inter-hemisphere decadal variations in sst, surface …atlantic basin. leading empirical orthogonal...
TRANSCRIPT
海洋科学技術センター試験研究報告 第41号 JAMSTECR, 41(March 2000)
57
*1 Institute for Global Change Research, Frontier Research System for Global Change
*2 Graduate School of Environmental Earth Science, Hokkaido University
*3 地球フロンティア研究システム
*4 北海道大学大学院地球環境科学研究科
Inter-Hemisphere Decadal Variations
in SST, surface wind and heat flux over the Atlantic basin
Youichi TANIMOTO*1 Shang-Ping XIE*2
Decadal climate variations are examined using a new observed dataset of marine meteorological variables in the Pan-
Atlantic basin. Leading empirical orthogonal functions (EOFs: spatial patterns) of sea surface temperature (SST) anomalies
on the decadal band (8-16 years) conducted in independent two subdomains north and south of equator feature one center
of action at 15oN and another center with opposite polarity at the same latitudes in the Southern Tropics. The same EOF
analysis for sea level pressure (SLP) anomalies also indicates two centers of action with opposing polarities around 30
degree latitudes, straddling the equator. The accompanying four principle components (PCs: time series) that contain
three cycles of decadal variations are correlated well with one another, indicative of the existence of the tropical dipole
mode in the ocean-atmosphere system.
Composite anomaly maps of wind velocity and heat fluxes, based on the PCs of leading modes of SST and SLP
anomalies, indicate that the latent heat flux induced by the cross-equatorial wind plays an important role in forcing the
dipole mode of the decadal SST variability. Anomalies on either side of equator show comparable amplitudes in the SST
field, but have quite different amplitudes in wind velocity and flux fields. The role of low-level clouds in forcing the SST
anomalies is discussed.
Key Words : Pan-Atlantic, decadal variability, ocean-atmosphere interaction
大西洋の海面水温,海面気圧海上風,海面熱フラックス,
下層雲におけるInter-hemispheric 10年スケール変動
谷本 陽一*3 謝 尚平*4
熱帯大気海洋系には強い結合変動があり,太平洋ではエルニーニョとしてしられている。大西洋においても結合変動は
みられるものの,その空間構造は太平洋のものと大きく異なり赤道反対称の双極子構造をとる。この双極子構造は熱帯大
西洋に卓越する唯一のモードではないため,観測的見地からの存在には未だ決定的な証拠が出されていない。本研究で
は,これまでとは異なった観点から卓越モードとしての双極子構造の存在を示す。
キーワード:環大西洋,10年スケール変動,大気海洋相互作用
JAMSTECR, 41 (2000)58
1. Introduction
Decadal sea surface temperature (SST) variations in
the tropical Atlantic are organized into dipole patterns
with centers of action around 10-15 degree latitudes
(Servain 1991, Nobre and Shukla 1996, Chang et al. 1997,
among others). At the same time, sea level pressure (SLP)
anomaly field also displays a dipole structure, whose cen-
ters of action locate slightly more poleward at 30 degree
latitudes and sign opposite to local SST anomalies
(Tanimoto and Xie 1999). This air-sea coupled tropical
dipole structure could be associated with the mid-latitudes
decadal variations via the atmospheric teleconnections
(Watanabe and Kimoto 1999). Rajagopalan et al. (1998)
presented that high coherences and in-phase (out-of phase)
relation were found between North Atlantic Oscillation
(NAO, Hurrell 1995) index and SST time series in north-
ern (southern) tropics. The extratropical North Atlantic
also displays pronounced decadal SST variations, which
are associated with a decadal change of mid-latitudes
westerlies (Deser and Blackmon 1993, Kushnir 1994,
Delworth, 1993, Halliwell and Mayer 1996). Similar situ-
ations occur in the SST and SLP fields in the Southern
Hemisphere (Venegas et al., 1997).
The dipole mode, however, is not the only mode of
SST variability in the tropical Atlantic. The interference
of different modes is considered to cause an apparent in-
ter-hemispheric decorrelation in both SST and SLP field
(Fig. 1). Previous empirical decomposition analyses and
their variations performed in domains that include the
whole tropics produce contradictory results as to whether
the northern and southern tropical SST anomalies vary
independently or can be decomposed into a pair of mono-
pole and dipole modes. The leading rotated EOFs of tropi-
cal SST anomalies in recent four decades (Houghton and
Tourre 1992) have one major center of action each con-
fined to one hemisphere but show no substantial signal in
the other hemisphere. Cross spectral analyses by Mehta
(1998) and Enfield et al. (1999) with longer data records
present little coherence of SST anomalies between north-
ern and southern tropics on any frequency domain. In
contrast, a singular value decomposition (SVD) analysis
of SST, wind stress and heat flux anomalies over 40 years
by Chang et al. (1997) showed that an SST dipole struc-
ture was maintained by equatorial anti-symmetric heat
flux anomalies, in association with cross-equatorial at-
mospheric flows. The same conclusion is reached from a
joint empirical orthogonal function (EOF) analysis of SST
and zonal wind anomalies (Nobre and Shukla 1996).
Most previous modal decompositions are applied to
both northern and southern parts of the tropical Atlantic
at the same time, and then tropics-extratropics linkages
are examined. Here we will further reexamine this inter-
hemispheric relation in the SST variability from a differ-
ent perspective. First, we will perform EOF analysis sepa-
Fig. 1 Scatter plot of zonal mean (a) SST (ºC) and (b) SLP (hPa) anomalies in the Northern tropics ( horizontal axis)
and Southern tropics (vertical axis). Zonal mean anomalies are calculated form unfiltered boreal winter in 8-
20º latitudes for SST and 20-40º latitudes for SLP.
JAMSTECR, 41 (2000) 59
rately for the North and South Atlantic, thus avoiding the
criticism that the EOF analysis over the whole tropics
might force artificial interhemispheric correlation. Sec-
ond, we will include the extratropics into our analysis
domains, recognizing the effects of atmospheric
teleconnections linking the tropics and mid-latitudes,
which in turn produce the Pan-Atlantic Decadal Oscilla-
tion (PADO; Xie and Tanimoto 1998). We will repeat
the same analysis on the SLP variability that presumably
most directly interacts with SST anomalies to see if these
interacting fields lead to a coherent interhemispheric re-
lation.
Observational and model studies indicate that surface
heat flux is crucial in forcing the dipole mode of SST
variability in the tropical Atlantic. Wagner (1996) exam-
ined contributions to SST dipole mode from each surface
heat flux component. His analysis method inevitably
emphasizes variability on interannual time scales where
significant positive contribution is seen only from wind-
induced latent heat variations. This latent heat flux con-
tribution has been independently confirmed in ocean gen-
eral circulation model (GCM) simulation (Carton et al.
1996), but it is still unclear if other heat flux components
might also contribute on longer decadal time scales. Di-
pole-associated wind variability is weak in amplitude and
not well organized in the South Atlantic and may not be
able to account for all the local SST anomalies that have
comparable amplitudes with those in the northern tropics
(Chang et al. 1997, Nobre and Shukla 1996, Tanimoto
and Xie 1999). In these analyses, wind anomaly ampli-
tudes north of equator are generally two or three times
larger than those south of equator even though SST
anomaly amplitudes are comparable on either side of
equator. Thus it is interesting to examine why this asym-
metric amplitudes of the atmospheric field could be as-
sociated with the symmetric amplitudes of the SST field.
We will show that low-level cloud variability is one of
the missing forcings for SST anomalies in the southern
tropics.
Now two types of gridded SST datasets are available
for the statistical analyses: One intends a complete spa-
tial coverage via an optimal method. This benefits nu-
merical experiments with a complete boundary condition,
just like GISST (Folland and Parker 1995) and GOSTA
(Bottomley et al. 1990). The other gridding method fills
a grid point only when there are enough number of ob-
servations in a grid for monthly seasonal averaging. Pre-
vious empirical studies (Mehta 1998, Enfield et al. 1999,
Xie et al. 1999) have employed the former dataset to cap-
ture the large-scale structure of Atlantic SST anomalies.
Over data sparse region like the South Atlantic, however,
heavy temporal and spatial interpolations can be a source
of signal distortion. Here in order to ensure the fidelity
of the gridded data, we require all grid points in the analy-
sis to have uninterrupted seasonal means (see the next
section for details). In the present study, we construct
such a new observational dataset of marine meteorologi-
cal variables including monthly SST, SLP, cloud amount
and ocean heat fluxes, calculated only from observations
by ship of opportunities. We did not use satellite-based
observations in calculation to avoid possible system bias
due to instrument changes. No spatial interpolation is
allowed. Later we will compare the results from this cut-
to-the-bone dataset with more heavily interpolated
datasets like the GISST and GOSTA.
The rest of paper is organized as follows; Section 2
describes the datasets and the analysis procedures. Sec-
tion 3 shows leading modes that explain the meridional
gradients of the inter-tropical SST and SLP anomaly
fields. Section 4 presents the Pan-Atlantic patterns for
SST, SLP, wind velocity and ocean heat fluxes. Section
5 gives a discussion of a lower cloud effect on the asym-
metric amplitudes of SLP and wind velocity, associated
with the tropical SST dipole. Concluding remarks are
given in Section 6.
2. Data set and analysis procedure
A monthly 4-degree latitude-longitude dataset of ma-
rine meteorological variables is constructed from qual-
ity-controlled ship and buoy observations compiled in
Long Marine Reports in fixed length records (LMRF) of
comprehensive ocean-atmosphere dataset (COADS; Woo-
druff et al. 1987) for the North and South Atlantic (70ºN-
50ºS) from 1950 through 1995. The domain contains the
Norwegian, North and Caribbean Seas, southern part of
Labrador Sea, Gulf of Mexico and Mediterranean. In the
present study, we examine SST, SLP, vector and scalar
wind speed, sensible and latent heat flux fields. A higher
resolution (2 degree x 2 degree) dataset of cloudiness is
also constructed from ship reports in LMRF of COADS.
The cloud amount is visually measuring a cloud cover-
age of the whole sky. Turbulent heat fluxes are calcu-
JAMSTECR, 41 (2000)60
lated using Kondo’s (1975) aerodynamic bulk method for
each of ship-buoy measurement. In regions like the South
Atlantic where there are few ship observations, the
COADS suffers sampling errors, and SLP and wind ve-
locity may not even satisfy basic dynamic constraints like
the geostrophic balance. We also complement the
COADS with the NCEP (National Centers for Environ-
mental Prediction, monthly 2 degree latitude-longitude
resolution) reanalysis dataset over 1958-1995, which pro-
vides dynamically-consistent SLP and wind velocity data
even with insufficient observed input in the Southern
Hemisphere to an assimilation model. In contrast, grid
point values of COADS are calculated from independent
observations of SLP and wind velocity. For each of these
variables we calculate a monthly climatological mean
annual cycle based on the entire period of record
(COADS: 46 years, NCEP: 38 years), and the monthly
anomalies are defined as departures from the climatologi-
cal means.
Seasonal averages are used in the following sections.
Averages are calculated only for boreal winters (Decem-
ber through March) only on those grid points with more
than three monthly-mean values. This study is based on
the modal decomposition (EOF and SVD analyses) of
SST and SLP anomalies at those grid points that contain
no missing boreal winter averages for the entire period of
1950/51 through 1994/95. Large variance is found on
interannual and decadal time scales (Servain 1991, Huang
and Shukla 1997, Mehta 1998) with a clear spectral gap
between the two time scales (Mehta and Delworth 1995,
Mehta 1998). Based on the above spectral structure of
tropical Atlantic SST anomalies, Tanimoto and Xie (1999)
applied a time-scale separation method to 51-year SST
time series and found negative (positive) correlation on
decadal (interannual) time scale in SST anomalies across
the equator. A band-pass filter is accepted to extract
decadal variations when substantial variances are found
in a frequency band. Explained variance of the leading
EOFs depends on the number of the grid points for which
a modal decomposition is performed. The grid points
employed in the modal decomposition are 312 (103) for
the North (South) Atlantic SST field, and 314 (113) for
the North (South) Atlantic SLP field. Composite anoma-
lies of SST, SLP, lower cloud amount and heat fluxes are
calculated based on the time series of the leading modes
to examine regional signals of the PADO.
3. Inter-hemispheric mode of decadal climate vari-
ability
Large variance appears in a decadal frequency domain
of 0.05-0.12 cycle per year in the tropical Atlantic SST
anomalies (Mehta 1998, Rajagopalan et al. 1998). In-
deed, Tanimoto and Xie (1999) showed that the cross-
equatorial gradient index of annual mean SST anomalies
varied on decadal time scales, often having an anti-sym-
metric dipole-like spatial pattern. Regressed SST, SLP
and wind vector anomalies onto the cross-equatorial gra-
dient index revealed a PADO pattern with the dipole in
the tropics. In this section, we present collaborative evi-
dence for the PADO based on different analysis methods.
Before we perform an EOF analysis, we divide the
Atlantic basin into two independent parts north and south
of the equator to eliminate an artificial-correlation prob-
lem in modal decomposition of tropical SST anomalies
(Houghton and Tourre 1992). Then, SST anomalies are
averaged for boreal winter and filtered through the decadal
band (8-16 year). The upper two curves in Figure 2 show
normalized principle components (PCs) of the leading
mode of SST anomalies in the North and South Atlantic,
respectively. Figure 3 depicts the SST regressions onto
the PCs instead of EOF eigenvectors. Grid points used
in the EOF analysis are shaded in the background. These
leading EOFs explain 37.0% and 54.9% of band-passed
variance of the used grid point values in the Northern and
Southern hemisphere, respectively. The second modes
explain only 19.0% and 13.2% of the variance in the
Fig. 2 Upper curves: the normalized principal components (PCs)
of SST anomalies in the North (solid) and South (dashed
line) Atlantic. Lower curves: PCs of SLP anomalies. The
vertical axis of SST anomalies is reversed.
JAMSTECR, 41 (2000) 61
Northern and Southern Hemisphere, respectively, ensur-
ing a fair separation of leading EOFs. The leading SST
patterns feature two tropical centers of action with op-
posing polarities across the equator with maximum re-
gression of 0.3º C in the Northern Tropics. SST anoma-
lies display a PADO pattern, with centers of action lining
up meridionally in the North Atlantic. Significant nega-
tive regressions, with a magnitude of -0.4ºC, extend from
south of Newfoundland through Gulf of Mexico and Car-
ibbean Sea, while small positive regressions of about
0.1ºC appear between South Greenland and south-west-
ern Europe. Negative regressions cover the whole the
Southern Hemisphere domain except in the southeastern
corner where poor data coverage generates an apparently
spurious center of action. The spatial structure of SST
anomalies will be discussed in Section 4.
These coherent patterns in fact fluctuate almost in phase
on the decadal time scales (Fig. 2, simultaneous correla-
tion coefficient is 0.63). Note again that these leading
EOFs are derived from independent fields so that there is
no a priori reason for them to be correlated. Decadal
variability is pronounced after mid 1960s while the agree-
ment of two PCs may be insignificant in the first 15 years
and the last 5 years. Simultaneous correlation maps onto
two PCs (not shown) present a similar pattern to regres-
sion maps. All centers of action have statistically-sig-
nificant correlations above 0.8 in the Pan-Atlantic domain.
The same analysis performed with the GISST dataset
gives a similar PADO pattern (Xie et al. 1999).
We perform the same analysis to the boreal winter SLP
anomalies in the two subdomains (Figure 4). The lead-
ing EOFs of SLP fields explain 36.4% and 50.2% of band-
passed variance of used grid point values in the Northern
and Southern Hemisphere, respectively. A subtropical
SLP center of action appears in 20-40ºN band in the cen-
tral North Atlantic, which is 10-15 degrees poleward of
the tropical SST center and has the opposite polarity to
the tropical SST anomalies. Another extratropical center
west of Europe also has significant regressions. The South
Atlantic EOF does not have much spatial structure, with
the SLP varying more or less uniformly over the whole
subdomain. The accompanying PCs of the SLP field (the
lower two curves of Figure 2), correlate to one another.
More strikingly, the SST and SLP pairs of PCs are well
correlated among themselves, despite the fact that they
are all derived from independent samples (Table 1). Two
minima in early 1970s and 1980s and three maxima in
late 1960s, late 1970s and early 1990s are shown up in all
Fig. 3 The first SST EOFs for the North and the South Atlantic,
which explain 37.0% and 54.9% of decadal band-passed (8-
16 years) boreal winter SST anomalies, respectively. Re-
gressed SST anomalies onto the PCs for the North (South)
Atlantic are shown in the upper (lower) panel. Negative
values are dashed. Contour interval is 0.1ºC.
Fig. 4 Same as Figure 3, but for the SLP anomalies. They explain
36.4% and 50.2% of decadal band-passed (8-16 years) bo-
real winter SLP anomalies for the North and the South At-
lantic, respectively. Contour interval is 0.2hPa
JAMSTECR, 41 (2000)62
four time series (Figure 2). These results indicate that an
air-sea coupled PADO dominates the recent three decades.
Scatter plots of zonal mean values in the 20-40ºN and
20-40ºS bands, calculated from bandpass filtered SLP
anomalies (not shown), confirm this out-of-phase rela-
tionship, with a tilted elliptical track much like the scat-
ters of decadal SST anomalies (see Fig. 5 in Tanimoto
and Xie 1999).
We also perform an SVD analysis to examine coupled
modes of SST and SLP fields in the combined Atlantic.
The leading SVD mode explains 60.1% of total squared
covariance. The heterogeneous regression maps of SST
and SLP fields (not shown) are similar to the pieced up
regression fields. All decomposed modes (EOFs and
SVDs) feature distinct NAO and associated SST patterns
(Deser and Blackmon 1993, Kushnir 1994) in the North-
ern Hemisphere, but show spatially uniform patterns in
the Southern Hemisphere.
The agreement between four time series of PCs is fairly
pronounced during three cycles of the decadal variability
from 1966 through 1990. Before and after this period,
however, the correlation among the PCs does not hold so
well. Although this could be due to the end effect of the
band-pass filter, similar EOF analyses of SST and SLP
fields for a shorter period of 1966-1995 reproduce the
three cycles of a decadal oscillation, raising the more
explained variance by about 15% (not shown). This re-
sult seems to suggest the nonlinear relationship between
this decadal variability and lower frequency fluctuations.
But a nonlinear diagnosis is out of scope in the present
study.
4. Decadal climate variability in Pan-Atlantic
To examine features common to three distinct cycles
of the distinct PADO, we made composite maps of me-
teorological variables based on the PCs of leading SST
and SLP modes. Compositing helps us to see the PADO
signature outside areas of EOF analyses. Six years each
are chosen to represent the positive phase (1968-70, 79-
81) and the negative phase (1972-74, 84-86) of the PADO.
Table 1 Correlation between leading PCs of SST and SLP fields in the two
subdomains north and south of equator
SLP N. Atl.
SLP S. Atl.
SST N. Atl.
SLP N.Atl.
1.00
-
-
SLP S.Atl.
0.63
1.00
-
SST N.Atl.
0.56
0.50
1.00
SST N.Atl.
0.69
0.78
0.63
Fig. 5 Difference maps of unfiltered boreal winter SST and SLP anomalies associated with the PADO, defined as the difference between
six positive phase years (1968, 69, 70, 79, 80, 81) and six negative phase years (1972, 73, 74, 84, 85,86). Contour interval is 0.2シC
and 0.5hPa for SST and SLP fields, respectively. Positive (negative) values are represented by the solid (dashed) contours.
JAMSTECR, 41 (2000) 63
form between 20 degree latitudes on either side of equa-
tor, while SST amplitudes increase to the east, exceeding
0.8ºC in the Northeastern Tropics. The composite SST
anomalies south of the equator exceed 0.6º C, but the spa-
tial pattern is less coherent. In the eastern boundary re-
gions, seasonal variations are largely due to the develop-
ment of the Guinea dome -the shallow domelike ther-
mocline feature in subsurface ocean- and the Angola dome
-a counterpart of Guinea dome in the Southern Hemi-
sphere-, respectively (Yamagata and Iizuka, 1995). These
domes develop due not only to an one-dimensional sur-
face heat flux, but also to active divergence of horizontal
heat transport in subsurface. Further investigations into
such subsurface variations in response to anomalous wind
stresses associated with cross-equatorial SST gradient are
desired.
In the difference map of wind vectors (Fig. 6), anoma-
lous southwesterlies in geostrophic balance with the SLP
difference reduce the climatological northeasterly trade.
This leads to a reduction in scalar wind speed by up to
1.5ms-1 (light shade in Fig. 6), suppressing the latent heat
flux release (negative anomalies) in the same region (Fig.
7a). The sensible heat flux (Fig. 7b) also depends on the
wind speed, but there is no substantial difference between
the two phases in the tropics. In the Southern Tropics,
the SLP di fference fie ld suggests anomalous
southeasterlies, which enhance the heat release (positive
anomalies) from the ocean surface. This is consistent
with the negative SST anomalies south of the equator.
Fig. 6 Same as Figure 4, but for wind velocity anomalies (vec-
tors). The wind velocity scale (5.0ms-1) are indicated on the
bottom of panel. Dark (light) shades are the regions in which
scalar wind speed anomalies are more than 0.5ms-1 (less than
-0.5ms-1).
Fig. 7 Same as Figure 4, but for (a) latent and (b) sensible heat flux anomalies. Contour interval is 10Wm-2.
The positive phase corresponds to a northward SST or a
southward SLP gradient in the tropics, and vice versa.
We will show difference maps of climate anomalies be-
tween the two phases.
Figures 5 shows the difference map of unfiltered SST
and SLP anomalies between the two phases. The polar-
ity of tropical SST and SLP anomalies is zonally uni-
JAMSTECR, 41 (2000)64
Wind velocity differences between the two phases dis-
play southeasterlies in the Southern Tropics. But the
amplitudes in the Southern Tropics are about one-third
of those in the Northern Tropics. Note that anomalous
southerlies on the equatorial grid points are stronger than
those further north in 8-12ºN. These strong southerly
anomalies are associated with a northward shift of the
ITCZ, a manifestation of interhemispheric interactions.
The heat flux anomalies show incoherent structures in
the Southern Tropics, becoming even worse south of 40ºS.
Few observations result in large sampling errors, espe-
cially in those higher order fields such as wind veloci-
ties, heat and momentum fluxes.
The atmospheric composites (right panel in Fig. 5 and
Fig. 6) in the Southern Hemisphere indicate a noisy anti-
cyclonic SLP pattern, small speeds and disorganized di-
rections of wind velocities. Composite maps of SLP and
wind vectors calculated from the NCEP reanalysis
datasets (Figure 8) are quite similar to those from COADS
in an overall sense. But the anticyclone centered on 30ºS
is better defined and associated wind pattern is well or-
ganized in the Southern tropics. Inter-hemispheric flows
within 10 degree latitudes have comparable amplitudes
both sides of the equator. Although the SLP and wind
velocity difference fields now have coherent structure,
their magnitudes poleward of 20ºS are still smaller than
those in the Northern subtropics.
In the extratropical North Atlantic, an atmospheric
NAO-like SLP and SST patterns (Figs. 5 and 8) are domi-
nant (Deser and Blackmon 1993, Kushnir 1994). Sub-
tropical SLP anomaly pattern in the North Atlantic shows
an intensification of the climatological Azores high, and
is sandwiched by negative SST anomalies off east coast
of United States and positive ones around Newfoundland
and south of Greenland. This association indicates an
ocean surface response to the atmospheric forcing by the
intensified westerlies to the south of the SLP center and
by weakened ones to its north. Positive SLP anomalies
in the Norwegian Strait are cooperative in weakening the
westerlies. The latent flux is one of the major compo-
nent in forming SST anomalies over most of the
extratropics, but the sensible heat flux makes comparable
contribution in the southern Labrador Sea. Such a change
in heat inputs into the extratropical atmosphere may in
turn maintain the polarity of SLP anomalies (Peng et al.
1997, Nakamura and Yamagata 1999, Rodwell et al.
1999), but a controversial issue needs further investiga-
tion.
Positive SST anomalies in 30-40ºS, 10-40ºW have a
somewhat coherent structure, but the SLP and wind ve-
locity anomalies do not. Because large sampling errors
are likely involved, we will not further discuss anomalies
in the extratropical South Atlantic.
5. Discussion
The previous studies of decadal variability have re-
vealed characteristic in the SST and SLP anomaly pat-
terns in the North Atlantic (Deser and Blackmon 1993,
Kushnir 1994, Peng and Fyfe 1996, Robertson 1996,
Bojariu 1997, Zorita et al. 1992, Watanabe et al. 1999)
and the South Atlantic (Venegas et al. 1997). These
anomaly patterns seem components of a single PADO
mode in the air-sea coupled field, as is demonstrated in
the Sections 3 and 4. Investigations of tropics-extratropics
connections (Xie and Tanimoto 1998, Tanimoto and Xie
1999) indicated that change in cross-equatorial SST gra-
dient, showing a distinct decadal variations, was strongly
Fig. 8 Same as Figure 5, but for SLP and wind velocity anomalies
from the NCEP reanalysis dataset. The reference wind ve-
locity (5.0ms-1) are indicated on the bottom of panel.
Contour interval is 0.5hPa for the SLP field. Positive (nega-
tive) values are represented by the solid (dashed) lines.
JAMSTECR, 41 (2000) 65
linked with extratropical decadal variability.
It remains controversial whether the meridional SST
gradient variability in the tropics represents an intrinsic
coupled mode (Chang et al. 1997, Xie and Tanimoto 1998,
Tanimoto and Xie 1999) or arises from fortuitous super-
position of two independent modes of SST variations
confined on either side of the equator (Houghton and
Tourre 1992, Mehta 1998). The results of our EOF analy-
ses conducted separately in two subdomains north and
south of the equator in Section 3 support the existence of
an air-sea coupled inter-hemispheric interaction, as is in-
dicated by the mutual temporal correlation among the four
PCs of SST and SLP fields and by a tropical dipole con-
figuration in their EOF spatial patterns.
Recent theoretical analysis with a generalized coupled
model (Xie et al. 1999) that includes both Bjerknes and
wind-evaporation-SST feedbacks provides some physi-
cal basis for our empirical modal decompositions. In an
ocean of Atlantic zonal size, arbitrary initial disturbances
in the model disperse into two sets of modes: equatorially
symmetric and anti-symmetric, respectively. Further-
more, the dispersion relations of these coupled models
also are such that their frequencies are well separated:
the anti-symmetric mode prefers decadal and longer time
scales, while the symmetric mode exhibits higher
interannual frequencies.
Simple/intermedium coupled models such as Xie et al.’s
(1999) produce a dipole mode of similar amplitudes of
the equator. While the observed SST pattern indicates
such a rough symmetry in amplitude, the SLP and wind
speed anomalies in the Southern Hemisphere are only one-
third of those in the Northern Hemisphere. While the
SLP and wind anomalies can be understood as the
baroclinic response to the SST dipole, the anomalous
cyclonic circulation centered on 35oN is largely a surface
signature of a deep barotropic response. It appears at
500hPa with its center shifted slightly westward (Fig. 9).
It will be interesting to include this barotropic response
in the atmospheric component of simple/intermedium
coupled models and see how coupled modes, particularly
the dipole, will change. We note that this hemispheric
difference in atmospheric response can be important for
understanding upper ocean variability that is largely wind-
driven. We can expect larger subsurface decadal vari-
ability in the North than the South Atlantic as ocean GCM
simulations seem to suggest (Huang and Shukla 1997).
Here we consider two factors which might cause asym-
metric amplitudes of the dipole-associated atmospheric
anomalies in the Atlantic. First, there are few observa-
tions outside of merchant ship routes in the Southern
Hemisphere. Tropical SST anomalies usually have a per-
sistence of more than one season. The persistence of at-
mospheric anomalies, by contrast, is much shorter than
that of SST anomalies. Few observation gives rise to
larger sampling errors in the atmospheric fields than in
the ocean, and in turn might mask climate signals. Simi-
larities between the results from NCEP and COADS
datasets, however, suggest that sampling errors are not a
critical problem in the tropics.
Second, the cloud shielding of solar radiation may con-
tribute to maintaining the tropical dipole mode of SST
anomalies. In boreal spring when the SST field in the
equatorial Atlantic is nearly uniform in both the zonal
and meridional directions, the ITCZ is sensitive to the
changes in an interhemispheric SST gradient associated
with the dipole (Nobre and Shukla 1996). This meridi-
onal shift of the ITCZ causes the decadal variability in
northeastern Brazil rainfall (Servain 1991, Mehta 1998,
among others). Composites based on a 2 degree latitude-
longitude higher-resolution dataset from the COADS cap-
ture this shift in ITCZ's latitude. Associated with an
anomalous northward SST gradient is an increase (de-
crease) in cloudiness at 5ºN (5ºS; Fig. 10). These near-
Fig. 9 Same as Figure 5, but for 1000hPa (thin contours) and
500hPa (thick contours) anomalies from the NCEP reanaly-
sis dataset.
JAMSTECR, 41 (2000)66
equatorial changes in cloudiness indeed seem associated
with convective activity as indicated by the convergence
(divergence) of anomalous winds at the surface (dotted
line in Fig. 10b). These near-equatorial changes in high
clouds act as a negative feedback to diminish the cross-
equatorial SST gradient.
Additional cloudiness anomalies are found in off-equa-
torial tropics poleward of 10 degree latitudes, which have
not been noted previously to our knowledge. These off-
equatorial cloudiness anomalies are negatively correlated
with local SST anomalies, but apparently not associated
with significant changes in surface wind convergence.
Thus they most likely correspond to changes in low-level
stratiform clouds. These low-level cloud anomalies are
spatially organized (Fig. 10). The cloud anomaly pattern
in the southern tropics is particularly robust, seen in all
the seasons. In annual mean, the southern cloudiness
anomalies are twice as large as the northern ones (not
shown). Two mechanisms are possible for causing
changes in low-level clouds. First is a top-down mecha-
nism: the shifts in the ITCZ change the subsidence in
off-equatorial tropics, affecting the height of and stratifi-
cation at the top of the planetary boundary layer (PBL).
The other is bottom-up: negative (positive) SST anoma-
lies increase (decrease) the stratification across the top of
the PBL provided temperatures in the free atmosphere
do not change. Enhanced (weakened) capping of the PBL
leads to an increase (decrease) in stratiform cloud cover
trapped near the top of the PBL. Increased (reduced) cloud
cover will in turn cause a further cooling (warming) in
SST through insolation change, completing a positive
feedback loop between local SST and stratus clouds.
In a coupled ocean-atmosphere model, the temporal
spectrum of the dipole mode response to a white-noise
forcing is sensitive to thermal damping rate in the SST
equation (Xie and Tanimoto 1998, Xie 1999). The SST
dependence of surface evaporation provides a major
mechanism for thermal damping, which can be linear-
ized as a Newtonian cooling term with a damping rate of
(1 year) -1 (Xie 1999). The rate of SST change due to
cloud shielding is -0.62(1-A)S0C'/(cpρH), where Reed's
(1977) formula for shortwave radiation has been used,
S0=300 Wm-2 is the solar radiation in clear sky, A=0.96
the albebo of sea surface, C’ the perturbation cloud
amount, cp and ρ are the specific heat at constant pres-
sure and density of sea water, and H=50m is the depth of
the mixed layer. Assuming that low-level clouds in off-
equatorial tropics vary with local SSTs, we have C'=-αT’
with α =0.1 K-1 from the right panels of Fig. 10. This
leads to an SST-stratus feedback coefficient, b = 0.62α
Fig.10 (a) Boreal spring (Feb.-Apr.) composite of cloud cover anomalies based on a higher resolu-
tion (2x2) COADS (left panel; heavy shading < -3.0% & light shading > 3.0%). (b) Zonal
mean anomalies of SST (upper right) and cloud cover (%; solid) along with surface wind
divergence (10-6s-1 in dotted line; lower right panel).
JAMSTECR, 41 (2000) 67
(1-A)S0/(cpρH)=(3.5 years) -1. Thus the local SST-stratus
feedback can reduce the Newtonian cooling rate for SST
by as much as 30%.
6. Concluding Remarks
We have examined dominant modes of the decadal
variability in the Pan-Atlantic basin, using the new ob-
servational datasets of marine meteorological variables
calculated from LMRF of COADS. An EOF analysis
was performed for decadal SST anomalies in the North
Atlantic and in the South Atlantic separately, avoiding
the artificial correlation between the northern and south-
ern tropics. The leading EOFs featured a dipole struc-
ture in the tropics across the equator and were associated
with substantial extratropical signals. The SLP EOF fea-
tured a similar dipole albeit with subtropical centers of
action on either side of the equator. Time series of these
leading modes correlated well with one another and pre-
sented three cycles of distinct decadal oscillations during
1966-90, indicative of the existence of an inter-hemi-
spheric dipole mode that involved ocean-atmosphere in-
teraction.
Composite maps, based on the positive and negative
phases of the tropical dipole mode, clearly showed that
the latent heat flux induced by anomalous wind vector
anomalies played a major role in coupling the atmosphere
and ocean. The composite SST anomalies had compa-
rable amplitudes on either side of the equator. However,
the magnitude of the SLP and wind velocity anomalies to
north of equator were three times larger than those to the
south. Furthermore an NCEP reanalysis dataset showed
a deep barotropic atmospheric pattern in the Northern
Hemisphere associated with the NAO pattern, but not in
the Southern Hemisphere at all. Whereas this asymmet-
ric amplitude structure might be a consequence of large
sampling errors due to insufficient observations in the
Southern Hemisphere, low-level clouds might play a role
in keeping SST anomalies having comparable amplitudes
across the equator. The response of cloud fields to the
SST dipole differed near and off the equator. Within 10
degrees latitude, it involved north-southward shift in the
ITCZ and changes in deep convective clouds, acting to
dampen the cross-equatorial SST gradient. Outside this
equatorial zone, low-level clouds responded to and posi-
tively fed back onto the local SST, reducing the thermal
damping rate by 30%.
Acknowledgment
The authors are grateful to Prof. T. Yamagata, Dr.
H. Nakamura, Dr. Iwasaka and Prof. Matsuno for stimu-
lating discussion. We also thank the NOAA/NCEP for
providing the reanalysis data and the NCAR for provid-
ing the COADS/LMRF dataset. This work was partly
supported by Frontier Research System for Global change.
References
1) Bojariu R (1997) Climate variability modes due to
ocean-atmosphere interaction in the central Atlantic.
Tellus 49A: 362-370.
2) Bottomley M., Folland CK, Hsiung J, Newell RE,
Parker DE (1990) Global Ocean Surface Tempera-
ture Atlas (GOSTA). Her Majesty’s Stationery Of-
fice.
3) Carton JA, Cao X, Giese BS, da Silva AM (1996)
Decadal and interannual SST variability in the tropi-
cal Atlantic Ocean. J Phys Oceanogr 26: 1165-1175.
4) Chang P., Ji L, Li H (1997) A decadal climate varia-
tion in the tropical Atlantic ocean from thermody-
namic air-sea interaction. Nature 385: 516-518.
5) Delworth TL (1993) North Atlantic interannual vari-
ability in a coupled ocean-atmosphere model. J Clim
9: 2356-2375.
6) Deser C, Blackmon ML (1993) Surface climate varia-
tions over the North Atlantic Ocean during winter:
1900-1989. J Clim 6: 1743-1753.
7) Enfield DB, Mestas-Nunez AM, Mayer DA, Cid-
Serrano L (1999) How ubquitous is the dipole rela-
tionship in the tropical Atlantic SST. J Geophys Res:
submitted.
8) Folland CK, Parker DE (1995) Correction of instru-
mental biases in historical sea surface temperature
data. Q J Roy Meteor Soc 121: 319-367.
9) Halliwell GR, Mayer DA (1996) Frequency response
properties of forced climatic SST anomaly variabil-
ity in the North Atlantic. J Clim 9: 3575-3587.
10) Hasternath S, Heller L (1977) Dynamics of climatic
hazards in northeast Brazil. Q J Roy Meteor. Soc 110:
77-92.
11) Houghton RW, Tourre YM (1992) Characteristics of
low-frequency sea surface temperature fluctuations
in the tropical Atlantic. J Clim 5: 765-771.
12) Huang B, Shukla J (1997) Characteristics of the
interannual and decadal variability in a general cir-
JAMSTECR, 41 (2000)68
culation model of the tropical Atlantic ocean. J Phys
Oceanogr 27: 1693-1712.
13) Hurrell JW (1995) Decadal trends in the North At-
lantic Oscillation: Regional temperature and precipi-
tation. Science 269: 676-679.
14) Kondo J (1975) Air-sea bulk transfer coefficient in
diabatic conditions Bound -Layer Meteor 9: 91-112.
15) Kushnir Y (1994) Interdecadal variation in North At-
lantic sea surface temperature and associated atmo-
spheric circulation. J Clim 7: 141-157.
16) Mehta VM (1998) Variability of the tropical ocean
surface temperatures at decadal-multidecadal
timescales. Part I: the Atlantic ocean. J Clim 11: 2351-
2375.
17) Mehta VM, Delworth T (1995) Decadal variability
of the tropical Atlantic ocean surface temperature in
shipboard measurements and in a global ocean-at-
mosphere model. J Clim 8: 172-190.
18) Nakamura H, Yamagata T (1999) Recent decadal SST
variability in the northwestern Pacific and associated
atmospheric anomalies. Navarra A, ed. “Beyond El
Niño: Decadal Climate Variability” Springer-Verlag:
in press.
19) Nobre P, Shukla J (1996) Variations of sea surface
temperature, wind stress, and rainfall over the tropi-
cal Atlantic and South America. J Clim 9: 2464-2479.
20) Peng S, Robinson WA, Hoerling MP (1997) The mod-
eled atmospheric response to mid-latitude SST
anomalies and its dependence on background circu-
lation states. J Clim 10: 971-987.
21) Peng S, Fyfe J (1996) The coupled patterns between
sea level pressure and sea surface temperature in the
midlatitude North Atlantic. J Clim 9; 1824-1839.
22) Rajagopalan B, Kushnir Y, Tourre YM (1998) Ob-
served decadal midlatitude and tropical Atlantic cli-
mate variability. Geophsy Res Lett 25: 3967-3970.
23) Reed RK (1977) On estimating insolation over the
ocean. J Phys Oceanogr 7: 482-485.
24) Robertson AW (1996) Interdecadal variability over
the North Pacific in a multi-century climate simula-
tion. Clim Dyn 12: 227-241.
25) Rodwell MJ, Rowell DP, Folland CK (1999) Oce-
anic forcing of the wintertime North Atlantic oscilla-
tion and European climate. Nature 398: 320-323.
26) Servain J, (1991) Simple climatic indices for the tropi-
cal Atlantic Ocean and some applications. J Geophys
Res 96: 15137-15146.
27) Tanimoto Y, Xie SP (1999) Ocean-Atmosphere Vari-
ability over the Pan-Atlantic basin. J Meteor Soc Ja-
pan 77: 31-46.
28) Venegas SA, Mysak LA, Straub DN (1997) Atmo-
sphere-ocean coupled variability in the South Atlan-
tic. J Clim 10: 2904-2920.
29) Wagner RG (1996) Mechanisms controlling variabil-
ity of the interhemispheric sea surface temperature
gradient in the tropical Atlantic. J Clim 9: 2010-2019.
30) Watanabe M, Kimoto M (1999) Tropical-extratropi-
cal connection in the Atlantic atmosphere-ocean vari-
ability. Geophys Res Lett.: submitted.
31) Watanabe M, Kimoto M, Nitta T, Kachi M (1999) A
comparison of decadal climate oscillations in the
North Atlantic detected in observations and a coupled
GCM. J Clim: in press.
32) Woodruff SD, Slutz RJ, Jenne RL, Steurer PM (1987)
A comprehensive ocean-atmosphere dataset. Bull
Amer Meteor Soc 68: 521-527.
33) Xie SP (1999) A dynamic ocean-atmosphere model
of the tropical Atlantic decadal variability. J Clim 12:
64-70.
34) Xie SP, Tanimoto Y (1998) A Pan-Atlantic decadal
climate oscillation. Geophys Res Lett, 25: 2185-2188.
35) Xie SP, Tanimoto Y, Noguchi H, Matsuno T (1999)
How and why climate variability differs between the
tropical Atlantic and Pacific. Geophys Res Lett: in
press.
36) Yamagata T, Iizuka S (1995) Simulation of the tropi-
cal thermal domes in the Atlantic: A seasonal cycle.
J Phys Oceanogr 25: 2129-2140.
37) Zorita E, Kharin V, von Stroch H (1992) The atmo-
spheric circulation and sea surface temperature in the
North Atlantic area in winter: their interaction and
relevance for Iberian precipitation. J Clim 5:1097-
1108.
(Manuscript received 15 December 1999)