the ocean to stochastic wind forcing. J.
Phys. Oceanogr., 27, 1533–1546.
Garreaud, R. D., and D. S. Battisti, 1999: Interannual ENSO and
interdecadal ENSO-like variability in the Southern Hemisphere
tropospheric circulation. J. Climate, 12, 2113–2123.
Kaylor, R. E., 1977: Filtering and decimation of digital time series.
Institute for Physical Science and Technology Tech. Rep. BN
850, University of Maryland, 42 pp.
Kessler, W. S., 1990: Observations of long Rossby waves in the
northern tropical Pacific. J. Geophy. Res., 95, 5183–5217.
Killworth, P., 1996: Time interpolation of forcing fields in ocean
models. J. Phys. Oceanogr., 26, 136–143.
Kirtman, B. P., and P. S. Schopf, 1998: Decadal variability in ENSO
predictability and prediction. J. Climate, 11, 2804–2822.
Latif, M., and T. Barnett, 1994: Causes of decadal climate variability
over the North Pacific and North America. Science, 266, 634–
637.
——, and ——, 1996: Decadal climate variability over the North
Pacific and North America—Dynamics and predictability. J. Climate, 9, 2407–2423.
Linsley, B. K., G. M. Wellington, and D. P. Schrag, 2000: Decadal
sea surface temperature variability in the subtropical South Pacific from 1726 to 1997 A.D. Science, 290, 1145–1148.
Liu, Z., 1999: Forced planetary wave response in a thermocline gyre.
J. Phys. Oceanogr., 29, 1036–1055.
Lysne, J., and C. Deser, 2002: Wind-driven thermocline variability
in the Pacific: A model–data comparison. J. Climate, 15, 829–
845.
Mantua, N. J., and S. R. Hare, 2002: The Pacific decadal oscillation.
J. Oceanogr., 58, 35–44.
——, ——, Y. Zhang, J. M. Wallace, and R. C. Francis, 1997: A
Pacific interdecadal climate oscillation with impacts on salmon
production. Bull. Amer. Meteor. Soc., 78, 1069–1079.
Maximenko, N. A., P. P. Niiler, G. G. Panteleev, T. Yamagata, and
D. B. Olson, 2002: Near-surface dynamical structure of the Kuroshio Extension derived from drifter and altimetry data. Exchanges, 7, 1–4.
Mestas-Nuñez, A., and D. B. Enfield, 1999: Rotated global modes
of non-ENSO sea surface temperature variability. J. Climate, 12,
2734–2746.
Miller, A. J., and N. Schneider, 2000: Interdecadal climate regime
dynamics in the North Pacific Ocean: Theories, observations and
ecosystem impacts. Progress in Oceanography, Vol. 47, Pergamon, 355–379.
——, D. R. Cayan, T. P. Barnett, N. E. Graham, and J. M. Oberhuber,
1994a: The 1976–77 climate shift of the Pacific Ocean. Oceanography, 7, 21–26.
——, ——, ——, ——, and ——, 1994b: Interdecadal variability of
the Pacific Ocean: Model response to observed heat flux and
wind stress anomalies. Climate Dyn., 9, 287–302.
——, W. B. White, and D. R. Cayan, 1997: North Pacific thermocline
variations on ENSO timescales. J. Phys. Oceanogr., 27, 2023–
2039.
——, D. R. Cayan, and W. B. White, 1998: A westward-intensified
decadal change in the North Pacific thermocline and gyre-scale
circulation. J. Climate, 11, 3112–3127.
VOLUME 33
Minobe, S., 2000: Spatio-temporal structure of the pentadecadal variability over the North Pacific. Progress in Oceanography, Vol.
47, Pergamon, 381–408.
Nakamura, H., G. Lin, and T. Yamagata, 1997: Decadal climate variability in the North Pacific during recent decades. Bull. Amer.
Meteor. Soc., 78, 2215–2225.
Oberhuber, J. M., 1993: Simulation of the Atlantic circulation with
a coupled sea ice–mixed layer–isopycnal general circulation
model. Part I: Model description. J. Phys. Oceanogr., 23, 808–
829.
Pedlosky, J., 1979: Geophysical Fluid Dynamics. Springer-Verlag,
624 pp.
Peng, S., and J. S. Whitaker, 1999: Mechanisms for determining the
atmospheric response to midlatitude SST anomalies. J. Climate,
12, 1393–1408.
——, W. A. Robinson, and M. P. Hoerling, 1997: The modeled atmospheric response to midlatitude SST anomalies and its dependency on background circulation states. J. Climate, 10, 971–
987.
Pierce, D. W., T. P. Barnett, N. Schneider, R. Saravanan, D. Dommenget, and M. Latif, 2001: The role of ocean dynamics in
producing decadal climate variability in the North Pacific. Climate Dyn., 18, 51–70.
Qiu, B., 1995: Why is the spreading of the North Pacific Intermediate
Water confined on density surfaces around s 5 26.8? J. Phys.
Oceanogr., 25, 168–180.
——, and K. A. Kelly, 1993: Upper-ocean heat balance in the Kuroshio–Oyashio Extension region. J. Phys. Oceanogr., 23, 2027–
2041.
Reed, R. K., J. D. Schumacher, P. J. Stabeno, C. H. Pease, A. W.
Kendall Jr., and P. Dell’Arciprete, 1994: Alaskan Stream inflow
and effects in the Bering Sea. Eos, Trans. Amer. Geophys. Union,
75, 342.
Reynolds, R. W., and T. M. Smith, 1994: Improved global sea surface
temperature analyses. J. Climate, 7, 929–948.
Ripa, P., 1986: Evaluation of vertical structure functions for the analysis of oceanic data. J. Phys. Oceanogr., 16, 223–232.
Robertson, A. W., 1996: Interdecadal variability in a multicentury
climate integration. Climate Dyn., 12, 227–241.
Schneider, N., and A. J. Miller, 2001: Predicting western North Pacific
Ocean climate. J. Climate, 14, 3997–4002.
——, ——, and D. W. Pierce, 2002: Anatomy of North Pacific decadal
variability. J. Climate, 15, 586–605.
Seager, R., M. B. Blumenthal, and Y. Kushnir, 1995: An advective
atmospheric mixed layer model for ocean modeling purposes:
Global simulation of surface heat fluxes. J. Climate, 8, 1951–
1964.
——, Y. Kushnir, N. H. Naik, M. A. Cane, and J. Miller, 2001: Winddriven shifts in the latitude of the Kuroshio–Oyashio Extension
and generation of SST anomalies on decadal timescales. J. Climate, 14, 4249–4265.
Stabeno, P. J., and R. K. Reed, 1994: Circulation in the Bering Sea
basin by satellite-tracked drifters: 1986–1993. J. Phys. Oceanogr., 24, 848–854.
Tourre, Y., W. B. White, and Y. Kushnir, 1999: Evolution of interdecadal variability in sea level pressure, sea surface temperature
and upper-ocean temperature over the Pacific Ocean. J. Phys.
Oceanogr., 29, 1528–1541.
——, B. Rajagopalan, Y. Kushnir, M. Barlow, and W. B. White, 2001:
Patterns of coherent decadal and interdecadal climate signals in
the Pacific basin during the 20th century. Geophys. Res. Lett.,
28, 2069–2072.
Trenberth, K. E., 1990: Recent observed interdecadal climate changes
in the Northern Hemisphere. Bull. Amer. Meteor. Soc., 71, 988–
993.
White, W. B., and T. P. Barnett, 1972: A servomechanism in the ocean/
atmosphere system of the midlatitude North Pacific Ocean. J.
Phys. Oceanogr., 2, 372–381.
——, and D. R. Cayan, 1998: Quasi-periodicity and global sym-
DECEMBER 2003
AUAD
metries in interdecadal upper ocean temperature variability. J.
Geophys. Res., 103, 21 335–21 354.
——, J. Lean, D. Cayan, and M. Dettinger, 1997: Response of global
upper ocean temperature to changing solar irradiance. J. Geophys. Res., 102, 3255–3266.
Xie, S. P., T. Kunitani, A. Kubokawa, M. Nonada, and S. Hosoda,
2503
2000: Interdecadal thermocline variability in the North Pacific
for 1958–1997: A GCM simulation. J. Phys. Oceanogr., 30,
2798–2813.
Zhang, R. H., and S. Levitus, 1997: Structure and cycle of decadal
variability of upper-ocean temperature in the North Pacific. J.
Climate, 10, 710–727.